Foreword and acknowledgements - Department of … · Web viewSpecific physical activity level (PAL) data for a range of activities were used to calculate overall daily PAL (as a multiple

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Citation:

Commonwealth Scientific and Industrial Research Organisation. The 2007 Australian National Children’s Nutrition and Physical Activity Survey Volume Six: Demography. Department of Health and Ageing, Canberra, 2012

iii

The 2007 Australian National Children’s Nutrition and Physical Activity Survey

Volume Six: Demography

Prepared by:

Dr Jane Bowen1, BSc, BNut&Diet (Hons), PhD

Dr Malcolm Riley1, BSc (Hons), DipNutrDiet, PhD

Julie Syrette1, BSc

Danielle Baird1, BNut&Diet (Hons)

Mary Barnes2, BAppSc(Hons), GDipMaths

Prof Ian Saunders2, BA (Hons) DipMathStats PhD

Acknowledgements

Dr Nadia Corsini1, BPsyc (Hons), PhD

Kylie Lange3 BSc(Ma&CompSci)(Hons)

1 CSIRO Food and Nutritional Sciences, 2 CSIRO Mathematics Informatics and Statistics, 3 The University of Adelaide, Discipline of Medicine

. This work is one in a series of publications made under the Additional Analyses and Reporting of Results from the 2007 Australian National Children’s Nutrition and Physical Activity Survey project, and created under contract by the Commonwealth Scientific and Industrial Research Organisation as contract material for the Department of Health and Ageing.

Important Disclaimer

The Commonwealth of Australia advises that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without first seeking expert professional, scientific and technical advice.

To the extent permitted by law, the Commonwealth of Australia (including its employees and officers) and its contractor CSIRO exclude all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole), and any information or material contained in it, in any way.

Enquires about obtaining a copy of this report should be directed by post to:

The Director – Nutrition Section

Department of Health and Ageing

GPO Box 9848

Canberra ACT 2601

Phone: (02) 6289 1555

Email: [email protected]

Enquiries about the analyses or results presented in this report should be directed to:

Julie Syrette

Commonwealth Scientific and Industrial Research Organisation

PO Box 10041

Adelaide SA 5000

Phone: (08) 8303 8800

Fax: (08) 8303 8899

Email: [email protected] 

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ii

Contents

Foreword and acknowledgements1

1Background information5

1.1Introduction5

1.2Related reports7

2Summary of findings10

2.1Foods eaten10

2.2Nutrient intakes (excluding dietary supplements)16

2.3Dietary supplements18

2.4Physical activity19

2.5Physical measures21

3Tabulations23

3.1Demographic breakdown: foods eaten23

3.2Demographic breakdown: nutrient intakes133

3.3Demographic breakdown: dietary supplement consumption158

3.4Demographic breakdown: physical activity162

3.5Demographic breakdown: physical measures167

Explanatory notes179

Abbreviations190

APPENDIX 1: Food groups193

APPENDIX 2: Unweighted cell counts201

APPENDIX 3: Statistical analyses246

Foods eaten249

Nutrient intakes334

Dietary supplement consumption344

Physical activity348

Physical measures354

Glossary357

References363

iii

List of Tables

Table 3.1 Mean intake of selected major and sub major food groups: all children by state/territory of residence23

Table 3.2 Mean intake of selected major and sub major food groups (consumers only): all children by state/territory of residence29

Table 3.3 Mean intake of selected major and sub major food groups: all children by country of birth ((average grams per person – all respondents) by Country of Birth )45

Table 3.4 Mean intake of selected major and sub major food groups (consumers only): all children by country of birth (mean grams per consumer)51

Table 3.5 Persons consuming (percent) selected major and sub major food groups: all children by country of birth56

Table 3.6 Mean intake of selected major and sub major food groups: all children by highest education level of either parent/carer63

Table 3.7 Mean intake of selected major and sub major food groups (consumers only): all children by highest education level of either parent/carer68

Table 3.8 Persons consuming (percent) selected major and sub major food groups: all children by highest education level of either parent/carer73

Table 3.9 Mean intake of selected major and sub major food groups: all children by household annual income grouping (average grams per person – all respondents) / Income grouping80

Table 3.10 Mean intake of selected major and sub major food groups (consumers only): all children by household annual income grouping86

Table 3.11 Persons consuming (percent) selected major and sub major food groups: all children by household annual income grouping93

Table 3.12 Mean intake of selected major and sub major food groups: all children by level of remoteness101

Table 3.13 Mean intake of selected major and sub major food groups (consumers only): all children by level of remoteness107

Table 3.14 Persons consuming (percent) selected major and sub major food groups: all children by level of remoteness112

Table 3.15 Mean intake of selected major and sub major food groups: all children by BMI classification118

Table 3.16 Mean intake of selected major and sub major food groups (consumers only): all children by BMI classification123

Table 3.17 Persons consuming (percent) selected major and sub major food groups: all children by BMI classification128

Table 3.18 Mean intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by state/territory of residence133

Table 3.19 Median intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by state/territory of residence135

Table 3.20 Mean intake of vitamins, minerals, and caffeine: all children by state/territory of residence136

Table 3.21 Median intake of vitamins, minerals, and caffeine: all children by state/territory of residence137

Table 3.22 Mean intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by country of birth138

Table 3.23 Median intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by country of birth139

Table 3.24 Mean intake of vitamins, minerals, and caffeine: all children by country of birth140

Table 3.25 Median intake of vitamins, minerals, and caffeine: all children by country of birth141

Table 3.26 Mean intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by highest education level of either parent/carer142

Table 3.27 Median intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by highest education level of either parent/carer143

Table 3.28 Mean intake of vitamins, minerals, and caffeine: all children by highest education level of either parent/carer144

Table 3.29 Median intake of vitamins, minerals, and caffeine: all children by highest education level of either parent/carer145

Table 3.30 Mean intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by household annual income grouping146

Table 3.31 Median intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by household annual income grouping147

Table 3.32 Mean intake of vitamins, minerals, and caffeine: all children by household annual income grouping148

Table 3.33 Median intake of vitamins, minerals, and caffeine: all children by household annual income grouping149

Table 3.34 Mean intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by level of remoteness150

Table 3.35 Median intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by level of remoteness151

Table 3.36 Mean intake of vitamins, minerals, and caffeine: all children by level of remoteness152

Table 3.37 Median intake of vitamins, minerals, and caffeine: all children by level of remoteness153

Table 3.38 Mean intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by BMI classification154

Table 3.39 Median intake of energy (kJ), moisture (g), macronutrients (g) and dietary fibre(g): all children by BMI classification155

Table 3.40 Mean intake of vitamins, minerals, and caffeine: all children by BMI classification156

Table 3.41 Median intake of vitamins, minerals, and caffeine: all children by BMI classification157

Table 3.42 Proportion of all children (%) consuming at least 1 dietary supplement on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by state/territory of residence158

Table 3.43 Proportion of all children (%) consuming at least 1 dietary supplement on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by country of birth158

Table 3.44 Proportion of all children (%) consuming at least 1 dietary supplement on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by highest education level of either parent/carer158

Table 3.45 Proportion of all children (%) consuming at least 1 dietary supplement on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by household annual income grouping160

Table 3.46 Proportion of all children (%) consuming at least 1 dietary supplement on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by level of remoteness160

Table 3.47 Proportion of all children (%) consuming at least 1 dietary supplement on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by BMI classification160

Table 3.48 Mean steps: 5–16 year old children by state/territory of residence162

Table 3.49 Mean steps: 5–16 year old children by country of birth162

Table 3.50 Mean steps: 5–16 year old children by highest education level of either parent/carer162

Table 3.51 Mean steps: 5–16 year old children by household annual income grouping164

Table 3.52 Mean steps: 5–16 year old children by level of remoteness164

Table 3.53 Mean steps: 5–16 year old children by BMI classification164

Table 3.54 Mean PAL: 9–16 year old children by state/territory of residence165

Table 3.55 Mean PAL: 9–16 year old children by country of birth165

Table 3.56 Mean PAL: 9–16 year old children by highest education level of either parent/carer165

Table 3.57 Mean PAL: 9–16 year old children by household annual income grouping166

Table 3.58 Mean PAL: 9–16 year old children by level of remoteness166

Table 3.59 Mean PAL: 9–16 year old children by BMI classification166

Table 3.60 Mean, median and range for height (cm): all children by state/territory of residence167

Table 3.61 Mean, median and range for height (cm): all children by country of birth167

Table 3.62 Mean, median and range for height (cm): all children by highest education level of either parent/carer167

