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User Guide 2007Australian National Children's Nutrition and

1. CAPI CAPI CAT CAT Total day 1 day 2 day 1 day 2 Summer Feb 40 32 72 lt l Mar 284 278 205 194 Apr 339 334 277 268 Autumn May 489 459 314 281 3 722 40 Jun 61l 614 492 456 ul 442 468 611 595 Winter Aug 173 186 373 452 5 473 59 Total 2 378 2 371 2 272 2 246 9 267 100 Participant characteristics Table 14 shows the sample characteristics of the study children at the different response stages completed CAPI completed CATI and all response components completed i e CAPI CATI and pedometer Note Tables 14 17 are based on demographic characteristics of the participants at the time of recruitment These demographic characteristics may vary with the characteristics of participants at the time of the CAPI i e participants may have had a birthday and entered a new age range between recruitment and CAPI The demographic results at the time of CAPI are presented in the database of results managed by the Australian Social Science Data Archive ASSDA For access to the data refer to the ASSDA website at http assda anu edu au Table 15 Table 16 and Table 17 show the characteristics of participants parents caregivers and households at different stages in the response process Information on those households who completed the CAPI but did not participate in the CATI or complete all components was obtained from the CAPI This analysis excludes households who did not participate in the CAPI Character
2. 12 cousin 3 other relative in law 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult 11 niece nephew 12 cousin 3 other relative in law 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 11 niece nephew 12 cousin 3 other relative in aw 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult One family household Two family household Three or more family household Family Household with non family members present One family household with non family members present Two family household with non family members present Three or more family household with non family members present Other Please specify N oO o s D15 Interviewer Note Record family type Couple family with Chi Idren under 15 years only Chi Idren under 15 years and dependent stu
3. N wo A nn an N Negative income loss Don t Know Refused oe oO SECTION K KEEPING IN TOUCH Address the parent care giver and child if 9 years and over If 9 16 years old We will be in touch by telephone in a fortnight on two occasions Firstly to complete a second nutrition survey and then again to complete another activity survey If under 9 we will be in touch over the next week KL Can I please have your Home Phone Number K2 What is the best number to contact you study child on K3 What is the best time of day to call 1 Monday 2 Tuesday 3 Wednesday K4 What is the best day to call 4 Thursday 5 Friday 6 Saturday 7 Sunday NOTE INSERTROTATION OF SURVEY DAY DEPENDANTON YESIERDAY S DATE AND LOOK UP TABLE INSTRUCTION Parent Mobile Parent Email KS So that we can send you a short 99 do not have refused 99 do not have refused reminder messages could I please Study Child Mobile Study Child Email have 99 do not have refused 99 do not have refused 92 Interviewer to check off instructions Place copies of all material to be left behind in the folder and hand it to them as their reference for the study The material includes Summary consent form Permission to contact form for carer teacher if applicable Medicare
4. 93 20 Data Item list FOOD AND NUTRIENTINTAKE THE PREVIOUS DAY detailed information per food beverage consumed for each person for each day Data Items Food code Food group Portion size grams tablets Time eaten Place of consumption Portion size estimated for each nutrient Descriptors Population unique code for each for each food beverage All See Section Enon Reference source not found All Amount consumed in grams for All foods beverages or tablets for dietary supplements Hours minutes All The location at which the food was consumed All Proximates All Energy kilojoules Energy including from fermentable fibre kilojoules Moisture water grams Protein grams Fat total grams Saturated fatty acids total grams Monounsaturated fatty acids total grams Polyunsaturated fatty acids total grams alpha linolenic fatty acid grams linoleic acid fatty acid grams long chain omega 3 fatty acids milligrams Cholesterol milligrams Carbohydrate total grams Sugars total grams Starch grams Dietary fibre grams Alcohol grams Vitamins Vitamin A expressed as retinol equivalents micrograms Preformed vitamin A retinol micrograms Provitamin A beta carotene micrograms Thiamin milligrams Riboflavin milligrams Niacin equivalents total milligrams Vitamin C milligrams Vitamin D micrograms Vitamin E as alpha tocopherol milligrams To
5. 2 Low reduced fat 3 Skim 4 Evaporated or sweetened condensed 5 Soy milk None of the above 6 7 Does not drink milk or 8 Don t know 1 Whole full cream 2 Low reduced fat 3 Skim 4 Evaporated or sweetened condensed 5 Soy milk 6 None of the above 7 Does not drink milk or 8 Don t know H2 How many serves of vegetables do you usually eat each day One serve is equal to halfa cup INTERVIEWER NOTE Show food prompt if nec essary Less than one serve 2 One serve 3 Two serves 4 Three serves 5 Four serves 6 Five serves 7 Six or more serves or 8 Don t eat vegetables 1 Less than one serve 2 One serve 3 Two serves 4 Three serves 5 Four serves 6 Five serves 7 Six or more serves or 8 Don t eat vegetables H3 How many serves of fruit do you usually eateach day One serve is equal to half a cup INTERVIEWER NOTE Show food prompt if necessary 1 Less than one serve 2 One serve 3 Two serves 4 Three serves 5 Four serves 6 Five serves 7 Six or more serves or 8 Don t eat fruit 1 Less than one serve 2 One serve 3 Two serves 4 Three serves 5 Four serves 6 Five serves
6. 5 unrelated adult 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 11 niece nephew 12 cousin 3 other relative in law 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult 11 niece nephew 12 cousin 3 other relative in law 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 11 niece nephew 12 cousin 3 other relative in aw 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult D14 Interviewer Note Record household type Family Household with only family members present 11 niece nephew 12 cousin 3 other relative in aw 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 11 niece nephew
7. 7 Six or more serves or 8 Don t eat fruit H4 Does the person who prepares your meal add salt when they are cooking 1 Yes usually 2 Yes sometimes 3 No 4 Don t know 1 Yes usually 2 Yes sometimes 3 No 4 Don t know H5 Is itiodised i e contains iodine 1 Yes usually 2 No 3 Don t know 1 Yes usually 2 No 3 Don t know H6 Do you add saltto your meal atthe table 1 Yes usually 2 Yes sometimes 3 No 4 Don t know 1 Yes usually 2 Yes sometimes 3 No 4 Don t know H7 Is itiodised i e contains iodine 1 Yes usually 2No 3 Don t know 1 Yes usually 2 No 3 Don t know H8 In the past 12 months have you always had sufficient money to buy food O 1 Yes go to H10 86 O 2 No O 3 Refused go to H10 H9 If no did you go without food O 1 Yes O 2 No O 3 Refused H10 Has child s name ever been breastfed O 1 Yes O 2 No go to H12 O 3 Don t Know go to H12 H11 If yes including times of weaning what is the total time your child was breastfed Weeks Months Currently breastfeeding o O Don t know 12 Has child s name ever been given infant formula regularly 1 Yes 2No go to H13 3 Don t Know go to H13 H m Oo m H12b If yes at
8. emam v o ae o sws e ae s jo Ha a E moma a eo o A a Australian Capia Teno 6 o _ a Sample selection The central issue that faces any sampling selection is the sampling frame Conceptually this frame is a listing of all the members of the population to be sampled but no such complete list exists A number of possibilities for the sampling frame were considered in the planning stages These included using administrative databases such as Medicare Australia reverse telephone directory CD ROM RDD or random door to door interviewing in Census District Areas After investigation of all options RDD was considered to be within the budget and timeframe parameters and provided a representative sample of Australian children RDD has been a commonly used method of sampling for population health studies 18 Creation of the sample frame The following steps were taken to create the sample frame e Identify all possible phone number prefixes from charging zones and exchange groupings of prefixes contained in the Telstra Charging Zones classifications The version of the listing used was the latest available dated 26 May 2006 http www telstra com au customerterms bus_charging htm e Based on charging zones or exchange locations prefixes were allocated to the region which includes all or the greater part of the exchange In this way the RDD generated sample is pre allocated to a postcode Generation of sample i
9. 12 Comments 89 SECTION J DEMOGRAPHICS Address the Parent care giver Now am going to ask a few questions about your job and finances Once again your answers are totally confidential and individual responses will not be provided to government agencies We need to have a broad range of Australian families included in our study Family Details J 1 Last week did you do any work at all in a job business or farm J 2 Last week did you do any work without pay in a family business J3 Did you have a job business orfam that you were away from because of holidays sickness or any other reason include casual on call oragency work J4 How many hours do you usually work each week in that job that business all businesses If iregular hours average over last 4 weeks Do not include travel time J5 Atany time during the last 4 weeks have you been looking for full time or part time work Mark all that apply J 6 If you had found a job could you have started work last week J 7 When did you last work for two weeks or more Parent 1 1 Yes gt Go to J4 2No 3 Permanently unable to work gt Go to J7 4 Permanently not intending to work if ged 65 only gt Go to J7 Q 1 Yes gt Go to J4 2No 3 Permanently not intending to work if aged 65 only gt Go to J7 1 Yes 2No gt Go to J5 3 Permanently not intending to
10. 15 Intetpret tion of res lis rini xcs dece emtansas sal aatirn cacat cad uaeiugs E Ri 58 Survey and Sample Design sos vcs cicada ssyaieseaggutecndetde sucpeducdade puiesasdawcsasdes ane cep eceudatesace 58 Cl ster Sample Size sith com aaat tain Melisa ulate cede ere etna eet aadea dd Jaattes 58 Rand mdisit diall ina ace a cans acu au nae E eee uale N N 58 Seasonality e sr a e se tate e e aes Guasston shes aai aea guoa 58 Dietary recalls cis sa ccsasicuydsacisaaian nnana A ER A E E ER 59 Physicalkactivity recall neninn na a a 60 Pedometr yonne eneee a a T A a anicatnens 60 Physical Meas re Sinnsir EA E E R a E s 61 Comparison with previous SULVEYS ccsececesececseececssececsseeecseccecsceecseeeeseeeesaes 61 Comparison with recommendations ssessseesseesseeesseseseeeesstessresseesseeeseressseessres 62 16 Estim tion PV OCCAUTES siini a A E E A AEE 64 N n Pr p rtionate Sampling reiceas 64 ELAI EA E EE EEE dase oe sant A EN AERE 65 Analysis Code sneonen e r a E E A E 67 17 Data output and Dissemination oossneensseeeesseseessssesesssesesssereesssseesssseeses gt 68 18 Issues arisin orane E A Rad eee E EA ea ae 69 19 GAPI sufvey Seripa ehonaad 70 20 D1017 2A I EE A ET E A E A AE 94 21 Fod groups oeren a as cals aa e a aa OE raa 103 22 LINZ24 output files sissccrceraiwitiavadtandstunsrriavncenaradindbicendd e iE 107 23 Activity setioa dor nap a a Gaia i ental 109 24 R code for non proportionate sampling We
11. An indicator of weight status calculated from the formula weight height2 or kg m Estimated average requirement the average daily nutrient intake level estimated to meet the requirement of half of the healthy individuals in a particular life stage and gender groups It is used to estimate the prevalence of potentially inadequate intakes in a population group The chemical energy that is available to the body from metabolism of carbohydrates protein fat and alcohol after digestion and absorption Energy intakes are reported in kilojoules kJ One Calorie is equivalent to approximately 4 186 kJ Energy including from fermentable fibre Fat Fine age groups Frankfort plane Height Major food groups NUTIAB 2006 The chemical energy that is available to the body from metabolism of carbohydrates dietary fibre protein fat and alcohol after digestion and absorption Energy intakes are reported in kilojoules kJ One Calorie is equivalent to approximately 4 186 kJ Fat provides a large part of energy in the human diet carries fat soluble vitamins and is the source of essential fatty acids Three fatty acid subtotals poly mono and saturated fatty acids do not add up to total fat because total fat includes a contribution from the non fatty acid components e g glycerol 2 3 years 4 8 years 9 13 years 14 16 years Positioning of the head such that the line of vision is perpendicular to the body Participants posit
12. Vitamins Vitamin A expressed as retinol Micrograms ug equivalents Preformed vitamin A retinol Micrograms ug Provitamin A beta carotene Micrograms ug Thiamin Milligrams mg Riboflavin Milligrams mg Niacin equivalents total Milligrams mg Vitamin C Milligrams mg Vitamin D Micrograms ug Vitamin E as alpha tocopherol Milligrams mg Total Folate Micrograms ug Dietary folate equivalents Micrograms ug Minerals amp electrolytes Potassium Milligrams mg Sodium Milligrams mg Calcium Milligrams mg Phosphorus Milligrams mg Magnesium Milligrams mg Iron Milligrams mg ZINC Milligrams mg lodine Micrograms ug Other Caffeine Milligrams mg 33 11 Physical Activity Physical Activity Recall Participants aged 9 16 years used the MARCA Ridley et al 2006 to self report use of time The MARCA is a computerised 24 hour recall which asks participants to recall everything they did on the previous day The MARCA shows moderate to good validity when compared to accelerometry Ridley et al 2006 It uses a segmented day format with meal times and or school bells as anchor points Within each time segment time sliders indicate the start and completion times for activities in time slices which can be as fine as 5 minutes Users choose from about 250 activities listed in a compendium under seven categories Inactivity
13. a b Sex to the data for each Region by Age grouping The residual variance from this model for a particular Region by Age grouping would be our variance estimate for all Regions by Family Structure by Age by Sex Classes having that Region and Age It may be that the variance will not vary much between Classes so that a single variance estimate will be appropriate for all Classes When the variance estimate appropriate to each Class has been obtained the standard error of the estimate 2 is If the quantity to be estimated is a proportion of children with a particular attribute such as the proportion of children in families with family income gt 2 000 per week rather than a mean of a quantitative variable the Class standard deviation is estimated from the estimated proportions in each Class The estimated proportion for the population is gt wil where J 1 for children who have the attribute 7 0 for other children 4 gt i 1 Let g be the Class containing child i and suppose there are ng children in Class g of whom mg have the attribute so that the proportion of children in Class g with the A attribute is p m n The estimated standard deviation of the indicator variable li is then 6 1 Thus the standard deviation of the estimate 4 is Note that the sums in equations 4 and 5 run over all children in the survey and not just over Classes They can be rewritten as sums over Classe
14. and folic acid analysis These more recent data form the basis of folate data published in AUSNUT 2007 Folate values are presented as both total folates including naturally occurring folate and added folic acid as in AUSNUT 1997 and as dietary folate equivalents DFEs The following equation was used to calculate DFEs DFE ug Food Folate ug 1 67 Folic Acid ug lodine lodine was not reported in the 1995 NNS or included in AUSNUT 1997 Since 2001 FSANZ has undertaken a number of analytical programs involving iodine analysis which were published in NUTTAB 2006 These data formed the basis for further imputation and estimation for the AUSNUT 2007 database Caffeine Caffeine was not reported in the 1995 NNS or included in AUSNUT 1997 Since 1995 FSANZ has undertaken an analytical program involving caffeine analysis the results of which were published in NUTTAB 2006 These data formed the basis for further imputation and estimation for the AUSNUT 2007 database Sodium FSANZ has updated a significant proportion of sodium analytical values in foods and included these in the reference database NUTTAB2006 These values are the basis for further imputation and estimation for the AUSNUT2007 database Sodium was not reported in the 1995 NNS or included in AUSNUT 1997 Food Group coding A revised dual food coding system was developed in collaboration with FSANZ CSIRO and the Technical Reference Group section 21 It reflects the
15. anthropomtery component Reason for non completion of stride test component Stride length measurements cm Stride length cm Descriptors The first second and third optional height measurements in cm Height in cm This is an average of all measurements taken The first second and third optional weight measurements in kg Weight in kg This is an average of all measurements taken The first second and third optional waist girth measurements in cm Waist girth in cm This is an average of all measurements taken Waist girth measurement taken over skin or clothing The calculated Body Mass Index Interviewer comments on why the anthro measurements were not completed Interviewer comments on why the stride test was not completed The first and second stride measurements in cm of the respondent Stride length in cm This is an average of the taken measurements Population All All All All All All All All All who did not complete anthropometry All eligible for pedometry All eligible for pedometry All eligible for pedometry 97 FOOD HABITS Data Items Main type of milk that you usually used Number of serves of vegetables usually eaten each day Number of serves of fruit usually eaten each day Is salt added by food preparer to meals during cooking Is salt Used in cooking iodised Is salt added to meals at the table Is salt used at table iodised In the past 1
16. estimated duration of removal The pedometer and log sheet were posted back to the survey team using a reply paid envelope Step counts data were gathered using the following strategies and various combinations of strategies to cross check data e Step count in returned pedometer e Log sheet e Data gathered during CATI interview Data gathered in follow up phone call not CATI Estimating stride length Stride length was estimated during the CAPI using the 10 steps method A linear distance of approximately 10 meters was marked out with a metal tape The participant was asked to line up the toes of both feet with the zero on the tape walk normally for 10 steps and stop by bringing both feet together Two trials were conducted after an initial familiarisation trial The average distance covered in centimeters was divided by 10 to provide stride length This distance was programmed into the pedometer so that the daily distance covered was individualised The default setting in the pedometer of 76 cm is based on adult data and was inappropriate for this survey 34 12 Physical Measurements Height weight and waist girth were measured on children aged 2 16 years according to the protocols of the International Society for the Advancement of Kinanthropometry ISAK Marfell Jones et al 2006 Choice of measurement instruments was influenced by the need for interviewers to collect data in participants homes and therefore conveniently
17. school day or empty non school day start time of first activity end time of first activity duration of first activity minutes MET value of first activity Example 123456 7 March 2007 31 July 1995 boy or girl 999 999 13 07 separated by space 999 missing Glenelg South Primary School text string user entered ABC 123 08 12 45 AM 7 00 AM 8 00 AM 12 30 PM 7 00 PM 10 35 PM 9 30 PM 07 00 AM 07 05 AM 005 02 7 52 23 ID of first activity 533020 24 name of first activity dressing amp undressing Items 19 24 are then repeated until all activities have been listed Cleaned data Raw MARCA profiles were cleaned using manual checks Cleaning involved e Checking participant IDs dates random IDs and school names for consistency with other files from the same child e Replacing any activity listed as other MARCA code 000000 with the best compendium equivalent Cleaned MARCA profiles were then combined periodically into a single file with each profile separated by a return These were named according to the following convention MARCA_ lt date gt lt CAPI or CATI gt txt for example MARCA_26Mar07CAPI txt The final file containing all cleaned MARCA profiles is named MARCA Final txt Extracted data The cleaned profiles were analysed to calculate values for a number of activity sets Values for activity sets were calculated by summing the total number of minutes in th
18. yr 212 4 208 4 191 4 600 699 wk 31 200 36 399 yr 187 4 181 4 176 4 500 599 wk 26 000 31 199 yr 180 4 174 4 164 4 400 499 wk 20 800 25 999 yr 162 3 154 3 146 3 300 399 wk 15 600 20 799 yr 115 2 105 2 94 2 200 299 wk 10 400 15 599 yr 67 65 60 100 199 wk 5 200 10 399 yr 12 0 12 0 12 0 50 99 wk 2 600 5 199 yr 5 0 5 0 4 0 1 49 wk 1 2 599 yr 0 0 Q Nil income 9 0 8 0 8 0 Negative income loss 11 0 1 0 1 0 Don t Know 164 3 15 3 138 3 Refused 105 2 101 2 98 2 Mean 70 238 70 559 70 838 44 14 Data Processing Demographics Interviewers submitted interviews to the secure web server on a daily basis l view downloaded all new interviews daily for editing Interviews were reviewed and data were checked for e Logic and consistency across each demographic variable e Valid ranges e Typing errors Completeness of survey data Clarification was obtained by telephoning interviewers or respondents where discrepancies existed General feedback was provided to all interviewers via weekly newsletters Dietary recall Interviewers submitted interviews to the secure web server on a daily basis CSIRO dietitians downloaded all new interviews daily for editing Interviews were reviewed and data were checked for e Unrealistic portion sizes and overall food intake e Inadequate detail e Typing errors e Comp
19. 13 years o daz as 0 4 16 years lo F fd 88 years 46 59 9 13 years o o ET 0 9 16 years Ce _ e 586 4 16 years W e e 200 Total 1671 1728 1753 1637 In 23 cases the parent care giver requested another child participate other than the child initially selected by the KISH table These requests were respected and details of the substitution have been retained in the data set 21 Scope and coverage Scope Urban rural and remote areas across all states and territories of Australia were included Some postcodes were excluded for a number of reasons mentioned in Section 6 Survey Design The scope included children aged 2 16 years who were residents of private dwellings A private dwelling was defined as any household with a fixed land line telephone Interviewing was conducted across school and non school days The proportion of interviews conducted on weekdays weekends public holidays and school holidays was selected to reflect the proportions of these days across the fieldwork period Table Table 1 Table Coverage Coverage rules were designed to ensure that as far as possible eligible persons had only one chance of being selected for interview The child was deemed to be a resident of the household if they usually stayed at the selected household on average for 4 or more days per week in the case of shared care Households with more than one fixed line telephone may have had a greater chance of selection however th
20. 341990 mucking around outdoors 321960 mucking around inside sitting 341903 playground equipment eg monkey bars hard 341901 playground equipment eg monkey bars light 341902 playground equipment eg monkey bars medium 341253 riding a scooter hard 341251 riding a scooter light 341252 riding a scooter medium 341273 riding a skateboard hard 341271 riding a skateboard light 341272 riding a skateboard medium 341313 rollerblading in line skating hard 341311 rollerblading in line skating light 341312 rollerblading in line skating medium 341463 rollerskating hard 341461 rollerskating light 341462 rollerskating medium 341483 running around hard 341481 running around light 341482 running around medium 341473 skipping rope jumping hard 341471 skipping rope jumping light 341472 skipping rope jumping medium 341553 snorkeling hard 341551 snorkeling light 341552 snorkeling medium 331590 stretching exercises 341603 surfing body or board hard 341601 surfing body or board light 341602 surfing body or board medium 341933 swimming playing in pool hard 341931 swimming playing in pool light 342773 playing catch hard 342771 playing catch light 342772 playing catch medium 341932 swimming playing in pool medium 331630 tai chi yoga 331993 totem tennis hard 109 code activity code activity 321880 playing in sandpit 33199
21. 53 The overall average was obtained by averaging the averages of the school and non school days in this case the average of 560 and 660 minutes or 610 minutes The rationale for this procedure is that across a year children soend about one day in two at school when accounting for holidays days off teacher free days etc In some cases four days were recalled but none were school days for example due to illness or unusual timetables or none were non school days for example there was school on Saturday In these cases average values for activity sets were calculated across all four days 54 Table 20 Variables extracted from the cleaned MARCA data no item format definition example 1 participant ID string 123456 2 random ID string ABC 123 3 date of birth date 11 Oct 94 4 date of test date 2 Jul O7 5 day type category school school day day non school day 6 PAL real 2 decimal places Physical Activity Level in METs 1 69 MPA real 0 decimal places minutes of moderate PA gt 3 to lt 6 140 METs VPA real 0 decimal places minutes of vigorous PA gt 6 METs 30 active transport real 0 decimal places minutes of active transport MARCA 30 codes 24005x 24009x 24007x 241080 34124x 34125x 34127x 34131x 34146x 10 PT work real 0 decimal places minutes spent in part time work codes 40 7230x0 7330x0 7430x0 11 chores real 0 decimal places minut
22. 6 months ago 3 6 up to 12 months ago 4 1 up to 2 years ago 5 2 up to 5 years ago 6 More than 5 years ago 7 Has never worked for 2 weeks or more 90 Family Details Parent 1 Parent 2 J 8 In the main job held last week what was 5 occupation GET PULL TITLE J 9 What are the main tasks that usually perfom s in that occupation GET PULL DETAILS J 10 Before income tax is taken out whatis your present yearly income for you and your partner combined INCLUDE PENSIONS AND ALLOWANCES BEFORE TAX SUPERANNUATION OR HEALTH INSURANCE 2400 or more per week 124 800 or more per year 2200 2399 per week 114 400 124 799 per year 2000 2199 per week 140 000 103 999 per year 1500 1999 per week 78 000 103 999 per year 1000 1499 per week 52 000 77 999 per year 800 999 per week 41 600 51 999 per year 700 799 per week 36 400 41 999 per year 600 699 per week 31 200 36 399 per year 500 599 per week 26 000 31 199 per year 400 499 per week 20 800 25 999 per year 300 399 per week 15 600 20 799 per year 200 299 per week 10 400 15 599 per year 100 199 per week 5 200 10 399 per year 50 99 per week 2 600 5 19 per year 1 49 per week 1 2 599 per year Nil income Som o fl o Ea gt E ht Lar
