Modeling the obesity epidemic: social contagion and its implications for control

Abstract

BackgroundAs an obesity epidemic has grown worldwide, a variety of intervention programs have been considered, but a scientific approach to comparatively assessing the control programs has still to be considered. The present study aims to describe an obesity epidemic by employing a simple mathematical model that accounts for both social contagion and non-contagious hazards of obesity, thereby comparing the effectiveness of different types of interventions.MethodsAn epidemiological model is devised to describe the time- and age-dependent risk of obesity, the hazard of which is dealt with as both dependent on and independent of obesity prevalence, and parameterizing the model using empirically observed data. The equilibrium prevalence is investigated as our epidemiological outcome, assessing its sensitivity to different parameters that regulate the impact of intervention programs and qualitatively comparing the effectiveness. We compare the effectiveness of different types of interventions, including those directed to never-obese individuals (i.e. primary prevention) and toward obese and ex-obese individuals (i.e. secondary prevention).ResultsThe optimal choice of intervention programs considerably varies with the transmission coefficient of obesity, and a limited transmissibility led us to favour preventing weight gain among never-obese individuals. An abrupt decline in the prevalence is expected when the hazards of obesity through contagious and non-contagious routes fall into a particular parameter space, with a high sensitivity to the transmission potential of obesity from person to person. When a combination of two control strategies can be selected, primary and secondary preventions yielded similar population impacts and the superiority of the effectiveness depends on the strength of the interventions at an individual level.ConclusionsThe optimality of intervention programs depends on the contagiousness of obesity. Filling associated data gaps of obesity transmission would help systematically understand the epidemiological dynamics and consider required control programs.

Smart Homes and Sensors for Surveillance and Preventive Education at Home: Example of Obesity

“…This result coincides with that presented in [20] using a social network analysis. The authors of [5] and [40] supported also the hypothesis of the existence of a social contagion, as well as the authors of [42], who show in their review that peers and friends play an important role in the physical activity level of the adolescents.…”

“…Several researchers studied the influence of friends and peers on the body mass index of an individual by using systems science tools that have been proposed to determine the impact of the collective behavior of the social network in the spread of obesity [36][37][38][39][40][41]. Some of these tools are based on the system dynamics approach [42,43], which is pertinent to study the transmission of obesity at the population level, while others use network analysis [33,44], as well as agent-based modeling [45] for investigating at the individual level.…”

“…Some of these tools are based on the system dynamics approach [42,43], which is pertinent to study the transmission of obesity at the population level, while others use network analysis [33,44], as well as agent-based modeling [45] for investigating at the individual level.…”

“…These determinants belong to the so-called "macro-environment" in [70], whose authors held that it involves income and socio-economic status, marketing of food, agricultural and food policy, as well as cultural norms and values. In [42], the authors studied the determinants of obesity in relation to the socio-economic status of middle-aged Swedish women, and they found that a low socio-economic status was an important factor involved in the increase of being overweight and obesity. In [71], family and social environment with high and middle-low income levels have been studied, and the authors found that there are much more fathers who are obese in middle-low income municipalities than in high income ones.…”

Qualitative Stability Analysis of an Obesity Epidemic Model with Social Contagion

“…With regard to its causes of social origin, the dynamics of obesity can be well modelled by epidemic-type models as a process of social contagion, as was evidenced by Christakis and Fowler who studied the spread of obesity in a large social network over 32 years and established that obesity can spread through social ties [7]. This approach has resulted in a wide range of papers of mathematical modelling in which obesity is studied as a social epidemic [8][9][10][11][12][13][14][15]. Social obesity epidemic models typically divide the population into two or several classes or subpopulations.…”