Table 3.63 Mean, median and range for height (cm): all children by household annual income grouping169

Table 3.64 Mean, median and range for height (cm): all children by level of remoteness169

Table 3.65 Mean, median and range for weight (kg): all children by state/territory of residence170

Table 3.66 Mean, median and range for weight (kg): all children by country of birth170

Table 3.67 Mean, median and range for weight (kg): all children by highest education level of either parent/carer170

Table 3.68 Mean, median and range for weight (kg): all children by household annual income grouping172

Table 3.69 Mean, median and range for weight (kg): all children by level of remoteness172

Table 3.70 Mean, median and range for waist circumference (cm): all children by state/territory of residence173

Table 3.71 Mean, median and range for waist circumference (cm): all children by country of birth173

Table 3.72 Mean, median and range for waist circumference (cm): all children by highest education level of either parent/carer173

Table 3.73 Mean, median and range for waist circumference (cm): all children by household annual income grouping175

Table 3.74 Mean, median and range for waist circumference (cm): all children by level of remoteness175

Table 3.75 Mean, median and range for waist circumference (cm): all children by BMI classification175

Table 3.76 Proportion of all children (%) and unweighted count (n) by BMI classification: state/territory of residence176

Table 3.77 Proportion of all children (%) and unweighted count (n) by BMI classification: country of birth176

Table 3.78 Proportion of all children (%) and unweighted count (n) by BMI classification: highest education level of either parent/carer176

Table 3.79 Proportion of all children (%) and unweighted count (n) by BMI classification: household annual income grouping178

Table 3.80 Proportion of all children (%) and unweighted count (n) by BMI classification: level of remoteness178

Table A2.1 Cell counts for children by state/territory of residence…………………………………………………………………………………….....201

Table A2.2 Cell counts for children consuming each food group (major and sub major) by state/territory of the residence…………………….201

Table A2.3 Cell counts for children by country of birth…………………………………………………………………………………………………..208

Table A2.4 Cell counts for children consuming each food group (major and sub major) by country of birth………………………………………208

Table A2.5 Cell counts for children by highest education level of the parent…………………………………………………………………………215

Table A2.6 Cell counts for children consuming each food group (major and sub major) by highest education level of either parent/carer215

Table A2.7 Cell counts for children by household annual income grouping…………………………………………………………………………..222

Table A2.8 Cell counts for children consuming each food group (major and sub major) by household annual income grouping………………222

Table A2.9 Cell counts for children by level of remoteness……………………………………………………………………………………………229

Table A2.10 Cell counts for children consuming each food group (major and sub major) by level of remoteness………………………………229

Table A2.11 Cell counts for children by BMI category…………………………………………………………………………………………………...235

Table A2.12 Cell counts for children consuming each food group (major and sub major) by BMI category………………………………………235

Table A2.13 Cell counts for pedometer data (steps) by state/territory of residence……………………………………………………………………...241

Table A2.14 Cell counts for pedometer data (steps) by country of birth…………………………………………………………………………………..241

Table A2.15 Cell counts for pedometer data (steps) by highest education level of either parent/carer……………………………………………242

Table A2.16 Cell counts for pedometer data (steps) by household annual income grouping…………………………………………………………..242

Table A2.17 Cell counts for pedometer data (steps) by level of remoteness…………………………………………………………………………242

Table A2.18 Cell counts for pedometer data (steps) by BMI classification………………………………………………………………………………..242

Table A2.19 Cell sizes for MARCA data by state/territory of residence……………………………………………………………………………………243

Table A2.20 Cell sizes for MARCA data by country of birth………………………………………………………………………………………………...243

Table A2.21 Cell sizes for MARCA data by highest education level of either parent/carer……………………………………………………………..244

Table A2.22 Cell sizes for MARCA data by reported household annual income grouping……………………………………………………………...244

Table A2.23 Cell sizes for MARCA data by level of remoteness…………………………………………………………………………………………...244

Table A2.24 Cell sizes for MARCA data by BMI classification……………………………………………………………………………………………...244

Table A3.1 Post-hoc comparisons used for tests of effects of state/territory of residence249

Table A3.2 Post-hoc comparisons used for tests of effects of highest education level of either parent/carer249

Table A3.3 Post-hoc comparisons used for tests of effects of household annual income grouping251

Table A3.4 Post-hoc comparisons used for tests of effects of BMI category251

Table A3.5 Results for statistical analysis of differences in mean intake for each food group (consumers only) by state/territory of residence; p value and significant post-hoc comparisons253

Table A3.6 Results for statistical analysis of differences in mean intake for each food group (consumers only) by highest education level of either parent/carer; p value and significant post-hoc comparisons262

Table A3.7 Results for statistical analysis of differences in mean intake for each food group (consumers only) by reported household annual income grouping; p value and significant post-hoc comparisons269

Table A3.8 Results for statistical analysis of differences in mean intake for each food group (consumers only) by level of remoteness; p value and direction of result276

Table A3.9 Results for statistical analysis of differences in the proportion of children consuming each food group by state/territory of residence; p value and significant post-hoc comparisons297

† The number of participants consuming this food was too small for a valid test of statistical significance. Where p values are shown, they should be considered indicative only. Table A3.10 Results for statistical analysis of differences in the proportion of children consuming each food group by highest education level of either parent/carer; p value and significant post-hoc comparisons307

Table A3.11 Results for statistical analysis of differences in the proportion of children consuming each food group by household annual income grouping; p value and significant post-hoc comparisons313

Table A3.12 Results for statistical analysis of differences in the proportion of children consuming each food group by level of remoteness; p value and direction of result320

Table A3.13 Results for statistical analysis of differences in the proportion of children consuming each food group by BMI classification; p value and significant post-hoc comparisons326

Table A3.14 Results for statistical analysis of differences in mean nutrient intake by state/territory of residence; p value and significant post-hoc comparisons335

Table A3.15 Results for statistical analysis of differences in mean nutrient intake by highest education level of either parent/carer; p value and significant post-hoc comparisons337

Table A3.16 Results for statistical analysis of differences in mean nutrient intake by reported household annual income grouping; p value and significant post-hoc comparisons339

Table A3.17 Results for statistical analysis of differences in mean nutrient intake by level of remoteness; p value and direction of result340

Table A3.18 Results for statistical analysis of differences in mean nutrient intake by BMI classification; p value and significant post-hoc comparisons342

Table A3.19 Results for statistical analysis of differences in the proportion of children consuming supplements on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by state/territory of residence; p value and significant post-hoc comparisons.344

Table A3.20 Results for statistical analysis of differences in the proportion of children consuming supplements on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by highest education level of either parent/carer; p value and significant post-hoc comparisons.345

Table A3.21 Results for statistical analysis of differences in the proportion of children consuming supplements on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by household annual income grouping ; p value and significant post-hoc comparisons.346

Table A3.22 Results for statistical analysis of differences in the proportion of children consuming supplements on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by level of remoteness; p value and direction of result.346

Table A3.23 Results for statistical analysis of differences in the proportion of children consuming supplements on CAPI day of recall, CATI day of recall, any day of recall and both days of recall by BMI classification; p value and significant post-hoc comparisons.346

Table A3.24 Results for statistical analysis of differences in the mean number of steps taken by children by state/territory of residence; p value and significant post-hoc comparisons.348

Table A3.25 Results for statistical analysis of differences in the mean number of steps taken by children by highest education level of either parent/carer; p value and significant post-hoc comparisons.349

Table A3.26 Results for statistical analysis of differences in the mean number of steps taken by children by reported household annual income grouping; p value and significant post-hoc comparisons.350

Table A3.27 Results for statistical analysis of differences in the mean number of steps taken by children by level of remoteness; p value and direction of result.350

Table A3.28 Results for statistical analysis of differences in the mean number of steps taken by children by BMI classification; p value and significant post-hoc comparisons.350

Table A3.29 Results for statistical analysis of differences in children’s mean PAL by state/territory of residence; p value and significant post-hoc comparisons.351

Table A3.30 Results for statistical analysis of differences in children’s mean PAL by highest education level of either parent/carer; p value and significant post-hoc comparisons.351

Table A3.31 Results for statistical analysis of differences in children’s mean PAL by reported household annual income grouping; p value and significant post-hoc comparisons.352

Table A3.32 Results for statistical analysis of differences in children’s mean PAL by level of remoteness; p value and direction of result.352

Table A3.33 Results for statistical analysis of differences in children’s mean PAL by BMI classification; p value and significant post-hoc comparisons.353

Table A3.34 Results for statistical analysis of differences in children’s mean height, weight and waist girth by state/territory of residence; p value and significant post-hoc comparisons354

Table A3.35 Results for statistical analysis of differences in children’s mean height weight and waist girth by highest education level of either parent/carer; p value and significant post-hoc comparisons355

Table A3.36 Results for statistical analysis of differences in children’s mean height, weight and waist girth by reported household annual income grouping; p value and significant post-hoc comparisons356

Table A3.37 Results for statistical analysis of differences in children’s mean height weight and waist girth by level of remoteness; p value and direction of result356

Table A3.38 Results for statistical analysis of differences in children’s mean waist girth by BMI classification; p value and significant post-hoc comparisons356

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Foreword and acknowledgements

Dietary intake is a key determinant of health and wellbeing, and overall intake is directly or indirectly related to many chronic diseases in the Australian population. Dietary intake in childhood and adolescence is particularly important not only because of its impact on immediate health, but also because of its impact on physiological development and possible influence on future dietary patterns.