23. Acting Assistant Secretary Population Health Division Department of Health and Ageing Mr Andrew Stuart former First Assistant Secretary Population Health Division Department of Health and Ageing Ms Margaret Lyons former First Assistant Secretary Population Health Division Department of Health and Ageing Mr Richard Souness General Manager Food Policy and Safety Branch Department of Agriculture Fisheries and Forestry Mr Dick Wells Chief Executive Officer Australian Food and Grocery Council Mr Geoffrey Annison Australian Food and Grocery Council Mr David Roberts Australian Food and Grocery Council Steering Group Project Officer Caroline Arthur Acting Director Nutrition Section Department of Health and Ageing The Technical Reference Group supplied guidance and advice to the Project Team The members of the Technical Reference Group were Professor A Stewart Truswell AO MD DSC FRCP FRACP FPHN Emiretus Professor of Human Nutrition University of Sydney Professor Katrine Baghurst BSc PhD Adjunct Professor Department of Medicine University of Adelaide Professor Jennie Brand Miller BSc Hons Food Tech PhD FAIFST FNSA Professor of Human Nutrition University of Sydney Ms Ingrid Coles Rutishauser BSc Nutrition MSc Epidemiology RPHNutr Coles and Rutishauser Consultants Professor Wendy Brown BSc Hons GradDip Phys Ed MSc PhD FASMF Professor of Physical Activity and Health School of Human Movement
24. Active Transport MARCA codes and activity names for activities included under the active transport category code activity 240051 walking light 240052 walking medium 240053 walking hard 240071 climbing stairs light 240072 climbing stairs medium 240073 climbing stairs hard 24009 1 walking carrying a load light 240092 walking carrying a load medium 240093 walking carrying a load hard 241080 walking using crutches 34124 riding a bicycle bike light 341242 riding a bicycle bike medium 341243 riding a bicycle bike hard 341251 riding a scooter light 341252 riding a scooter medium 341253 riding a scooter hard 341271 riding a skateboard light 341272 riding a skateboard medium 341273 riding a skateboard hard 341311 rollerblading in line skating light 341312 rollerblading in line skating medium 341313 rollerblading in line skating hard 341461 rollerskating light 341462 rollerskating medium 341463 rollerskating hard 113 Screen Time MARCA codes and activity names for activities included under the screen time category code activity 111030 watching TV lying quietly 121050 watching TV sitting 420050 computer work e g typing internet 722190 computer playstation games Note that the following activities are excluded from screen time code activity 114190 sending text messages SMS lying down 124170 sending text messages S
25. Alcoholic Beverages Pre mixed drinks SPECIAL DIETARY FOODS 105 1995 Food Code 291 192 301 302 303 304 305 306 31 311 312 313 314 Food Group Name Formula Dietary Foods Enteral formula MISCELLANEOUS Beverage Flavourings Yeast Yeast Vegetable And Meat Extracts Artificial Sweetening Agents Herbs Spices Seasonings And Stock Cubes Essences Chemical Raising Agents And Cooking Ingredients INFANTFORMULAE AND FOODS Infant Formulae And Human Breast Milk Infant Cereal Products Infant Foods Infant Drinks 2007 Revised Food Code 301 302 31 311 312 313 314 315 32 321 322 323 324 331 332 333 334 335 336 337 338 339 Revised Food Group Name Formula Dietary Foods Enteral formula MISC ELLANEOUS Yeast Yeast Vegetable And Meat Extracts Intense Sweetening Agents Herbs Spices Seasonings And Stock Cubes Essences Chemical Raising Agents And Cooking Ingredients INFANT FORMULAE AND FOODS Infant Formulae And Human Breast Milk Infant Cereal Products Infant Foods Infant Drinks DIETARY SUPPLEMENTS Multivitamin and Mineral Single mineral Single vitamin Herbal And Homeopathic Supplements Oil Supplement Protein Supplement Sports Supplement Fibre Supplement Probiotics and Prebiotics 106 22 LINZ24 output files Four types of files are exported from the LINZ24 software ready for nutrient analysis Respondent information Ca
26. Australia data release form if agreed Change of address form Service agency listing Respondent brochure if they do not already have one Food Habits Survey Pedometer and instruction sheet Nutrition and Meal Serving Size Guide Card Reply paid Envelope Invite them to visit the respondent website www kidseatkidsplay cOm du to keep in touch with what is happening with the study Let them know that you will ring back in a two weeks time to do the follow up survey or so to see how they have gone with the self complete s and the pedometer Explain that it is possible that someone from the Office may be in touch to verify that you have conducted the interview Thank them sincerely for their time and cooperation and check if there are any outstanding queries It is very important that you take the time to talk with the respondent about any questions they have about the study Take care packing up your equipment check against the list of materials that you have everything Repeat your full name and the 1800 10 80 12 phone number for the respondent to contact your supervisor if they have any queries or would like to verify the validity of the study Sign and date a PR Card and hand to respondent This card is to be left with respondents so they have your name and I View contact details and this is part of our IQCA requirements
27. Commercially Sterile Crustacea And Molluscs Excluding Commercially Sterile Other Sea And Freshwater Foods Packed Commercially Sterile Fish And Seafood 103 1995 Food Code 55 56 16 61 62 63 64 65 66 67 68 69 17 71 72 73 81 82 83 84 85 86 87 88 89 191 911 92 93 94 95 96 97 98 20 201 202 Food Group Name And Seafood Fish And Seafood Products Mixed Dishes With Fish Or Seafood As The Major Component FRUIT PRODUCTS AND DISHES Pome Fruit Berry Fruit Citrus Fruit Stone Fruit Tropical Fruit Other Fruit Mixtures Of Two Or More Groups Of Fruit Dried Fruit Preserved Fruit Mixed Dishes Where Fruit Is The Major Component EGG PRODUCTS AND DISHES Eggs Dishes Where Egg Is The Major Ingredient Egg Substitutes and Dishes MEAT POULTRY and GAME PRODUCTS and DISHES Muscle Meat Game And Other Carcase Meats Poultry And Feathered Game Organ Meats And Offal Products And Dishes Sausages Frankfurts And Saveloys Processed Meat Mixed Dishes Where Beef Or Veal Is The Major Component Mixed Dishes Where Lamb Or Pork Bacon Ham Is The Major Component Mixed Dishes Where Poultry Or Game Is The Major Component Dairy Milk Milk Fluid Fat Increased Yoghurt Cream Cheese Frozen Milk Products Other Dishes Where Milk Or A Milk Product Is The Major Component Milk Substitutes Flavoured Milks SOUP Soup Dry Soup Mix 2007 R
28. In addition AUSNUT 2007 reports energy including contribution from fibre 8kJ g Carbohydrate For some foods data for total carbohydrates includes a contribution from glycogen sugar alcohols and oligosaccharides where the level of these carbohydrates is known For these foods the sum of the total sugars and starch will not equal the total carbohydrate value Dietary fibre Total dietary fibre values have been analysed by the Association of Official Analytical Chemists AOAC enzymic gravimetric method Section 985 29 AOAC 2000 This includes soluble insoluble fibre some resistant starch and lignan Fatty acids FSANZ has updated a significant proportion of fatty acid data including omega 3 fatty acids since AUSNUT 1997 These values are the basis for further imputation and estimation for the AUSNUT 2007 database The sum of the three fatty acid subtotals given in the database is always less than the total fat value The difference is due to the contribution of the non fatty acid components in the triglyceride unit such as the glycerol backbone possible phosphate groups and sterols The total long chain omega 3 fatty acid values were calculated by summing all omega 3 polyunsaturated fatty acids containing at least 20 carbon atoms Linoleic acid values include conjugated linoleic acid where this has been measured separately to other isomers Vitamin D NUTTAB 2006 included few analytical values for vitamin D Most of the
29. N v i l where N 4 837 is the number of children in the Survey yi is the value of the variable for the ith child in the survey and wiis the weight assigned to that child The calculation of standard errors requires calculation of an estimated variance within each Class for each variable being studied This cannot be done separately from the analysis of the variables and so values cannot be given here If the sample numbers were larger these variances could be calculated from the within class sample variances but this is not feasible here since many of the Classes have very small sample numbers Instead a model based approach to estimating the variance will be required It is not possible to prescribe in advance what model will be appropriate for each variable since this will emerge from the analysis However the general approach is likely to be similar The model will assume that the variance is constant within some larger grouping of the data such as Region by Age and the variance within each cell of that grouping estimated by the residual variance from fitting a regression model within the cell For example consider a hypothetical variable Nutritional Value which is assumed to have constant variance within each Region by Age group 65 If we believe from prior information that Family Size will have little effect on the variable but it may differ by sex then we would fit a simple regression model Nutritional Value
30. Response rates There are several places where sample may be lost Figure 2 shows the sample loss through various stages of the study Figure 2 Sample loss flow chart RDD sample generated 347 187 Yes Yy Conduct CATI 4695 Complete Interview 4695 Discard Contact Made No Code as Non by telephone Contact 137 653 Yes Discard Discard Code as Quota gt Eligible Code as Not Full t Age by location quota full Household No Eligible 3320 192 927 Yes Is there Discard consent No gt Code as Refusal 6489 Yes y Send out Letter about Fieldwork and information brochure 6789 Discard Code as Quota j Contact 1800 Full t Age by location quota full i by CAPI onii 1450 nterviewer Yes Is there Discard corisent No gt Code as Refusal 502 Yes y Conduct CAPI 4837 Discard gods S t Age by location quota full Contact Made 96 Yes is there Discard consent No gt Code as Refusal 46 37 Of the 16 598 eligible households that were contacted 10 109 agreed to participate in the study which equalled a response rate of 61 Of these 10 109 households 3 320 were subsequently not required to participate as the quota for children in their age group had already been filled Out of the 6 789 households recru
31. characteristic Primary Parent Care Giver Completed In Completed Completed all Characteristic Home Telephone components Parent Care giver Primary Male 484 10 469 10 449 10 Female 4 353 90 4 226 90 4 038 90 4 837 4 695 4 487 ATSI No 4 752 98 4 614 98 4 411 98 Aboriginal and or Torres Strait 81 2 77 2 72 2 Refused 4 O 4 O 4 O 4 837 4 695 4 487 Education Tertiary Education 2 161 45 2 113 45 2 020 45 No Tertiary Education 2 661 55 2 067 55 2 452 55 Refused 15 0 15 O 15 0 4 837 4 695 4 487 Language spoken at home English only 4 420 91 4 304 92 4 122 92 Other 416 9 390 8 364 8 Refused g 1 0 0 4 837 4 695 4 487 Country Born Australia 3 820 79 3 717 79 3 547 79 Other 1 017 21 978 21 940 21 4 837 4 695 4 487 Work Status Working 3 448 7 3 359 72 3 221 72 Not Working 1 389 29 1 336 29 1 266 28 4 837 4 695 4 487 42 Table 16 Second parent caregiver characteristic Second Parent Care Giver Completed In Completed Completed all Characteristic Home Telephone components Parent Care giver Second Male 3 711 77 3 613 77 3 467 77 Female 424 9 414 9 398 9 No 2nd Parent 702 15 668 14 622 14 4 837 4 695 4 487 ATSI No 4 068 84 3 964 84 3 805 85 Aboriginal and or Torres Strait 63 1 59 1 56 1 Refused 4 0 4 O 4 0 No 2nd Parent 702 15 668 14 622 14 4 837 4 695 4 487 Education Tertiary Education 1 584 33 1 541 33 1 483 33 No Te
32. databases including British food tables Food Standards Agency 2002 New Zealand food tables Athar et al 2006 Danish food tables M ller et al 2005 United States Department of Agriculture USDA 2006 Australian food and supplement label data Recipes Supplement data provided by the TGA Other imputed calculated or taken from the 1995 NNS database AUSNUT 1997 Development of the nutrient database A subset of NUTTAB 2006 was used as a basis for developing the survey specific database AUSNUT 2007 The subset was developed by reproducing foods published in NUTTAB 2006 that were likely to be relevant to the survey and ensuring full coverage of all nutrients to be reported as part of the survey This involved incorporating e unpublished nutrient data from an analytical program which collected analytical data for approximately 40 foods that form the major nutrient sources for children aged 2 to 15 years e imputed borrowed estimated and calculated nutrient data Dosage unit in this Survey refers to one tablet or capsule or to 1ml or 1 g for those supplements supplied in liquid or powder form respectively 46 The nutrient composition data developed for survey foods during the collection period were derived using a range of methods These include Matching a single NUTTAB 2006 food to a single survey food Where the description of a food published in NUTTAB 2006 matched that of a survey food the NUTTA
33. for CATI 24 hour dietary recall and 33 minutes for the CATI 48 hour use of time recall Table 7 Overview of survey participation Stage Task Whom 1 Participant RDD recruitment Primary care giver recruitment Receive letter Primary care giver about fieldwork 2 CAPI Consent Primary care giver 2 13 years Primary care giver and child 14 16 years Demographics Primary care giver Dietary recall Primary care giver for child aged 2 8 years child 9 years Food habits question Primary care giver for child aged 2 8 years child 9 years Use of time Child 9 yearst Anthropometric Child measures 3 Pedometer Child 5 years 6 days 4 CATI Dietary recall Primary care giver for child aged 2 8 years child 9 years Use of time Child 9 yearst 26 Table 8 Overview of instrumentation Data collected Instument 24hour dietary recall Life in New Zealand LINZ24 Otago University with modifications 24hour use of time Multimedia Activity Recall for Children and recall Adolescents MARCA UniSA Step count Pedometer New Lifestyles NL 1000 Height Stadiometer Invicta Height Measure Waist circumference Girth Lufkin W606PM metal tape Body weight Tanita HD332 scales Table 9 Weekday distribution of CATI and CAPI interview CAT Not Complete Day of the Week of CAPI Interview Mon m 12 3 106 Tes 104 9 1
34. fs age sizeorder lt fs age sizeorder fs sizeorder lt order sizeorder 1 FS sizeorder lt fs sizeorder FS numt1 Find State and Region for each study child from postcode Sample Region lt factor IncludedPostcodesS Region match wgtdata PC IncludedPostcodes Postcode Sample State lt factor IncludedPostcodesS State match wgtdataSPC IncludedPostcodes Postcode Study Child Sex as numerical value male 1 female 2 Sample Sex lt as numeric factor StChGen levels c Male Female Study Child age and age group calculated from age Some recorded ag groups are inconsistent Sample Age lt as numeric as character wgtdata SCA Sample AgeGrp lt cut Sample Age breaks c 1 3 8 13 16 labels 1 4 117 Calculation of weights Read in Sample and ABS data and determine family structure counts for each cat flush console source data ABSAnalysis r cat flush console source CURFAnalysis txt cat flush console Set up table of population counts sample counts and weights States lt sort unique Boys aggrSState nStates lt length States Regions lt unique Boys aggr Region nRegions lt length Regions Empty table to hold counts wt table lt data frame matrix nrow nStates nRegions 80 4 2 ncol 9 names wt table lt c State Region FS Size AgeGrp Sex Popn Sample Weight Classif
35. interviewers and verifying interviewing technique Section 7 e Outcome evaluation which involves an automated assessment of profile quality The outcome evaluation involved checking each profile for Number of different activities recalled e Average estimated daily energy expenditure Physical Activity Level or PAL Fewer than 10 activities recalled usually signals a poor effort at recall and PALs lt 1 1 or gt 3 0 multiples of estimated resting metabolic rate are considered suspicious Profiles meeting any of these criteria were examined on an individual basis In some cases the interviewer had noted a plausible reason e g that the child was sick or engaged in a sports competition In these cases the profiles were retained Pedomety Quality assurance of pedometer data Eighty three percent of participants who wore a pedometer returned a log sheet In most cases the pedometer logs were able to be validated by 3 5 days of data stored in the pedometer To be retained for analysis a participant s pedometer data met the following criteria e Minimum of 6 days of data provided e Oneach of these days there was a minimum of 1000 reported steps e Oneach of these days the pedometer was not removed for more than 4 hours 240 minutes Each day of data was sorted by number of steps distance MVPA and also a ratio of steps distance to find those that were at the extremes Outliers were then looked at on a case by case basis to see i
36. the family structure for each study child NOTE the term child always means a person aged from 2 to 16 according to the CURF age data a child of Parent x means a child with relationship code 6 to 12 for Parent x There is some apparent inconsistency in the identification of relationships in the data For simplicity any relationship from 6 to 12 with the Parent s will be taken to indicate a child in the same family as the study child tidy up from past runs while wgtdata in search detach wgtdata while sink number gt 0 sink Read survey data curf lt read csv CURF_201007 csv sep header TRUE strip white TRU fl Read file containing short names new names lt read csv VarNames csv sep header FALSE Apply short names names curf lt new names 2 Include only those children recruited and interviewed wgotdata lt curf curf Rec Recruited amp curfSCAPSt INTERVIEW attach wgtdata Create Family Structure identifiers for each study child Identify other children in the household with the same parents Get the age of Person 4 to Person 12 PersonAge lt wgtdata paste P 4 12 A sep 116 Relationship code to Parent 1 of Person 4 to Person 12 RelP1 lt wgtdata paste P 4 12 RelP1 sep Is Person 4 to 12 a child of parent 1 ChildofPl lt RelP1 gt 6 amp RelP1 lt 12 amp PersonAge gt 2 amp Pe
37. the various Total columns omitted The column headers are Xwxyz where w no of 2 3yos x no of 4 8yos y no of 9 13yos z no of 14 l6yos 115 Count of number of families with family structure i table2 lt read csv Table2 csv sep Reorder to have one row for each postcode and family structure Table2 long lt reshape table2 varying list names table2 1 direction long times substr names table2 1 2 5 timevar FS idvar postcode Omit excluded postcodes Table2 long lt Table2 long Table2 longSpostcode in IncludedPostcodes Postcode Append Region information based on postcode Table2 long lt cbind Table2 long IncludedPostcodes match Table2 longSpostcode IncludedPostcodes Postcode c 3 12 Aggregate postcode values to State x Region Table2 aggr lt aggregate Table2 long x0000 by list FS Table2 long FS Region Table2 long Region State Table2 longSState sum names Table2 aggr 4 lt Count Replace the FS strings by th quivalent numerical values Table2 aggrSFS lt rep 0 80 13 Read and process Nutrition Survey data Code to set up sample data ready for weighting calculations Since Household and Family size data from ABS seem to be inconsistent this analysis will neglect the small number of multifamily households and calculate weights purely on the basis of family structure Thus the only calculation needed here is the identification of
38. to 143 in main paf percentiles by age sex report and day type school vs non school days Raw profiles Raw profiles are txt files one for each 24 hour recall The filenames obey the following convention M lt participant ID gt lt date recalled gt txt for example M 110006 14Mar07 txt MARCA profiles consist of a single line of data with items separated by commas Here is an example 110006 14 March 2007 18 February 1994 Girl 999 999 13 07 Summer Heights High School ABE006 01 07 00 am 09 00 am 11 00 am 01 00 pm 03 00 pm 08 30 om 07 00 am 07 05 am 005 02 7 533020 dressing amp undressing 07 05 am 07 10 51 am 005 02 0 531010 brushing teeth 07 10 am 07 35 am 025 02 5 430140 packing unpacking bag 07 35 am 07 40 am 005 01 5 522030 eating sitting 07 40 am 08 00 am 020 01 2 121050 watching TV sitting 08 00 am 08 05 am 005 04 2 240092 walking carrying a load medium 08 05 am 08 30 am 025 03 8 341901 playground equipment eg monkey bars light 08 30 am 08 45 am 015 01 3 221120 riding in a bus 08 45 am 08 55 am 010 02 9 240051 walking light 08 55 am 09 00 am 005 05 0 341990 mucking around outdoors 09 00 am 10 00 am 060 01 4 420060 writing sitting 10 00 am 11 00 am 060 01 2 121050 watching TV sitting 11 00 am 11 25 am 025 01 5 124090 sitting talking 11 25 am 12 25 pm 060 01 4 420040 taking notes class discussion 12 25 pm 01 00 pm 035 01 4 420110 sitting quietly eg assembly listening to teacher 01 00 pm
39. to be entered including recipes and the ingredients portion size and brand and product name if applicable e 3d pass A recall review was used to make corrections or additions The interviewer read aloud all items time and place of consumption brand and product name recipe details and portion size All elements of the recall could be edited Items could be deleted and new items added Interviewer variability was minimised by the fixed structure of the interview process and the probe questions A comprehensive food list and brand name data base enabled interviewers to immediately identify the item during the interview reducing the possibility of errors associated with the subsequent food coding Foods brand and product names and portion sizes that were not listed in LINZ24 could be entered as free text description and subsequently coded by CSIRO dietitians Permission to modify LINZ24 was given and the adaptations made by CSIRO included e Addition of an Australian brand and product names list provided by FSANZ for commonly consumed foods under major food group categories biscuits bread butter and margarine cereal dietary supplements energy drinks ice cream novelty i e stick ice cream take home i e tub juice cordial and powdered beverages milk wrapped snack bars yoghurt and dairy foods e Modification of some food names to reflect Australian terminology e Addition of foods commonly consumed in
40. transport equipment A minimum of two measurements were taken for each anthropometric variable A third measure was taken where the second measure was not within 5 mm for height 0 1 kg for weight and 10 mm for waist girth The mean value was used as the final score if two measurements were taken The median value was used as the final measure if three measurements were taken Height Height was measured on all consenting participants who were able to stand upright and stand still enough while height was measured Height was measured without shoes or thick socks The stadiometer was checked before each use against a steel girth tape to ensure correct assemblage The participant stood with the heels together and the heels buttocks and upper part of the back touching the upright of the stadiometer The head was kept in the Frankfort plane while the participant held a deep breath during the measurement In a few cases particularly among the very young children the interviewer was unable to take a measure due to a restless or uncooperative participant Reasons for missing data were recorded by the interviewer A loss of 1 in height is common over the course of the day The time of measurement was automatically recorded by the interview software Weight Weight was measured in light indoor clothing with shoes coats and jumpers removed using Tanita HD332 portable electronic scales The scale was placed on a hard even surface not carpet The
41. were calculated Estimates of usual intakes should be utilised when comparing intakes to recommended Nutrient Reference Values and when trying to estimate the prevalence of potentially inadequate intakes in the population On any one day children may report very high or very low intakes that are not representative of their usual intake Nutrient requirements are recommended amounts to be consumed over the longer term and so relate to usual nutrient intakes therefore the effects of daily variation within individuals needs to be minimised for the purposes of comparing population intakes to the Nutrient Reference Values The C side software package Software for intake distribution estimation developed by lowa State University was utilised to obtain estimates of usual nutrient intake distributions This analysis entailed the following e preliminary data adjustment to incorporate the population weightings e transformation of data to normal distributions e estimation of within and between individual variances These variances are used to determine the distributions of Usual nutrient intakes e reversion of the data to the original scale providing 59 e population nutrient usual intake means and standard deviations medians and perceniiles This effectively removes the effects of within individual variability e percentage consuming comparison less than the EAR or Al where appropriate The C side software includes the same capacity for d
42. work if aged 65 only gt Go to J7 1 hour or more 000 gt Write number Hours gt go to J8 Less than 1 gt hour go to J5 1 Yes full time work 2 Yes part time work 3 Yes casual work 4 No gt Go to J7 5 Don t know gt Go to J7 1 Yes gt Go to J10 if no parent 2 2 No gt Go to J10 if no parent 2 1 Within the last three months 23 up to 6 months ago 3 6 up to 12 months ago 4 1 up to 2 years ago 5 2 up to 5 years ago 6 More than 5 years ago 7 Has never worked for 2 weeks or more Parent 2 1 Yes gt Go to J4 2No 3 Permanently unable to work gt Goto J7 4 Permanently not intending to work if ged 65 only gt Go to J7 Q 1 Yes gt Go to 17 2 No 3 Permanently not intending to work if aged 65 only gt Go to J7 1 Yes 2No gt Goto J5 3 Permanently not intending to work if aged 65 only gt Go to J7 1 hour or more oo00 gt Write number Hours gt go to J8 Less than 1 gt hour go to J5 1 Yes full time work 2 Yes part time work 3 Yes casual work 4 No gt Goto J7 5 Don t know gt Go to J7 1 Yes gt Go to J10 if no parent 2 2 No gt Go to J10 if no parent 2 1 Within the last three months 2 3 up to
43. 0 99 2 0 80 1233 n os 9n BEE 657 687 63 30 760 62 From this total of 4837 4 487 provided complete data sets from both the CAPI and CATI interviews 27 9 Demographic Questionnaire The demographic data items relating to each participant and their household was collected at the CAPI Responses were provided by the parent or care giver of the participant Section19 Section 20 Household composition e Postcode of residence e State of residence e Number of adults in household aged gt 16 years e Number of children in household aged lt 16 years e Household type Family Type and Household members Parent 1 was the primary care giver who knew most about the child s food intake or activity and Parent 2 was their spouse or significant other care giver in the household Parent 1 e Gender Age e Aboriginal and Torres Strait Islander ATSI e Country of Birth e Language spoken e School Education e Higher Education Parent 2 e Gender e Relationship to Parent 1 e ATSI e Country of Birth e Language spoken e School Education e Higher Education Study Child e Gender e Child Age e Date of Birth e Relationship to Parent 1 e Relationship to Parent 2 e ATSI e Country of Birth e Language Spoken e Medical Condition Other Person e Gender e Age e Relationship to Parent 1 e Relationship to Parent 2 28 Income and Occupation Parent 1 Worked last w
