Child Health Status 2011 Queensland Report pptx

• Children aged 5–17 years who lived in the most disadvantaged areas of Queensland were over two times more likely to be obese than those living in the most advantaged areas... Compared

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Child Health Status 2011

Queensland Report

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1 Q UEENSLAND R EPORT

Copyright protects this publication However, Queensland Health has no objection to this material being reproduced with acknowledgement, except for commercial purposes Permission to reproduce for commercial purposes should be sought from the Policy and Quality Officer, Queensland Health, GPO Box 48, Brisbane Qld 4001

Suggested citation: Queensland Health Child health survey 2011: Queensland report Queensland Health: Brisbane; 2011

This document is also available on the Queensland Health internet site at

http://www.health.qld.gov.au/epidemiology/default.asp

Acknowledgements

• This report was prepared by Nelufa Begum, Claire deBatts, Susan Clemens and Catherine Harper

of the Population Epidemiology Unit, Strategic Partnerships and Epidemiology Branch,

Preventative Health Directorate, Division of the Chief Health Officer

• The survey was developed by Catherine Harper, Susan Clemens, and Darren White of the

Population Epidemiology Unit

• The Child Health Status 2011 survey was funded by the Division of the Chief Health Officer,

Queensland Health

• Thanks are due to the individuals within the Preventative Health Directorate who provided expert advice during the development of the survey or reports and to the thousands of Queenslanders who gave their time to share their experiences and contribute to this research

For further information or a copy of this report, contact:

Population Epidemiology Unit

Strategic Partnerships and Epidemiology Branch

Preventative Health Directorate

Division of the Chief Health Officer

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Summary of health indicators Children aged 5 to 17 years:

Includes walking or transport by bicycle, skateboard or scooter on a usual week

Body Mass Index (BMI)

Fruit and vegetable consumption

Drink consumption

Food habits

Physical activity

One or more hours of organised sport in school(c) 5-17 52.1 49.8-54.3

Screen-based entertainment

Commute to or from school

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Summary of key indicators for comparison to CHS 2009

Children aged 5 to 15 years:

Queensland 2011

(a)

Any participation in organised sport in the past week.

Fruit and vegetable consumption

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Introduction

The Child Health Status (CHS) survey series is conducted about biennially to provide accurate and timely information on the health of Queensland children This report summarises health information collected by the CHS 2011 survey Information is used to monitor, understand, and respond to changes

in the occurrence of behaviours that may put children’s health at risk as they grow up The information

is used by the Queensland Government to report against key health indicators for state wide health initiatives, as well as to meet nationally standardised health reporting requirements

Methods

The CHS 2011 survey was commissioned by Queensland Health and conducted between 08/06/2011 and 28/07/2011 using computer assisted telephone interviewing (CATI) methodology by a specialist CATI provider Data were not collected during the school term holidays (27/06/2011 to 14/07/2011) which also included the week following school term holidays in order that questions about events over the previous week accurately reflected usual activities

Interviews were conducted with parents or guardians who provided information regarding their child’s health and lifestyle The average interview length was 12 minutes Trained telephone interviewers and supervisors conducted and monitored the interviews

Combinations of daytime and evening interviewing sessions were used to give parents, particularly shift workers, every opportunity to participate Standard interviewing sessions were Monday to Friday 9:00 am–8:30 pm, Saturday 10:00 am–3:00 pm and Sunday 11:00 am–4:00 pm Once a household was contacted, every effort was made to obtain an interview from the parent, including multiple call backs and scheduling to suit the respondent

The CHS adheres to all applicable legislation and standards such as the Privacy Act (1988), the Public

Health Act (2009), the Telemarketing and Research Calls Industry Standard (2007) and has been

approved by a Human Research Ethics Committee

There were 2,484 respondents to the survey throughout Queensland The response rate achieved was 86% of the contacted in-scope households

Target population and sample frame

The target population for the survey was households in Queensland with at least one child aged

between 5 and 17 years From each selected private household the parent or guardian who was the primary caregiver provided information on the child who had most recently had a birthday

The CHS used a randomly generated telephone number sampling frame which permitted the inclusion

of unlisted and silent numbers The sample of telephone numbers was sourced from a specialist

random telephone number sampling frame provider A small, but unknown, proportion of the target population was excluded from selection in the survey because their household did not have a fixed telephone The inclusion of mobile telephone numbers in CATI sampling frames has recently been demonstrated to have no significant effects on reported prevalence of preventive health indicators in South Australia.1

The CHS 2011 collected information for the following health areas:

• Soft drink consumption • Screen time

The health areas included on the CHS 2011 are similar to those on the CHS 2009 In several instances, identical questionnaire items were used and data are therefore comparable For others, while the content area is similar, different questionnaire items were used and findings should not be compared