Dietary behaviour is a complex activity encompassing what foods and drinks are consumed, how they are prepared, how much is consumed and with what, and where food and drinks are consumed. The meaning of dietary intake in terms of nutrients consumed is important to assess aspects of dietary adequacy and overconsumption. This description of how the population of Australian children and adolescents consume food and drink will be useful to the public and private sector in assessing how dietary intake is changing, and in working towards improving dietary intake. The information will be of practical use to government policy makers, health professionals, the food and beverage industry and health advocates. Healthy life-long eating habits are important for all Australians.

This publication is one of a series of eight publications which presents data on food and beverage consumption, nutrient intake and physical activity by the Australian population aged 2–16 years. The data are derived from the 2007 Australian National Children’s Nutrition and Physical Activity Survey (ANCNPAS) which collected information on food and nutrition, body size and physical activity.

The 2007 ANCNPAS was jointly funded by the Australian Food and Grocery Council, the Commonwealth Department of Health and Ageing and the Commonwealth Department of Agriculture, Fisheries and Forestry. The survey was conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) through its Preventative Health National Research Flagship, and the University of South Australia. The survey fieldwork was undertaken by I-view Pty Ltd. In particular the following persons are thanked for their contribution:

CSIRO Preventative Health National Research Flagship

Professor Lynne Cobiac (moved to Flinders University at the beginning of 2007) BSc, PhD, MBA (Adv), Post Grad Dip Nut Diet

Dr Jane Bowen, BSc, BNut&Diet (Hons), PhD

Ms Jill Burnett, BSc, Dip Nut & Diet, DipEd

Ms Julie Syrette, BSc

Mr James Dempsey, BInfTech(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 Ian Saunders, BA (Hons), DipMathStats, PhD

University of South Australia

Professor Timothy Olds, BA (Hon), BSpSc(Dist), PhD(Syd), PhD(UNSW)

Dr James Dollman, BS, MSc, DipEd, PhD

Mr Tim Kupke, BAppSc, BHlthSc (Hons)

I–view Pty Ltd

Ms Kylie Brosnan, BBus, Dip MRSA

Mr Daniel Pole, BA

Ms Mary Plumridge

Acknowledgement and thanks are extended to Food Standards Australia New Zealand (FSANZ) who developed a customised nutrient database for use in the survey and offered expert advice. In particular the following persons are thanked:

FSANZ: Food Composition Team

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

Acknowledgement and thanks are extended to the following members of the project Steering Group and expert members of the Technical Reference Group:

Steering Group Members:

Ms Jenny Bryant, First 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

Associate members of the Steering Group:

Ms Jennifer McDonald, former Assistant Secretary, Population Health Division, Department of Health and Ageing

Ms Cath Peachey, Acting Assistant Secretary, Population Health Division, Department of Health and Ageing

Dr Geoffrey Annison, Australian Food and Grocery Council

Dr David Roberts, Australian Food and Grocery Council

Steering Group Project Officer: Ms Caroline Arthur, Acting Director Nutrition Section, Department of Health and Ageing.

Technical Reference Group

Professor A. Stewart Truswell, AO, MD, DSC, FRCP, FRACP, FPHN, Emeritus 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

AbbreviationsForeword and acknowledgements

Abbreviations

Ms Ingrid Coles-Rutishauser, BSc (Nutrition), MSc (Epidemiology), RPHNutr, Coles and Rutishauser Consultants

4 2007 Australian National Children’s Nutrition and Physical Activity Survey: Volume 6 Demography

2007 Australian National Children’s Nutrition and Physical Activity Survey: Volume 6 Demography 3

Background informationIntroduction

The 2007 Australian National Children’s Nutrition and Physical Activity Survey (ANCNPAS) was conducted between February and September of 2007. Complete datasets from a total of 4487 children aged 2–16 years from across all Australian states and territories were obtained in the survey following parental consent, after being randomly selected to participate on a household basis. Children residing in very remote areas or in households without a fixed telephone line were not included in the survey.

This survey collected the following data:

· demographics, including sex, age, state/territory of residence, child’s country of birth, parent(s)/carer(s) education level, household income and Indigenous status,

· dietary consumption, including all foods, beverages and dietary supplements consumed using two 24-hour three-pass dietary recalls,

· physical activity and sedentary behaviours using four 24-hour recalls,

· pedometer data measured over six days,

· anthropometric, including height, weight and waist measurements, and

· food habit information by questionnaire.

The first 24-hour dietary recall was provided during a computer assisted personal interview (CAPI) with a trained interviewer in the participant's home, followed by the second recall 7–21days later during a computer assisted telephone interview (CATI). Life in New Zealand dietary recall software (LINZ24©) and a food model booklet were used to assist in recording sufficient detail about items consumed.

Nutrient intakes were estimated from the food, beverage and dietary supplement data using the AUSNUT2007 food composition database developed for this survey by Food Standards Australia New Zealand.

The first two 24-hour physical activity recalls (recalling the two days prior to the interview day) were provided during the CAPI, followed by a third and fourth recall 7–21 days later during the CATI. Data relating to physical activity were collected only for children aged 9–16 years. MARCA software (Multimedia Activity Recall for Children and Adolescents) was used to assist in recording detail about physical activity and sedentary behaviour.

Specific physical activity level (PAL) data for a range of activities were used to calculate overall daily PAL (as a multiple of resting metabolic rate).

Children aged 5–16 years wore a pedometer, a device which counts steps, for up to seven consecutive days. Pedometer data was retained for analysis when a minimum of six days was provided.

The physical measurements were taken during the CAPI. 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 measure if two measurements were taken. The median value was used as the final measure if three measurements were taken. Body mass index (BMI) was calculated as average weight in kilograms divided by the square of average height in metres, and is a commonly used index of weight for height in children. It is widely used as an estimate of body fatness.

Children were categorised by BMI (underweight, normal weight, overweight and obese) according to international standards of age- and sex- specific BMI cut offs (Cole et al. 2000, Cole et al. 2007). These cut offs, which are based on combined international population samples of children, are developed to correspond to adult values of 25 kg.m-2 (the lower limit for adult overweight) and 30 kg.m-2 (the lower limit for adult obesity). The proportion of children categorised into each BMI class was calculated.

Comprehensive details of the survey methodology and procedures are provided in the 2007 User Guide (CSIRO et al. 2010), available for download from the Australian Social Sciences Data Archive (ASSDA) website. The User Guide should be referred to in conjunction with this report.

This volume describes the reported consumption of food, beverages and dietary supplements, nutrient intake, physical activity, and physical measures by demographic factors.

Specifically, tables are provided stratified by demographic variables for:

· mean intake for each food group (all children),

· median intake for each food group (children who consumed only),

· proportion of children that consumed from each food group,

· mean and median nutrient intake[footnoteRef:1], [1: 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. To FSANZ 2008) suggests that total vitamin D values reported in AUSNUT 2007 may significantly overestimate total vitamin D activity. The intakes of vitamin D estimated as part of this Survey should therefore not be relied upon as being robust.” Extract from User Guide: notes on nutrient data (CSIRO et al. 2010).]

· proportion of children that consumed dietary supplements,

· mean daily number of steps (pedometer data),

· mean physical activity level (MARCA data),

· mean, median and range height, weight, and waist circumference, and

· proportion of children classified by BMI.

The six demographic variables used for stratification are:

· state/territory of residence,

· country of birth,

· highest education level of either parent or carer (see Glossary),

· household income grouping,

· remoteness indicator, and

· BMI classification.