44. 007 by the Commonwealth Scientific and Industrial Research Organisation CSIRO and the University of South Australia UniSA on behalf of the Commonwealth Department of Health and Ageing DOHA the Department of Agriculture Fisheries and Forestry DAFF and the Australian Food and Grocery Council AFCG Food beverage dietary supplement nutrient intake food habits demography anthropometry and objectively and self reported physical activity were measured in 4 487 children aged 2 16 years The information from the survey will enable food beverage supplement and nutrient intakes among children to be assessed against the Dietary Guidelines for Children and Adolescents in Australia the Australian Guide to Healthy Eating and the revised Nutrient Reference Values for Australia and New Zealand and e physical activity levels among children to be assessed against the National Physical Activity Guidelines for Children and Young People Existing information National Surveys This is the first survey to combine nutrition and physical activity in the one survey The last national survey which collected anthropometric data and quantitative information on children s food and beverage intake was the National Nutrition Survey conducted in 1995 while the last survey to collect data on physical activity was the Australian Health and Fitness Survey in 1985 Since then many state and regional surveys have collected data on various aspects of chi
45. 01 05 pm 005 02 0 532140 drinking while standing 01 05 pm 01 30 pm 025 05 0 341990 mucking around outdoors 01 30 pm 02 00 pm 030 01 5 124090 sitting talking 02 00 om 02 25 om 025 03 8 331991 totem tennis light 02 25 pm 03 00 pm 035 03 8 342241 hand tennis four square light 03 00 pm 03 05 pm 005 01 3 221000 riding in driving a car 03 05 pm 03 10 pm 005 02 5 430140 packing unpacking bag 03 10 pm 03 20 pm 010 02 7 533020 dressing amp Undressing 03 20 pm 03 25 pm 005 01 5 522130 drinking sitting 03 25 pm 05 30 pm 125 01 2 121050 watching TV sitting 05 30 pm 05 55 pm 025 01 4 521080 sitting in bath 05 55 pm 06 00 pm 005 02 7 533020 dressing amp undressing 06 00 pm 06 20 pm 020 01 5 522030 eating sitting 06 20 pm 06 50 pm 030 02 3 630270 washing or clearing dishes 06 50 pm 08 00 pm 070 01 1 111030 watching TV lying quietly 08 00 om 08 30 pm 030 02 7 533050 getting ready for bed 08 30 pm 07 00 am 630 00 9 100010 sleeping The data format for MARCA profiles is Item Item name aARKRWN participant ID date of test date of birth Sex height weight age school comments random ID interviewer ID empty empty used if bedtime is after midnight wake up time school s in time school day or breakfast time non school day start of recess school day or lunch time non school day start of lunch school day or dinner time non school day school s out time school day or bed time non school day bed time
46. 1 totem tennis light 321950 playing with animals sitting 331992 totem tennis medium 341293 playing with animals walk run hard 341683 trampoline hard 341291 playing with animals walk run light 341681 trampoline light 341292 playing with animals walk run medium 341682 trampoline medium 321920 playing with toys lego dolls action figures 342860 wrestling with mates 110 Sport MARCA codes and activity names for activities included under the organised sport and play category code activity code activity 341753 aerobics health hustle hard 342382 netball medium 341751 aerobics health hustle light 341393 orienteering hard 341752 aerobics health hustle medium 341391 orienteering light 331000 archery 341392 orienteering medium athletics track and field hurdles 341663 steeplechase hard 342403 paddleball hard athletics track and field hurdles 341661 steeplechase light 342401 paddleball light athletics track and field hurdles 341662 steeplechase medium 342402 paddleball medium 341653 athletics track and field jumping hard 332040 pool billiards snooker 341651 athletics track and field jumping light 341893 race walking hard athletics track and field jumping 341652 medium 341891 race walking light 341673 athletics track and field throwing hard 341892 race walking medium 341671 athletics track and field throwing light 342433 racketball hard athletic
47. 2 months have you always had sufficient money to buy food If no did you go without food Has child ever been breastfed Number of weeks breastfed Number of months breastfed Has child ever been given infant formula regularly Number of weeks formula fed Number of months formula fed Age in weeks child was first given solid food regularly Age in child respondent was first given solid food regularly Birth weight pounds Descriptors Whole full cream Low reduced fat Skim Evaporated or sweetened condensed Soy milk None of the above Does not drink milk or Don t know Less than one serve One serve Two serves Three serves Four serves Five serves Six or More serves or Don t eat vegetables Less than one serve One serve Two serves Three serves Four serves Five serves Six or More serves or Don t eat fruit Yes usually Yes sometimes No Don t know Yes usually No Don t know Yes usually Yes sometimes No Don t know Yes usually No Don t know Yes No Refused Yes No Refused Yes No 3 Don t know PRON HKHWNHKHRWNHKHONAOKRWBNHNHKHONAOAKRWBNH KH ONAOKRWDN WNHN WN ON Y Yes 2 No 3 Don t know Birth weight of child portion in pounds Population All All All All If answered 1 or 2 above All If answered 1 or 2 above All If answered 2 above All If ever breastfed If ever breastfed All If ever formula fed I
48. 8cm x 4cm the food model booklet was used to determine these proportions see below and the volume is automatically calculated by LINZ24 CSIRO dietitians subsequently converted the volume to mass Once the portion size was entered interviewers were prompted to ask how many of these did you have allowing entry of fractions or multiple serves consumed e g 0 5 of a banana or 3 slices of bread Food model booklet amp measuring aids To assist with estimation of portion sizes participants received a food model booklet and interviewers had a set of measuring aids The Food Model Booklet was developed based on a booklet used by the United States Department of Agriculture USDA with permission It was modified for Australian foods and adapted for children Its use in children aged 10 years was validated at the time of the pilot survey The validation showed moderate to strong correlations between weighed portion and recalled portion for almost all foods and that recall can be considered a reasonable interpretation of actual consumption at the group level The booklet was used during the CAPI and remained with the participants for reference during the CATI 31 The booklet included e Life size drawings of mugs glasses other beverage containers bowls take away food containers cans and pats for different soreads e Amorphous mounds suitable for measuring foods e g mashed potato rice or peas e Life si
49. API Following completion of the CAPI participants were provided a randomly generated date for the CATI which was 7 21 days after the CAPI The date was rescheduled if participants could not undertake the CATI on that date The CAPI was conducted in the home of the study child The primary caregiver or a responsible adult provided consent for children aged less than 14 years Children aged 14 16 years provided their own consent along with that of a parent or responsible adult The CAPI gathered household demographic data 24 hour dietary recall food habits weight height and waist circumference measurements and physical activity over 48 hours depending on the age of the child Pedometers were fitted to children aged 5 years and over CATI were conducted to gather a second 24 hour food recall and a second 48 hour physical activity recall Separate telephone calls were made for the CATI food and activity recalls minimising respondent fatigue The measures and details of who provided the information are summarised in Table 7 Equipment is described in Table 8 Interview length The average CAPI interview length varied according to the age of the child being interviewed and the number of tasks that needed to be completed The average CAPI interview length for children aged 2 4 years was 71 minutes 85 minutes for children aged 5 8 years and 118 minutes for children aged 9 16 years The overall average telephone interview length was 37 minutes
50. Australia e Modifications to the serving sizes where these varied between Australia and New Zealand e Modifications to the probe questions to reflect the Australian food supply and cooking methods 30 For each food entered time of consumption and information on the place of consumption was obtained according to whether they were consumed at Home Any other residence e g friend or relative e Place of purchase e g caf or fast food outlet e Institution e g school pre school after school care e Leisure activity sport music lesson cinema park e During transport e g bus car walking e Other When ingredients were known recipes for mixed dishes were entered as either the whole recipe with the fraction of the recipe the participant consumed or the amount of each ingredient consumed by the participant Cooking methods available in the recall software were e Not cooked e Unknown method e Baked roasted e Stewed Boiled simmered poached e Steamed e Grilled BBQ e Deep fried submerged in fat e Pan Fried shallow fat e Stir fried minimal fat Microwaved The options for entering portion size information were e Direct entry where the amount is known e g 20 g packet of crisps e Adrop down list of measure descriptors relating to that particular food e g one cup of cooked rice e The dimensions of the food e g slice of lasagne can be entered as 10cm x
51. B 2006 nutrient data were used without amendment Combining several NUTTAB 2006 foods to produce a single survey food Where a description of a survey food was less specific than a NUTTAB 2006 food nutrient data from several NUTTAB 2006 foods were combined to produce a representative nutrient profile for the survey food This approach was used for most of the fruits and vegetables consumed during the survey where the cultivars were not reported For example the different cultivars of peeled potatoes including coliban sebago desiree and pontiac were weighted according to their approximate market share to produce a representative nutrient profile of Potato unspecified variety amp skin peeled raw Modification of a NUTTAB 2006 food to produce a new survey food Where the description of a NUTTAB 2006 food was similar to a survey food except for a particular characteristic the NUTTAB 2006 food was modified to account for that characteristic This approach was used for many of the low or reduced fat reduced salt fortified or intense sweetened varieties of products consumed during the survey These characteristics were modified by e Imputing nutrient data from a similar NUTTAB 2006 food for example if a respondent reported consuming Milk flavoured banana reduced fat the NUTTAB 2006 food Milk flavoured banana regular fat would be used as a basis for developing a new record and the fat content would be modified based on the fa
52. D4 What was age last birthday e D5 Whatis date of birth D6 How iis related to parent 1 Family Details Parent 1 1 legal spouse 2 de facto partner 3 other relative in aw 4 boarder housemate 5 unrelated adult Parent 2 Partner D D MMY Y 6 biological child 6 biological child 7 adopted child 7 adopted child 8 step child 8 step child 9 foster child 9 foster child 10 grandchild 10 grandchild 11 niece nephew 11 niece nephew 12 cousin 12 cousin 3 other relative in 3 other relative in aw aw 13 unrelated child 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult Study Child Person 4 75 D7 Howis related to parent 2 partner D8 Is of Aboriginal or Tones Strait Isander origin D9 In which county was bom 1 No slander 4 Yes both all countries 2 Yes Aboriginal 3 Yes T Strait nsert SACC codes for 6 biological child 6 biological child 7 adopted child 7 adopted child 8 step child 8 step child 9 foster child 9 foster child 10
53. I This provided an objective estimate of overall activity levels Weight height waist circumference and recalled birth weight were collected for all participants during the CAPI Demographic and socioeconomic data were collected from the primary caregiver during the CAPI including state territory of residence child s country of birth primary care giver s education level household income and Indigenous status The data were checked cleaned and collated into an electronic database The Department of Health and Ageing will manage and administer these data at the completion of the survey A summary of the data collected is provided in Table 1 Table 1 Summary of data collected and target number Data Age Data collected Target Achieved group years Demographic and socioeconomic 2 16 CAPI 4 400 4 837 information Physical measurements 2 16 CAPI 4 400 4 745 Foods habits questionnaire 2 16 CAPI 4 400 4 837 2 x 24 hour dietary recall of foods 2 16 CAPI amp CATI 4 400 4 437 beverages and dietary supplements 4 x 24 hour use of time recalls 9 16 CAPI amp CATI 2 200 2 246 Objective physical activity 5 16 Between CAPI amp 2 750 2 829 measurements at least 6 days CATI pedometer data CAPI computer assisted personal interview CATI computer assisted telephone interview Survey arrangements This survey was jointly funded by the Commonwealth Department of Health and Ageing
54. MS sitting 134180 sending text messages SMS standing 121130 sitting at the movies cinema theatre 732201 playing video centre e g Intencity Timezone games light 732202 playing video centre e g Intencity Timezone games medium 732203 playing video centre e g Intencity Timezone games hard 114 24 R code for non proportionate sampling weights Read and process ABS data files Read in data from files provided by ABS Read Postcodes with State and Region Capital vs Rest of State Note Postcodes and ABS Postal Areas are taken to be the sam postcodesl csv is from the CURF which shows the excluded postcodes allpostcodes lt read csv postcodesl csv sep names allpostcodes 2 lt Region Remove postcodes excluded from the survey IncludedPostcodes lt allpostcodes is na allpostcodesSExcluded Table 1 contains household data which is used only to determine the sex ratios for each Region Tablel csv is a simplified version of the ABS file 2006 Census Table 1 No of occupied private dwellings by no of males aged 2 16 by females aged 2 16 xls Count of Dwellings by number of males amp females aged 2 16 One row for each postcode tablel lt read csv Tablel csv sep Remove excluded postcodes tablel lt tablel tablelSpostcode in IncludedPostcodesSPostcode tablelSRegion lt IncludedPostcodes Region match tablel postcode IncludedPostcodesS Postcode tablel
55. S State lt IncludedPostcodes State match tablelSpostcode IncludedPostcodesS Postcode First digit in X fields is female second is male Calculate the number of Boys and Girls in each Postcode Boys lt table1l X01 table1 X11 tablel1 X21 table1 X31 2 tablel x02 2 table1l Xx12 2 tablel X22 2 table1 X32 3 tablel x03 3 table1 X13 3 tablel X23 3 tab le1 X33 Girls lt table1 X10 table1 X11 2 table1 X21 3 table1 X31 2 table1 X20 table1 X12 2 table1 X22 3 table1 X32 3 table1 X30 table1 X13 2 table1 X23 3 tabl 1 X33 Aggregate postcode values to State x Region Boys aggr lt aggregate Boys by list Region table1 Region State tablelSState sum names Boys aggr 3 lt Count Girls aggr lt aggregate Girls by list Region table1 Region State tablelSState sum names Girls aggr 3 lt Count Calculate proportions of Boys and Girls for each Region Sex ratio lt cbhind Boys aggr Girls aggr Count names Sex ratio 3 4 lt c Boys Girls Sex ratioSTotal lt Sex ratio Boys Sex ratio Girls Sex ratio Pr Boy lt Sex ratio Boys Sex ratio Total Sex ratio Pr Girl lt Sex ratio Girls Sex ratio Total Table 2 contains counts of families by family structure Table2 csv is a simplified version of the ABS file 2006 Census Table 2 No of families by No of children aged 2 3 by No aged 4 8 by No aged 9 13 by No aged 14 16 Po csv in particular with
56. Studies University of Queensland Professor Robert Newton BHMS Hons MHMS PhD AEP CSCSD FAAESS Foundation Professor Exercise and Sport Science Edith Cowan University Professor Martin Silink AM MB BSc Hons MD FRACP Professor of Paediatric Endocrinology University of Sydney Dr Ann Cowling PhD Ms Janis Baines BA Hons Chemistry MSc Human Nutrition Section Manager Food composition Evaluation and Modelling Section FSANZ Dr Amanda Lee Manager Nutrition and Physical Activity Health Promotion Unit Queensland Health Food composition Team prepared the food composition data base The members of the Food Composition Team were FSANZ Ms Janis Baines BA Hons Chemistry MSc Human Nutrition Section Manager Food composition Evaluation and Modelling Section FSANZ Dr Judy Cunningham BSc Food Tech PhD Food Composition Studies Ms Renee Sobolewski BAppSc Human Nutrition Mr Charles Wannop Database Support IT Contractor Millpost Technologies Pty Ltd Therapeutic Goods Administration Mr Shaun Flor ELF Technical Manager Listed Medicines and Communication Section Office of Complementary Medicines TGA 4 Background Introduction The most recent National Nutrition Survey NNS was conducted in 1995 and the last National Physical Activity Survey was in 1985 The intervening decades have seen substantial changes in the Australian food supply and eating habits an increase in technologies that facilitate sedentary
57. Transport Sport and Play School Self Care Chores and Miscellaneous If the activity required is not available in the activity compendium the participant can enter the activity as other and enter a text description Each child recalled a total of four days two days prior to the CAPI and two days prior to the CATI During both the CAPI and CATI the child recalled the two days in either order Pedometry Pedometers were used to collect objective physical activity data for most participants aged 5 16 years The pedometer used in this survey was the New Lifestyles NL 1000 which provides the number of steps a day the distance covered and the number of minutes spent in moderate to vigorous physical activity MVPA gt 3 metabolic equivalents METs The pedometer was worn for 7 consecutive days by attaching to a belt or waistband in a position corresponding to mid thigh on the right side of the body A security strap and clip was used to secure the pedometer in place and to prevent loss of the pedometer if it slipped from its position At the CAPI the participant or a parent was instructed on how to retrieve data from the pedometer and how to complete the log sheet The participant was asked to wear the pedometer from when he or she got out of bed in the morning until going to bed at night Those occasions when the pedometer was removed e g showering swimming or playing contact sports were recorded on the log sheet along with the
58. User Guide 2007Australian National Children s Nutrition and Physical Activity Survey Prepared for DEPARTMENT OF HEALTH AND AGEING mesoa GI I view Table of Contents 1 List OF Abbreviati nse sansa shail satacecti ta daca e siapideadetela a aa a ea aiaa 4 PAE a 1111 EE A E EEE 5 Dh Pr ject TeamMeron ir n iE E EEA E A E A E 6 4 Backer und nnm a a inns E a 8 Titrod Cti oN Weer eee Ree ne er entre aa ET tet her Seer Serpe E A aT a aAa eee Eee 8 Existing informati m e renan ean Mai yastet ea taa E TERN 8 Survey develop E r Sis sss acy os ON 11 Survey objectives and overview wczszsdelasteessua dees leasannsobevaeassuacsuenstes teseaeenstedsiaszawetes 12 Survey arrangements sisin teii ern e ai E S A R E A E S 13 Ethics and Comrie mtr ale ya 5 4542 doccascoeaedsideecadadseaeae ds saccosaoseeeeedi dace eee 15 De PU A T cess aeeanala ets fase pn nd ge LR AS 16 6 4 S fvEy TESTO oii ciwariavadreaertatmn tia EA EEEE A AREN NERE EE AEEA A R Eia 17 Sample DESI sccjesssvecadsvesgeceis o a a A satan E E E ders 17 Sample selections isnan o a T E a 18 Scope and covera Sennen a EE gees bat aes eot sateen aaeet 22 7 Interviewer training and Supervision sssessseesseeseeessseesserssersserersseessresserssee 24 8 Datac llecti nszsennnns nn E E E E E RR 26 9 Demographic Quest ONNGILE cei sisecas usstdsievescdslaus sual cheng teased tteaddla sa eediawbeces 28 10 Food and Nutrient TALON aiaciais i catia ile dlon ieee tastes ssiicc
59. Yoghurts SOUP Soup Prepared Ready to Eat Dry Soup Mix 104 1995 Food Code 203 21 211 212 22 221 222 224 225 23 231 232 233 234 235 236 237 238 239 241 242 25 251 252 253 254 2542 26 261 262 263 27 271 272 273 28 281 282 283 284 29 Food Group Name Canned Condensed Soup SEED and NUTPRODUCTS AND DISHES Seeds And Seed Products Nuts And Nut Products SAVOURY SAUCES AND CONDIMENTS Gravies And Savoury Sauces Pickles Chutneys And Relishes Salad Dressings Stuffings VEGETABLE PRODUCTS AND DISHES Potatoes Cabbage Cauliflower And Similar Brassica Vegetables Carrot And Similar Root Vegetables Leaf And Stalk Vegetables Peas And Beans Tomato And Tomato Products Other Fruiting Vegetables Other Vegetables And Vegetable Combinations Dishes Where Vegetable Is The Major Component LEG UME AND PULSE PRODUCTS AND DISHES Mature Legumes And Pulses Mature Legume And Pulse Products And Dishes SNACK FOODS Potato Snacks Corn Snacks Extruded Snacks Pretzels And Other Snacks Other Snacks SUGAR PRODUCTS AND DISHES Sugar Honey And Syrups Jam And Lemon Spreads Chocolate Spreads Dishes amp Products Other Than Confectionery Where Sugar Is Major Component CONFECTIONERY AND HEALTH BARS Chocolate And Chocolate Based Confectionery Cereal Fruit Nut And Seed Bars Other Confectionery ALCOHOLIC BEVERAGES Beers Wines Spirits Ot
60. achieved The data were collected at a face to face home visit computer assisted personal interview CAPI and a subsequent telephone interview computer assisted telephone interview CATI conducted 7 21 days after the CAPI Food beverage and dietary supplement intakes were collected from all participants using a standardised computer based three pass 24 hour recall methodology during the CAPI and the CATI a total of two days dietary recall per child The food and beverage intake data were translated to daily nutrient intake data using a specifically designed Australian nutrient composition database AUSNUT 2007 Each child and or parent was asked questions relating to food habits during the CAPI such as usual consumption of fruits vegetables type of milk use of salt and earlier infant feeding practices Two consecutive days of physical activity and use of time recall data were collected for children aged 9 16 years using validated use of time software during the CAPI and the CATI a total of four days activity recall per child Minutes spent in various activities and energy expenditure over 4 days was estimated from these data Pedometers were worn over 6 days in 5 16 year old participants to collect objective information on the number of steps each child took and minutes of moderate to vigorous physical activity each day The stride length of each child was measured 12 and the pedometers were fitted during the CAP
61. all information that you give me will be kept confidential and we have strict processes to ensure the security of your information will start by asking a few questions about the household how many people live here and a little bit about each person also will ask about study child s general family background such as your and your partner s work and educational background This will give us a general idea of the home environment study child grows up in Then will ask the child some questions about their food intake and what they have done over the last 48 hours am also going to ask if can take some measurements of your child such as his her weight height and waist circumference will then ask the child to conduct a stride test and show you how to wear the pedometer which we ask they do over the next 7 days There will be a few questions on general food habits and finally will ask you some questions about your housing and income Once have finished asking you questions have a short form that will ask you to fill in by yourself and return with the pedometer in the envelope supplied Before we start will need to obtain your formal consent for this study will read you a statement and you will need to provide your signed agreement to take part in the study So that s generally what we are going to be doing do you have any questions at this point Dol have your agreement for you to be part of this study will
62. amin milligrams Riboflavin milligrams Niacin equivalents total milligrams Vitamin C milligrams Vitamin D micrograms Vitamin E as alpha tocopherol milligrams Total Folate micrograms Dietary folate equivalents micrograms Minerals amp electrolytes Potassium milligrams Sodium milligrams Calcium milligrams Phosphorus milligrams Magnesium milligrams Iron milligrams Zinc milligrams lodine micrograms Other Caffeine milligrams 95 Amount of each nutrient per 1000 kJ of energy consumed per person per day Percentage contribution of macronutrient to energy intake per person per day Food intake the previous day compared to usual intake As listed above All Protein All Fat total Saturated fatty acids total Monounsaturated fatty acids total Polyunsaturated fatty acids total Carbohydrate total Sugars total FOOD AND NUTRIENT INTAKE THE PREVIOUS DAY summary information available per person per day including intake from dietary supplements Data Items Allas above Starch Alcohol All Was the recalled day unusual All who reported unusual recall Comments about why recalled day was unusual day Descriptors Population 96 PHYSIC AL MEASUREMENTS Data Items Height measurements cm Height cm Weight measurements kg Weight kg Waist girth measurements cm Waist girth cm Method used for measuring waist girth BMI Reason for non completion of
63. behaviour e g video games and mobile phones and changing family life and structure e g increased participation of both primary and secondary care givers in the workforce All of these factors are likely to impact on what children eat and what they do Indeed the prevalence of overweight and obesity has rapidly increased since the mid 1980s State based surveys indicated that currently 5 of Australian children are obese and a further 20 are overweight using internationally agreed criteria National level data on children s intake and energy expenditure are needed for monitoring and understanding weight status and to assess the adequacy of children s diets and activity patterns The Dietary Guidelines for Children and Adolescents in Australia was published by the National Health and Medical Research Council NHMRC in 2003 In 2004 the Department of Health and Ageing issued the National Physical Activity Guidelines for Australians with recommendations aimed at children aged 5 18 years and included recommendations for limiting screen time television computers and video games National level dietary intake and physical activity data are needed to assess progress against these guidelines for the development of future guidelines and to inform interventions designed to improve nutrition and increase physical activity levels The Australian National Children s Nutrition and Physical Activity Survey was conducted between February and August 2