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Additional information regarding questionnaire items and comparability with previous years is included

at the end of this report in “Additional methodological information specific for this report”

Weighting

Data presented in this report are weighted by the age and sex distribution of children aged 5 to 17 for Queensland as reported in the Estimated Resident Population (ERP) for Queensland 2009.2 The data were also weighted for the number of children in that age group per household and the number of fixed telephone lines to the household The weighted results and associated confidence intervals can be considered an accurate representation of the demographic profile of the 5 to 17 year old residents of Queensland

Additional information regarding data collection methods, including a copy of the questionnaire, may be obtained from Population Epidemiology Unit by contacting the investigators at the email address

included on the inside front cover of this report

Guide to interpretation

This CHS 2011 was designed for Queensland level reporting and all results have been population weighted Population weighting adjusts for over- or under-representation of subpopulations during data collection (see Weighting section above) Population weighted prevalence is used to compare different subpopulations within a geographic area, for example different age groups, or between males and females Population weighted prevalence is also used to indicate the number of cases in an area, for example the number of children that are of a healthy weight in Queensland This information is valuable for service planning

The 2010 ERP for Queensland children aged 5-17 years was 773,586, comprised of 396,877 boys and 376,709 girls Some indicators in the reports are for the specific age groups of 5-7 years (172,537 children), 8-11 years (234,998 children), 12-15 years (241,472 children) and 16-17 years (124,579 children) Where appropriate, these demographic data have been used to estimate the number of people in Queensland with specific health related attributes

Reliability of estimates

In this report, 95% confidence intervals (CI) and relative standard error (RSE) are used to demonstrate the precision of the estimates The CI is a range of values that would contain the true population value 95% of the time if this survey were repeated on multiple samples It is a function of sample size and prevalence of the health factor being investigated, thus, smaller sample sizes result in larger confidence intervals and a less precise estimate

RSE is calculated by dividing the standard error of the estimate by the estimate itself and is expressed

as a percentage of the estimate It is particularly useful when assessing the reliability of estimates with large confidence intervals As based on methodology used by the Australian Bureau of Statistics, prevalence with RSE less than 25% are considered reliable, prevalence with an RSE between 25% and 50% should be interpreted with caution (marked with ‘*’) and prevalence with an RSE greater than 50% are not considered reliable and are not included in the tables (marked with ‘**’) Only estimates with an RSE less than 25% are noted in text or indicated as different in tables

Additionally, reliability of an estimate may be reduced when there are few respondents with that

characteristic or when a subpopulation (for example, youth aged 16–17 years) for which you want information hasn’t achieved a sufficient sample size In rare circumstances, a trait may be infrequent enough that publication of the result would compromise strict privacy protocols For these reasons, findings are only reported when

• At least 10 respondents report the characteristic of interest, and

• There are at least 30 respondents in the subpopulation, and

• There are at least 50 respondents in the total population (this was not encountered in the course of these analyses)

The reliability of an estimate may also be affected when the sample doesn’t reflect the demographic characteristics of the population

Table 1 presents the number of respondents (Sample n), weighted sample percent and 2010 ERP by demographic categories for Queensland When the sample size is small or where the weighted sample percent varies markedly from the 2010 ERP, estimates will be less reliable This is most likely to be

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observed in the youngest and oldest age categories or by area of socioeconomic

2010

Weighted sample

2010

Weighted sample

2010 ERP

Minor changes occurred in a small number of SLA geographies between 2006 & 2010 resulting in slightly imperfect mapping

of the 2006 ARIA SEIFA SLA classifications to 2010 SLAs

Determining statistically significant differences

In this report series, statistically significant differences between groups are determined based on overlap of confidence intervals The precision of the estimate, as discussed above, affects the ability to detect differences When confidence intervals are small and estimates have sizable numerical

non-differences, statistical differences are more clear; when confidence intervals are wide, it is possible a difference may exist but that sample size wasn’t sufficient to make a distinction The reporting of

difference between categories is noted only when the difference is statistically significant (based on non-overlap of 95% confidence intervals) If this criterion is not met, no difference is noted in the text Occasionally confidence intervals will appear to overlap in tables but results are noted as significant in text; such discrepancies are due to rounding

Results

Findings from the CHS 2011 are presented in Table 2 to Table 13 Data are stratified by sex, age, age

by sex, the socioeconomic index3 and the Accessibility/Remoteness Index of Australia (ARIA)4 based

on respondents’ area of residence Significant differences are noted in text where they are of primary importance or indicate trends across socio-demographic characteristics All significant differences are not discussed but are available by assessing non-overlap of confidence intervals in the tables as

discussed above

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Table 2: Children’s body mass index, Queensland, 2011