Results are presented for all children combined (not categorised by age or sex) due to small cell sizes and the complexity of interpreting the large number of contrasts. Although tabulations are presented in this volume, summary information country of birth is not provided. This is due to the very small cell sizes for children born outside of Australia. Tabulated results should therefore be treated as descriptive only, and caution exercised when interpreting perceived differences.

Data presented here are from the first (CAPI collected) 24-hour dietary recall. Results are weighted using the population weighting factors provided with the data set, however these weighting factors are intended to provide population estimates for Australian children in general and may give incorrect estimates for the data when stratified by the demographic variables used here.

All nutrient data presented in this report excludes the nutrient contribution of dietary supplements. For food intake data, the mean value represents the mean of all subjects (including zero values) for foods ‘as consumed’, i.e. cooked weights where relevant. Median values are for those who consumed only (i.e. zero values are excluded).

The AUSNUT2007 food composition database categorises foods using multiple levels of classification. Food categories presented in this volume are major and sub-major food groups (appendix 1). Foods and beverages are classified broadly based on their biological origin. For mixed foods, the classification generally depends on the major ingredient by weight (for example meat pies are classified as ‘cereal based products and dishes’). This food coding system was developed to reflect the current food supply but also to maintain comparability with the food groups used in the 1995 National Nutrition Survey. Refer to supporting documentation at Food Standards Australia Newzealand website for AUSNUT 2007 - AUSNUT 1999 matching excel file. Additional food groups were added for infant foods and formulae and dietary supplements. In addition the food, beverage and supplement intake data were translated to daily nutrient intake data using the most recent Australian nutrient composition database. The User Guide provides more detailed information on this process.

Related reports

The summary findings from the survey have been previously reported (CSIRO et al. 2008). This is the sixth report in a series of eight related volumes reporting detailed results from the 2007 ANCNPAS.

Collectively, the eight volumes provide extensive tabulations and analyses on children’s current food and nutrient intakes (including supplement use); food, nutrition and physical activity practices; physical measures; demographic characteristics; together with significant linkages between these fields. Supplementary to this work, further analyses were conducted to explore children’s estimated acute and chronic dietary exposure to food sourced chemicals.

Volumes one to eight are outlined below.

Volume 1: Foods Eaten

Volume one describes the reported consumption of food and beverages by children using one day 24-hour dietary recall, presented for males, females and all children by age group (2–3, 4–8, 9–13 and 14–16 years). Results are reported within food categories for mean intakes (all children and consumers only); proportion consuming; average portion size consumed; and intake by time of day, place of consumption and meal occasion.

Volume 2: Nutrient Intakes

Volume two describes the nutrient intake by children based on reported food and beverage consumption excluding dietary supplements. Results are presented for males, females and all children by age group (2–3, 4–8, 9–13 and 14–16 years). One day 24-hour dietary recall data is used to report mean and median nutrient intakes and nutrient density for direct comparison with foods consumed (volume 1 of this report series, CSIRO 2011), including the proportion of nutrient intake by food group, time of day, place of consumption and meal occasion. Usual nutrient intake was estimated using two days of 24-hour dietary recall to report the percentile distribution of daily nutrient intakes.

Volume 3: Dietary Supplements Consumed

Volume three describes the reported consumption of dietary supplements by children, presented for males, females and all children by age group (2–3, 4–8, 9–13 and 14–16 years). Data from two days of 24-hour dietary recall are presented in this report to describe the proportion of children consuming dietary supplements; the proportion of total nutrient intake from such supplement use; and the mean and median nutrient intakes for consumers versus non-consumers.

Volume 4: Physical Activity

Volume four describes the physical activity (PA) practices of children, presented for males, females and all children by age group (2–3, 4–8, 9–13 and 14–16 years). Physical activity practices were collected as four 24-hour recalls of PA and sedentary behaviours (9–16 year olds only) and six days of objective pedometer data (5–16 year olds only). Specifically, results include average PA level; average moderate and/or vigorous PA; time spent on non-sedentary, sedentary and screen based activities; and average number of steps and distance travelled.

Volume 5: Physical Measures

Volume five describes children’s physical measurements, presented for males, females and all children by age group (2–3, 4–8, 9–13 and 14–16 years). Physical measures reported include average height, weight and waist circumference, and the proportion of children by weight status (underweight, normal, overweight and obese) according to international standards of age- and sex- specific BMI cut offs.

Volume 6: Demography (this volume)

Volume six describes children’s reported consumption of food, beverages and dietary supplements, nutrient intakes, physical activity, and physical measures presented by demographic breakdown. Six demographic variables are presented in this volume, including state of residence; country of birth; highest education level of parent; household annual income grouping; remoteness indicator; and BMI classification. Results are presented for all children (not by age or sex sub-groupings due to small cell sizes for some of the demographic variables).

Volume 7: Data Linkages

Volume seven describes the relationship of body fatness with a range of variables measured in the survey including selected nutrient intakes, physical activity practices, and demographics.

Volume 8: Dietary exposure to food sourced chemicals

Volume eight describes children’s estimated acute and chronic dietary exposure to food sourced chemicals from reported food and beverage consumption as well as the effects of seasonality on food intake and estimated chemical exposure since the last National Nutrition Survey in 1995.

Summary of findingsFoods eatenSelected major and sub-major food groups State/territory of residence

Statistical analysis for differences in mean intake or percentage of people who consumed a food group by state or territory of residence excluded the territories (Australian Capital Territory (ACT) and Northern Territory (NT)) because of the small number of children sampled (Table A2.2).

The state-based analysis indicated a significant difference between the percentage of children who consumed in different states for the major food groups fats and oils; soup; snack foods; and confectionery and cereal/nut/fruit/seed bars (Table 3.3).

The percentage of children who consumed from the fats and oils group was 58% in Tasmania, significantly less than in Queensland (67%, p≤0.01) and South Australia (66%, p≤0.01). Within the sub-major food groups, a smaller percentage of Tasmanian children used vegetable/nut oil (2.2%) than in New South Wales, Queensland, South Australia, Victoria and Western Australia where the percentage was greater than 6.7% (all p≤0.01, except Queensland where p≤0.05) (Table 3.3). There were significantly fewer consumers of dairy blends in New South Wales (8%) compared with Queensland (14%) and Victoria (17%) (Table 3.3). There was no statistically significant difference between states in the mean amount used by consumers of either total fats and oils, dairy blends or vegetable/nut oil (Table 3.2).

For soup, the percentage of children who consumed in Queensland (4.6%) was significantly less than that in Western Australia (10.9%, p≤0.05) or Victoria (9.8%, p≤0.05) (Table 3.3). There was no statistically significant difference between States in the mean amount consumed (by consumers) (Table 3.2).

The percentage of children who consumed snack foods was significantly higher in Tasmania (36%) than Victoria (36% versus 27%, p≤0.05) (Table 3.3). The mean amount of snack foods consumed by consumers did not vary significantly (Table 3.2). Within this major food group, the percentage of children from Queensland who consumed extruded or reformed snacks (1%) was lower than for New South Wales (3%, p≤0.01), South Australia (3%, p≤0.01) and Western Australia (5%, p≤0.01), while for other snacks, the percentage of children who consumed in Tasmania (11%) was much higher than in Queensland (6%, p≤0.05), South Australia (5%, p≤0.01), New South Wales (4%, p≤0.01), Victoria (4%, p≤0.01) and Western Australia (2%, p≤0.01) (Table 3.3).

Confectionery and cereal/nut/fruit/seed bars were consumed by 56% of children in South Australia – significantly more than in Queensland (46%, p≤0.01), Western Australia (47%, p≤0.01) or Tasmania (48%, p≤0.05) (Table 3.3.). Within this major food group, the percentage of South Australian children who consumed chocolate and chocolate-based confectionery (33%) was significantly higher than that in Queensland (21%, p≤0.01), New South Wales (23%, p≤0.05) or Western Australia (24%, p≤0.05). The mean amount of confectionery and cereal/nut/fruit/seed bars consumed (consumers only) was greater in Queensland (48 g) than in Tasmania (39 g, p≤0.01) (Table 3.2).

There were a number of differences between states for the percentage consuming a sub-major food group where there was no difference for the major food group.

A higher percentage of children consumed cordial in Tasmania (36%) compared to each of the other states (all p≤0.01), while a smaller percentage of Western Australian children consumed cordial (12.8%) than in New South Wales, South Australia or Tasmania (Table 3.3.). The mean amount consumed (consumers only) did not differ by State (Table 3.2).

