World map of the prevalence of adult obesity (age 20+ years) in 2016 (a) Women (b) Men.
Source: NCD Risk Factor Collaboration [1].
Figure 2.3 World map of the prevalence of childhood obesity in girls (a) and boys (b) aged 2–4 years in 2015.
Source: The Global Burden of Disease Obesity Collaborators [11]. Note: Estimates of obesity were calculated by the Institute for Health Metrics and Evaluation using the International Obesity Taskforce growth reference.
Figure 2.4 World map of the prevalence of childhood obesity in girls (a) and boys (b) aged 5–19 years in 2016.
Source: NCD Risk Factor Collaboration (NCD‐RisC) [1]. Note: Estimates of obesity were calculated by NCD‐RisC using the World Health Organization growth reference.
Social determinants of obesity
The observation that no country or population subgroup appears to have escaped the obesity epidemic suggests universal, distal drivers of weight gain [56]. These include social, economic, political, environmental, and cultural factors, as described in detail in this section.
National economic development
The relationship between GDP per capita – a marker of national economic growth – and BMI [57,58], overweight [59], and obesity [60] takes an inverted U‐shape among women but is linear and positive among men and children. One previous analysis found that this association diminished in magnitude between 1980 and 2008 [57]. Following the collapse of the Soviet Union, Russia may be an exception to this phenomenon because income was a stronger positive predictor of obesity in 2004 compared to 1994 [61]. Among men, previous studies have found that the association is positive for low‐income and lower‐middle‐income countries but plateaus for upper‐middle‐income and high‐income countries [57,58]. A previous study found that up to 18% of the increase in obesity among urban US adults from 1976 to 2000 could be explained by relative reductions in food prices [62], and another study reported that 40% of the increase in obesity in the United States from 1976 to 2004 could be attributed to decreasing food prices [63]. Thus, weight gain may be an inadvertent consequence of stabilizing food markets.
One previous analysis of 21 high‐income countries found a significant positive association between income inequality and obesity among women and men [64], but an analysis that included 68 countries spanning low to high income did not find a significant association between the Gini index (an indicator of income inequality) and the prevalence of obesity among women or men [60].
Individual socioeconomic status
The relationship between individual socioeconomic status and obesity varies according to national economic development. As GDP per capita increases, the burden of obesity shifts from wealthy individuals to poor individuals [12]. Thus, in high‐income countries, the prevalence of obesity tends to be highest among the poor. In the United States, for example, the prevalence of obesity is increasing among white women with low incomes, but not among women in other ethnic groups or women in the highest income group [65]. Among US men, the prevalence of obesity increased in all three income groups in 2011–2014 [65]. Among US children, the socioeconomic status gradient in obesity increases as they age [66].
In England, socioeconomic gradients in obesity have been reported as early as 5 years of age, which supports a strong role for the home environment [67]. Moreover, the obesity prevalence gap between the haves and have‐nots has widened over time: the prevalence gap between the most and least deprived areas in England in 2016–2017 was 13.4% compared to 8.5% in 2006–2007 [67].
Urbanization
Urbanization is considered one of the key drivers of the global rise in obesity [68]. The percentage of a country’s population living in urban areas is one of the strongest positive correlates of BMI among both women and men [57,58,69]. Living in urban areas is associated with a greater probability of being overweight, even after controlling for education, but the association between urban residence and overweight is weaker in countries with higher per capita GDP levels [59]. For example, a study in Peru has shown that urban residents and rural‐to‐urban migrants have a higher level of obesity than the rural population [70]. These differences are mostly associated with transportation, food access, open spaces, mass media, and sedentary jobs (mostly associated with mechanization), resulting in less physical activity, more sedentary time, and overall higher levels of overweight and obesity.
Within urban areas, it is increasingly evident that there is a difference in obesity levels between low‐ and high‐income neighborhoods, with residents of the former showing higher levels of obesity [71]. One of the underlying drivers of this disparity is the food environment. Areas can be classified as “food deserts,” defined as a lack of access to affordable, nutritious foods, or “food swamps,” defined as areas with a high density of fast‐food restaurants and junk food [72]. In both food deserts and food swamps, residents are at greater risk of obesity due to unhealthy diets. A recent review has shown a positive association between access to green spaces and physical activity and a negative association between access to green space and screen time, BMI, and weight among children [73].
Nonetheless, a recent global study has shown that more than 55% of the global increase in the average BMI observed over the past three decades is due to an increase in BMI in rural areas [74]. This disparity is due to a faster increase in BMI in rural areas when compared to urban areas in low‐ and middle‐income countries. As a consequence of current trends, the urban–rural gap is closing, especially for women, and in high‐income countries, the mean BMI is higher in rural areas.
Several studies have also explored spatial patterning of obesity within a given country. For example, in the United States, adults living in medium or small metropolitan areas have a higher prevalence of obesity compared to those living in large metropolitan areas, even after adjustment for age, race and Hispanic origin, education level, and smoking status [75]. Women living in non‐metropolitan areas also had a higher prevalence of obesity compared to women living in large metropolitan areas, even after adjustment for the aforementioned factors [75]. A comparative urban–rural analysis in the prevalence of central obesity in China showed that in 2011, both central and general obesity in rural adults exceeded that in urban adults [76].
Technology
Technological advances are considered one of the possible explanations behind the global increase in obesity. One consequence of increasing mechanization, automation, computerization, and service‐driven economies is a reduction in work‐related physical activity. In the United States, low physical activity at work is a risk factor for total and central obesity, especially among men working more than 40 hours per week [77].
Another recognized determinant of obesity, especially among children, is excess screen time leading to reduced physical activity, increased calorie intake particularly through snacking triggered by advertising, and reduced sleep time [78,79]. A meta‐analysis of 14 cross‐sectional studies of over 100,000 children showed
