Pathways to obesity Identifying local, modifiable determinants of physical activity and diet Mai Stafford, Amanda Sacker Dept of Epidemiology & Public.

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Presentation transcript:

Pathways to obesity Identifying local, modifiable determinants of physical activity and diet Mai Stafford, Amanda Sacker Dept of Epidemiology & Public Health, UCL Sally Macintyre, Anne Ellaway MRC Social & Public Health Sciences Unit, Glasgow Steve Cummins Dept of Geography, Queen Mary College London R D Wiggins Dept of Sociology, City University

Neighbourhood influences on health of increasing interest Methodological developments Empirical evidence focuses on deprivation index as exposure Neighbourhood deprivation associated with -mortality (all-cause, suicide, deaths from heart disease) -morbidity (self-rated health, disability, smoking, quality of life, common mental disorder) Background/rationale

Composition or context? Multilevel data and analysis Reviews of evidence conclude there is an association between neighbourhood deprivation and health Neighbourhood deprivation = black box

What neighbourhood characteristics might influence health? Neighbourhood deprivation index Service environment e.g. health services, public transport, retail Built environment Social environment e.g. social disorder, social capital

Unpacking the black box Identify specific, amenable neighbourhood determinants of health How do these relate to each other? How do they jointly influence health? Focus on obesity – a major public health issue Key determinants of obesity are diet and physical activity

Service environment and diet, physical activity and obesity Local sport & leisure facilities Greater physical activity Giles-Corti et al, 2002 Presence of supermarket Higher fruit & veg consumption, lower fat intake Morland et al, 2002 Poorer access (proximity & car) Lower fruit & veg consumption Cheadle et al, 1991 Availability low fat/high fibre foods Greater intake low fat & high fibre Rose et al, 2004 No. fast food outlets Obesity Maddock, 2004

Built environment Mixed commercial- residential land use Greater levels of walking Doyle et al, 2006; Frank et al, 2006 Urban sprawl (population density) Lower levels of walking Morenoff et al, 2006 Attractive scenery open spaces Greater physical activity Brownson et al, 2001; Sugiyama et al, 2005

Social environment- neighbourhood disorder Neighbourhood safety Childhood obesity Lumeng et al, 2006 Fear on streets fear of attack Less outdoor physical activity Ross, 1993 Fear of crimeLess walking for pleasure Parkes & Kearns, 2006 Litter and graffitiObesity Ellaway et al, 2005

Leisure centres Neighbourhood disorder High physical activity Obesity Good diet Urban sprawl Supermarkets Fast-food outlets Demographic & socioeconomic characteristics Environmental characteristics Individual characteristics Mixed commercial/ residential use ? - -

Data & methods I. Measuring obesity Health Survey for England ( ) and Scottish Health Survey (1995 & 1998) Nationally representative Height and weight measured by trained nurse Obesity = body mass index = weight/height 2 Age, gender and occupation-based SES Neighbourhood unit = postcode sector Average population ~ 5000

Data & methods II. Selecting neighbourhoods for study Eligible neighbourhoods Ensure range of environments Select sample of neighbourhoods 35 Health Survey participants Stratify on population density & Carstairs index of deprivation Stratified random sample Data complete for 398 neighbourhoods Collect neighbourhood data

Data & methods III. Measuring the service & built environment Various sources: administrative data from central government, local government, commercial organisations e.g. violent crime per capita, number of supermarkets Difficult to obtain data –not available –not complete –not comparable England and Scotland Data collected or converted to postcode sector

Data & methods IV. Measuring neighbourhood disorder Local Area Social Capital Survey conducted in item postal questionnaire Sent to random sample of residents 16+ years Response rate 42% 5 items capture neighbourhood disorder

Data & methods V. Linking data Administrative/ commercial data Service environment Built environment Postal survey Neighbourhood disorder Existing health survey Individual level obesity Link via postcode sector identifier

Violent crime rate # special constables Vacant/derelict land Sports participation rate BMI Population density # supermarkets Age Male SES Neighbour- hood disorder # police officers # missed waste collections High street facilities # swimming pools # McDonalds

Data & methods VI. Structural Equation Modeling Aim to investigate inter-relationships between various neighbourhood characteristics and their relationship with obesity Beyond estimation of direct effects Examine causal processes underlying observed relationships Estimate relative importance of different causal pathways

Data & methods Some neighbourhood characteristics modeled using latent variables i.e. measured variables are indicators of underlying construct Want to know about relationships between underlying constructs (not between measured variables)

Neighbourhood disorder Graffiti/ vandalism People cant be trusted Afraid to walk alone Area full of rubbish Neighbours threatening

High street facilities # pharmacies # optician practices # dental practices # libraries # building societies # banks # Bingo halls distance to post office

Data & methods Step 1: confirmatory factor analysis to assess how well measured variables capture underlying construct Step 2: structural equation model linking neighbourhood characteristics to obesity Allow for clustering of participants within neighbourhoods Present standardised factor loadings and path coefficients Mplus software

Results Factor analysis confirmed that i) neighbourhood disorder well-measured by the 5 items from the Social Capital Survey ii) high street facilities well-measured by 5 items (3 dropped) High street facilities # pharmacy # optician practices # dental practices # building societies # banks High street facilities # pharmacy # optician practices # dental practices # libraries # building societies # banks # Bingo halls distance to P.O.

Violent crime rate # special constables Vacant/derelict land Sports participation rate BMI Population density Supermarkets AgeMSES Neighbourhood disorder # police officers Missed waste High street facilities Swimming pools Post office

Summary of findings Previous studies show neighbourhood deprivation is associated with obesity Our findings illustrate some specific features of the neighbourhood environment that are associated with obesity These are neighbourhood disorder, mixed commercial/residential land use and urban sprawl In turn, policing and vacant/derelict land influence levels of neighbourhood disorder

Discussion Study illustrates how data from various sources can be combined Latent variables can be used when have several indicators of the same underlying construct Structural equation models can be used to explore theoretical causal pathways Limitations include i.lack of neighbourhood data capturing the theoretical constructs of interest ii.self-selection of participants into different types of neighbourhood iii.cross-sectional iv.defining neighbourhood boundaries – to fit the data or to fit residents perceptions and experience

Concluding remarks Our findings illustrate that several determinants of obesity are not within traditional remit of healthcare sector Private sector and non-healthcare public sector has an important role Stronger links and even representation of public health in police force, land use planning bodies and groups supporting local business are needed Dont forget individual characteristics also strongly related to obesity