64. borated with CSIRO to develop the nutrient composition database AUSNUT 2007 Funding for FSANZ was provided by the Department of Health and Ageing FSANZ also liaised with the Therapeutic Goods Association TGA in relation to the nutrient composition of supplements 14 Ethics and confidentiality Ethics approval covering ethical privacy and confidentiality was obtained from the NHMRC registered Ethics Committees of CSIRO and UniSA for all of the components of the survey including the pilot study and any subsequent changes to the original protocol Relevant NHMRC guidelines for research involving children were also adhered to The sub contractor I View complied with the Australian Market and Social Research Organisations Market and Social Research Privacy Principles the European Society for Opinion and Marketing Research ESOMAR World Research Codes guidelines for interviewing children and young people and the International Chamber of Commerce ICC ESOMAR International Code of Marketing and Social Research Practice The project team l view supervisors and interviewer team signed a deed of confidentiality with the Commonwealth Department of Health and Ageing 15 5 Pilot A pilot took place in Whyalla South Australia and in two cluster areas of Brisbane North and South Queensland in October 2006 The objectives of the pilot were to e test the effectiveness of proposed survey methodology excluding recruitment e refine t
65. ce to height The force the body exerts in a standard gravitational field Body mass is measured with the subject in light indoor clothing 121 26 Units of measurement g grams kJ kilojoule mg milligram u microgram MET metabolic equivalent 122 27 References Abbott RA Macdonald D Mackinnin L Stubbs CO Lee AJ Harper C Davies PSW 2006 Healthy Kids Queensland Survey Summary Report Queensland Health Brisbane 2007 Athar N McLaughlin J Taylor G Mishra S 2006 The Concise New Zealand Food Composition Tables 7th edition Palmerston North New Zealand Institute for Crop and Food Research Australian Bureau of Statistics 1998a National Nutrition Survey Users Guide 1995 cat no 4801 0 ABS Canberra Australian Bureau of Statistics 19986 National Nutrition Survey Nutrient Intakes and Physical Measurements Australia 1995 cat no 4805 0 ABS Canberra Australian Bureau of Statistics 2006 National Health Survey Summary of Results Australia 2004 05 cat no 4364 0 ABS Canberra Booth M Okely AD Denney Wilson E Hardy L Yang B Dobbins T 2006 NSW Schools Physic al Activity and Nutrition Survey SPANS 2004 Summary Report Sydney NSW Department of Health Cancer Council of Victoria 2006 Australian secondary school students use of alcohol in 2005 Report accessed on line http www health gov au internet drugstrategy publishing nsf Content monoss Cohen J 1988 Statistical power analysis for the behaviou
66. cord Pedometer ID F6 Pedometer ID 6 digit number Record first measure F6 Height data 1 If smaller than 90cm or greater than 200 cm alert the interviewer to CHECK HEIGHT MEASURE But allow to ovenide Record second measure F7 Height data 2 Record third measure F8 Height data 3 ASK IF difference between height 1 and height 2 is 5mm or greater Record first measure F9 Weight data 1 Record Second measure F10 Weight data 2 Record Second measure FLL Weight data 3 ASK IF difference between weight 1 and weight 2 is 0 1kg or greater Record first measure F12 Waist girth 1 Record Second measure F13 Waist girth 2 Record third measure F14 Waist girth data 3 ASK IF difference between waist girth 1 and waist girth 2 is 10mm or greater F15 Waist girth measured over skin clothing Fl5a Comments Automatically recorded measure 83 F16 Final Height c m Automatically recorded measure F17 Final Mass kg Automatically recorded measure F18 Final Waist Girth cm Automatically recorded measure F18 BMI kg m2 F20 Date of measurement Day DATE STAMP AUTOMATICALLY F2LTime of measurement TIME STAMP AUTOMATICALLY Month Year DATE STAMP AUTOMATICALLY DATE STAMP AUTOMATICALLY In
67. current food supply but also maintains comparability with the food groups used in the 1995 NNS Subcategories were added to separate foods on the following basis e Caffeinated or decaffeinated e Sugar sweetened or intense sweetened e Fortified product or unfortified product Additional food groups were added to reflect infant foods and formulae and dietary supplements There are a set of codes that are the same as the 1995 NNS and a second set that reflect the changes described above Quality assurance of nutrient database Quality assurance required detailed scrutiny of nutrient data by trained staff as well as manual checking of some individual intakes and assessment of unusual values Quality assurance on nutrient data is detailed in the AUSNUT 2007 Users Guide 50 Physical activity recall Each activity in the MARCA has a unique ID code and an associated child appropriate energy cost in METs or default adult value Ridley et al 2006 The MARCA s analytical engine allows data to be extracted from MARCA profiles A profile is one 24 hour recall by one child It derives the estimated number of minutes spent on an activity and the amount of energy expended in individual activities or in activity sets such as active transport organised sport play or moderate to vigorous physical activity Activity sets are defined as lists of MARCA codes Section 23 Data format Four types of files contain MARCA data Table e Raw pro
68. d Type Family Type Worked last week Unpaid Work Away from Work Worked hours Number of hours worked Looking for work Full time Looking for work Part time Looking for work Casual Looking for work No Looking for work Don t Know Start Work Last Work Population All All All All All All All All All All All All who have 2nd Parent All who have 2nd Parent All who have 2nd Parent All who have 2nd Parent All who have 2nd Parent All who have 2nd Parent All who have 2nd Parent All who have 2nd Parent All All All All All All All All All All who have Person 4 12 in household All who have Person 4 12 in household All who have Person 4 12 in household All who have Person 4 12 in household All All Parent 1 and Parent 2 where applicable All Parent 1 and Parent 2 where applicable not working in last week All Parent 1 and Parent 2 where applicable not working in last week All working Parent 1 and Parent 2 where applicable All working Parent 1 and Parent 2 where applicable All not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable All not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable All not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable All not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable Al
69. d adjusted for within person variation based on this small sub sample e The repeat 24 hour recall in this survey was conducted with the use of CATI whereas the 1995 NNS repeat 24 hour recall also took place in the form of a personal interview 61 Food nutrient composition database this survey utilised the 2007 AUSNUT database and the 1995 NNS utilised the AUSNUT 1995 database Both of these food composition databases reflect the composition of foods at the time the survey was completed The number of major food groups used to report food intake has been increased to include categories for dairy substitutes and supplements Some additional sub groups have also been created to better reflect the current food supply Comparison with recommendations Comparisons with dietary recommendations The NHMRC has recently released the Nutrient Reference Values for Australia and New Zealand NHMRC 2006 Nutrient Reference Values NRV include a range of values for comparison including the estimated average requirements EAR recommended dietary intakes RDI and adequate intakes Al for 2 3 years 4 8 years 9 13 years and 14 16 years For those aged 14 years and above the acceptable macronutrient distribution range AMDR and suggested dietary targets SDT are set for certain nutrients that may help in prevention of chronic disease The Core Food Groups NHMRC 1995 recommends quantities of cereals fruits vegetables meat and meat alte
70. d cebonassteesanescaptentouedskaatee 30 Food Nta Ken ei esi Sh oN Gh cha Steal ah Raab Shirt Saree cia ual OERE 30 Nu trient Intake nsnsi nen aa R doe dgaes RRE IS 32 Foods Habits Questions cc cccccccccssesssssssecececececsesensececececsesesesseaeeeseeeeseneeenteaeees 32 if Physical ACTIVID anaes p E tors avant aaa EER aE 34 Physical Activity IR CCAM ceased casa ottoind aces ay naceauctiv esau cduuaasauauseasd eos sea EER E 34 Sh IIMS GIF costs teases ventas aaa rege oases nee sea ae 34 12 Physical Measurements ooonoooososeessseeesseeeosseseessssresssseresssereesseseessssseesssseess 35 FAS Sc ices os dear ote aaa n a a a a A NN 35 Welg hte eemo ni onor a a R AEE A eon R 35 B dy Mass d k cne e e ae aa a i e a e r 35 Waist 10 ho Ost E E E T E E T E E Gale RE 35 Wal SETHE TENE ratio eneen a E a N eE REE EEA 35 13 SUTVEY r SpON SE e ie adds E A A E aea ar a Si 36 Measures to maximise TESP ONS C5535 2505 92 fae adn teves seas cushcodcesscsateeafesaeeesoteeos 36 RESPONSE TALES syifa eae a a ER EE E E S 37 Participant characteristi Sssencsinie e a a E E ae 40 14 Data Processin imeni e a R E E A A aa 45 Demographics ssmiers eenas E R E OA EE aaa aS 45 DIA Ea Ke l E EEEE E E EEEE E E EE TE 45 N trent analy S18 se moras de caen Sedation aa at a a shan a a 45 Physical activity TeCall jacis5ieascigesaasaugeadstansdcncnsystaasnaesncedaunteca A R AIR R 51 PCC OPS a EA E E E E E AE E E TAT 57 Physica Meas re Sisiane na a e a E AES 57
71. data on this nutrient have been obtained from a limited range of unpublished analytical data label data overseas food composition databases including the USDA Danish and British food composition tables or by imputation They should be considered as indicative values only and users should be aware that reported values are likely to be revised in subsequent FSANZ publications Total vitamin D activity has been calculated as Vitamin D ug Cholecalciferol ug ergocalciferol ug 5 25 hydroxy cholecalciferol ug 5 25 hydroxy ergocalciferol ug There does not appear to be international consensus on the most appropriate factors to use when reporting total vitamin D activity based on individual vitamins Recent advice Jakobsen pers comm 2008 suggests that total vitamin D values reported in AUSNUT 2007 may significantly overestimate total vitamin D activity Exposure to sunlight is the primary source of vitamin D for humans For most healthy individuals diet does not form a significant source of vitamin D unless supplements are taken The 1995 NNS did not include nutrient intake data on vitamin D 49 Folate total In AUSNUT 1997 the majority of total folate data were derived from overseas food composition tables primarily the British food tables and generated using superseded methods of analysis that may underestimate naturally occurring folate Since 1995 FSANZ has undertaken a number of analytical programs involving folate
72. dents Chi Idren under 15 years and other people Children over 15 only Chi Idren over 15 years and dependent students Chi Idren over 15 years and other people aJJ AJJ N 78 One parent family Children under 15 years only Children under 15 years and dependent students Children under 15 years and other people Children over 15 only Children over 15 years and dependent students Children over 15 years and other people Other Please specify 79 SECTION E Rotate between UNZ24 and MARCA Address Parent if under 9 otherwise Address the child Interviewer Note If child is 9 years and older only rotate between LINZ24 and MARCA If child is under 9 years do the LINZ E1 MARCA Completed gt Only if 9 years or older Day One Yes ONLY No E2 ONLY DAY ONE OF MARCA COMPLETED specify reason E3 MARCA NOTCOMPLEIED spec ify reason E4 LINZ24 Completed gt If 2 8 years only Yes No gt If 9 years or older E5 LINZ24 NOTCOMPLETED specify reason 1 Yes data included E6 CARER FORM USED 2 To be edited later upon return 3 No 80 SECTION F Anthrop Measures and Placement of Pedometer InterviewerNote Only if child is 5 years or older If child is
73. e SSS Ss i ss i es 2 NNNN 3 4 Select child numbered CIES CONO NO S AAUOUUOUONN Number of children aged 2 16 5 aAnMNwRWNDNDN o ROankKWNDNDN 20 The number of children required in the sample for each of the age cohorts was not proportional to the number of children in each of the age cohorts in the population Therefore children aged 2 3 years or 14 16 years had a higher probability of selection than children aged 4 to 13 years in any one household However across the whole population a purely random selection using Kish would produce too many children aged 4 to 13 years than needed for the survey s quota As such the Kish table was biased to select a child in the following order e Child aged 14 16 years then e Child aged 2 3 years and then e Child 4 13 years However this did not rectify the observed skew towards children aged 4 13 years when recruiting participants The result was that a number of in scope households who agreed to participate were not interviewed as the quota of children in their location had been completed Table 5 Table 5 Selected child by the number of children in the household Age group of the child selected Composition of children in the household 2 3 aa 4 8 years 9 13 years 14 16 years 2 3 years 2 8 years a 2 13 years iol fo years years 2 16 years ie als 2 3 and 14 16 bo j years 2 8 and 14 16 be years o Jm 4 8 years 4
74. e 43 Vegetable Oil 44 Other Fats 45 Unspecified Fats 15 ASH and SEAFOOD PRODUCTS AND DISHES 51 Fin Fish Excluding Canned 52 Crustacea And Molluscs Excluding Canned 53 Other Sea And Freshwater Foods 54 Packed Canned And Bottled Fish 2007 Revised Food Code 11 N NO 122 123 124 125 126 131 132 133 134 135 136 141 142 143 144 145 146 151 152 153 154 Revised Food Group Name NON ALCOHOLIC BEVERAGES Tea Coffee And Coffee Substitutes Fruit And Vegetable Juices And Drinks Cordials Soft Drinks And Flavoured Mineral Waters Electrolyte Energy and Fortified Drinks Mineral Waters And Water Other Beverage Flavourings and Prepared Beverages CEREALS AND C EREAL PRODUCTS Flours And Other Cereal Grains And Starches Regular Breads And Bread Rolls Plain Unfilled Untopped Varieties English Style Muffins Flat Breads And Savoury and Sweet Breads Pasta And Pasta Products Breakfast Cereals and Bars Unfortified and Fortified Varieties Breakfast Cereal Hot Porridge Type CEREAL BASED PRODUCTS AND DISHES Sweet Biscuits Savoury Biscuits Cakes Buns Muffins Scones Cake Type Desserts Pastries Mixed Dishes Where Cereal Is The Major Ingredient Batter Based Products FATS AND OILS Butters Dairy Blends Margarine and Table Spreads Vegetable Nut Oil Other Fats Unspecified Fats ASH and SEAFOOD PRODUCTS AND DISHES Fin Fish Excluding
75. e approach and tools for measuring and monitoring physical activity in children and young people in Australia Workshop participants included invited experts from the academic and non government sectors as well as representatives of Health Departments from most of the state and territory governments and from the Australian Government The workshops produced a series of recommendations which influenced the development and implementation of the Australian National Children s Nutrition and Physical Activity survey These recommendations included e Age range Surveillance of physical activity and sedentary behaviours should be undertaken amongst 5 18 year olds with self reporting measures alone not recommended for use with children under 10 years of age e Concurrent items for the same individuals Data collection on physical activity behaviours sedentary behaviours food and nutrient intakes and anthropometric measures should be collected simultaneously from respondents e Objective measurement When measuring the activity levels of children younger than 10 years of age objective measures such as pedometry and accelerometry can be useful e the choice of objective measures should be developmentally appropriate for the children participating in surveys e Surveillance items for physical activity It was recommended that the survey measure the minutes of participation in organised and non organised forms of moderate and vigorous inte
76. e day training program was provided for CATI interviewers which replicated the CAPI training but excluded anthropometric measurement pedometer placement and demographic questionnaire instructions CATI training was conducted in Brisbane February 2007 Training was facilitated by staff from I view research dietitians from CSIRO and exercise physiologists from UniSA Training for Multimedia Activity Recall for Children and Adolescents MARCA and anthropometry was conducted by exercise physiologists Training for LINZ2424 was conducted by research dietitians The training involved e formal lectures e familiarisation with the software package e guided exercises e interview techniques identifying gaps in responses probing open questions e experiential learning All CAPI interviewers were trained in anthropometric techniques and technical errors of measurement TEM were established Intra tester TEMs represent precision of measurement while inter tester TEMs represent accuracy by comparing measures taken by interviewers with those of an International Society for the Advancement of Kinanthropometry ISAK Level 4 criterion anthropometrist For this survey all interviewers demonstrated inter tester TEMs of lt 2 and intra tester TEMs of 1 5 All interviewers practiced interviews with children from all age groups to ensure they were competent in all aspects of the survey Volunteers were recruited for the practice and were involved i
77. e profile devoted to each activity in the activity set For example Table 19 shows the codes that constitute the activity set screen time Table 19 Screen time codes Code Activity 111030 watching TV lying quietly 121050 watching TV sitting 420050 computer work e g typing internet 722190 computer playstation games The MARCA s analytical engine searches the profile for any occurrence of each of these codes and adds together the durations for each occurrence The variables were extracted from the MARCA cleaned data Table The extracted data were collated in a single long file The rows of this file represent individual profiles The columns include the activity sets A wide file was generated where each row represented an individual child and the columns the activity sets for each recall day plus summary data across all four days Summary data Summary data were calculated for each child using the following procedure e The average value for a given activity set was obtained across all school days which could be from one to three days For example if sleep times on three recalled school days were 600 550 and 530 minutes the school days average would be 560 minutes e The average value for each activity set was calculated for all non school days from one to three recalled days If one non school day was recalled with a sleep time of 660 minutes then that value was retained as the non school day average
78. e summed nutrient composition of all items recalled for each child for each interview including nutrients from dietary supplements Variable name Short Description Respondenild Unique identifier for each respondent Interviewld LINZ24 software code for interview number Randomld Unique identifier for day of interview nut to nutxx Nutrient analysis per day 3 Nutrient intakes from foods and beverages for each child This table contains the summed nutrient composition of all items recalled for each child for each interview excluding nutrients from dietary supplements Variable name Short Description Respondentid Unique identifier Interviewld LINZ24 software code for interview number nut to nutxx Nutrient analysis per day Nutrient database FSANZ developed a nutrient database AUSNUT 2007 which contains data for 37 nutrients that are expressed per 100g edible portion food or per 100 dosage units supplements AUSNUT 2007 contains data only for those foods and supplements consumed during the survey Sources of nutrient data AUSNUT 2007 incorporates food and nutrient composition data from a range of sources These include e Food and nutrient composition data published in NUTTAB 2006 FSANZ 2007 e Unpublished food and nutrient composition data commissioned by FSANZ for the purpose of this survey e Food and nutrient composition data borrowed from international food composition tables and
79. ee with or without honours 4 Advanced diploma diploma 5 Certificate III IV including trade ertificate 6 Other O equivalent 4 School year 9 or equivalent 5 School year 8 or below 6 Never attended school 7 Still at school 1 A postgraduate diploma or higher 2 Graduate diploma Graduate certificate 3 A bachelor degree with or without honours 4 Advanced diploma diploma 5 Certificate III IV including trade ertificate 6 Other O 76 D13 Does lt study child gt have any medical conditions and or disabilities that have lasted or are likely to last for6 months or more MAY SELECT MORE THAN ONE Family Details D2 What is their first name D3 Is male orfemale D4 What was age last birthday D5 How is related to parent 1 Person 5 Who else lives here 1 male 2 female 3 no person 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild Person 6 Who else lives here 1 male 3 no person 2 female Sight problems not corrected by glasses or contact lenses Hearing problems Speech problems Blackouts fits or loss of consciousness Difficulty learning or understanding things Limited use of arms or fingers Difficulty gripping
80. eek Unpaid work last week Away from work last week Number of hours worked on average Looking for work Start work if found a job Last worked if not currently working Job description Job tasks Australian Standard Classification of Occupations ASCO Code Household annual income 29 10 Food and Nutrient Intake This section describes the food and nutrient intake information collected during two 24 hour recalls conducted with each participant on non consecutive days Food Intake A license was obtained from the University of Otago to use the 24 hour dietary recall software from the Life in New Zealand LINZ24 survey Parnell et al 2003 LINZ24 allowed direct computer assisted data entry LINZ24 employs a three pass 24 hour dietary recall method to record all foods beverages and supplements consumed on the day prior to each interview from midnight to midnight The three pass methodology included the following stages e 15 pass A quick list of all foods beverages and dietary supplements consumed from midnight to midnight the day before the interview Each quick list item has a unique sequence of probe questions which follow in the 2nd pass e 2d pass The time and place of consumption for each quick list item was entered Any additions e g the spread on toast are added to the list The sequence of probe questions then allowed a detailed description of each quick list item and all additions
81. entiality purposes the database will contain no personal information on the respondents with resoondents names replaced with a unique identification number The results database will be linked to the dietary analysis software and food database developed by Food Standards Australia New Zealand 68 18 Issues arising Delays in data collection arose due to The original proposition that the sample would be drawn from the Medicare administrative data base but this was not achievable in the timeframe A decision was made to change to RDD to recruit participants This resulted in a 2 5 week delay to the start of field work A delay in pedometers being returned at the beginning of fieldwork Pedometers were not returned at the same rate as the pilot This resulted in insufficient pedometers available for reissue at subsequent interviews To maintain progress interviewers targeted children aged less than 5 years during this shortage pedometers were only fitted to children aged 5 years and over This resulted in a higher proportion of younger children being interviewed in the earlier phase of the fieldwork Additional pedometers were purchased to adaress this The difficulty in recruiting 14 16 year old participants compared to other age groups resulting in more data from these participants at the end of the survey period Natural disasters occurring in four locations Tasmania Maitland Sale Katherine which delayed interviewing for several
82. es spent doing chores code 0 4XXXXX 12 IV real 0 decimal places minutes spent watching TV codes 400 111030 121050 13 computer real 0 decimal places minutes spent at the computer e g 25 typing internet code 420050 14 videogames real 0 decimal places minutes spent playing video or 150 computer games code 722190 15 phone real 0 decimal places minutes spent talking on the phone 25 codes 114070 124100 134170 16 texting real 0 decimal places minutes spent texting codes 20 114190 124170 134180 17 passive real 0 decimal places minutes of passive transport codes 60 transport 221000 221110 221120 18 inactivity real 0 decimal places minutes spent in activities requiring 21 to 450 lt 2 METs 19 light activity real 0 decimal places minutes spent in activities requiring 22 to 60 lt 3 METs 20 other sedentary real 0 decimal places minutes spent sitting lt 3 METs code 200 X2XXXXX 21 lying awake real 0 decimal places minutes spent lying down excluding 10 sleep Code x1xxxx 22 sleep real 0 decimal places minutes of sleep code 100010 620 23 wake up time time 06 30 am 24 bed time time 1 15 PM 25 cull status category OK low PAL Profile is a candidate for culling for low OK high PAL activities activity PAL lt 1 1 high activity PAL gt 3 0 or too few activities lt 10 55 The summary data are in the form of a series of tables in the main report They are derived from
83. est of NSW 527228 14 400 9 395 9 Melbourne SD 638887 16 600 14 593 13 Rest of VIC 294309 8 280 6 292 7 Brisbane SD 321616 8 320 7 338 8 Rest of QLD 416547 11 420 10 424 10 Adelaide SD 207792 5 620 14 614 14 Rest of SA 88961 2 260 6 263 6 Perth SD 273450 7 240 5 260 6 Rest of WA 116547 3 160 4 152 3 Greater Hobart SD 42685 1 80 2 106 2 Rest of TAS 62772 2 80 2 78 2 Darwin SD 19070 0 40 1 55 1 Rest of NT 28725 1 40 1 41 1 Canberra SD 68691 2 160 4 179 4 Rest of ACT 160 0 0 0 0 0 Other territories 914 0 0 0 Total 3876721 4400 4487 Note Booster sample increases the proportion of South Australia sample in the study e g other Australian Islands 23 7 Interviewer taining and supervision Thirty seven telephone interviewers were trained for recruitment Training for the telephone recruitment staff took place in Melbourne in February 2007 There were 58 CAPI interviewers and 32 CATI interviewers 36 percent of the CAPI interviewers had a tertiary degree or higher in dietetics or nutrition The remaining interviewers had a tertiary degree in health science or other relevant disciplines All of the CATI interviewers had a health science or other relevant tertiary background Training for the CAPI and CATI interviewers was separate due to the difference in requirements for the two interview methods CAPI training took place over four and a half days in Sydney February 2007 A modified thre
