Obesity is a major global public health concern with an annually increasing prevalence rate in most urban areas(1). China has recorded the highest number of obese individuals, with an obesity rate as high as 25.9% and an overweight rate as high as 33.4% in Beijing in 2018 (2). The high prevalence is also associated with a considerable economic burden of about 1.1 trillion yuan each year (3). Reforms in the country have increased employment opportunities in the past 40 years, with a noticeable change in the urban environment as more people migrate, affecting the health of residents (4, 5).
Evidence suggests that the environment plays a central role in causing obesity, mostly through its conducive or inhibitive effects on physical activity and diet (6, 7). However, studies in different countries and regions have revealed that different cities have varied effects on obesity prevalence, with significant differences observed even between neighboring communities and neighboring provinces (8). Residents living in communities with higher land-use density, higher land-use structure, fewer crimes, higher traffic safety, and more access to entertainment facilities typically prefer physical activities to sedentary indoor activities, such as watching TV, surfing the Internet, and playing computer games (9). Of the surveyed environmental characteristics, those most consistent with the body mass index (BMI) were neighborhood socioeconomic status, walking environment, and opportunities for activities in leisure facilities (10).
The correlation between the urban built environment and obesity is conspicuous (1, 11–13). However, differences in ethnicity, culture, social development, economic development, and many other factors contribute to the uncertainty of overweight and obesity risk of a specific population. For instance, the influence of the built environment on obesity may vary according to individual characteristics in residents belonging to different groups. As residents grow older, they are less likely to exercise and more likely to spend their time indoors and have lesser interaction with the built environment (14). Generally, women are less physically active compared with men (15–17). Moreover, the poor built environment and less safe communities make residents more likely to stay indoors, thus increasing the possibility of obesity (14). In the process of using nearby facilities, more abundant service facilities (services and entertainment facilities) and natural facilities (attractive open space and rivers) can enhance people's willingness to travel, which is more conducive to maintaining a healthy weight of residents (18). Street characteristics can also affect people's obesity. According to a Canadian survey, obesity or overweight in a particular area was negatively correlated with street intersection density (i.e., the ratio of street intersections in a certain area) (19). Personal perception of the environment, including the safety perception of the venue, evaluation of the venue (or street) facilities, and evaluation of personal health, affects the residents' obesity (20).
Another challenge is the measurement of the built environment. There are no fixed standards for description of the built environment (21), and it is usually measured in terms of the physical space environment, economic environment, social culture, and political environment in the ideal context of the built environment research (22–24). Common measures are population density, the mixture of land use, the layout of service facilities, and street space. The characteristics of the physical space environment are that they can be evaluated subjectively and measured objectively. Typically, the subjective evaluation is a self-reported perception of the environment (25). However, the objective measurements are directly collected in the field or calculated from available land-use data sets. The built environmental factors may directly or indirectly affect the risk of obesity (which may vary between individuals) (26).
In this study, we included the experimental data set of subjective evaluation and objective measurement. The published studies have applied different measurement methods (27–36) for the built environment, which is decomposed into specific elements that can be described quantitatively to facilitate subsequent calculations and standards for implementation of future countermeasures. The quantified environmental indicators were of 5 categories, and 15 sub-categories of variables possibly related to obesity (7, 12, 30, 34, 37, 38). The five categories are community demographic characteristics (to describe the street-level population); the economic value of a location (to measure the social status); the mixture of land use (the mixture of POI points, meaning the level of the mixture of land use) and facility layout (to measure the accessibility of entertainment facilities); spatial characteristics of streets (to describe the quality of physical space of streets); and subjective evaluation of residents for space use of streets, as is presented in Table 1. Each of the statistical data were obtained from official statistical channels in China. Detailed information on health and built environment variables of 15 residents included in this study is presented in Table 1. The health data of BMI, age, gender, and home address were obtained from the health registration data of a certain leading hospital in Beijing. Subjective evaluation data were obtained from investigation and interview and consisted of the street walking facility score (subjective evaluation of whether the street is suitable for walking) and the street cycling facilities score (subjective evaluation of whether the street is suitable for riding) (11, 39).
In this study, we aimed to determine the effect of the built environment on obesity in the residents of the Shijingshan district of Beijing through subjective evaluation and objective measurement of BMI and built environment. We mainly focused on the ranking of the contribution of each index in the built environment to obesity.