The percentage of children who consumed potatoes was 35% in Western Australia – lower than in Victoria (45%, p≤0.01), Queensland (45%, p≤0.05) and South Australia (47%, p≤0.01) (Table 3.3.). For tomato and tomato products, the percentage of children who consumed in Western Australia was 29% - higher than in Victoria (17%, p≤0.01), South Australia (19%, p≤0.01) and New South Wales (22%, p≤0.05).

The mean intake for consumers of vegetable products and dishes; and milk products and dishes differed by state of residence. Mean intake for consumers for vegetable products and dishes in New South Wales was 167 g, significantly lower than in Western Australia (186 g, p≤0.01), Tasmania (192 g, p≤0.01) and South Australia (199 g, p≤0.05) (Table 3.2). For milk products and dishes, the mean intake for consumers in Tasmania (441 g) was higher than in Victoria (388 g, p≤0.05), South Australia (379 g, p≤0.05) and Western Australia (366 g, p≤0.01). The mean intake in Queensland (432 g) was also significantly higher than the mean intake of consumers in South Australia (p≤0.05) and Western Australia (p≤0.01) (Table 3.2).

The mean intake of tea for consumers differed for every state of residence (all p≤0.01). While the percentage of children drinking tea was less than 10% in each state (Table 3.3.), the mean intake for consumers was 469 g in Tasmania, 329 g in Western Australia, 321 g in Queensland, 302 g in South Australia, 289 g in New South Wales and 242 g in Victoria (Table 3.2).

For the 26% of children resident in Tasmania who consumed cakes, buns, muffins, scones, and cake-type desserts, the mean amount consumed (116 g) was significantly larger than that consumed by consumers in any other state (all p≤0.01,Table 3.2). On the other hand, the 23% of children resident in Tasmania who consumed pasta and pasta products consumed a smaller mean amount (153 g) compared to the mean intake of consumers from any other state except New South Wales (all p≤0.01).

Country of birth

Statistical tests on differences in food intake across different birth countries were not performed due to the low number of children in the survey (less than 7%) who were born outside of Australia (Table A2.3).

Highest education level of either parent/carer

Statistically significant differences in foods consumed were observed for the following:

Overall, the proportion of children who consumed non-alcoholic beverages did not differ by level of education of the parent (Table 3.9.), however the mean intake amongst consumers of non-alcoholic beverages was significantly lower in households with at least one parent completing a bachelor degree or higher (1107 g) compared to year 12 or lower (1247 g) or a trade qualification (1226 g) (p≤0.01) (Table 3.8.). The proportion of children consuming cordials; and soft drinks, and flavoured mineral waters was lower from households with at least one parent completing a bachelor degree or higher (p≤0.01) (Table 3.9.).

While the proportion of children consuming cereals and cereal products did not differ between different categories of parental education there were observed differences in the mean intake of cereals and cereal products by consumers. Children consumers from households where at least one parent completed a bachelor degree or higher had higher intakes of cereals and cereal products (219 g) than those from households where at least one parent had a trade qualification (196 g) or households where highest parental education level was secondary school (187 g) (p≤0.01) (Table 3.8.).

A greater proportion of children from households where at least one parent had completed a bachelor degree or higher reported consuming cereal-based products and dishes compared to children from households with a parent completing year 12 or lower (82% compared to 76%, p≤0.05) (Table 3.9.). This was primarily a result of the differences observed in the proportion of children consuming savoury biscuits and batter-based products (p≤0.01). Consumers from households with a higher level of parental education (bachelor degree or higher) reported significantly lower mean intakes of cereal-based products and dishes (139 g) than consumers from households with the other levels of education (160 g, p≤0.05 for year 12 or lower, and160 g, p≤0.01 for trade qualification) (Table 3.8).

With increasing parental education level, the proportion of children who reported consuming fruit products and dishes was greater (p≤0.01) - 75% for parent(s) completing a bachelor degree or higher, 64% for parent(s) with a trade qualification and 58% for parent(s) completing year 12 or lower (Table 3.9.). The mean intake of fruit products and dishes amongst consumers was greater with increasing level of parental education (224 g, 231 g and 246 g respectively for children with parent(s) completing year 12 or lower, at least one parent with a trade qualification, and at least one parent with a bachelor degree or higher, p≤0.05) (Table 3.8).

More children from households where at least one parent had competed a bachelor degree or higher reported they had consumed vegetable products and dishes (81%) compared to year 12 or lower (76%) or a trade qualification (76%) (p≤0.01) (Table 3.9), However, the mean intake of vegetable products and dishes amongst consumers was lower for those with at least one parent with a bachelor degree or higher (168 g) compared to those from households with parent(s) completing year 12 or lower (197 g, p≤0.05) or those with at least one parent with a trade qualification (186 g, p≤0.05) (Table 3.8). Potato consumption (mean intake of consumers and proportion who consumed) was significantly lower in the households with higher parental education qualification (116 g and 38% respectively for households with at least one parent with a bachelor degree or higher compared to 137 g and 48% for households whose highest parental education was at the secondary level, and 132 g and 45% for households where at least one parent had a trade qualification, p≤0.05 for differences in amount consumed and p≤0.01 for differences in proportion consuming). Conversely, the proportion who consumed tomato and tomato products; and other fruiting vegetables was higher in the households with higher parental education (see Tables 3.8 and 3.9).

While children’s mean intake of snack foods did not differ between the different categories of highest education of either parent/ carer, the proportion of children who consumed snack foods was lower for the households with at least one parent completing a bachelor degree or higher (25% compared with 32% for other education categories, p≤0.01), and notably for potato snacks (14% for the households with at least one parent completing a bachelor degree or higher compared with 19% for households where at least one parent had a trade qualification, p≤0.01) (Table 3.9).

Household income category

Statistically significant differences in foods consumed were observed for the following:

At the major food group level, there were no significant differences across household income categories in the proportion consuming and the mean intake of non-alcoholic beverages. However, a smaller proportion of children from the highest household income category consumed cordial compared to the lowest income category (17% compared to 25%, p≤0.01, Table 3.12). The proportion of children who consumed fruit and vegetable juice was higher for the highest household income category compared to the lowest household income category (48% compared to 42%, p≤0.05, Table 3.12), however the mean intake was not significantly different between categories. For soft drink consumption, post-hoc analyses indicated a significant difference in the proportion consuming between children from the lowest and second highest household income categories (36% compared to 28% respectively, p≤0.05) (Table 3.12).

Mean intake of cereals and cereal products was lower for children (consumers only) from the lowest household income category (188 g) compared to consumers from the highest income category (219 g, p≤0.01) and the second highest income category (215 g, p≤0.05) (Table 3.11) but there were no significant differences in the proportion of consumers in each income category. Children consumers in the refused/don’t know category of household income consumed significantly lower amounts of cooked porridge compared to all other groups (89 g compared to 218–284 g, p≤0.01) (Table 3.11).

The proportion of children in the refused/don’t know income category who reported consuming fish and fish products was higher than any other category (21% compared with 11–12%) (Table 3.12).

Significantly fewer children from the lowest household income category consumed fruit and fruit products (61%) compared to all other income categories (69–73%, p≤0.01, Table 3.12), however mean intake amongst consumers was not significantly different (Table 3.11).

Level of remoteness

Statistically significant differences in foods consumed were observed for the following:

The proportion of children who consumed each of the major food groups was similar for children from metropolitan regions (i.e. metro category) and non-metropolitan regions (i.e. rest of state category) with the exception of fish and fish products; soup; legumes; and miscellaneous foods. More children in metropolitan regions consumed these food groups than children from non-metropolitan regions (Table 3.15). At the sub-major food group level there were a higher proportion of consumers in non-metropolitan regions compared to metropolitan regions for cordial (23% compared with 18%); custards (4% compared with 3%); flavoured milk (10% compared with 7%); potatoes (45% compared with 40%); carrots (36% compared with 31%); and sugar/honey (38% compared with 35%) all p≤0.05. Whereas there were a higher proportion of consumers in metropolitan regions compared to non-metropolitan regions for flour (22% compared with 13%, p≤0.01); sweet biscuits (32% compared with 29%, p≤0.05); and vegetable oil (10% compared with 6%, p≤0.05).