84. etermining usual intakes for foods Data were not collected in a way that groups foods into meals although time of consumption may be used to indicate mealtimes Physical activity recall The 24 hour recall methodology imposes the discipline of fitting all activities into a 24 hour time frame and exploits innate chronological narrative data storage and retrieval methods However all recalls are subject to the limitations of memory social desirability effects and mis estimation of time all of which vary with age sex and individual characteristics Children aged less than 9 years are not able to accurately recall what they did the day before and place events into a temporal frame Therefore the MARCA was administered only to children aged 9 years and over To assist with recall interviewers were trained to use aids such as television guides and school diaries Parents were also invited to assist with recalling events such as meal times and outside of the home commitments There is substantial random within individual day to day variability in the activity patterns of children and systematic differences such as school vs non school days For this reason activity patterns should be sampled over a number of days In this survey activity patterns were sampled on four days including wherever possible one school day and one non school day There is no gold standard for how many days should be sampled The number of days required
85. evelopment Details of the Physical Activity workshop have been published National Public Health Partnership 2006 Survey objectives and overview The objective of this survey was to assess food and nutrient intake physical activity and measure weight height and waist circumference in a sample of children aged 2 16 years randomly selected from across Australia An initial target quota of 1 000 children 50 boys and 50 girls for each age group 2 3 years 4 8 years 9 13 years and 14 16 years was set This was supplemented in South Australia to allow more detailed estimates for that state increasing the final survey sample by 400 equally across the age groups A total of 4 487 children completed all components of the survey The sample was designed to provide e national level estimates by gender and four age groups e state and territory estimates by broad age groups It was not designed to provide a representative sample of smaller sub populations of children such as Indigenous groups children from a range of culturally and linguistically diverse backgrounds or children with special disabilities Households with children aged 2 16 years were randomly selected using random digit dialing RDD from all Australian states and territories in metropolitan rural and remote areas The number of children included from each state was proportional to the population of children in that state A response rate of 40 of eligible households was
86. evised Food Code 155 156 16 161 162 163 164 165 166 167 168 169 17 171 172 173 181 182 183 184 185 186 187 188 189 19 191 192 193 194 195 197 198 20 201 202 203 204 205 21 211 212 Revised Food Group Name Fish And Seafood Products Homemade and Takeaway Mixed Dishes With Fish Or Seafood As The Major Component FRUIT PRO DUCTS AND DISHES Pome Fruit Berry Fruit Citrus Fruit Stone Fruit Tropical Fruit Other Fruit Mixtures Of Two Or More Groups Of Fruit Dried Fruit Preserved Fruit Mixed Dishes Where Fruit Is The Major Component EGG PRODUCTS AND DISHES Eggs Dishes Where Egg Is The Major Ingredient Egg Substitutes and Dishes MEAT POULTRY and GAME PRODUCTS and DISHES Muscle Meat Game And Other Carcase Meats Poultry And Feathered Game Organ Meats And Offal Products And Dishes Sausages Frankfurts And Saveloys Processed Meat Mixed Dishes Where Beef Veal Or Lamb Is The Major Component Mixed Dishes Where Pork Bacon Ham Is The Major Component Mixed Dishes Where Poultry Or Game Is The Major Component MILK PRODUCTS AND DISHES Dairy Milk cow sheep and goat Yoghurt Cream Cheese Frozen Milk Products Other Dishes Where Milk Or A Milk Product Is The Major Component Flavoured Milks Dairy Substitutes Dairy Milk Substitutes Unflavoured Dairy Milk Substitutes Flavoured Cheese Substitute Soy Based Ice Confection Soy Based
87. ewers undertaking the CAPI 17 The steps for postcode selection are summarised below Exclusion of postcodes with a Very Remote index using Accessibility Remoteness Index of Australia ARIA 2001 2 Exclusion of postcodes with less than 80 households with at least one child aged 2 16 years using 2001 ABS population data 3 Exclusion of postcodes with more than 50 of the children aged 2 16 years in the population identified as Indigenous 2001 ABS data 4 Postcodes sorted into strata s of state territory and capital city rest of state 5 Assign a random number to each postcode Excel RAND function 6 Within each stratum the postcodes were sorted into ascending order by their random number 7 The required number of locations 50 was selected to cover each strata from the top of each strata list compiled in step 6 8 4 5 postcodes of geographical proximity to the 50 locations identified in step 7 were added to meet the required number of postcodes 230 9 The postcodes identified in step 8 were allocated a code 1 50 to identify each interview location Table 3 shows the number of postcodes selected and the number of interviewing locations Note that additional postcodes were added to the numbers described above for the SA booster sample Table 3 Interview and locations selections Postc odes Locations a region Capital Restof Total Capital Restof Total os state state New New South Wales Wales Ca ce wema o ae e a a
88. f a cluster postcode are effectively no more like each other than they are to others within their state rural or metropolitan area population then the intra cluster correlation is zero and there is no design effect However where regional clusters result in cluster members being more like each other and less like other members of their regional population then even where the intra cluster correlation is quite small there will be a design effect the size of which is then dependent upon the size of the cluster Cluster Sample Size The target sample size was achieved for each region There was no set quota by cluster of postcodes Some clusters were skewed with either more postcodes or postcodes with higher populations of children 2 16 years There were some postcodes where no children were selected as all numbers were exhausted with no recruitment high industrial commercial areas and there were other postcodes included that were not part of the initial selection phone number transportability but the family was still recruited Random digit dialling The majority of households in Australia have a fixed land line It is estimated that at least 96 of eligible households in an area will be covered by using RDD although over the past few years there has been an increase in households particularly high density urban with mobile only and no land line Australian Communications and Media Authority estimates that the number of basic fixed
89. f data needed to be culled or not Physical Measures Each measurement height weight waist girth and BMI were sorted by each age group to find those at the extremes Also ratios of height weight waist girth height and weight waist girth were sorted in the same manner Outliers were examined for plausibility Where one of the three measurements was clearly incompatible with the other two it was excluded from the calculation of the mean 57 15 Interpretation of results Survey and Sample Design There are limitations to the use of postcodes as the primary sampling unit as postcodes can cover a wide geographic area one postcode can include urban rural and remote areas However postcodes do offer a degree of clustering to enable cost effective face to face interviews to be conducted and allow a reasonable geographic distribution of the sample across Australia A potential sample design effect is the loss in statistical precision resulting from a clustered sample that does not fully cover the diversity of specific response variables evident in the entire population The extent of loss in statistical precision largely depends on whether and how much the specific response variables have underlying geographic variations The potential design effect on the precision of estimates derived from a clustered sample is essentially related to the heterogeneity of the stratum metropolitan or rural population for their state If the members o
90. f ever formula fed All All All 98 Birth weight ounces Birth weight kg Birth weight g Was a written record used to recall the birth weight Usual way of eating Other usual way of eating not described above Birth weight of child portion in ounces Birth weight of child portion in kilograms Birth weight of child portion in grams Yes or no No special way of eating Vegetarian diet Weight reduction diet Diabetic diet Fat modified diet to lower cholesterol Other Refused NOOK WD Text description on other usual way of eating All All All All All If answered 6 above 99 MARCA EXTRACTED DATA for eligible respondents Data Items Date of test Type of day Physical Activity Level PAL in METs MPA minutes of moderate PA gt 3 to lt 6 METs VPA minutes of vigorous PA gt 6 METs Total minutes of active transport Total minutes spent in part time work Total minutes spent doing chores Total minutes spent watching TV Total minutes spent at the computer e g typing internet Total minutes spent playing video or computer games Total minutes spent talking on the phone Total minutes spent texting Total minutes of passive transport Total minutes spent in inactivity activities requiring 21 to lt 2 METs Total minutes spent in light activity activities requiring 22 to lt 3 METs Total minutes spent sitting other sedentary activity activities requiring lt 3 METs To
91. files a profile is one 24 hour recall by one child Profiles are saved to a text file when a MARCA recall is complete Researchers will rarely want to access these files but they have been retained as part of the audit trail e Cleaned profiles Profiles that have been manually checked for anomalies Researchers may choose to access these files if they want to extract data which have not been extracted as part of the process described below e Extracted data Data that have been obtained when the MARCA profiles have been analysed by the MARCA s programmable analytical engine e g minutes of screen time Researchers will often wish to access these files for detailed analysis e Summary data Means standard deviations and percentiles for extracted data for demographic slices e g age and sex groups These are the headline data which will be most frequently referenced Table 18 MARCA Data formats Data type Contents Filename Format Raw raw MARCA profiles M lt participant ID gt lt date txt files item separated recalled gt txt by commas one file per profile Cleaned cleaned MARCA MARCA_ lt date gt txt Ixt file items separated profiles by commas records by returns single file Extracted extracted data such as MARCA _FoursBy Profile xls xls file rows represent moderate to vigorous subjects columns physical activity represent variables MVPA screen time Summary means SDs and Tables 90
92. for an accurate snapshot of typical activity varies according to e the type of activity being measured e the purpose of the survey e g estimating population means estimating prevalence of compliance with physical activity guidelines e the methods of data treatment e g normalising data via transformations There were no differences in data quality or average values for major outcome variables MVPA screen time sleep between CAPI and CATI recalls when corrected for age and day type i e school vs non school day Pedometry The data are based on complete days defined by at least 1 000 steps and the pedometer was removed for no more than 240 minutes Assuming that the sleep duration for most respondents in this survey is between 8 and 10 hours allowing 4 hours of pedometer removal still gives at least 10 to 12 hours in which data were collected This is in line with recent accelerometer studies that include measurement days on which at least 10 hours of data are recorded Several studies discard days on which the pedometer was removed for more than 60 minutes This is an issue as disregarding days when subjects participated in long periods of swimming or contact sports will lead to spurious estimates of daily physical activity In the survey seasonal differences in activity choices will impact on the measurement periods with aquatic activities more likely in the summer The vast 60 majority of reasons for
93. ght measures Of the 4695 households who participated in both the CAPI and CATI 4487 had all of the above data items Table 10 38 Table 10 Response components to tasks 2 4 5 8 9 13 14 16 Age of Study Child years years years years Total eee Serco co 1 499 956 1 219 1163 4 837 100 Anthropometric Measures x 3 1 433 950 1 206 1 156 4 745 98 24 hour activity recall 1 n a n a 1 218 1 160 2 378 99 24 hour activity recall 2 n a n a 1 212 1 159 2 371 100 24 hour activity recall 3 n a n a 1 154 1 118 2 272 96 24 hour activity recall 4 n a n a 1 138 1 108 2 246 95 24 hour diet recall 1 CAPI 1 494 953 1 217 1 162 4 826 100 24 hour diet recall 2 CATI 1 429 934 1 171 1 132 4 666 96 6 days Pedometer Data n a 833 1 017 979 2 829 85 Data sets for analysis 1 359 928 1 109 1 091 4 487 93 All tasks completed Record 1 359 815 948 942 4 064 84 note that age groups for tasks are different to the age groups for sample quota 1 Includes cullable records 2 A record with all tasks completed includes Interviews were conducted seven days a week during the fieldwork period 22 February 2007 to 30 August 2007 The participation over the days of the week and the seasons are shown in Table 11 and Table 1 People generally did not want to schedule interviews on Sundays and Mother s Day and Easter Sunday were during this field period which fu
94. grandchild 10 grandchild 11 niece nephew 11 niece 12 cousin nephew 3 other relative in 12 cousin aw 3 other relative 13 unrelated child in law 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate 5 unrelated adult 1 No 2 Yes Aboriginal 3 Yes T Strait slander 4 Yes both 1 No 2 Yes Aboriginal 3 Yes T Strait Ilander 4 Yes both nsert SACC codes for alll nsert SACC codes for countries all countries D10 Does speak a language nsert ASCL codes for Insert ASCL codes for all Insert ASCL codes for other than English at home all languages anguages all languages Family Details Parent 1 Parent 2 Partner Study Child Person 4 D11 Whatis the 1 School year 12 or 1 School year 12 or highest year of equivalent equivalent primary or 2 School year 11 or 2 School year 11 or secondary school equivalent equivalent that have FOGI hool completed 3 Se ool year 10 or 3 School year 10 or D12 Whatis the level of highest qualification that has ever completed equivalent 4 School year 9 or equivalent 5 School year 8 or below 6 Never attended school 7 Still at school 1 A postgraduate diploma or higher 2 Graduate diploma Graduate certificate 3 A bachelor degr
95. he interviewer selection and training program e test the response rate between the CAPI and CATI e test the survey instruments e trial data collection data transfer processes and analysis procedures e verify the appropriateness of equipment The interviewer training was conducted in Adelaide and recruitment of participants commenced the following week Subjects were recruited from the White pages in Whyalla and a client list in Brisbane i e the survey recruitment strategy not piloted Complete interview data i e all CAPI and CATI data were obtained for 100 children with an equal number of children from each location CAPI data collection occurred over the period of one fortnight CATI was conducted 7 21 days after CAPI The average lengths of the interviews were within the expected range The main outcomes of the pilot survey were e The need to refine the selection criteria for interviewers to include tertiary education and a intermediate or higher PC and Windows software skills e To extend the interviewer training program from 4 days to 4 5 days e Toreduce the estimated number of CAPI interviews to achieve the required number of completed CATI i e fewer households needed to be recruited due to a higher than expected response rate between CAPI and CATI e To make minor modifications to the interviewer manuals e To increase the number of pedometers in circulation to allow for slower than anticipated return by participants e Toinc
96. her Alcoholic Beverages SPECIAL DIETARY FOODS 2007 Revised Food Code 213 221 222 231 232 233 234 241 242 243 244 245 246 247 248 249 251 252 26 261 262 263 264 265 271 272 273 281 282 283 291 292 293 294 295 Revised Food Group Name Canned Condensed Soup Unprepared SEED and NUT PRODUCTS AND DISHES Seeds And Seed Products Nuts And Nut Products SAVOURY SAUC ES AND CONDIMENTS Gravies And Savoury Sauces Pickles Chutneys And Relishes Salad Dressings Stuffings VEGETABLE PRODUCTS AND DISHES Potatoes Cabbage Cauliflower And Similar Brassica Vegetables Carrot And Similar Root Vegetables Leaf And Stalk Vegetables Peas And Beans Tomato And Tomato Products Other Fruiting Vegetables Other Vegetables And Vegetable Combinations Dishes Where Vegetable Is The Major Component LEG UME AND PULSE PRODUCTS AND DISHES Mature Legumes And Pulses Mature Legume And Pulse Products And Dishes SNACK FOODS Potato Snacks Corn Snacks Extruded Or Reformed Snacks Pretzels Other Snacks SUGAR PRODUCTS AND DISHES Sugar Honey And Syrups Jam And Lemon Spreads Chocolate Spreads Sauces Dishes amp Products Other Than Confectionery Where Sugar Is Major Component CONFECTIONERY AND CEREAL NUT FRUIT SEED BARS Chocolate And Chocolate Based Confectionery Cereal Fruit Nut And Seed Bars Other Confectionery ALCOHOLIC BEVERAGES Beers Wines Spirits Other
97. ic nutrient database AUSNUT 2007 The project team acknowledges the contribution of Flinders University in the analysis of the dietary data This guide describes the objective of the survey the development and methodologies used in the survey and data processing techniques employed to assist with appropriate interpretation of the survey results 3 ProjectTeam University of SA Professor Timothy Olds BA Hon BSpSc Dist PhD Syd PhD UNSW Dr James Dollman BS MSc DipEd PhD Mr Tim Kupke BAppSc BHIthSc Hons CSIRO Professor Lynne Cobiac moved to Flinders University at the beginning of 2007 PhD MBA Adv Post Grad Dip Nut Diet Dr Jane Bowen BSc BNut amp Diet Hons PhD Ms Jill Burnett Bsc Dip Nut amp Diet DipEd Ms Julie Syrette BSc Mr James Dempsey Blnffech Eng Mr Shane Bailie Dip IT Software Dev Dr Carlene Wilson BA Hons PhD MBA MAPS Ms Ingrid Flight BA MPH Mr Norm Good Dip IT Prof lan Saunders BA Hons DioMathStats PhD I view Pty Ltd Ms Kylie Brosnan BBus Dip MRSA Mr Daniel Pole BA Ms Mary Plumridge Acknowledgement is given to Dr Michelle Miller and Ms Alison Yaxley of Flinders University for final food and nutrient data analysis Steering Group Ms Jenny Bryant First Assistant Secretary Population Health Division Department of Health and Ageing Ms Jennifer McDonald former Assistant Secretary Population Health Division Department of Health and Ageing Ms Cath Peachey
98. ication factor levels wt table 1 lt factor rep States ach nRegions 80 4 2 levels States wt table 2 lt factor rep rep Regions each 80 4 2 nStates levels Regions wt table 3 lt rep rep 1 80 each 4 2 nStates nRegions wt table 4 lt rep rep fs tot 1 each 4 2 nStates nRegions wt table 5 lt rep rep 1 4 each 2 nStates nRegions 80 wt table 6 lt rep 1 2 nStates nRegions 80 4 cat n population counts for each row of the table ChildrenPerFamily lt fs age cbind wt table 3 1 wt table 5 number of children of this agegroup in this FS Pr Sex lt as numeric Sex ratio cbind match paste wt tableSState wt tableSRegion paste Sex ratioSState Sex ratioSRegion wt table Sex 5 nFam lt Table2 aggr Count match paste wt tableSState wt tableSRegion wt tableSFS paste Table2 aggrS State Table2 aggr Region Table2 aggrS FS wt tableSPopn lt nFam ChildrenPerFamily Pr Sex Sample counts for each row of the table Five way array of counts with dimensions defined so that the counts are stored in the correct order temp tab lt table Sample Sex Sample AgeGrp factor FS num levels 1 80 Sample Region Samp le State Copy into wt table dim temp tab lt NULL wt tableSSample lt temp tab Calculate weights for each set of factors wt tableS Weight lt wt table Popn wt table Sample Wts lt wt tableSWeight Weight
99. ics Dept Nutrition Danish Institute for Food and Veterinary Research www foodcomp dk National Public Health Partnership 2006 Monitoring and Surveillance of Physical Activity of Children and Young People Report of a National Consensus Workshop December 2005 Melbourne NPHP National Health and Medical Research Council 1991 Recommended Dietary Intakes for use in Australia Canberra NHMRC National Health and Medical Research Council 1994 The Core Food Groups The scientific basis for developing nutrition education tools Canberra NHMRC National Health and Medical Research Council 2005 Nutrent Reference Values for Australia and New Zealand Canberra NHMRC Olds T Ridley K Wake M Hesketh K Waters E Patton G Williams J 2007 How should activity guidelines for young people be operationalised 2 Intemational J oumal of Behavioral Nutrition and Physical Activity 4 43 Parnell W Scragg R Wilson N Schaaf D Fitzgerald E 2003 NZFood NZChildren Key results of the 2002 National Children s Nutrition Survey Wellington Ministry of Health Ridley K Olds T Hill A 2006 The Multimedia Activity Recall for Children and Adolescents MARCA development and evaluation Intemational J oumal of Behavioral Nutrition and Physical Activity 3 10 United States Department of Agriculture National Nutrient Databank for Standard Reference 2006 Release 19 www nal usda gov fnic foodcomp search 124
100. ight ccccccccessececeestsceeeeeesees 115 Read and process ABS data files lt cccsscc cssscsessascevesedeesreaversceeandeccensecesanedebsaerens 115 Read and process Nutrition Survey data ecceescceesseceeeseceesseeeeseeeeeneeeenaeeees 116 Calculation Of WEIS BiS a EE A a eleva R dose odode 118 25 OBST ien a a a a a aa a a AOE 120 26 Units of measurement neea R EOE aa ea 122 27 Referente Sen tanesin i tied bated RR EEA E E A a ia 123 1 Listof Abbreviations ABS ACHPER AFGC Al AMDR ARIA CAPI CATI CCD CSIRO DAFF DAA DFE DTMS DoHA ESOMAR EAR FSANZ ISAK ISO LINZ24 MARCA MET MVPA NHMRC nfs ns NNS 1995 NRV RDD RDI SDT TEM TGA UniSA Australian Bureau of Statistics Australian Council for Physical Education and Recreation Australian Food and Grocery Council Adequate Intake Acceptable Macronutrient Distribution Range Accessibility Remoteness Index of Australia Computer Assisted Personal Interview Computer Assisted Telephone Interview Census Collector District Commonwealth Scientific Industrial and Research Organisation Department of Agriculture Fisheries and Forestry Dietitians Association of Australia Dietary Folate Equivalents Desktop Marketing System Department of Health and Ageing European Society for Opinion and Marketing Research Estimated Average Requirements Food Standards Australia New Zealand International Society for the Advancement of Kinanthropometry Internatio
101. ill leave with you these sticky reminder notes if you think it will be hard to remember to put the pedometer on each morning Interviewer disc usses strategic places to stick the labels We will also send text messages during the coming week to remind you to put the pedometer on each day and write down the numbers each night If you do forget to put the pedometer on one day don t give up all together please put the pedometer on the following day and try to remember from then on until insert day just need to measure your stride length so can enter this information into the pedometer This will only take a couple of minutes need to find an area where you can walk in a line for 10 steps Negotiate a suitable location inside or outside Open out measuring tape ina straight line Please place the tips of your shoes alongside the zero on the tape Now take 10 normal steps and will measure the distance Now we need to do that one more time so that can get an average Thanks that s it Interviewer calculates and enters stride length Let s leave the pedometer in a place that you will definitely find it tomorrow morning Yes No FL Stride Test Completed F2 NOTCOMPLEIED specify reason Record first measure F3 Stide data 1 Record second measure F4 Stride data 2 82 Calculate Average F5 Stride data 3 Re
102. ioned this way for height measurements The perpendicular distance between the transverse plane of the vertex and the inferior aspects of the feet The subject should not be wearing shoes and the head should be in the Frankfort plane No stretch is applied Foods are categorised according to major groups of foods of similar description or usage A reference nutrient database produced by FSANZ based mainly on analytical data for Australian foods Used as the basis for developing the survey specific data base generated for this survey 120 Percentage contribution to energy intake Scope Stadiometer Refers to the target population covered by a data collection The scope of this survey was children aged between 2 16 years inclusive who were residents of private dwellings in Australia Device used for measuring height 24 hour dietary recall Individuals recall of everything eaten and drunk including Waist girth Waist to height ratio Weight water and supplements over a 24 hour period In this survey it was taken from midnight to midnight The circumference of the abdomen at its narrowest point when viewed from the front between the lower costal 10th rib border and the top of the iliac crest in the mid axial line When there is no visible narrowing the circumference is measured half way between the lower costal border and the top of the iliac crest Measurements are taken end tidally The ratio of the waist circumferen
103. ions which were used in deriving the weights Further in order to achieve the required equal representation of age groups in families with more than one child preference was given to children in the 2 3 and 14 16 age groups Thus children in larger families in age groups 4 8 and 9 13 were proportionally under represented in the sample In addition the gender balance in the sample was not controlled Given that it is likely that there will be differences between boys and girls in the outcome variables it is appropriate to post stratify by gender to correct for any bias resulting from chance differences in gender balance Ideally the weightings to correct for non proportionate sampling would be based on e Age e Gender e Household size e Family Structure the number of children of each age in the family e Region as defined above However this proved to give many cells with no data in the sample or very small sample numbers This would give very high weight to some individuals and result in very inaccurate results Family size and structure were unlikely to be major influences on nutritional variables and so it was decided to weight only on Age Gender and Region This leaves potential biases due to family size and structure which can be assessed with other potential biases in the non response bias study Data from the ABS based on the 2006 Census on household size by Postal Area by State by Capital Rest of State were used t
104. is was identified at the screening interview It is difficult to rely fully on telephone prefixes to indicate geographic location as an increasing number of people elect to take advantage of phone number portability where they take an existing phone number with them when they move For this reason access to a full listing of numbers with an effective geographic tag such as an address postcode or Census Collector District CCD was limited RDD allows for the inclusion of silent unlisted and recently listed numbers in the sample which would not occur with a sample drawn from listed numbers i e White pages Further with the end of Desktop Marketing System s Marketing DTMS product the most recent electronic listing of residential numbers is out of date There are two situations where RDD does not provide a listing of all the eligible households in a postcode e Households where there is no fixed phone line e Households where the telephone prefix has been ported in from another area and is not a prefix allocated to the postcode they now reside in or the survey sampling database 22 Table 6 ABS reference population estimates June 2001 and corresponding regional distribution for children aged 2 16 years SD statistical division concordance to postal areas Population Sample Required Sample Achieved number number number Sydney SD 768367 20 700 16 697 16 R