Male 8.0 (6.4-10.0) 63.5 (60.5-66.5) 19.4 (17.1-22.0) 9.1 (7.5-11.0) 28.5 (25.8-31.4) Female 5.9 (4.6-7.7) 69.4 (66.3-72.4) 16.8 (14.5-19.3) 7.9 (6.2-9.9) 24.6 (21.9-27.6)

5-7 years 10.5 (7.8-13.9) 62.0 (57.3-66.6) 14.4 (11.3-18.1) 13.1 (10.2-16.7) 27.5 (23.4-32.0) 8-11 years 6.3 (4.6-8.7) 59.6 (55.6-63.6) 23.5 (20.3-27.1) 10.5 (8.1-13.4) 34.0 (30.3-38.0) 12-15 years 5.6 (3.9-7.9) 71.4 (67.7-74.9) 17.1 (14.4-20.3) 5.9 (4.3-8.0) 23.0 (19.9-26.5) 16-17 years 6.3 (3.9-9.8) 75.1 (69.9-79.7) 14.9 (11.3-19.4) *3.7 (2.1-6.5) 18.6 (14.6-23.4)

5-7 years 10.7 (7.3-15.3) 61.7 (55.3-67.7) 14.6 (10.6-19.8) 13.1 (9.5-17.7) 27.6 (22.3-33.7) 8-11 years 7.2 (4.7-11.1) 59.3 (53.6-64.8) 22.8 (18.5-27.9) 10.6 (7.4-14.9) 33.4 (28.3-39.0) 12-15 years 6.9 (4.3-10.6) 66.6 (61.2-71.6) 19.0 (15.3-23.5) 7.5 (5.1-11.0) 26.6 (22.1-31.6) 16-17 years *8.0 (4.2-14.6) 67.9 (59.8-75.0) 20.1 (14.2-27.5) *4.1 (2.1-7.8) 24.2 (18.0-31.7)

5-7 years 10.2 (6.4-15.9) 62.4 (55.2-69.1) 14.2 (9.9-19.8) 13.2 (8.9-19.1) 27.4 (21.4-34.2) 8-11 years 5.4 (3.3-8.6) 60.0 (54.2-65.5) 24.3 (19.7-29.6) 10.3 (7.2-14.7) 34.6 (29.3-40.4) 12-15 years *4.3 (2.4-7.3) 76.4 (71.1-81.0) 15.2 (11.3-20.0) *4.2 (2.6-6.8) 19.4 (15.1-24.4)

Major cities 6.2 (4.8-7.8) 67.3 (64.4-70.1) 18.1 (15.9-20.5) 8.4 (6.8-10.4) 26.5 (23.9-29.3) Inner/Outer regional 8.3 (6.4-10.6) 64.6 (61.1-67.9) 19.0 (16.4-22.0) 8.1 (6.4-10.2) 27.1 (24.1-30.4) Remote/Very remote ** 71.6 (62.2-79.4) *11.6 (6.8-19.0) *12.1 (7.2-19.4) 23.6 (16.6-32.5)

* Estimate has a relative standard error of 25% to 50% and should be used with caution

** Not available for publication Estimate does not meet RSE or sample size criteria and is not considered reliable for general use

Included in totals where applicable

Body mass index

• 66.4% of Queensland children aged 5–17 years were of a healthy weight; 26.6% were overweight

or obese and 7.0% were underweight

• Girls aged 16–17 years were more likely than boys to be of a healthy weight with the prevalence of healthy weight 22% higher for girls than for boys of this age

• Amongst girls, those aged between 12 and 17 years were more likely to be of a healthy weight than girls aged between 5 and 11 years

• Children aged 5–17 years who lived in the most disadvantaged areas of Queensland were over two times more likely to be obese than those living in the most advantaged areas

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Table 3: Children’s fruit and vegetable intake, Queensland, 2011

Adequate fruit intake

Mean daily fruit

intake

Adequate vegetable

intake

Mean daily vegetable

• Mean daily vegetable intake generally increased with age Compared to children aged 5–7 years, those aged 16–17 years consumed 21% more daily vegetable serves and those aged 12–15 years consumed 16% more vegetables

• Children living in remote locations had an 85% higher prevalence of adequate vegetable intake and

a mean daily vegetable intake that was 25% higher than those living in major cities Compared to children in regional areas, children in remote areas had a 16% higher prevalence of adequate vegetable intake and a mean daily vegetable intake that was 9% higher

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Table 4: Children’s carbonated beverage consumption, Queensland, 2011