Mean intake was higher for consumers from metropolitan regions compared to children from non-metropolitan regions for cereals and cereal products (219 g in metropolitan regions compared to 186 g in the rest of state category, p≤0.01) but lower for cereal-based products and dishes (142 g compared to 160 g, p≤0.01); milk products and dishes (391 g compared to 416 g, p≤0.01); vegetable products and dishes (172 g compared to 188 g, p≤0.01) ; and legume and pulse products and dishes (106 g compared to 142 g, p≤0.05) (Table 3.14). At the sub-major food group level, the mean intake of the foods primarily contributing to these results were - for cereals and cereal products, flour (182 g compared to 154 g, p≤0.01) and pasta products (199 g compared to 178 g, p≤0.01); and for vegetable products and dishes, carrots (12 g compared to 16 g, p≤0.01) (Table 3.13). Other sub-major food groups that showed significant regional differences in the amount consumed were tropical fruit (118 g in metropolitan regions and 135 g in rest of state regions, p≤0.01) and mixed dishes with pork as the major ingredient (89 g metropolitan compared to 195 g rest of state, p≤0.01) (Table 3.13).

Body Mass Index (BMI) classification

Statistically significant differences in foods consumed were observed for the following:

Regardless of BMI classification, almost all children reported they had consumed non-alcoholic beverages on the day surveyed (99–100%) (Table 3.18). The mean intake (of consumers only) of non-alcoholic beverages for children classified in the overweight (1296 g) and the obese category (1346 g) was greater than for those in the normal weight category (1139 g, p≤0.01 for each comparison) and the underweight category (1141 g, p≤0.05 for each comparison) (Table 3.17). For soft drinks specifically, more children in the obese category reported they had consumed (46%) compared to those in the normal weight category (28%, p≤0.01) and those in the overweight category (34%, p≤0.05) (Table 3.18).

Although mean intake was not significantly different by BMI category, more children in the normal weight category reported they consumed cereal-based products and dishes compared to children in the overweight category (81% compared to 76%, p≤0.05) and children in the obese category (81% compared to 70%, p≤0.05) (Table 3.18). The consumption of savoury biscuits was consistent with this pattern. In the normal weight category 28% consumed savoury biscuits compared to 22% in the overweight category (p≤0.05), and 15% in the obese category (p≤0.01). More children in the normal weight category reported consumption of cakes, buns, muffins etc (23%) and pastries (17%) than did children in the obese weight category (15% and 10% respectively, p≤0.05) (Table 3.18).

The proportion of children in the obese category who consumed fruit products and dishes was significantly less than that for the underweight category (54% compared to 76%, p≤0.01), the normal weight category (54% compared to 69%, p≤0.01) and the overweight category (54% compared to 66%, p≤0.05) (Table 3.18), however mean intake of consumers was not significantly different between BMI categories (Table 3.17). Children’s intake of tropical fruit appears to be an important determinant of this relationship - the proportion of children in the obese category who consumed tropical fruit was significantly less than the proportion in the normal weight category (14% compared to 25%, p≤0.01) and the underweight category (14% compared to 30%, . p≤0.01) (Table 3.17). Amongst consumers, the mean intake of fruit products and dishes did not vary significantly but there were some differences observed in the mean amounts of berry and citrus fruits consumed. Children classified as obese reported lower consumption of berry fruits than normal or overweight children (27 g compared to 86 g, p≤0.01 and 74 g, p≤0.05 -consumers only), and children classified as underweight consumed less citrus fruit per consumer than the children in the normal or overweight categories (94 g compared with 121 g and 138 g, p≤0.05) (Table 3.17).

Mean intake of milk products and dishes amongst consumers and the proportion of children who consumed milk products and dishes did not differ by BMI category. By sub-major food group, dairy milk was consumed by a smaller proportion of children in the obese category compared to children in the normal weight category (63% compared to 75%, p≤0.05) and compared to children in the underweight category (63% compared to 78%, p≤0.05) (Table 3.18). The proportion who consumed yoghurt was higher in the normal weight category compared to children in the obese category 21% compared to 14%, p≤0.05) (Table 3.18) and for consumers of custards the mean amount of consumed by children in the obese category (130 g) was lower than that of children in the normal weight category (187 g, p≤0.01) (Table 3.17).

Nutrient intakes (excluding dietary supplements)State/territory of residence

The territories (ACT and NT) were excluded from the statistical comparisons of estimated nutrient intake by state/territory of residence because the number of subjects from these territories was relatively small.

Generally, estimated macronutrient intakes were similar across all states/territories (Table 3.18). Although not significantly different, South Australian children reported the highest mean energy intake (8394 kJ) and children from Victoria reported the lowest mean energy intake (8033 kJ).

Children in Queensland and Western Australia reported significantly higher mean intake of vitamin A retinol equivalents (786 micrograms and 777 micrograms respectively) than children in Victoria (697 mcg, both p≤0.05) (Table 3.20). Tasmanian children showed a higher estimated mean intake of preformed vitamin A (427 mcg) than children from New South Wales (374 mcg, p≤0.01) and Victoria (353 mcg, p≤0.01). Estimated mean provitamin A intake was higher in children residing in Western Australia than for those in New South Wales (p≤0.05). Western Australian children had a lower mean intake than South Australian children for thiamin (1.7 mg compared to 1.9 mg, p≤0.01), total folate (375 mcg compared to 423 mcg, p≤0.01), dietary folate equivalents (430 mcg compared to 500 mcg, p≤0.01).

The mean riboflavin intake in Western Australian children (2.3 mg) was lower than that for Queensland children (2.6 mg, p≤0.01), South Australian children (2.6 mg, p≤0.01) and Tasmanian children (2.7 mg, p≤0.01).

The mean sodium intake was higher for South Australian children (2653 mg) than for children from Victoria (2440 mg, p≤0.01) and Western Australia (2380 mg, p≤0.01) (Table 3.21).

Country of birth

Statistical tests on differences in food intake across different birth countries were not performed due to the low number of children in the survey (less than 7%) who were born outside of Australia (Table A2.3).

Highest education level of either parent/carer

There was no evidence of difference in estimated mean energy and macronutrient intake across categories of highest education level attained by the parent/primary carer.

Children with at least one parent with a bachelor degree or higher had a higher mean intake of dietary fibre (21.6 g) compared to children with a parent completing year 12 or lower (19.6 g, p≤0.01) or a trade qualification (20.3 g, p≤0.05) (Table 3.26). Mean intake of magnesium was consistent with this pattern (293 mg for children in the category of at least one parent completing a bachelor degree or higher compared to 280 mg for children with a parent with a trade qualification (p≤0.05 ) and 272 mg for children where parents have completed Year 12 or less (p≤0.01) (Table 3.28).

Estimated mean sodium intake was lower for children from households where at least one parent had completed a bachelor degree or higher (2400 mg) compared to parents completing year 12 or lower (2626 mg, p≤0.01) or a trade qualification (2515 mg, p≤0.05) (Table 3.28).

For children with at least one parent with a bachelor degree or higher, the estimated mean intake of vitamin C and phosphorous was significantly higher compared to children of parents completing year 12 or lower (118 mg compared to 96 mg, p≤0.01 and 1405 mg compared to 1317 mg, p≤0.01 respectively) (Table 3.28). For children with parent(s) of the highest educational qualification category, mean intake of total folate (414 micrograms), vitamin E (6.1 mg), calcium (888 mg) and potassium (2773 mg) were all significantly higher compared to children of parents who had completed year 12 or lower (total folate (377 micrograms), vitamin E (5.6 mg), calcium (829 mg) and potassium (2620 mg); all comparisons p≤0.05) (Table 3.28).

Household income category

Children from the highest household income category had a higher estimated mean protein intake compared to children from the lowest income category (84.2 g compared to 79.0 g, p≤0.05) (Table 3.30). Dietary fibre followed the same pattern (21.7 g compared to 20.1 g, p≤0.01) while energy and other macronutrients did not differ significantly by household income category (Table 3.30).

Estimated mean intake of total folate was higher for children from the highest reported household income category (432 mcg) compared to all other income categories (p≤0.05), including the lowest household income bracket (377 mcg, p≤0.01) (Table 3.32).

Compared to the lowest household income category, children from the highest income households had higher estimated mean intakes of dietary folate equivalents, vitamin C, phosphorous, magnesium and zinc (p≤0.01), and higher mean intakes of phosphorous, magnesium and zinc compared to the second lowest income category (p≤0.05) (Table 3.32).

Level of remoteness

In comparison to children from metropolitan regions, children from the non-metropolitan regions (i.e. rest of state category) had a higher mean intake of saturated fat (33 g compared to 31 g, p≤0.05) and of sugar (129 g compared to 121 g, p≤0.01). Energy and other macronutrients did not differ significantly by remoteness category (Table 3.34).