105. isplay and write the number in steps column on the Pedometer Log Sheet Interviewer shows study child parent care giver the procedure Press the MODE button again and the little black marker should be under DIST please write this in the DIST column on the Pedometer Log Sheet Interviewer shows study child parent care giver the procedure Press the MODE button again and the little black marker should be under ACT MIN please write this in the ACT column on the Pedometer Log Sheet Interviewer shows study child parent care giver the procedure You then close the pedometer and place it where it will be easily found in the morning Please remember to do this each night for the next 7 days 81 Please remove the pedometer only when you have to This will be when you go to bed each night and when the pedometer would get wet such as when you swim or have a shower or bath Each night would like you to write down on the pedometer log sheet how long it was not worn that day except for sleeping at night Interviewer shows study child parent care giver the example on the Pedometer Log Sheet All you need to do is put the pedometer on each morning from tomorrow until insert day After you have recorded the information on the last night please put the pedometer into this envelope and post it back to us the following morning It is very important that the pedometer is in the post as soon as possible after the 7 days w
106. istics with a significant difference at 95 confidence level between the sample that completed the CAPI n 4837 and the sample who did not complete all components n 350 were e parent or care giver speaks a language other than English at home e parent or care giver not working e five or more people in the household e income less than 20 799 per annum 40 Table 14 Study child characteristic Study Child Characteristic Completed CAPI Completed CAT Completed all components Study Child Male 2 439 50 2 360 50 2 249 50 Female 2 398 50 2 335 50 2 238 50 4 837 4 695 4 487 Age 2 3 years 1 236 26 1 181 25 1 112 25 4 8 years 1 244 26 1 213 26 1 194 27 9 13 years 1 234 26 1 198 26 1 124 25 14 16 years 1 123 23 1 103 24 1 057 24 4 837 4 695 4 487 BMI lt 20 3 461 72 3 357 72 3 249 72 20 24 996 21 972 21 932 21 25 332 7 319 r 305 Z Refused 48 1 47 1 1 O 4 837 4 695 4 487 Medical Conditions None 3 839 79 3 722 79 3 567 80 At least one 998 21 973 21 920 21 4 837 4 695 4 487 ATSI No 4 683 97 4 548 97 4 349 97 Aboriginal and or Torres Strait 150 3 143 3 134 3 Refused 4 O 4 O 4 O 4 837 4 695 4 487 Language spoken at home English only 4 504 93 4 380 93 4 189 93 Other 331 7 313 7 297 7 Refused 2 0 2 O O 4 837 4 695 4 487 Country Born Australia 4 528 94 4 401 94 4 198 94 Other 309 6 294 6 289 6 4 837 4 695 4 487 41 Table 15 Parent caregiver
107. ited 502 then refused and 4 837 completed the CAPI The CATI was completed by 4 695 participants The final response rate for completed CAPI and CATI was 40 when calculated as a proportion of eligible households Table 16 Table 9 Overall Response Rates Sample Eligible Households 16 598 REC RUMMMENT Quota full 3 320 Recruited 6 789 Refused 6 489 Recruit Response Rate 51 CAPI in home interview Quota Full 1 450 CAPI Interview 4 837 Refused 502 CAPI Completion Rate2 91 CAT follow up telephone interview Quota Full 96 CATI Interview 4 695 Refused 46 CATI Completion Rate3 99 FINAL RESPONSE Completed CAPI and CATI 4 695 Eligible less quota full4 11 732 Final Response Rate 40 1 Recruitment Response Rate Recruits Eligible less quota full 2 CAPI Completion Rate complete CAPI interview Recruits less quota full 3 CATI Completion Rate complete CATI interview CAPI Interviews less quota full 4 Eligible less quota full quota full at recruitment quota full at CAPI quota full at CATI SFinal Response Rate completed CAPI and CATI interview Eligible less quota full The final data set for analysis includes only those records with all of the following components completed e Demographic questions e Food habits e 2x24 hour recall food intake CAPI and CATI e 4x24 hour recall activity in 9 16 years only CAPI and CATI e Weight waist hei
108. ium 34291 34291 34291 34291 34291 34291 34219 3 dodge ball poison ball brandy speed ball hard 3 dodge ball poison ball brandy speed ball hard 1 dodge ball poison ball brandy speed ball light 1 dodge ball poison ball brandy speed ball light 342763 playing with young children hard 342761 playing with young children light 342762 playing with young children medium 341823 pogo stick hard 341821 pogo stick light 341822 pogo stick medium 331420 quoits 342443 red rover hard 342441 red rover light 342442 red rover medium 341243 riding a bicycle bike hard 2 dodge ball poison ball brandy speed ball medium 341241 riding a bicycle bike light 2 dodge ball poison ball brandy speed ball medium 341242 riding a bicycle bike medium 342193 frisbee general hard 1 frisbee general light 342192 frisbee general medium 342203 frisbee ultimate hard 342201 frisbee ultimate light 342202 frisbee ultimate medium 341233 hacky sack hard 341231 hacky sack light 341232 hacky sack medium 342243 hand tennis four square hard 342241 hand tennis four square light 342242 hand tennis four square medium 342830 hide and seek 341283 hopscotch hard 341281 hopscotch light 341282 hopscotch medium 331330 juggling 342353 kickball hard 342351 kickball light 342352 kickball medium 341970 mini golf or putt putt 341980 mucking around indoors walk run
109. key ice hard 341801 tap dancing light 342271 hockey ice light 341802 tap dancing medium 342272 hockey ice medium 342643 tennis court hard 321293 horseback riding hard 342641 tennis court light 321291 horseback riding light 342642 tennis court medium 321292 horseback riding medium 342060 tenpin bowling 341303 ice skating hard 342813 touch football hard 341301 ice skating light 342811 touch football light 341302 ice skating medium 342812 touch football medium karate martial arts judo kick boxing 341322 medium 342703 volleyball beach hard 341323 karate martial arts judo kick boxing hard 342701 volleyball oeach light 341321 karate martial arts judo kick boxing light 342702 volleyball beach medium 341343 kayaking hard 342693 volleyball court hard 341341 kayaking light 342691 volleyball court light 341342 kayaking medium 342692 volleyball court medium 342363 lacrosse hard 342713 wallyball hard 342361 lacrosse light 342711 wally all light 342362 lacrosse medium 342712 wallyball medium 342370 lawn bowls 331733 water skiing hard 331963 lifting weights hard 331731 water skiing light 331961 lifting weights light 331732 _ water skiing medium 331962 lifting weights medium 341743 whitewater rafting hard 342383 netball hard 341741 whitewater rafting light 342381 netball light 341742 whitewater rafting medium 112
110. kiing downhill light 342103 cricket hard 341532 skiing downhill medium 342101 cricket light 341543 skindiving SCUBA hard 342102 cricket medium 341541 skindiving SCUBA light 341110 croquet 341542 skindiving SCUBA medium 111 code activity code activity 342123 curling hard 342183 soccer field indoor hard 342121 curling light 342181 soccer field indoor light 342122 curling medium 342182 soccer field indoor medium 342253 European handball team hard 342563 softball or t ball hard 342251 European handball team light 342561 softball or t ball light 342252 European handball team medium 342562 softball or t ball medium 321870 fishing 341573 speed skating competitive hard 342153 football Australian hard 341571 speed skating competitive light 342151 football Australian light 341572 speed skating competitive medium 342152 football Australian medium 342583 squash hard 341213 golf hard 342581 squash light 341211 golf light 342582 squash medium 341212 golf medium 341613 swimming laps hard 341223 gymnastics hard 341611 swimming laps light 341221 gymnastics light 341612 swimming laps medium 341222 gymnastics medium 342623 table tennis hard 342263 hockey field hard 342621 table tennis light 342261 hockey field light 342622 table tennis medium 342262 hockey field medium 341803 tap dancing hard 342273 hoc
111. l not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable All not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable All not working excluding permanently not in workforce Parent 1 and Parent 2 where applicable 101 Job Description All working Parent 1 and Parent 2 where applicable Job Tasks All working Parent 1 and Parent 2 where applicable ASCO CODE All working Parent 1 and Parent 2 where applicable Annual Income All 102 21 Food groups 1995 Food Group Name Food Code 11 NON ALCOHOLIC BEVERAGES 111 Tea 112 Coffee And Coffee Substitutes 113 Fruit And Vegetable Juices And Drinks 114 Soft Drinks Flavoured Mineral Waters And Electrolyte Drinks 115 Mineral Waters And Water 116 Water With Other Additions As A Beverage 12 CEREALS AND CEREAL PRODUCTS 121 Flours And Other Cereal Grains And Starches 122 Regular Breads And Rolls 123 Breakfast Cereals Plain Single Source 124 Fancy Breads Flat Breads English Style Muffins And Crumpets 125 Pasta And Pasta Products 126 Rice And Rice Products 127 Breakfast Cereals Mixed Source 128 Breakfast Cereal Hot Porridge Type 13 CEREAL BASED PRODUCTS AND DISHES 131 Sweet Biscuits 132 Savoury Biscuits 133 Cakes Buns Muffins Scones Cake Type Desserts 134 Pastries 135 Mixed Dishes Where Cereal Is The Major Ingredient 136 Batter Based Products 14 FATS AND OILS Al Dairy Fats 42 Margarin
112. ldren s food intake dietary habits and or physical activity patterns However these earlier surveys have not always collected quantitative data or used comparable data collection or sampling methodologies to the present survey preventing direct comparisons 1985 Australian Health and Fitness Survey The 1985 Australian Health and Fitness Survey surveyed 5 224 children aged 10 15 years in urban and rural schools in all Australian states and territories Department of Community Services and Health 1988 1989 Children completed a 24 hour dietary record assisted by trained physical education staff The 24 hour recording period commenced immediately after the children had received instructions at school The survey selected from a two stage list sample of firstly schools both primary and secondary and then classes within schools achieving a reported 75 3 response rate excluding initial non contacts and includes partial participants This was conducted in conjunction with the Australian Health and Fitness Survey of the Australian Council for Physical Education and Recreation ACHPER Data were collected between May and October 1985 across all weekdays Monday to Friday The survey estimates were adjusted by post stratification population weights split by state of residence age and Sex The 1985 survey nutrient composition database was used to estimate nutrient intakes and the matching of foods consumed to appropriate nutrient data was ma
113. leteness of recipe Clarification was obtained by telephoning CAPI interviewers and via the supervisors of CATI interviewers General feedback was provided to all interviewers via weekly newsletters Nutrient analysis The 24 hour food beverage and supplement intakes were converted into nutrient intakes using a food and nutrient composition database developed specifically for this survey by FSANZ Each item consumed was matched to an 8 digit food code which in turn referred to a set of nutrient data The 8 digit food code was derived from 5 digit food group codes which were used to categorise foods and beverages Three files are produced from the dietary analysis 1 Nutrient intake per unique food item recalled by each child for each interview This table contains the total nutrient composition for the total amount of each unique food item recalled by each child for each interview Variable name Short Description Respondenild Unique identifier for each respondent Interviewld LINZ24 software code for interview number Randomld Unique identifier for day of interview FoodName 100 character long name of food Amount Amount consumed throughout the day FSANZ food code FSANZ database food code 8 digit Food Group FSANZ food group numbers 5 digit nut to nutxx Nutrient analysis per amount of food consumed throughout the day 45 2 Total Nutrient intake for each child This table contains th
114. levision and what influenced their food choices was collected Weight status was recorded 2003 Physical Activity and Nutrition Levels in Western Australian Children and Adolescents Report A total of 2 274 children from Years 3 5 7 8 10 and 11 from 17 secondary and 19 primary schools were surveyed from a stratified sample representative of the WA population Children were asked to complete a 24 hour food record a FFQ a physical activity questionnaire and 7 day pedometer diary Hands et al 2004 Anthropometric data for weight status and waist girth were collected Additional physical activity information In addition to those surveys listed above some of the more recent major surveys are e 2004 Children and Sport Australian Sports Commission UniSA e 2006 Children s Participation in Cultural and Leisure Activities ABS 10 A number of cohort studies have surveyed children s activity patterns e 1973 77 Busselton WA surveys e latel980s Raine Study Telethon Institute for Child Health Research e 1995 Health of Young Victorians Study e 2003 Growing Up in Australia Longitudinal Study of Australian Children e 2005 LOOK Lifestyle Of Our Kids Survey development In September 2005 DOHA announced its intention to establish a National Children s Nutrition and Physical Activity Survey Prior to the development of the survey a series of workshops were conducted for the purpose of achieving consensus on the best practic
115. line services at 30 June 2005 was 11 46 million a 1 7 per cent decrease compared to 11 66 million services 12 months earlier RDD as a recruitment strategy is limited by the lack of information about non respondents Population weightings were applied to assist with overcoming differences in the probability of selection amongst the study children Seasonality The survey collection period February to August should be considered when interpreting the results 58 Dietary recall The 24 hour recall methodology relies on the participant s ability to recall the details of all foods beverages and supplements consumed over a 24 hour period This method is associated with under mis non reporting of foods and beverages consumed along with inaccuracies in portion size estimation and level of detail to describe the items Interviewers were trained in various techniques to minimise this source of error but it remains unavoidable In recognition of the varying age groups of the participants the interviews were conducted with the primary care giver for all children below the age of nine years and with the study child for children aged 9 years and over Primary care givers were encouraged to be present for all interviews To assist with quantifying the recall during the CAPI measuring aids and a food model booklet were used During the CATI only the food model booklet was available to assist with the estimation of portion size One 24 hour
116. lled participantdetails txt VARIABLE NAME Short Description Respondentid Unique identifier Randomld Unique identifier for day of interview DateOfBirth Date of birth Food Item called unitrecord_sub_list txt contains data relating to the quick list items including time of consumption VARIABLE NAME Short Description Respondentid Unique identifier Interviewld LINZ24 software code for interview number ItemNum Unique quick list item number FoodName 50 character long name of food Time Time of consumption Food Component called unitrecord_com_list txt contains data relating to each addition item of the quick list item including foodcode and amount Ingredients list VARIABLE NAME Short Description Respondentid Unique identifier Interviewld LINZ24 software code for interview number ItemNum Unique quick list item number CompNum Unique addition number Component Text description of addition CodeNum LINZ24 foodlist code number RecipeNum Unique recipe number within Interviewld Amount Amount consumed Unit Units for measuring amount UnitAmount Description of unknown amount NumMeasure Number of reference measure shape consumed Measure Measure description code as defined in OFLM Shape Shape used for volume calculation Dimension Dimension 1 of shape Dimension2 Dimension 2 of shape Dimension3 Dimensio
117. lude a self completed daily log sheet for pedometer step counts Toimprove data edit checking audit and reconciliation of data files procedures No major equipment problems were encountered However it was originally proposed that 7 days of data stored in the pedometer would be used to determine the average number of steps taken per day by each participant During the pilot it became apparent that data stored in the pedometers was lost during transit from the participant to the survey team For the main survey a daily step count diary log was added to the survey methodology 16 6 Survey design At the time of the survey children aged 2 16 years made up just over 21 of the total Australian population and at any given time approximately one in three Australian households occupied dwellings had a child aged 2 16 years based on ABS 2001 Census data The survey was conducted using a quota sampling scheme stratified by state territory and by capital city statistical division rest of state The primary sampling units in each state were postcodes Postcodes were allocated to a stratum using the ABS postal area to statistical local area concordance Households private dwellings from selected postcodes were then recruited to the survey using RDD The telephone number prefix acted as a geographic indicator that corresponded to postcode Households with children aged 2 16 years eligible in scope were identified and asked if they wo
118. n 3 of shape Prodnum Product code number Prodname Product description if not found in list Notepad Unknown item description called unitrecord_ing_list txt contains data relating to each ingredient of any home or uncooked recipes incl food code and amount VARIABLE NAME Short Description Respondentid Unique identifier Interviewld LINZ24 software code for interview number RecipeNum Unique recipe number within Interviewld IngredientNum Unique ingredient number within RecipbeNum Ingredient Ingredient description CodeNum LINZ24 foodlist code number Amount Amount consumed Unit Units for measuring amount UnitAmount Description of unknown amount NumMeasure Number of reference measure shape consumed Measure Shape used for volume calculation Shape Dimension 1 of shape Dimension Dimension 2 of shape Dimension2 Dimension 3 of shape 107 Dimension3 Shape used for volume calculation Prodnum Product code number Prodname Product description if not found in list Notepad Unknown item description 108 23 Activity sets Free Play MARCA codes and activity names for activities included under the free play category code activity code activity 342853 chasey hard 342851 chasey light 342852 chasey medium 341840 climbing trees 341133 dancing general hard 341131 dancing general light 341132 dancing general med
119. n the CAPI and CATI training Interviewers were provided with a comprehensive set of manuals covering e Interviewer instruction Dietary assessment e Physical activity Anthropometry Reference summary sheets were provided for use during interviews During the data collection phase five CAPI and CATI interviews for every interviewer were audio recorded for assessment and feedback Interviews were reviewed by a dietitian for the dietary recall component exercise physiologist for the physical activity component and a field supervisor for interview administration 24 Throughout the data collection phase interviewers were assisted by dedicated supervisors who were health professionals with survey experience Supervisors answered queries provided on going training reviewed interview recordings and undertook systematic field checks validations and observations of the interviewers Interviewers also had email and telephone access to the MARCA and LINZ24 trainers Dietitians from CSIRO checked every interview within a day of being lodged except interviews on Fridays Saturdays which were checked on Mondays Section 14 25 8 Data collection The households that agreed to participate in the survey were posted information including background information details of data collection the address for the survey website and the details of a 1800 hotline Interviewers then contacted recruited families to arrange a time for the C
120. nal Standards Organisation Life In New Zealand Multimedia Activity Recall for Children and Adolescents Metabolic equivalent Moderate to Vigorous Physical Activity National Health and Medical Research Council not further specified not specified 1995 National Nutrition Survey Nutrient Reference Values Random Digit Dialing Recommended Dietary Intakes Suggested Dietary Targets Technical Error of Measurement Therapeutic Goods Association University of South Australia 2 Preface The scope of the 2007 Australian National Children s Nutrition and Physical Activity Survey was to obtain food nutrient physical activity and anthropometric data on a national sample of children aged 2 16 years The survey was jointly funded by the Commonwealth Department of Health and Ageing the Department of Agriculture Fisheries and Forestry and the Australian Food and Grocery Council A representative from each of the three funding agencies made up a Steering Group which was involved in the management of the survey The implementation of the survey was a collaborative effort between the Commonwealth Scientific and Industrial Research Organisation CSIRO Preventative Health Flagship and the University of South Australia together with management of the fieldwork by I view Pty Ltd A Technical Reference Group was convened to provide expert advice Food Standards Australia New Zealand FSANZ in collaboration with CSIRO developed the survey specif
121. now get you to formally sign your consent Let s get started then Introduction child aged 14 to 16 years Address the Parentand Child Thanks for agreeing to take part in the Kids Eat Kids Play study First of all want to assure you both that all information that you give me will be kept confidential and we have strict processes to ensure the security of your information will start by asking a few questions to parent care giver about the household how many people live here and a little bit about each person also will ask about study child s general family background such as Parent and your partner s work and educational background This will give us a general idea of the home environment child grows up in Then I will ask study child some questions about their food intake and what they have done over the last 48 hours am also going to ask if can take some measurements of study child such as his her weight height and waist circumference will then ask study child to conduct a stride test and show you how 72 to wear the pedometer which we ask they do over the next 7 days There will be a few questions on general food habits and finally will ask parent care giver some questions about your housing and income Once have finished asking you both questions have a short form that will ask parent care giver to fill in by yourself and return with the pedometer in the envelope supplied Before we s
122. nsity physical activity and the days of the week when that participation occurred where participation occurred and the key motivators and barriers to participation e Surveillance items for sedentary behaviours The best practice approach involves measuring the minutes spent each day on small screen recreation TV DVD Computer and Internet distinguishing between these activities and when each activity took place includes day time activities week days and weekends Further the survey should also assess the number of minutes spent daily on other non screen based sedentary activities e g reading listening to music etc e Sample size The following socio demographic data always be collected age date of birth language spoken at home parental education level rurality and Indigenous status e Selection criteria The essential criteria for the selection of the physical activity and sedentary behaviour measurement and monitoring tools were stated to be validity reliability sensitivity comparability with existing state based data cost efficiency burden of response flexibility and the sustainability of data 11 e Piloting It was recommended that the instrument as a whole be piloted in the context for which it is to be used e Seasonality Surveillance should take into account the seasonal nature of physical activity behaviours e Consultation Key stakeholders should be consulted from the earliest stages of survey d
123. nually performed A significant proportion of the foods consumed in 1985 did not have Australian nutrient composition data 1995 National Nutrition Survey The 1995 NNS was designed and undertaken by the Australian Bureau of Statistics ABS in collaboration with the then Commonwealth Department of Health and Family Services as a sub sample of the 1995 National Health Survey Data were collected from February 1995 to March 1996 across all Australian states and territories on all days of the week There were 13 858 participants of which 2 574 were children aged 2 15 years and another 433 were aged 16 18 years making a total of 3 007 children aged 2 18 years Participants completed a 3 phase multiple pass 24 hour dietary recall The survey data were collected via a multi stage area sample of private dwellings houses flats etc for persons aged two years and over achieving an overall response rate of 65 5 of those invited to participate Both children and adults undertook a 24 hour recall interview at home assisted by trained nutritionists and proxy interviews with parents were conducted for children aged two to four years Children aged 5 11 years were asked to participate in the 24 hour recall interview with the assistance of an adult household member The 24 hour period was from midnight to midnight The information was collected using a standard interview approach and a pre determined set of probing questions ABS 1998a Approximatel
124. o vigorous physical activity and accumulate no more than 120 minutes of screen time television videogames and computer each day especially during daylight hours The definition of compliance is unclear in the guidelines Olds et al 2007 Compliance can be defined as e the child satisfies the guidelines on all days of the survey period the all days method e the child satisfies the guidelines on most days of the survey period the most days method e the child satisfied the guidelines when MVPA and screen time are averaged across the survey period the average method 62 e the level of compliance can be understood as the probability that a randomly chosen child on a randomly chosen day will satisfy the guidelines the child x day method In this report all four definitions of compliance are analysed For each age x sex x day type school vs non school slice the percentage of children who are compliant on 0 1 2 3 and all 4 sampled days are shown as well as the percentage of children who are compliant when MVPA and screen time are averaged across all four days The probability that a randomly chosen child on a randomly chosen day meets the guidelines is also displayed 63 16 Esimation procedures The survey collected data on nutrition and physical activity for 4 837 children aged 2 16 years across Australia Because stratified sampling with non proportional samples was used the results mu
