The first report is from the UK. Fat Chance? Exploring the Evidence on Who Becomes Obese is a curious example of what happens when a sugar company (AB Sugar) partners with a health organization (2020 Health) to produce a policy document.
The report examines the role of age, gender, socioeconomic factors, the built environment, mental health and disability, sleep, bullying and child abuse, smoking, ethnicity, and religion as factors in obesity—everything except diet and activity levels.
The press release for the report gives key findings, among them:
- Obesity rates are rising rapidly among the poor as well as other groups who experience social instability.
- Uncertainty seems to be a significant factor for weight gain.
- Fast food outlets near working environments have a significant impact on the BMI of men; the lack of green space has an impact on obesity rates particularly among girls.
- Half of all people suffering with psychosis are obese.
- Parental obesity, especially in mothers, is a far more predictive factor in childhood obesity than is ethnicity.
Its authors write:
What is particularly highlighted in recent research, though rarely explicitly stated, is that obesity rates seem to be deeply influenced by social change (not just influences within static social categories). The studies we have compiled for this review show a subtle trend that has become increasingly evident over the last decade. It is highlighted in economic mobility, rising rates of mental illness, technological habits and engagements, and rapidly shifting urban ground. Argued here, broadly speaking, is that many of these categories strongly hint to a meta-structure that remains profoundly under-researched and largely ignored. This is the structure of uncertainty, a type of habitus that influences the terms of emotional engagement between an individual and their daily life. Insidiously, it undermines health seeking behaviour by making daily decision processes cognitively intolerable and emotionally taxing.
…approaches to obesity that recognise and incorporate complexity might impact a host of rising health problems that affect communities across Britain. The same interventions that encourage healthy BMI may improve energy levels through metabolic process and sleeping habits, while reducing risk of mental health problems, diabetes and a range of other comorbidities not discussed in this report.
But they don’t say what those interventions might be.
Could they possibly have something to do with removing sugary drinks and foods from local environments?
For doing just that, the World Cancer Research Fund International has produced Curbing Global Sugar Consumption: Effective Food Policy Actions to Help Promote Healthy Diets & Tackle Obesity.
Examples of actions which have had these effects include school nutrition standards in Queensland, Australia; a vending machine ban in France; a front-of-package symbol that led to product reformulation in the Netherlands; soda taxes in France and Mexico; a programme targeting retail environments in New York City, USA; a programme promoting increased water consumption in schools in Hungary; school fruit and vegetable programmes in Netherlands and Norway; a healthy marketing campaign in Los Angeles County, USA and a comprehensive nutrition and health programme in France.
The first report asks us to solve problems of poverty, instability, and mental health before taking action to prevent obesity, even when actions are known to be effective. The second calls for such actions now.
Could AB Sugar’s sponsorship possibly have something to do with this difference?