Compared to children from metropolitan regions, estimated mean intake of vitamin A retinol equivalents, pro-vitamin A, vitamin D and calcium was higher in children from the non-metropolitan regions (all p≤0.05) (Table 3.36).

BMI classification

The estimated mean energy intake was significantly lower for children in the obese BMI category (7654 kJ) compared to those in the normal weight category (8273 kJ, p≤0.01) and those in the overweight category (8265 kJ, p≤0.05) (Table 3.38). This is consistent with the significantly higher mean intake of carbohydrates, sugars, dietary fibre and magnesium (p≤0.01), and total folate and potassium (p≤0.05), for normal weight and overweight children in comparison to obese children (Tables 3.38 and 3.40). Mean iodine intake was also higher for children in the normal weight BMI category compared to those in the obese category (133 mcg compared to 115 mcg, p≤0.05) (Table 3.40).

Dietary supplementsState/territory of residence

The territories (ACT and NT) were excluded from the statistical comparisons of the percentage of children who took a dietary supplement by state/territory of residence because the number of subjects from these territories was relatively small.

The percentage of children who reported taking a dietary supplement on both survey days was largest in New South Wales (8%) and Queensland (7.8%). Both were significantly greater than the percentage in Tasmania (4.1%, both p≤0.01). New South Wales and Queensland also had the highest percentage of children who took a dietary supplement on either day of the survey at 21.8% and 21.4% respectively. The percentage for both states was significantly higher than for Tasmania (11.9%, both p≤0.01), and the percentage for New South Wales was also higher than for South Australia (13.4%, p≤0.01) (Table 3.42).

Country of birth

Statistical tests on differences in food intake across different birth countries were not performed due to the low number of children in the survey (less than 7%) who were born outside of Australia (Table A2.3).

Highest education level of either parent/carer

A higher proportion of children consumed dietary supplements on both days of recall from households where at least one parent completed a bachelor degree or higher (8%) compared to year 12 or lower (4%, p≤0.01) or a trade qualification (5%, p≤0.05) (Table 3.44).

Household income categories

There was no statistical evidence for a difference in the proportion of children who consumed dietary supplements by category of household income (Table 3.45).

Level of remoteness

The proportion of children who consumed dietary supplements was not significantly different between those living in metropolitan regions compared to those living in non-metropolitan regions (i.e. rest of state) (Table 3.46).

BMI classification

The proportion of children who consumed dietary supplements did not differ significantly across BMI categories (Table 3.47).

Physical activityState/territory of residence

The territories (ACT and NT) were excluded from the statistical comparisons of physical activity measures by state/territory of residence because the number of subjects from these territories was relatively small.

The average number of steps per day as recorded by pedometer in children aged 5–16 years was similar across all states (Table 3.48) whereas the mean physical activity level (PAL) recorded via MARCA software (Multimedia Activity Recall for Children and Adolescents) in children aged 9–16 years was higher on school days for children from Queensland (1.74) than from New South Wales (1.67) (p≤0.01) (Table 3.54).

Country of birth

Statistical tests on differences in food intake across different birth countries were not performed due to the low number of children in the survey (less than 7%) who were born outside of Australia (Table A2.3).

Highest education level of either parent/carer

The mean number of steps recorded via pedometer (children aged 5–16 years only) did not differ significantly across the different categories of highest parental education, regardless of the day of measurement (school day versus non-school day versus all days) (Table 3.50).

There was no significant difference in PAL recorded via MARCA (children aged 9–16 years only) with highest education level of either parent/carer (Table 3.56).

Household income category

The mean number of steps recorded on weekend days was significantly higher for children from households earning $78,000–$104,000 per year compared to those from households earning $52,000 or less per year (11,577 steps compared with 10,658 steps, p≤0.05) and those who refused to divulge or did not know household income (10,420 steps, p≤0.01, Table 3.51).

Regardless of the day of measurement, children from the highest reported annual household income category (>$104,000) reported a higher mean PAL than children from the lowest income category (all days p≤0.01, school and non-school days p≤0.05) (Table 3.57).

Level of remoteness

Compared to children from metropolitan regions, children from non-metropolitan regions (i.e. rest of state) recorded a higher mean number of steps on weekend days and all days combined (p≤0.01) but no significant difference for weekdays alone (Table 3.52).

Children from non-metropolitan regions recorded a higher mean PAL on non-school days and all days combined (p≤0.01) in comparison to children from metropolitan regions, but mean PAL recorded on school days only was not found to be significantly different (Table 3.58).

BMI classification

The mean number of steps on weekdays for children from the normal weight BMI category (12,243 steps), was greater than that of the overweight category (11,699 steps, p≤0.05) and the obese category (10,992, p≤0.01) (Table 3.53). Similarly, the mean number of steps on weekend days for children from the normal weight category (11,316 steps), was greater than that of the overweight category (10,529 steps, p≤0.05) and the obese category (9588, p≤0.01) (Table 3.53).

Overall, children in the normal weight and in the overweight BMI categories had a higher mean PAL compared to children in the obese category (both 1.67 compared to 1.57, both p≤0.01) and the underweight category (both 1.67 compared to 1.60, both p≤0.05) (Table 3.59). On school days alone PAL was not significantly different between groups, however on non-school days children in the normal weight category and the overweight category reported a higher PAL compared to children in the obese category (both 1.63 compared to 1.52, both p≤0.01) (Table 3.59).

Physical measuresState/territory of residence

There were no significant differences between states (territories were excluded) in mean height (Table 3.60), mean weight (Table 3.65) or mean waist circumference (Table 3.70).

Country of birth

Statistical tests on differences in food intake across different birth countries were not performed due to the low number of children in the survey (less than 7%) who were born outside of Australia (Table A2.3).

Highest education level of either parent/carer

HEIGHT – Children with at least one parent who had completed a bachelor degree or higher had a smaller mean height than children from parents who had completed a trade qualification (-2.2 cm, p≤0.05) (Table 3.62).

WEIGHT – Children in households where the highest parental education level attained was either secondary school or a trade qualification had a higher mean weight than those in households where at least one parent had completed a bachelor degree or higher (+3.5 kg, p≤0.01; and +2.7 kg, p≤0.01 respectively) (Table 3.67).

WAIST GIRTH – As with weight, children from households where the highest parental education level was either secondary school or a trade qualification had a significantly larger mean waist circumference in comparison to children from households whose parent(s) completed a bachelor degree or higher (+3.2 cm, p≤0.01; and +2.1 cm, p≤0.01 respectively) (Table 3.72).

Household income category

HEIGHT – There was no significant difference in mean height of children by household income category (Table 3.63).

WEIGHT – Mean measured weight for children from households reporting an annual income of $78,000–$104,000 per year was 2.3 kg less compared to children from households where annual income was $52,000 or less (p≤0.05) (Table 3.68).

WAIST GIRTH – Mean waist circumference was significantly larger for children from the lowest household annual income category (less than $52,000) compared to children from households reporting an annual income $52,000–$77,999 (64.6 cm compared to 62.7 cm, p≤0.05), households reporting an annual income $78,000–$103,999 (64.6 cm compared to 62.7 cm, p≤0.01) and households reporting an annual income $104,000 or greater (64.6 cm compared to 62.9 cm, p≤0.05) (Table 3.73).

Level of remoteness

HEIGHT, WEIGHT, WAIST GIRTH – There were no significant differences in mean height, weight or waist girth of children when categorised by remoteness of residence (Tables 3.64, 3.69, and 3.74).

