A Secondary Analysis of the CrossSectional Data Available in the Welsh Health Survey for Children to Identify Risk Factors Associated with Childhood Obesity in Wales Presented by Claire Beynon ID: 722101
Download Presentation The PPT/PDF document "Insert name of presentation on Master Sl..." is the property of its rightful owner. Permission is granted to download and print the materials on this web site for personal, non-commercial use only, and to display it on your personal computer provided you do not modify the materials and that you retain all copyright notices contained in the materials. By downloading content from our website, you accept the terms of this agreement.
![[Insert Project Name] Operational Readiness Review (ORR)](https://thumbs.docslides.com/713702/insert-project-name-operational-readiness-review-orr.jpg)
Slide1
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 UniversitySlide2
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.Slide3
Claire Beynon
Why is childhood obesity a problem?
Lobstein and Jackson Leach in Foresight Report, UK Government Office for Science,
2007.Slide4
Claire Beynon
The Data Choice in the UK
Childhood Measurement ProgrammeMillennium Cohort StudyWelsh Health SurveyEnglish Health SurveyCollecting new dataSlide5
Claire Beynon
Welsh Health Survey
Adult SurveyChildren's SurveyGeographyQuestion development
Sampling frame
Sampling technique
Response rateSlide6
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.Slide7
Claire Beynon
1032 records excluded on basis of non-English; not relevant; not in age range; incorrect outcome; data not collected in WHS
1086 titles and abstracts screened using inclusion criteria
41 full-text articles excluded on basis of non-English; not relevant; not in age range; incorrect outcome; data not collected in WHS
13 articles included in review of the literature
54 full-text articles assessed for eligibility using inclusion criteria
Total of 1086 records identified using ‘Childhood Obesity’ and ‘Risk Factors’ from four electronic databases
754 records identified through EMBASE electronic database
281 records identified through MEDLINE electronic database
41 records identified through PSYCHINFO electronic database
10 records identified through Cochrane Library
Literature reviewSlide8
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.Slide9
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. Slide10
Claire Beynon
Results
Body Mass Index classifications for children by year of WHS Slide11
Claire Beynon
Results
Body Mass Index classifications for children’s age groupSlide12
Claire Beynon
Odds Ratios
How to calculate:OR = Odds of exposure in cases
Odds of exposure in control
How to interpret:
OR>1
increased risk
OR=1 no difference
OR<1 decreased risk
Confidence
intervals, if
they
cross
1 not significantSlide13
Claire Beynon
Results
Risk Factor
Odds Ratio
95% CI
P value
Sex
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 * Slide14
Claire Beynon
Results
Risk 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*
Highest1.230.99 to 1.53p=0.06Slide15
Claire Beynon
Results
Risk Factor
OR
95% CI
P value
Illness
No illness
Reference
One illness
1.20
1.05 to 1.38
p=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*Slide16
Claire Beynon
Results
Risk Factor
OR
95% CI
P value
Fruit & Vegetables
Not daily
Reference
Both daily
0.96
0. 85 to 1.09
p=0.82
Sugar sweetened
beverages
Not daily
Reference
Daily
1.02
0.83 to 1.27
p=0.82
Crisps,
chips or sweets
Not daily
Reference
Daily
0.89
0.79 to 1.01
p=0.08
No significant association between childhood obesity and the following factors:Slide17
Claire Beynon
Differences from CMP dataSlide18
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.Slide19
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.Slide20
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. Slide21
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.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.