125. o estimate the population numbers 64 Data from the survey were used to estimate the sample numbers and hence the weights for each individual child The ABS data obtained for determining the weights consisted of a table of number of households by number of children of each sex The ABS family data was used to construct a table of the number of children in each Region by Age The sex ratio for each Region was calculated from the ABS Household data and the proportions of boys and girls applied as a multiplier to each cell in the table to give estimated numbers by sex This gave a table of the estimated total number of children in each Region by Age by Sex class a total of 104 Classes The corresponding sample counts were calculated from the Sample data by tabulation The weight to be applied in computing estimated population means from the data is the ratio of the Population counts to the Sample counts for the Class to which the child belongs Results Tables of weights File WeightTable csv gives the weights for each of the 104 Classes together with the estimated population count and the sample count for each Class File Weights csv gives the weight assigned to each child in the survey identified by the Unit Record number and Respondent ID Use of weighted data The weights allow calculation of the estinated population mean levels of a variable as Sum of Sample value x weight Sum of weights Or in mathematical terms N wy i l
126. onse Measures to maximise response The project team attempted to maximise response however some non response is unavoidable when people choose not to participate or cannot be contacted Strategies to maximise participation through all stages were Stressing the importance of selected households participating in the survey to represent others in their local area Stressing the importance of participation for planning and policy for child health Stressing the confidentiality of all information under the Privacy Legislation and ESOMAR code of conduct Provision of written information in the form of a letter about fieldwork information brochure and website Provision of a Freecall Hotline for information regarding the survey Fieldwork procedures that made every effort to contact and recruit each phone number selected Minimum of 6 call attempts at various times of the day on weekdays and weekends before classifying as a non contact Minimum of 3 call attempts to honour an appointment and where on the third attempt there is a positive indication that the family will participate additional calls were made Appointment management through flexible approach and targeted approach procedures Interviewing skills for refusal avoidance Careful monitoring of interviewer performance and overall adherence to survey procedures Use of interpreters for households that did not speak English Public awareness and publicity of the survey 36
127. participant stood still on the centre of the scales without support and with the weight distributed evenly on both feet Body Mass Index Body Mass index was calculated as weight in kilograms divided by height in metres squared Age and sex specific BMI cutoffs for normal weight overweight and obese among children and adolescents were applied to the data Cole et al 2000 For underweight Grade 3 thinness corresponding to an adult BMI of 18 5 kg m was used as a cut off Cole et al 2007 Waist girth Waist was measured on all consenting participants who were able to stand upright and stand still enough while waist was measured Using the cross over technique the measurement tape was positioned mid way between the lower costal 10th rib border and the top of the iliac crest in the mid axillary line perpendicular to the long axis of the trunk Measurements were taken against the skin or over light clothing such as aT shirt lf measured over clothing a coloured sticker was used to temporarily identify the level at which the measurement was taken The subject assumed a relaxed standing position with the arms folded across the chest The subject breathed normally and the measurement was taken at the end of a normal expiration end tidal The Lufkin W606PM metal tape was used to measure waist girth Waist to height ratio Waist to height ratio was calculated by dividing waist in centimetres by height in centimetres 35 13 Survey resp
128. pedometer removal during the waking hours as recorded on the log sheets related to unavoidable circumstances such as exposure to water and engagement in contact sports Relatively few were due to forgetting or refusing to wear the pedometer As pedometers are most sensitive to activities involving running and walking and are removed for aquatic activities and contact sports caution is advised when using pedometer data to assess compliance with physical activity guidelines It is recommended that engagement in sufficient physical activity also be assessed using criterion referenced step counts currently 11 000 12 000 and 13 000 15 000 per day for girls and boys respectively Having these cut off points established in accordance with weight categories normal vs overweight obese avoids the issue associated with inferring daily MVPA from pedometer data It should also be noted that Day Type weekday vs weekend in the pedometer data tables should not be interpreted as school day and weekend The weekdays in these tables include school holidays long weekends and pupil free schools days Physic al Measures The methodology of performing physical measurements on participants was designed to minimise errors and be consistent Normally measurements should not be taken after training or competition sauna swimming or showering since exercise warm water and heat can produce dehydration and or increased blood flow Mea
129. ral sciences Hillsdale NJ Erlbaum Cole TJ Bellizzi MC Flegal KM Dietz WH 2000 Establishing a standard definition for child overweight and obesity worldwide international survey British Medical J oumal 320 1240 3 Cole TJ Flegal KM Nicholls DF Jackson AA 2007 Body mass index cut offs to define thinness in children and adolescents British Medical J oumal 335 7612 194 Department of Community Services and Health 1988 National dietary survey of schoolchildren 10 15 years 1985 No 1 Foodsconsumed AGPS Canberra Department of Community Services and Health 1989 National dietary survey of schoolchildren 10 15 years 1985 No 2 Nutrient Intakes AGPS Canberra Food Standards Agency 2002 McCance and Widdowson s The Composition of Foods 6th Summary Edition Cambridge Royal Society of Chemistry Food Standards Australia New Zealand 2007 NUTTAB 2006 Available from http www foodstandards gov au monitoringandsurveillance nuttab2006 index cfm Hands B Parker H Glasson C Brinkman S Read H 2004 Physical Activity and Nutrition Levels in Westem Australian Children and Adolescents Report Perth Western Australia West Australian Government Marfell Jones M Olds T Stewart A Carter L 2006 Intemational standards for anthropometric assessment Potchefstroom RSA North West University 123 Meller A Saxholt E Christensen AT Hartkopp HB Hess Ygil K 2005 Danish Food Composition Databank revision 6 0 Food Informat
130. re developed using labelled ingredients The amount of each ingredient was modified so that the final nutrient data were similar to the nutrient data presented on the product s nutrition information panel Developing a new survey food Where the methods outlined above were not appropriate new survey foods were developed by e borrowing nutrient data from international food tables and databases such as the USDA UK NZ and Danish food tables e using industry or label data e imputing nutrient data from similar foods or from levels permitted in the Food Standards Code e reproducing nutrient data published in AUSNUT 1997 Where data from international food composition tables were used care was taken to ensure that the units and mode of expression matched those used in the survey USDA 2006 Food Standards Agency 2002 Athar et al 2006 Maller et al 2005 Food descriptions with characteristics not specified Unspecified survey foods were developed where a respondent was unable to identify the exact food or cooking method of the food they consumed Nutrient data for unspecified foods were derived using two approaches e Ensuring the nutrient data are representative of all survey foods that had a similar description but varied with respect to the characteristic of interest For example a nutrient line for bread white not further specified drew on nutrient data for all white fresh or toasted fortified or unfortified b
131. reads weighted according to consumption patterns observed in the survey e Assigning an unspecified food a nutrient profile of the most frequently consumed product from the relevant category For example Chicken ns2 as to part cooked nfs3 ns2 as to skin could be assigned the nutrient line for Chicken breast baked without skin as this might have been the most frequently consumed type of chicken and cooking method reported during the survey The nutrient composition data developed for survey dietary supplements were derived using formulation data provided by the TGA Data provided by TGA included information on the product s name AUST L number maximum daily dose and formulation with the name and amount of each active excipient and proprietary ingredient provided on a per dose basis In a small number of cases label or web information was used to develop nutrient data Where necessary data provided by TGA were converted into the units and the modes of expression used that were in this survey Notes on nutrient data Energy The AUSNUT 2007 energy data are determined using the following equation Not specified 3 Not further specific 48 Energy kJ Protein g 17 total sugars g 16 total fat g 37 starch g 17 dextrin g 17 maltodextrin g 17 sorbitol g 16 lactic acetic acids g 15 malic quinic citric g 10 alcohol g 29 The energy factors were the same as those used in the 1995 NNS
132. recall is considered appropriate to estimate the usual mean and median intake of a group It is not suitable for assessing the usual intake of individuals because of the considerable day to day variability in food beverage and supplement intake within individuals For this reason the present survey obtained a second 24 hour recall of intake by CATI for all participants with 99 of these completed on a non consecutive day Provided there are no systematic differences between the CAPI and CATI data the two days of intake data for each individual can be used to obtain an estimate of usual intakes Analyses were undertaken to determine the extent of any systematic bias between the two methodologies CAPI vs CATI A repeated measures analysis of variance was undertaken to determine if there was any statistical significance in nutrient intakes between the two measures Cohen s generally accepted criteria of size of the effect were used in the evaluation of the within individual variance Cohen 1988 While some of the differences in nutrient intakes collected through the two different methods were statistically significant p lt 0 01 the effects were small accounting only for up to 4 of the total variance in nutrient intakes The older age groups 9 13 years and 14 16 years showed greater variation in nutrient intakes between the two interviews than the younger age groups Following the analysis described above estimates of usual nutrient intake
133. requiring specialised equipment a special play area and time It is often supervised For example games such as football and basketball activities such as horse riding Section 23 e Free play Active recreation which is essentially unstructured For example playground games riding bikes and scooters and mucking about Typically free play requires no special playing area few rules and minimal supervision Section 23 e Active transport Locomotion where the subject provides most of the energy For example walking cycling skateboarding and rollerblading Section 23 Data analysis Activity variables have been described using means standard deviations and percentiles by age and sex subsets However it is important to note that some activity variables such as minutes of MVPA show very strong positive skews so median values provide more appropriate estimates of typical activity patterns Where data were analysed on per child basis i e across all four recall days for an individual child average values were determined by calculating the average for all school days n 4 207 and then for all non school days n 4 593 and then taking the average of the averages The rationale for this approach is that children soend about one day in two in school over the course of a year 56 Quality assurance of physical activity data There are two main quality assurance mechanisms e Process evaluation which involves training
134. rial is removed from the study data before it is made available for evaluation and research Only combined results from the study will be discussed and published Participation in this study is voluntary You may choose not to answer some of the questions and you are free to withdraw from the study at any time You should understand that you will not benefit personally from this research although the information gathered will be of use in deciding better nutrition and physical activity policies for children If you require further information or if you have any problems concerning this project or the way that it is being conducted please contact the Project Director Professor Tim Olds phone 0423 147 955 email tim olds unisa edu au You may also contact the Chair of UniSA s Human Research Ethics Committee Ms Vicki Allen 0883023118 and mention Kids Eat Kids Play or visit the website www kidseatkidsplay com au if you have any queries or if you wish to notify us of change of address details Interviewer Note Go to consent form CL Interviewer Note Confim that Parent has Yes No signed consent form 1 2 Temninate Interview If No terminate interview Enter reason for Refusing C2 Interviewer Note Is study child 14 or over Yes No 2 Go to C4 C3 Interviewer Note Confim that Study Child ha
135. rnatives and dairy products which were designed to meet 70 of the RDIs for all nutrients except energy NHMRC 1991 The Core Food Groups were under review to account for the NRVs at the time of this publication Direct comparisons of intakes of foods with the recommended core food groups should wait until the review has been completed The Dietary Guidelines for Children and Adolescents in Australia NHMRC 2003 provides general recommendations without specifying the amounts recommended for consumption Information on the number of children consuming these foods can be examined These dietary guidelines are also being reviewed by NHMRC The Australian Guide to Healthy Eating provides consumers with information about the amounts and kinds of food that need to be eaten each day to get enough of the nutrients essential for good health and well being The Guide aims to encourage the consumption of a variety of foods from each of the five food groups every day in proportions that are consistent with the Dietary Guidelines for Australians The Guide also provides information on the number of serves required from the five food groups and offers practical examples Comparisons with physical activity recommendations The National Physical Activity Guidelines issued by DOHA in 2005 recommended levels of physical activity and sedentary behaviour for children aged 5 18 years These guidelines recommended that children get at least 60 minutes of moderate t
136. rsonAge lt 16 Relationship code to Parent 2 of Person 4 to Person 12 RelP2 lt wgtdata paste P 4 12 RelP2 sep Is Person 4 to 12 a child of parent 2 or in a 1 parent family ChildofP2 lt RelP2 gt 6 amp RelP2 lt 12 RelP2 0 amp PersonAge gt 2 amp PersonAge lt 16 InFamily lt ChildofPl amp ChildofP2 set ages of persons not in family to 0 so they are not counted in the family structure These are persons outside the age range or not in the same nuclear family PersonAge InFamily lt 0 function to convert ages of children to a family structure make fs lt function x x lt unlist x grps lt cut x breaks c 1 3 8 13 16 labels 1 4 return table grps Get the family structure for each study child FS lt t apply cbhind SCA PersonAge 1 make fs Convert counts gt 2 to 2 FS FS gt 2 lt 2 Numerical value of FS as ternary number FS num lt apply FS 1 function x 3 3 3 x 1 x 2 x 3 x 4 FS as string FS str lt apply FS 1 paste collapse Code to reorder family structures in ascending order of family size if needed later This is not needed for the current analysis which does not use household data fs age lt NULL for i ini1 4 fs age lt cbind fs age rep rep 0 2 each 3 4 1 3 i 1 fs tot lt apply fs age 1 sum sizeorder lt order fs tot fs age 1 fs age 2 fs age 3 fs age 4
137. rther reduced the opportunity to survey households on 2 4 years of age Waist Height Mass 2 days diet recall demography 5 8 years of age Waist Height Mass 2 days diet recall demography 6 days pedometer 9 16 years of age Waist Height Mass 2 days diet recall demography 6 days pedometer 4 days physical activity recall including cullable records Sundays Table 11 comparison of days of the week for CATI and CAPI Day of the Week of CATI Day of the Week of CAT Not CAPI Mon Tues Wed Thurs Fri Sat _ Sun _ Completed Total Mon 116 126 93 106 78 102 69 21 711 Tues 104 96 106 99 88 95 74 19 681 Wed 119 116 134 125 103 106 86 33 822 Thurs 98 104 95 127 107 101 77 18 727 Fri 103 106 91 112 90 101 72 25 700 Sat 98 90 80 128 116 132 94 19 757 Sun 57 49 58 63 80 59 66 7 439 Total 695 687 657 760 662 696 538 142 4 837 39 Table 12 Seasonality of Dietary Recall CAPI CAT Total Summer Feb 71 2 73 lt Mar 683 508 Apr 757 673 4 519 48 Autumn May 1 091 807 Jun 1 286 1 137 Jul 715 1 148 4 900 52 Winter Aug 223 391 Total 4 826 4 666 9 492 100 More than half of the activity recall days were collected in winter 58 many were collected in autumn 40 and a small number at the end of summer 1 Table Table 13 Seasonality of Activity Recall
138. rtiary Education 2 492 52 2 429 52 2 326 52 Refused 59 1 57 1 56 1 No 2nd Parent 702 15 668 14 622 14 4 837 4 695 4 487 Language spoken at home English only 3 758 78 3 667 78 3 528 79 Other 376 8 359 8 336 8 Refused 1 0 1 O O No 2nd Parent 702 15 668 14 622 14 4 837 4 695 4 487 Country Born Australia 3 180 66 3 105 66 2 973 66 Other 955 20 922 20 892 20 No 2nd Parent 702 15 668 14 622 14 4 837 4 695 4 487 Work Status Working 3 838 79 3 738 80 3 595 80 Not Working 290 6 289 6 270 6 No 2nd Parent 709 15 668 14 622 14 4 837 4 695 4 487 43 Table 17 Household characteristic Completed In Completed Completed all Household Characteristic Home Telephone components Family Couple 4 075 84 3 969 85 3 811 85 Lone Parent 761 16 725 15 675 15 Refused O 1 O 1 O Number in household 2 232 5 219 5 199 4 3 866 18 840 18 792 18 4 2 168 45 2 104 45 2 021 45 5 1 101 23 1 082 23 1 047 23 6 312 7 298 6 282 6 7 101 2 96 2 92 2 8 41 40 39 9 7 O 7 0 7 0 10 5 0 5 0 5 O 11 3 0 3 0 2 0 12 0 0 0 Income 2 400 wk 124 800 yr 725 15 709 15 683 15 2 200 2 399 wk 114 400 124 799 yr 208 4 202 4 192 4 2 000 2 199 wk 104 000 113 999 yr 313 7 302 6 294 7 1 500 1 999 wk 78 000 103 999 yr 913 19 897 19 854 19 1 000 1 499 wk 52 000 77 999 yr 1 060 22 1 033 22 996 22 800 999 wk 42 000 51 999 yr 388 8 376 8 365 8 700 799 wk 36 400 41 999
139. s track and field throwing 341672 medium 342431 racketballl light 342013 badminton hard 342432 racketball medium 342011 badminton light 341453 rockclimbing hard 342012 badminton medium 341451 rockclimbing light 341793 ballet hard 341452 rockclimbing medium 341791 ballet light 342163 rugby league hard 341792 ballet medium 342161 rugby league light 342023 baseball hard 342162 rugby league medium 342021 baseball light 342173 rugby union hard 342022 baseball medium 342171 rugby union light 342033 basketball hard 342172 rugby union medium 342031 basketball light 331493 sailboard windsurfing hard 342032 basketball medium 331491 sailboard windsurfing light 342053 bobsled toboggan luge hard 331492 sailboard windsurfing medium 342051 bobsled toboggan luge light 321943 sailing boating hard 342052 bobsled toboggan luge medium 321941 sailing boating light 342073 broomball hard 321942 sailing boating medium 342071 broomball light 341503 shuffleboard hard 342072 broomball medium 341501 shuffleboard light 341083 calisthenics hard 341502 shuffleboard medium 341081 calisthenics light 341523 skiing cross country hard 341082 calisthenics medium 341521 skiing cross country light 341093 canoeing rowing hard 341522 skiing cross country medium 341091 canoeing rowing light 341533 skiing downhill hard 341092 canoeing rowing medium 341531 s
140. s Yes No signed consent form 1 2 Go to Section D Teminate Interview If No teminate interview Enter reason for Refusing C4 May I record this interview for training purposes Yes No and quality contol procedures 5 Record Do not record 74 SECTION D ABOUT THE HOUSEHOLD Address the parent care giver Now I d like to take a few details about yourself and other members of your household Some of these may seem a bit detailed but if we sort this information out now the rest of the interview will be quicker We are interested in family members who usually live here even if they are away at present Interviewer note usually refers to family members who when not working spend at least 50 of their time residing at the household Firstly am going to ask about the people who normally live in your household Adults Children D1 How many adults and children live in the household err i 99 _ If Refused enter 999 Family Details Parent 1 Parent 2 Partner Study Child Person 4 Let s start with you Is there another Next the study child Who else lives here Enter Parent 1 first parentof child living Enter child s first name here or your name partner D2 What is their first name D3 Is male or female 1 male 2 female 1 male 2 female 1 male 2 female 1 male 02 female 3 No person 3 No person
141. s for non empty population classes and non empty sample classes Wts lt Wts wt tableSPopn gt 0 amp wt table Sample gt 0 Create weight table but without family structure attach wt table wt table3 lt aggregate wt table 7 8 by list Sex Sex AgeGrp AgeGrp Region Region State S tate sum na rm T detach wt table wt table3 Weight lt wt table3SPopn wt table3 Sample 118 Look up weights for each study child Sample Weight3 lt wt table3 Weight match paste Sample Stat Sex Sample Region Sample AgeGrp Sample paste wt table3 State wt table3 Region wt table3SAgeGrp wt table3 Sex Weights may be missing if the postcode missing weights to zero Sample Weight3 is na Sample Weight3 lt 0 curf2 lt curf curf Recruited Recruited Weights lt data frame curf2 Sample Weight3 Set is in th xcluded rang amp curfSCAPI Status INT ERVI EW write table Weights file Weights4 csv sep row names T col names T eol n 119 25 Glossary AUSNUT Energy A survey specific database generated from a reference data base such as NUTTAB 2006 but providing nutrient data on a larger number of foods consumed that are relevant for a consumer intake survey Includes a subset of nutrients included in the reference data base which is based mainly on analytical data AUSNUT 2006 is the survey database specific to Kids Eat Kids Play Body mass index
142. s if required Note that p and Wi are the same for all children in Class g so can be denoted by P and Wg G LMM Py Estimated population proportion 4g a g l With standard deviation 66 where G is the number of Classes Analysis code The calculations for the weights were carried out using the R statistical package version 2 5 04 The R code used in the calculations is given in the Section 24 4R Development Core Team 2007 R A language and environment for statistical computing R Foundation for Statistical Computing Vienna Austria ISBN 3 900051 07 O URL http www kR project org 67 17 Data output and Dissemination In 2008 the key findings from the survey are to be released to stakeholders and the general public in the form of a media launch jointly presented by the Ministers for Health and Ageing and for Agriculture Fisheries and Forestry and the Chairman of the AFGC Following the official launch of the survey results interested and expert parties will have the opportunity to conduct independent analysis and interpretation of the data from the survey via the results database Access to the results database is likely to be controlled by the Department of Health and Ageing However access can be made available to individuals and groups through an application process This comprehensive database will contain all of the data generated through the implementation of this survey For confid
143. serves and frequency of consumption of unhealthy non core foods per week defined as fast food meals snack foods and high energy drinks Cancer Council of Victoria 2006 State Surveys 2007 Healthy Kids Queensland Data were collected in urban and rural and remote Queensland from April to September 2006 Abbott et al 2007 A total of 3 691 school children aged 5 17 years who were undertaking the grades 1 5 or 10 at schoolcompleted a 24 hour dietary record and a food frequency questionnaire FFQ Schools n 112 were chosen using a random cluster design from all government and non government primary and secondary schools Data were weighted to take into account the sampling framework and correct for unequal probability of inclusion 2004 Schools Physical Activity and Nutrition SPANS New South Wales Overall almost 5 500 school children from 93 urban and rural primary and secondary government and non government schools ranging from kindergarten Years 2 4 6 8 and 10 i e students aged 5 to 16 years were surveyed in 2004 Booth et al 2006 A food habits and eating habits questionnaire was used on children aged 11 16 years regarding consumption of fruits vegetables bread rice and pasta meat chicken and fish milk fruit juice soft drinks and confectionery Nutrient intakes were not estimated Information on how often students consumed breakfast lunch dinner ate fast food ate at a fast food outlet ate dinner in front of the te
144. son also will ask about study child s general family background such as your and your partner s work and educational background This will give us a general idea of the home environment study child grows up in Then will ask you some questions about their food intake and what they have done over the last 48 hours am also going to ask if can take some measurements of your child such as his her weight height and waist circumference will then ask the child to conduct a stride test and show you how to wear the pedometer which we ask they do over the next 7 days There will be a few questions on general food habits and finally will ask you some questions about your work and finance Once have finished asking you questions have a short form that will ask you to fill in by yourself and return with the pedometer in the envelope supplied Before we start will need to obtain your formal consent for this study will read you a statement and you will need to provide your signed agreement to take part in the study 71 So that s generally what we are going to be doing do you have any questions at this point Dol have your agreement for you to be part of this study will now get you to formally sign your consent Let s get started then Introduction child aged 9 to 13 years Address the Parent Care Giver Thanks for agreeing to take part in the Kids Eat Kids Play study First of all I want to assure you that
