Obesogenic Environments Flashcards
Global scale of obesity (WHO, 2021)
Adults:
- 1.9 billion adults worldwide overweight in 2016 (39% global population) and 650 million were obese (13% population)
- Worldwide prevalence nearly tripled between 1975 and 2016
- ↑ risk of CVD, diabetes, musculoskeletal disorders, some cancers - 4 million people dying each year as a result of being overweight or obese
Children:
- In 2019 an estimated 38.2 million children under 5 were overweight or obese
- In 2016 340 million children 5-19 were overweight or obese – a dramatic rise from 1975
- Fastest rate of increase now seen in low and middle income countries
- Obese infants & young children tend to become obese adolescents & adults without intervention
THE simple Vs realistic view of obesity
Simple..?
The fundamental cause of obesity and overweight is an energy imbalance between calories consumed and calories expended
Realistic…
The inherent intricacies of how we consume and use energy are highly complex and often interrelated.
Obesity systems map (foresight, 2007)
‘Complex web of societal and biological factors that have, in recent decades, exposed our inherent human vulnerability to weight gain’
The term ‘obesogenic environment’ was first used in the 1990s and refers to the role environmental factors may play in determining both energy intake and expenditure
The Interface Between Genes and Environment Clément (2005)
Monogenetic, polygenetic, environmental
Monogenic obesity
- Single mutations in certain genes wholly explain development of obesity – but rare, severe and starts in early childhood
Polygenic genotype/environmental factors
- Obesity resulting from an interaction between environmental factors (overeating and/or reduction in physical activity) and hereditary factors.
- ‘Environmentally driven changes in body weight in the population occur against a background of susceptibility to weight gain determined by genetic factors’ (Farooqi & O’Rahilly, 2006)
Environmental obesity
- But studies indicate that genetic contribution to body weight is highly heritable (~40-70%)
Obesity regarded as a ‘normal response to an abnormal environment’ (Eggers & Swinburn, 1997)
“98% of hominid existence has been shaped by hunting and foraging with selection for cognitive and behavioural repertoires, nutritional requirements and physiological patterns adapted to harsh environments with fluctuations in food availability, food shortages and periodic high energy expenditure…
…These once adaptive cognitive, behavioural and physiological genotypes and phenotypes persist today in evolutionary-novel environments characterised by an abundance of supersized energy-dense foods with low energy-cost availability.” (Lieberman, 2006)
What is an obesogenic environment? (Elinder & Jansson, 2009)
- Definition
Defined as the ‘sum of the influences that the surroundings, opportunities or conditions of life have on promoting obesity in individuals and populations’.
What is an obesogenic environment? (Elinder & Jansson, 2009)
Food availability/ accessibility & sedentariness intrinsically linked with economic growth & development
- Geographic differences in obesity rates
- explained by local opportunities for healthy eating & physical activity
- different groups may react differently to the same obesogenic drivers
Notably, not everyone who inhabits an obesogenic environment is obese
Environments or behaviours? (Procter et al. 2008)
Environments
- Scale of urban development
- Level of deprivation (incl. receipt of benefits & low income)
- Low SEC group
- More than 1 TV/household
- Poor leisure facilities
- Poor access to supermarkets
- Teenage loiterers & vandals
- Good public transport
Behaviours
- Lack of physical activity
- No or low consumption of F&V
- No school meal consumption
- Low expenditure on food
effects not the same in all areas (Edwards et al., 2010)
Obesogenic environments are non-stationary - different variables have differing effects on obesity rates in different areas:
Affluent = intake of fruit and veg
how can environment affect body weight?
ANGELO + EnRG
ANGELO framework =
to characterise the elements within environments with may have an influence on diet, physical activity and sedentary behaviour (axis for level and type of environment). No individual info?