BMI classification

WAIST GIRTH – Mean waist girth was significantly higher in each successive BMI category and for all contrasts between different BMI categories the mean waist girth was highest in the higher BMI category (all contrasts p≤0.01). (Table 3.75)

TabulationsDemographic breakdown: foods eatenState/territory of residence

Table 3.1 Mean intake of selected major and sub major food groups: all children by state/territory of residence

(average grams per person – all respondents)[footnoteRef:2] [2: refer to appendix 2, Table A2.1 for cell counts]

 

ACT (State/territory of residence)

NSW (State/territory of residence)

NT (State/territory of residence)

QLD (State/territory of residence)

SA (State/territory of residence)

TAS (State/territory of residence)

VIC (State/territory of residence)

WA (State/territory of residence)

NON-ALCOHOLIC BEVERAGES

958.9

1151.5

1321.6

1317.4

1179.7

1111.3

1077.4

1198.2

Tea

17.5

20.0

7.4

18.3

21.6

25.8

17.4

28.6

Coffee And Coffee Substitutes

3.5

6.6

11.4

13.9

8.9

16.5

4.6

5.9

Fruit And Vegetable Juices, And Drinks

166.3

163.1

102.9

145.0

137.1

138.7

121.7

126.8

Cordials

4.3

15.2

16.3

14.4

17.0

21.1

11.5

8.5

Soft Drinks, And Flavoured Mineral Waters

88.1

135.7

153.7

130.3

150.0

144.2

130.0

114.1

Electrolyte, Energy And Fortified Drinks

19.6

14.9

21.5

14.5

18.1

4.7

10.9

9.2

Mineral Waters And Water

625.5

772.9

998.8

968.3

807.3

729.9

766.2

887.7

Other Beverage Flavourings And Prepared Beverages

34.0

23.2

9.7

12.8

19.8

30.4

15.2

17.3

CEREALS AND CEREAL PRODUCTS

246.5

207.1

215.1

189.5

187.0

165.4

191.7

206.1

Flours And Other Cereal Grains And Starches

45.5

40.0

38.9

25.0

23.5

20.5

27.2

33.2

Regular Breads, And Bread Rolls (Plain/Unfilled/Untopped Varieties)

73.6

68.2

66.7

69.4

69.5

63.1

67.0

73.5

English-Style Muffins, Flat Breads, And Savoury And Sweet Breads

9.0

12.2

17.3

13.5

12.8

10.9

14.8

13.1

Pasta And Pasta Products

76.3

48.8

57.3

48.6

49.8

35.5

49.1

53.4

Breakfast Cereals And Bars, Unfortified And Fortified Varieties

29.1

26.8

29.8

27.0

26.3

28.6

27.8

22.8

Breakfast Cereal, Hot Porridge Type

13.1

11.1

5.1

6.0

5.1

6.9

5.9

10.0

CEREAL-BASED PRODUCTS AND DISHES

117.4

120.7

84.7

123.3

132.6

128.2

114.8

109.8

Sweet Biscuits

9.1

9.8

8.2

10.9

9.8

8.5

9.8

10.3

Savoury Biscuits

6.6

7.4

5.4

6.8

7.3

6.9

7.8

6.5

Cakes, Buns, Muffins, Scones, Cake-Type Desserts

18.6

17.5

10.3

15.2

18.0

30.4

17.9

23.2

Pastries

21.8

21.2

21.5

25.0

28.6

29.2

29.5

24.4

Mixed Dishes Where Cereal Is The Major Ingredient

50.0

56.3

34.5

57.3

58.5

45.6

40.9

38.0

Batter-Based Products

11.3

8.5

4.9

8.1

10.5

7.6

9.0

7.5

FATS AND OILS

6.6

6.9

9.3

8.3

8.0

6.7

6.6

6.5

Butters

1.5

1.5

1.3

2.1

1.6

2.0

1.6

1.8

Dairy Blends

0.7

1.0

1.6

1.6

1.4

1.1

1.6

0.9

Margarine And Table Spreads

4.0

3.7

5.7

4.3

4.4

3.5

2.9

3.0

Vegetable/Nut Oil

0.3

0.7

0.7

0.3

0.7

0.1

0.5

0.6

Other Fats

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Unspecified Fats

0.1

0.1

0.1

0.1

0.0

0.0

0.0

0.1

FISH AND SEAFOOD PRODUCTS AND DISHES [footnoteRef:3] [3: refer to appendix 2, Table A2.1 for cell counts]

7.9

14.8

5.1

11.5

9.9

17.1

15.0

14.0

Fin Fish (Excluding Commercially Sterile)

0.9

3.6

1.9

2.3

1.1

9.6

3.4

2.1

Crustacea And Molluscs (Excluding Commercially Sterile)

0.3

1.6

1.9

0.3

0.4

1.4

0.4

2.7

Other Sea And Freshwater Foods

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Packed (Commercially Sterile) Fish And Seafood

3.0

3.5

1.3

2.5

3.1

1.1

3.4

3.5

Fish And Seafood Products (Homemade And Takeaway)

3.7

5.5

0.1

6.3

3.1

2.9

6.9

5.7

Mixed Dishes With Fish Or Seafood As The Major Component

0.0

0.6

0.0

0.2

2.2

2.0

0.8

0.1

FRUIT PRODUCTS AND DISHES

185.8

161.8

108.2

152.0

151.5

174.1

164.2

167.7

Pome Fruit

87.6

61.8

36.0

54.8

63.1

74.3

67.7

76.6

Berry Fruit

2.3

5.1

0.0

2.1

4.4

5.5

6.0

1.3

Citrus Fruit

19.0

23.5

15.4

22.4

22.7

21.8

20.8

23.7

Stone Fruit

8.3

6.2

9.9

5.2

3.0

6.3

4.4

5.0

Tropical Fruit

31.8

30.6

23.3

29.7

30.4

28.0

30.3

29.7

Other Fruit

26.7

27.9

16.6

30.4

22.3

30.3

23.0

24.6

Mixtures Of Two Or More Groups Of Fruit

4.7

4.2

2.9

4.9

2.1

0.9

9.5

4.6

Dried Fruit, Preserved Fruit

2.0

2.3

2.2

1.9

2.6

3.0

2.3

1.5

Mixed Dishes Where Fruit Is The Major Component

3.5

0.3

2.0

0.5

0.7

4.0

0.3

0.9

EGG PRODUCTS AND DISHES

10.0

8.4

4.8

8.3

7.0

4.4

7.0

9.9

Eggs

4.2

5.8

4.8

6.0

3.9

4.1

4.0

6.3

Dishes Where Egg Is The Major Ingredient

5.8

2.5

0.0

2.4

3.2

0.3

2.9

3.5

MEAT, POULTRY AND GAME PRODUCTS AND DISHES

97.7

106.7

116.0

105.4

104.7

97.7

102.2

106.3

Muscle Meat

33.2

25.5

27.5

33.2

25.0

25.1

24.1

30.1

Game And Other Carcase Meats

0.0

0.0

0.0

0.0

0.1

0.0

0.1

0.0

Poultry And Feathered Game

20.5

21.2

41.9

18.8

18.5

24.7

24.4

23.8

Organ Meats And Offal, Products And Dishes

0.0

0.1

0.3

0.1

0.1

0.1

0.1

1.0

Sausages, Frankfurts And Saveloys

7.7

9.4

9.4

11.8

11.7

5.3

6.6

10.2

Processed Meat

14.9

11.1

19.7

14.6

17.0

13.2

13.3

14.2

Mixed Dishes Where Beef, Veal Or Lamb Is The Major Component

11.5

15.1

2.4

12.3

10.4

12.7

15.2

14.3

Mixed Dishes Where Pork, Bacon, Ham Is The Major Component

0.0

0.3

0.0

1.7

0.3

0.0

0.7

0.5

Mixed Dishes Where Poultry Or Game Is The Major Component

9.9

24.2

14.9

12.9

21.7

16.7

17.8

12.3

MILK PRODUCTS AND DISHES

336.2

367.3

361.5

393.8

350.8

406.9

350.4

334.8

Dairy Milk (cow, sheep and goat)

214.0

258.4

253.6

276.4

240.9

290.5

247.4

229.0

Yoghurt

36.4

28.0

21.1

31.8

23.9

31.6

26.6

28.6

Cream

1.5

0.9

0.5

1.3

2.2

2.0

1.0

1.3

Cheese

16.6

14.2

13.6

15.4

18.3

17.2

13.6

20.7

Frozen Milk Products

20.6

24.6

30.6

23.2

22.2

25.0

22.6

25.9

Custards

3.6

7.7

3.8

9.4

9.4

1.5

4.1

2.0

Other Dishes Where Milk Or A Milk Product Is The Major Component

4.5

2.9

1.1

3.4

3.3

0.0

5.9

4.9

Flavoured Milks

38.9

30.6

37.4

33.0

30.6

39.2

29.2

22.3

DAIRY SUBSTITUTES

7.5

10.2

3.2

9.0

6.8

2.6

11.0

5.1

Dairy Milk Substitutes, Unflavoured

6.9

7.2

0.8

6.6

3.9

2.6

9.1

3.9

Dairy Milk Substitutes, Flavoured

0.7

2.4

2.4

1.6

2.5

0.0

1.6

0.8

Cheese Substitute

0.0

0.0

0.0

0.0

0.0

0.0

0.0

0.0

Soy-Based Ice Confection

0.0

0.1

0.0

0.2

0.2

0.0

0.1

0.2

Soy-Based Yoghurts

0.0

0.5

0.0

0.7

0.3

0.0

0.1

0.2

SOUP [footnoteRef:4] [4: refer to appendix 2,