A Secondary Analysis of the Cross-Sectional Data Available in the ‘Welsh Health Survey for...

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Insert name of presentation on Master Slide A Secondary Analysis of the Cross-Sectional Data Available in the ‘Welsh Health Survey for Children’ to Identify Risk Factors Associated with Childhood Obesity in Wales. Presented by :Claire Beynon Supervisor :Professor David Fone, Cardiff University

Transcript of A Secondary Analysis of the Cross-Sectional Data Available in the ‘Welsh Health Survey for...

Page 1: A Secondary Analysis of the Cross-Sectional Data Available in the ‘Welsh Health Survey for Children’  to Identify Risk Factors Associated with Childhood Obesity in Wales

Insert name of presentation on Master Slide

A Secondary Analysis of the Cross-Sectional Data Available in the ‘Welsh Health Survey for Children’ to Identify Risk Factors Associated with Childhood Obesity in Wales.

Presented by :Claire BeynonSupervisor :Professor David Fone, Cardiff University

Page 2: A Secondary Analysis of the Cross-Sectional Data Available in the ‘Welsh Health Survey for Children’  to Identify Risk Factors Associated with Childhood Obesity in Wales

Claire Beynon

Why is childhood obesity a problem?• Prevalence of childhood obesity in Wales 12%.• Impacts on both quality and quantity of life.• Immediate effects:

low self esteem; bullying; depression; type II diabetes.

• Long term effects:Premature mortality; adult morbidity.

• Obesity costs £73 million per annum in Wales.

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Claire Beynon

Why is childhood obesity a problem?

Lobstein and Jackson Leach in Foresight Report, UK Government Office for Science, 2007.

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Claire Beynon

Research Question• What are the important risk factors for childhood

obesity for children aged 4 to 15 years in Wales?

Research Objectives• Identify and quantify cross-sectional associations

between obesity in children in Wales aged 4-15 years and the risk factors available in the Welsh Health Survey.

• Make recommendations for policy where appropriate.

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Claire Beynon

Study Design• Secondary Analysis of Data from the WHS.

• Dataset included n=11,279 children (aged 4-15 years) between 2008 and 2011.

• Descriptive statistics, and logistic regression.

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Claire Beynon

Risk Factors• Socio-demographic/socioeconomic variables:

Sex, age, National Statistics Social Classification (NSSEC), housing tenure and Welsh Index of Multiple Deprivation (WIMD).

• Lifestyle variables: Unhealthy food consumption; sugar sweetened beverages; physical activity (PA) levels

• Illness: Currently treated illnesses.

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Claire Beynon

Results

Risk Factor Odds Ratio 95% CI P valueSex Male Reference

Female 0.79 0.70 to 0.89 p<0.001*

Age 4-6 Reference

7-9 1.42 1.19 to 1.70 p<0.001*

10-12 1.65 1.39 to 1.97 p<0.001*

13-15 1.44 1.20 to 1.73 p<0.001*

Significant association between childhood obesity and the following factors denoted with *

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Claire Beynon

ResultsRisk Factor OR 95% CI P value

NSSEC 3 Professional/ Managerial Reference

Intermediate 1.17 0.98 to 1.38 0.08

Routine/ Manual 1.32 1.14 to 1.54 p<0.001*

WIMD Lowest Reference

Low 1.08 1.19 to 1.70 p=0.44

Mid 1.23 1.01 to 1.50 p=0.04*

High 1.33 1.09 to 1.62 p=0.005*

Highest 1.23 0.99 to 1.53 p=0.06

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Claire Beynon

ResultsRisk Factor OR 95% CI P value

Illness No illness Reference

One illness 1.20 1.05 to 1.38 0.008*

Two or more illnesses 1.50 1.22 to 1.85 p<0.001*

Physical Activity

Meets recommendation Reference

Does not meet recommendation

1.33 1.17 to 1.52 p<0.001*

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Claire Beynon

Results

Risk Factor OR 95% CI P valueFruit & Veg Not daily Reference

Both daily 0.96 0. 85 to 1.09 p=0.82

SSB Not daily Reference

Daily 1.02 0.83 to 1.27 p=0.82

Junk food Not daily Reference

Daily 0.89 0.79 to 1.01 p=0.08

No significant association between childhood obesity and the following factors:

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Claire Beynon

Strengths of the study• WHS uses stratified random sampling.• Results for 3000 children achieved per annum.• Good response rate at 75%.• Known confounding accounted for by use of multivariable

analysis.• Provides new insights into existing data.• Information from Wales on which to base Welsh policy.

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Claire Beynon

Limitations of the study• Risk of bias, e.g. recall bias; reporting of food

consumption and physical activity reporting. Non response bias.

• Reverse causality possible due to study design.• Selection bias, private homes surveyed (not

institutions).• Unknown confounding possible (not all risk factors

measured).• Interactions not explored.

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Claire Beynon

Conclusions• Some risk factors associated with childhood obesity

are not modifiable (e.g. sex and age of the child). • Some risk factors are not easily modifiable in the short

term, e.g. the circumstances of the family (NS-SEC classification of the parent and housing tenure).

• Two findings are potentially more easily modifiable:

– the association between childhood obesity and not meeting the PA recommendations

– the NHS response to the care planning of children with a long term condition.

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Claire Beynon

Recommendations• Increase physical activity in schools to an hour a day,

so all children have levels of PA that protect them from obesity without increasing inequalities in health.

• Extend the number and type of physical activity options available to children across Wales both in schools and out of school.

• Utilise the CMP feedback to provide advice on relevant physical activity options that are affordable and accessible e.g. green spaces; walks; free swimming.

• Ensure all children with a long term condition get help to avoid or manage obesity through an holistic care package.

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Claire Beynon

Current Recommendations• Physical activity

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Claire Beynon

ResultsSignificant association between childhood obesity

and the following factors: • being female OR 0.79 (95% CI: 0.70 to 0.89, p<0.001);• older age categories than the reference group (4-6

years) with ORs varying between 1.42 and 1.65 (all significant at p<0.001);

• parents being in the routine, manual, never worked or long term unemployed group OR 1.32 (95% CI: 1.14 to 1.54, p<0.001);

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ResultsSignificant association between childhood obesity

and the following factors: • mid and high quintiles of the WIMD.

OR for mid 1.23 (95% CI: 1.01 to 1.50, p=0.04) and for high deprivation OR 1.33 (95% CI: 1.09 to 1.63, p=0.005);

• having one or two currently treated illnesses.OR for one illness 1.20 (95%CI: 1.05 to 1.38, p=0.008) and for two or more illnesses OR 1.50 (95% CI: 1.22 to 1.85, p<0.001)

• not meeting the PA recommendations OR 1.33 (95% CI: 1.17 to 1.52, p<0.001).