Why Are Some Population Interventions for Diet and Obesity More Equitable and Effective Than Others? The Role of Individual Agency

Abstract

Jean Adams and colleagues argue that population interventions that require individuals to use a low level of agency to benefit are likely to be most effective and most equitable.

Socioeconomic Inequalities in Body Mass Index across Adulthood: Coordinated Analyses of Individual Participant Data from Three British Birth Cohort Studies Initiated in 1946, 1958 and 1970

“…[79] Given our findings of progressively widening BMI inequalities across adulthood, and the fact that BMI tends to track across life,[56] interventions may be most effective when initiated as early as possible in adulthood. Interventions which require little individual agency[80] may be especially efficacious at lowering population BMI levels and reducing inequalities. For example, increasing taxation on unhealthy foods while subsidizing others may be effective, despite potentially being financially regressive in the short term.…”

A description of interventions promoting healthier ready-to-eat meals (to eat in, to take away, or to be delivered) sold by specific food outlets in England: a systematic mapping and evidence synthesis

“…Also, few of the interventions operated at a population level. Population level interventions have the advantage that they are often more effective and equitable than more individualistic interventions, although have not been popular with governments in the UK [36, 37]. …”

The need for a complex systems model of evidence for public health

“…7,8 Achievement of meaningful impacts on complex multicausal problems, like obesity, requires more than single interventions, such as traffic light food labelling or exercise on prescription, many of which require high levels of individual agency, have low reach and impact, and tend to widen health inequalities. [9][10][11] Shifts within multiple elements across the many systems that influence obesity are required, some of which might only have small effects on individuals but can drive large changes when aggregated at population level. 12 Although randomised controlled trials of individual-level interventions are relatively straightforward to do, it is often impossible to randomise a population-level intervention, such as the introduction of a national tax on sugar-sweetened beverages, or the multiple factors that support cycling, such as physical infrastructure, spatial planning, and integration with public transport.…”