Non-diet soft drink at least

daily Diet soft drink at least daily

Non-diet flavoured drink (a) at

(a)

Includes non-diet soft drink, sport drink, energy drink and flavoured water

Soft drink

• 6.5% of Queensland children aged 5–17 years consumed non-diet soft drink at least daily

• Of Queensland children, boys were 77% more likely than girls to consume non-diet soft drink daily

• The highest prevalence of daily non-diet soft drink consumption, 18.8%, was among boys aged 16–

17 years Among boys, the prevalence of consuming non-diet soft drinks increased almost four times between the ages of 8–11 years and 16–17 years, whereas among girls the prevalence was stable across childhood

Non-diet flavoured drink

• 8.6% of Queensland children aged 5–17 years consumed non-diet flavoured drinks at least daily

• Boys aged 5–17 years were 59% more likely than girls to drink flavoured non-diet drinks on a daily basis

• The prevalence of daily consumption of flavoured non-diet drinks increased with age Those aged 16–17 years were 5.4 times more likely to consume these drinks daily than those aged 5–7 years

• Among boys, the prevalence of daily flavoured non-diet drink consumption increased with age Boys aged 16–17 years were 3.8 times more likely to drink non-diet flavoured drinks daily than boys aged 8–11 years and were almost twice as likely to do so as boys aged 12–15 years

• Boys aged 16–17 years were 2.4 times more likely to consume non-diet flavoured drinks than their female peers, 24.6% compared to 10%, respectively

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Table 5: Children’s food habits, Queensland, 2011

Takeaway food at least weekly

Usually drink full

Dinner eaten in front of

Takeaway food

• Almost half of Queensland children ate takeaway food at least weekly, with over 40% consuming takeaway weekly for both sexes and most age groups

• Queenslanders aged 16–17 years were more likely than children of other ages to consume

takeaway food once a week or more Those aged 16–17 years were up to 35% more likely to consume takeaway food at least weekly compared to the other age groups

• Boys aged 16–17 years were up to 49% more likely to have eaten takeaway weekly than boys of other ages

Full cream milk

• Two thirds of children aged 5–17 years usually drank full cream milk

• Queensland boys aged 5–17 years were 18% more likely to usually drink full cream milk than their female counterparts

• The prevalence of usually consuming full cream milk was lowest among 16–17 year old girls Compared to 16–17 year old girls, boys of the same age were 59% more likely to usually drink full cream milk

• Prevalence of usually consuming full cream milk was up to 33% lower among 16–17 year old girls compared to girls in other age groups and up to 44% lower compared to boys in other age groups

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• The prevalence of usual consumption of full cream milk decreased as socioeconomic advantage increased Children living in the most disadvantaged areas of Queensland were 34% more likely than those living in the most advantaged areas to usually drink full cream milk

• Children living in inner or outer regional areas were up to 17% more likely to usually drink full cream milk than those living in major cities

Breakfast

• 88.5% of Queensland children ate breakfast every day

• The prevalence of eating breakfast every day generally decreased with age, with a 20% decline between the ages of 5–7 years and 16–17 years A similar pattern was observed for males and females

• Children living in the most advantaged areas of Queensland were 8% more likely to eat breakfast every day than those living in the most disadvantaged areas

Dinner

• 13.5% of children aged 5–17 years ate dinner in front of the television every day

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Table 6: Children’s physical activity, Queensland, 2011

(a)

One hour or more of physical activity per day (b)

One hour or more per week

Recent physical activity

• 44.0% of children aged 5–17 years met the recommended physical activity guidelines for health benefit of one hour or more of physical activity per day in the previous seven days This has

recently been established as the national physical activity indicator for children Among children aged 12–17 years, 30.2% (27.3%–33.3%) met the recommended physical activity guidelines for health benefit of one hour or more of physical activity per day in the previous seven days whereas 56.4% (53.4%–59.4%) of children aged 5–11 years had done so (data not shown)

• Queensland boys were 28% more likely than girls to have been sufficiently active in the previous seven days

• The prevalence of sufficient physical activity in the past seven days decreased with age,

particularly for girls Girls aged 5–7 years were 3.6 times more likely than girls aged 16–17 years to

be sufficiently active whereas boys aged 5–7 years were 78% more likely to be sufficiently active than boys aged 16–17 years

• Boys aged 16–17 years were two times more likely than girls of the same age to undertake

sufficient physical activity in the previous week

• Prevalence of sufficient physical activity in the previous week decreased as socioeconomic

advantage increased Children living in the most disadvantaged areas of Queensland were 41% more likely to have completed an hour or more of physical activity per day in the last week

compared to those living in the most advantaged areas

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