(Swinburn et al., 1999; image from Lakerveld et al. 2017)
EnRG framework =
how do environmental factors may have an impact on obesogenic behaviours and also how mediated and moderated by individual level factors
(Kremers et al., 2006; image from Lakerveld et al. 2017)
Overconsumption
“Evidence for the impact of the food environment on health revealed that provision of healthier and affordable food could be effective in improving dietary attitudes and behaviours, and reducing dietary fat intake and BMI in public service settings (i.e., schools, community settings, council offices).” (PHE 2017b, p64)
Food - access
case study
New Zealand (Day & Pearce, 2011)
- Mapping
- Fast-food/ convenience outlets (400m & 800m from schools)
- Clustering of outlets within walking distance esp. in more socially-deprived settings
Preston, UK (Caraher et al., 2010)
- Preston has more fast-food outlets than general grocers
- Deepdale (S. Asian, Muslim)
affordable
- Ingol (working class, white British)
more expensive; less specialist and fresh produce; shops more >500m away
- Both poor availability of healthy alternatives (e.g. brown, wholemeal)
Food - car reliance (Hinde & Dixon, 2005)
- Captive audience to market
- (radio, billboards)
- Eating on the run and drive-thru food
- Possible reduced self-regulation of consumption in car
- (‘private space’)
- Altered grocery purchasing behaviours
food - availability
case study
British Columbia, Canada (Naylor et al. 2010)
- Food in these publicly-funded recreational facilities are obesogenic environments
88% had no food policy for children/ youth programmes
61% had a café/ snack bar
most commonly ordered food was fried (38%). - Av/ 3.6 vending machines/ facility
- 57% contained SSBs
South & West Yorkshire & Derbyshire (Ashworth et al. 2016)
- Characterisation of café & vending offers in leisure centres
- Vending: predominantly ‘less healthy’ according to NPT
- Café: inconsistency between locations
food - the built environment
case study
Neighbourhood Food environments (Lake 2018):
- Clustering of outlets selling nutrient poor, energy dense foods in more deprived areas (deprivation amplification)
- convenience stores to supermarkets
- restaurants & takeaways
- Access & intake are associated
- Significant methodological challenges
“…poorer neighbourhoods often encompass aspects harmful to health, lacking the healthful resources found in wealthier areas.” (Townshend &Lake 2017)
Mediators of inactivty?
“People in the UK are around 20% less active now than in the 1960s. If current trends continue, we will be 35% less active by 2030” (PHE 2022)
uk physical activity guidelines (UK chief medical officers, 2019)
1-5 = 180mins per day
5-18 = 60mins per day
older adults = 150 mod. activity per week - 70 mins vig. per week
physical activity in UK adults & children (NHS digital, 2020)
the more deprived aren’t as active in adults and children
girls and females are less active in adults and children
physical activity – convenient facilities
Convenient physical activity facilities may help reduce rates of overweight/ obesity in Irish adolescents (Nelson & Woods, 2009)
“convenient facilities for physical activity are associated with reduced rates of overweight and obesity. This adds to accumulating evidence that creating supportive environments for health means creating supportive environments for physical activity.”
physical activity – car reliance (hinde & Dixon, 2005)
- Sedentary activity
- Displaces active transport
- ↑ in car numbers
- Concerns around road safety for pedestrians/ cyclists
- Reduced levels of ‘play’
Activity – environmental factors associated with physical activity in children & adolescents (Ferreira et al., 2006)
Systematic review of 150 studies over 25 years
Environmental factors associated with physical activity in children and young people using ANGELO framework
- Positive association with physical activity levels and:
- In children - father’s PAL, time spent outdoors, school PA-related policies
- In adolescents - support from others, mother’s education level, family income, non-vocational school attendance, low crime incidence in neighbourhood
Implications
- Research limitation - most studies cross-sectional with subjective measures of environment & physical activity levels
- Further research on longitudinal and intervention studies, more objective measures of PA and environmental determinants
- Multilevel interventions to increase PA in children and adolescents, targeting variables highlighted.
sedentary behaviour- screen time
Average US child/adolescent watches an average of 3 hours TV/day (not including computer games etc).
- TV access in bedroom
- lack of parental limit-setting on use
- few/no family dinners
Television watching cross-sectionally and prospectively related to childhood adiposity in epidemiological studies (dose-response relationship)
- ? competes with other more physically active behaviours
- ? promotes unhealthy snacking
- ? mirroring of parental behaviours
- TV viewing at age 5 also shown to be associated with BMI at 30 years of age (Viner & Cole, 2005)
- Reduction of sedentary behaviour (e.g. TV watching) as part of a family-based weight management programme shown in a RCT to be as effective for weight loss and fitness as physical activity programme (Epstein et al., 2000).
- UK guidance (NICE NG7, 2015) recommends <2 hours total ‘leisure’ screen time/day
Planning policy (lake, Townshend & Burgoine, 2018)
Local authorities can consider relationship between planning the built environment and impacts on health: National Planning Policy framework includes section on promoting ‘healthy communities’ e.g.
only allowing takeaways in specified areas (but may ↑ clustering)
restricting concentration of takeaway outlets (e.g. max 3 in a row, <5% store frontage)
restricting proximity to schools, parks etc
fee charged, used for obesity prevention
Challenges:
Appeals to planning inspectorate
Other outlets – corner shops
Recent – evidence lacking
advertising restrictions
Evaluation of impact (Yau et al., 2022)
Controlled interrupted time series analysis (‘natural experiment’) to evaluate impact of TfL HFSS advertising restrictions on HFSS purchases
Food and drink purchases recorded by 977 households in London (intervention group) compared with 993 matched north of England (control group) households
Estimated average weekly energy content of food purchases for 44 weeks post intervention, compared with pre-intervention/control group
↓6.7% energy purchases in intervention households (plus reductions in fat, saturated fat and sugar from HFSS products)
Conclusion: association between implementation of restrictions on outdoor HFSS advertising and relative reductions in energy, sugar and fat purchased from HFSS foods.