145. st be weighted for appropriate analysis The weight assigned to an individual child is chosen to adjust the stratum averages by the proportion of children in that stratum in the population This derivation of the appropriate weights for non proportionate sampling is described below It must be noted that it is not possible to allow for non response bias by such weighting If the likelihood of responding is related to the nutrition and activity status in some way independent of the weighting variables used here the weighting will not provide any correction Non Proportionate Sampling The sampling for the survey used randomly selected clusters of postcodes chosen to give an approximately equal number of respondents in each age group 2 3 4 8 9 13 14 16 from each of the metro and non metro areas within each State Parents were then contacted using random digit dialling Thus apart from families with no phone assumed here to be a negligible number the selection within the chosen postcode clusters was by household Thus a given child had probability proportional to 1 number of children in household of being selected so that children in small households were proportionately over represented The data was classified by State Territory and separately by Capital City and Rest of State within each State Territory There was no Rest of State data for ACT and no Capital City data for Tasmania or the Northern Territory This gave 13 Reg
146. surements taken under those circumstances have the potential to affect body mass and girth measurements To counter this potential issue physical measurements were taken part way through the interview when the participant had been sitting for at least 30 minutes Measurement of weight was taken with light clothing on possibly slightly inflating the weight and BMI results Waist girth was occasionally taken over light clothing when requested by the subject and this could also increase the waist girth results The difference associated with wearing the light clothing would be small in each of these measurements Comparison with previous surveys Comparison with previous dietary surveys Dietary information recorded in this survey may differ from data obtained using a different method to assess food and nutrient intake such as a food record or a semi quantitative food frequency questionnaire a different food composition database or if different age groups were assessed The methodology used in this survey is broadly comparable to that used in the 1995 NNS Differences between the two surveys include e Sampling frame e The age groups used for reporting differ between the two surveys The 1995 NNS reported intakes for 2 3 years 4 7 years 8 11 years 12 15 years and 16 18 years e Repeat 24 hour recalls were collected on all participants for this survey whereas the 1995 NNS collected repeat 24 hour recalls on only 10 of the sample an
147. t study child s general family background such as your and your partner s work and educational background This will give us a general idea of the home environment study child grows up in Then I will ask you some questions about their food intake am also going to ask if can take some measurements of your child such as his her weight height and waist circumference There will be a few questions on general food habits and finally will ask you some questions about your work and finance Once have finished asking you questions have a short form that will ask you to fill in by yourself Before we start will need to obtain your formal consent for this study will read you a statement and you will need to provide your signed agreement to take part in the study So that s generally what we are going to be doing do you have any questions at this point Dol have your agreement for you and study child to be part of this study will now get you to formally sign your consent Let s get started then Introduction child aged 5 to 9 years Address the Parent Care Giver Thanks for agreeing to take part in the Kids Eat Kids Play study First of all want to assure you that all information that you give me will be kept confidential and we have strict processes to ensure the security of your information will start by asking a few questions about the household how many people live here and a little bit about each per
148. t content of the NUTTAB 2006 food Milk flavoured strawberry reduced fat Other nutrient modifications may also have been necessary for example changing the cholesterol value when the fat content is reduced e Using nutrient data from product labels For example if a respondent reported consuming Juice orange no added sugar added vitamin C the NUTTAB 2006 food Juice orange unsweetened unfortified would be used as a basis for developing a new food and the vitamin C value would be modified to reflect the vitamin C value presented on the nutrition information panel of commonly consumed brands of orange juice fortified with vitamin C Recipe calculation Recipe calculations were used to generate nutrient data for mixed dishes prepared at home or purchased commercially where the respondent was unable to identify the individual ingredients or their amounts The general approach involved e consulting current popular recipe books Australian food magazines and websites to identify appropriate recipes for home prepared foods e combining individual ingredients and their relative proportions e applying an appropriate nutrient retention factor to each individual ingredient if necessary e applying an appropriate weight change factor to the uncooked recipe if necessary 47 The retention and weight change factors used in these calculations were taken from published literature e g USDA 2006 Recipes for commercial products we
149. tal Folate micrograms Dietary folate equivalents micrograms Minerals amp electrolytes Potassium milligrams Sodium milligrams Calcium milligrams Phosphorus milligrams Magnesium milligrams Iron milligrams Zinc milligrams lodine micrograms Other Caffeine milligrams 94 FOOD AND NUTRIENT INTAKE THE PREVIOUS DAY summary information available per person per day excluding intake from dietary supplements Data Items Day of week of intake Type of Day Season of intake Total amount of each nutrient per person per day Descriptors Population Monday All Tuesday Wednesday Thursday Friday Saturday Sunday Weekday All Weekend Day School Holiday Public Holiday Summer All Autumn Winter Spring Proximates All Energy kilojoules Energy including from fermentable fibre kilojoules Moisture water grams Protein grams Fat total grams Saturated fatty acids total grams Monounsaturated fatty acids total grams Polyunsaturated fatty acids total grams alpha linolenic fatty acid grams linoleic acid fatty acid grams long chain omega s3 fatty acids milligrams Cholesterol milligrams Carbohydrate total grams Sugars total grams Starch grams Dietary fibre grams Alcohol grams Vitamins Vitamin A expressed as retinol equivalents micrograms Preformed vitamin A retinol micrograms Provitamin A beta carotene micrograms Thi
150. tal minutes spent lying down excluding sleep Total minutes of sleep Wake up time Bed time PEDOMETER DATA for eligible respondents Data Items Day Number sequential Date of recording The number of steps made during the 24 hours The distance traveled in km The number of minutes of physical activity The number of minutes in which the pedometer was not worn The date on which the pedometer was sent back Population All All All All All All All All All All All All All All All All All All All All All Population All All All All All All All 100 Main Interview Demography postcode of residence state of residence Number of adults in Household aged 218 years Number of children in Household aged lt 18 years Parent 1 Gender Parent 1 Age Parent 1 ATSI Parent 1 Country Born Parent 1 language spoken Parent 1 School Ed Parent 1 Higher Ed Parent 2 Gender Parent 2 Age Parent 2 Relationship to Parent 1 Parent 2 ATSI Parent 2 Country Born Parent 2 language spoken Parent 2 School Ed Parent 2 Higher Ed Study Child Gender Study Child Age Study Child Date of Birth Study Child Relationship to Parent 1 Study Child Relationship to Parent 2 Study Child ATSI Study Child Country Born Study Child Language Spoken Study Child Medical Condition Person 4 to 12 Gender Person 4 to 12 Age Person 4 to 12 Relationship to Parent 1 Person 4 to 12 Relationship to Parent 2 Househol
151. tart will need to obtain formal consent for this study from the parent care giver and study child will now read a statement and will need you to provide your signed agreement to take part in the study So that s generally what we are going to be doing do you have any questions at this point Dol have both your agreement to be part of this study will now get you both to formally sign your consent Let s get started then 73 SECTION C CONSENTSC REEN I now have to obtain your formal consent for this study and have to read to you the following statement You and your family are being asked to take part in the Australian National Children s Nutrition and Physical Activity Survey Kids Eat Kids Play in conjunction with the CSIRO and the University of South Australia The study will measure the physical activity nutrition habits and body size and shape of a large group of children aged two to sixteen years The Kids Eat Kids Play is being conducted on behalf of the Australian Government by the CSIRO and the University of South Australia who have contracted I view to collect the data on their behalf All the information collected will be kept strictly confidential except where it is required to be reported by law and or there is a risk of harm to yourself or others Information that identifies you will only be disclosed to research consultants for the purposes of administering the Kids Eat Kids Play Identifying mate
152. tation That is the first household uses Table A the second Table B1 etc e Asking the parent care giver for the name gender and age in years of each child in the household aged 2 16 years e Ordering the children by age oldest to youngest e Numbering the children in the sorted listing sequentially from one e Assigning priority for age group if applicable highest priority assigned to children aged 14 16 years then children aged 2 3 years if present in household e Looking up the person number corresponding to the total number of children aged 2 16 years in the allocated Kish table Table 4 and nominate that person as the study child 19 Figure 1 Sample Generation Flow Chart Repeat Process for each Location until required numbers achieved Compile a list of postcodes for each location Compile a list of 6 digit phone number prefixes for each location based on postcodes Randomly select prefix t Randomly select 2 digit suffix t Create 8 digit phone number by appending suffix to prefix s number in database No Flag acceptable phone numbers with location i Add to CATI Sample file Table 4 Kish Table Discard gt Yes Load file into CATI system in batches after exhaustion of sample Summary of Kish Tables A Bl B2 C D El E2 F Kish Tabl
153. tems The sample was generated for each location using prefixes flagged as belonging to the postcodes for that location For each location prefixes were randomly selected with equal probability of selection A randomly generated 2 digit suffix 00 99 was then appended to the prefix to create a complete phone number The resultant number was checked to ensure it had not been generated in the previous sample The number was then appended to the bottom of the sample list which remained in order of item generation The RDD sample generation process is summarised in Figure i The postcodes were grouped as a cluster location for sample selection The probability of a sample being selected within each postcode was proportional to the list of phone number prefixes for that postcode within the cluster location Selection of participants The sample unit is the study child Only one child per household was invited to participate For younger children lt 9 years the primary care giver defined as the person who knows the most about the study child s diet and activity patterns provided demographic information and acted as a proxy for the study child Where there was more than one child aged 2 16 years in a household a Kish method of child selection was used to ensure adequate representation of age and gender of children within the sample The method for child selection involved e Pre allocating a Kish Table to be used for the household by ro
154. terviewer Alert Please write down height amp weight on a notepad needed this later for MARCA F22 ANTHRO completed Yes No F23 NOTCOMPLEIED specify reason If child is under 9 Thank you very much for your help today you have done very well at the measurement activities Thatis all need to ask you today now have some questions for your mum dad other 84 SECTION G Rotate between LINZ24 and MARCA Address the child over 9 years Interviewer Note _ If child is 9 years and older only conduct either the LINZ24 or MARCA that was not completed in SECTION E G4 LINZ24 Completed gt If 9 years or older G1 MARCA Completed gt Only if 9 years orolder Day One Yes ONLY No G2 ONLY DAY ONE OF MARCA COMPLETED specify reason G3 MARCA NOTCOMPLETED specify reason Yes No G5 UNZ24 NOTCOMPLEIED specify reason G6 CARER FORM USED 1 Yes data included 2 To be edited later upon return 3 No 85 SECTION H FOOD HABITS SURVEY Address the child if over 9 years otherwise address the parent care giver Interviewer Note Please give parent Food Habits Survey questions if not already completed duri ANTHRO H1 Whatis the main type of milk that you usually use Parent 1 Study Child if 9 years only 1 Whole full cream
155. the Department of Agriculture Fisheries and Forestry and the Australian Food and Grocery Council A representative from each of the three funding agencies formed a Steering Group which was involved in managing the development and implementation of the survey Section 0 The Steering Group selected The University of South Australia UniSA and the Commonwealth Scientific Industrial and Research Organisation CSIRO to undertake the survey by a tender process and together they sub contracted l view Pty Ltd to manage the fieldwork This project team UniSA CSIRO and l view Section 0 further defined the content and methodology and implemented the survey UniSA provided anthropometric measurement and physical activity assessment expertise CSIRO provided dietary assessment expertise data management population weighting factors and overall project management I View managed the recruitment fieldwork and supervised the interviewers All project team members contributed to survey development and interviewer training The project team acknowledges Flinders University for contribution towards analysis of the dietary data The Technical Reference Group appointed by the Steering Group provided advice on a variety of issues relating to conducting and interpreting nutrient intake and physical activity surveys The Technical Reference Group was comprised of experts in the fields of nutrition physical activity and survey development 13 FSANZ colla
156. the extracted data weighted to reflect the Australian population The summary data consist of descriptive means standard deviations and percentiles for the following groups of variables e physical activity e sedentary behaviour e miscellaneous activity sets and e prevalence of compliance with activity and screen time recommendations Physical activity variables The variables used to describe physical activity were e Physical Activity Level PAL The average rate of energy expenditure over the course of a day It is expressed in multiples of child specific resting metabolic rate or metabolic equivalents METs For example a PAL of 1 7 would mean that a child uses on average 1 7 times the amount of energy required to sit still all day In this survey PAL was estimated from MARCA data PAL is calculated by multiplying the estimates of activity specific energy expenditure by the number of minutes reported for each activity and averaging across the 1440 minutes of each day e Moderate to vigorous physical activity MVPA The number of minutes spent performing activities which require at least 3 METs based on the MARCA Compendium Section 23 or three times resting metabolic rate e Vigorous physical activity VPA The number of minutes spent performing activities which require at least 6 METs or six times resting metabolic rate e Organised sport and play Active recreation which is structured and rule governed typically
157. things Limited use of legs or feet Nerves or emotional conditions that need treatment Any disfigurement or deformity Chronic or recurring pain Any condition that restricts physical activity or physical work e g back problems migraines Shortness of breath or difficulty breathing Any mental illness for which help or supervision is required Long term effects as a result of a head injury stroke or other brain damage Any other long term condition such as arthritis asthma heart disease Alzheimer s disease dementia etc Any other long term condition that requires treatment or medication 99 NONE Person 7 Who else lives here Person 8 12 Who else lives here 1 male 2 female 1 male 2 female 3 no person 3 no person 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 6 biological child 7 adopted child 8 step child 9 foster child 10 grandchild 77 D6 How is related to parent 2 partner 11 niece nephew 12 cousin 3 other relative in law 13 unrelated child 14 sibling 15 parent 16 grandparent 17 aunt uncle 4 boarder housemate
158. uld participate One child within the household was selected as the study child for the purposes of the survey In some cases recruitment of the study child did not proceed because the age and gender quota for that location was filled Sample Design Postcode exclusion There were 576 postcodes excluded from selection Table 2 Areas identified in the 2001 ABS Census as having very few in scope children and very remote areas were excluded from the survey sampling frame due to budgetary and time restrictions Additionally this survey was not designed to obtain information from a representative number of Indigenous groups to accurately record their intake and activity patterns Using the 2001 ABS population data postcodes covering areas where there were more than 50 of the population identified as Indigenous were excluded Table 2 Postcodes excluded from selection State Total ACT 2 NSW 68 NT 11 QLD 94 SA 95 TAS 26 VIC 159 WA 121 Total 576 Postcode selection The number of postcodes selected in each state was proportional to the population by state and metropolitan non metropolitan areas Postcodes had an equal chance of initial selection within strata An initial selection of 50 postcodes locations was undertaken Postcodes in close geographical proximity to these locations were then added to expand the cluster sizes to obtain a total of 230 postcodes This minimised travel time and costs for intervi
159. under 5 years skip to SECTION Anthrop Physical Measures Pedometer instructions and interviewer script Here is the pedometer that we want you to wear for 6 days straight starting tomorrow morning Once have measured your stride length will put a plastic tie around it to stop it from opening Please do not remove the tie it is there to make sure that we don t lose the information that the pedometer is collecting When you get dressed tomorrow morning would like you to fit the pedometer by placing it half way between your belly button and your hip the right way up Interviewer demonstates position and shows what to do for different types of clothing Please clip the security strap to a belt loop belt or pocket opening this is to make sure that the pedometer is not lost if it slips off After a while you will forget that you are wearing the pedometer it is so small and light The idea is to do the things that you usually do and not to change what you do just because you are wearing the pedometer Each night when the pedometer is removed would like you to open the pedometer to write the stored information on the pedometer log sheet Interviewer shows c hild parent the Pedometer Log Sheet First write the day and the date in the Pedometer Log Sheet here Interviewer shows study child parent care giver the Pedometer Log Sheet All you need to do then is press the MODE button until the black marker is under STEPS on the d
160. usually eaten each day 1 serve 1 medium piece of fruit Number of serves of vegetables usually eaten each day 1 serve cup cooked vegetables e Type of milk usually consumed full cream reduced fat soy e Whether salt is usually added to food after it is cooked e Whether salt is usually added to food during cooking e Use of iodised or non iodised salt The primary care giver was asked about e Food security If the household always had sufficient money to buy food e Infant feeding habits e Ifthe child had ever been breastfed and when did weaning occur e If the child had ever been given infant formula regularly e What age were solids introduced e Child s birth weight and the source of that information 32 Table 10 Nutrients and food components collected in the survey Nutrient food component Unit Proximate constituents Energy Kilojoules kJ Energy including from fermentable fibre Kilojoules kJ Moisture water Grams g Protein Grams g Fat total Grams g Saturated fatty acids total Grams g Monounsaturated fatty acids total Grams g Polyunsaturated fatty acids total Grams g alpha linolenic fatty acid Grams g linoleic acid fatty acid Grams g long chain omega 3 fatty acids Milligrams mg Cholesterol Milligrams mg Carbohydrate total Grams g Sugars total Grams g Starch Grams g Dietary fibre Grams g Alcohol Grams g
161. weeks Delayed fieldwork meant that some field interviewers had to resign before the data collection was completed due to prior commitments 69 19 CAPI survey Script SECTION A STARTSC REEN lt aaal23 gt Al Enter the RESPONDENTID number from the Family Contact Fom A2 Enter the Random ID from the Family Contact Form A3 Enter the DOB of the child from the Family Contact Fom AG Enter the postc ode Enter the State AGa AZ Select Interviewer ID A8 Date of Interview A9 Day of Interview A10 Day Type lt add ina code list gt Drop down list retains last state selected NSW VIC QLD SA WA TAS NT ACT lt insert list when interviewers confirmed gt Record Automatically Record Automatically 1 Monday 2 Tuesday 3 Wednesday 4 Thursday 5 Friday 6 Saturday 7 Sunday Record Automatically 1 Weekday 2 Weekend 3 Public Holiday 4 School Holiday 70 SECTION B INTRODUCTION SC REEN Introduction child aged 2 to 4 years Address the Parent Care Giver Thanks for agreeing to take part in the Kids Eat Kids Play study First of all want to assure you that all information that you give me will be kept confidential and we have strict processes to ensure the security of your information will start by asking a few questions about the household how many people live here and a little bit about each person also will ask abou
162. whatage was your child first given infant fomula regulary Weeks Months O Don t know H13 At whatage was child s name first given solid food regularly Weeks Months O Don t know H14 How much did child s name weigh at birth kilograms grams OR pounds ounces H14f Wasa written record used to recall the birth weight O 1 Yes O 2 No 87 H15 Which one of the following best describes child s name usual way of eating O 1 No special way of eating O 2 Vegetarian diet O 3 Weight reduction diet O 4 Diabetic diet O 5 Fat modified diet to lower blood fat cholesterol O 6 Other Specify O 7 Refused If child is over 9 Thank you very much for your help today you have done very well at the all the activities and tasks now have some questions for your mum dad other but I will talk to you again before I leave about the follow up survey over the telephone 88 SECTION I RECALL DAYS Address the child if over 9 years otherwise address the parent care giver I1 Was there anything unusual about yesterday that should be noted forthe researchers analysing the food intake or activity data for this child 1 Yes record comment 2 No Skip to 13 12 Comments 13 Was there anything unusual about the day before yesterday that should be noted for the researchers analysing the activity data for this child 1 Yes record comment 2 No Skip to Section J
163. y 10 of the survey participants provided a second 24 hour recall on a different day of the week generally within ten days of the first recall This additional data enabled an estimate of the within person variation in nutrient intake to be obtained This within person variation data was used to adjust the one day intakes from the survey to provide a more accurate approximation of the usual intake for the group ABS 1998b The 1995 NNS nutrient composition data base called AUSNUT 1997 was used The person specific weights were adjusted for regional probability of selection and non response based on a number of geo demographic characteristics 2004 05 National Health Survey This survey conducted by the ABS was designed to obtain national information on the health status of Australians their use of health services and facilities and health related aspects of their lifestyle ABS 2006 The survey included some short dietary habits questions asking about the usual fruit and vegetable consumption number of serves for participants aged 12 years and over and current breastfeeding practices for infants and children ages three and under Activity was assessed in those aged 15 years and above 2005 Australian Secondary Students Alcohol and Drug Survey Secondary students n 18 486 aged between 12 and 17 years from all states except Western Australia were asked short dietary questions to measure usual fruit and vegetable intake number of
164. zed photograph of potato chips e Aset of 10 concentric rings a grid and a moveable wedge to help determine three dimensional sizes of irregular foods e g pizza lasagna or watermelon e Photographs of beef lamb and chicken cuts chocolate milk drinks carbonated drinks juices yoghurt and muesli snack bars were included to assist with correct identification of product not portion size The following measuring aids were available for the CAPI only and included e Household spoons a metal teaspoon and tablespoon e Measuring cups labelled 3 and 1 cup e Measuring spoons labelled 1 4 tsp 2 tsp 1 tsp 1 tbsp e Ruler a plastic ruler with fractions e Measuring container for measuring fluids Caregiver Fom A caregiver form was provided to record intake if the participant was aged less than nine years and had been in the care of others during the recall period This information was added to the dietary recall during the interview Nutrient Intake The 24 hour food beverage and supplement intakes were converted into nutrient intakes Table Section 14 using a nutrient composition database developed specifically for this survey by FSANZ Foods Habits Questions A series of food related questions provided additional information on the usual eating habits of participants All participants were asked the following questions e Usual eating habits i e lactose free vegetarian Number of serves of fruit

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