Book Description

Obesity is one of the most serious public health challenges of the twenty-first century. It is both a disease itself and a major risk factor for many other life-threatening diseases. It has been rapidly growing worldwide during the last four to five decades and continues to affect millions of people in the world. Researchers and practitioners agree that in addition to genealogical/biological factors, obesogenic diets and physical inactivity are two major risk factors of obesity. Longitudinal data and research in the USA show that rapid growth in obesity rates during the last four to five decades coincided with declines in dietary quality and increasing sedentary lifestyles. Finding appropriate and effective policy interventions to control the obesity epidemic is a challenge for researchers, policymakers, and practitioners. In this dissertation, my goal is to investigate the relationships of the built environment with dietary and physical activity lifestyles and obesity prevalence. I conducted three independent but related studies. I examined the relationships of built-environmental factors with obesogenic dietary-intake patters (chapter 2), with physical inactivity lifestyles (chapter 3), and obesity prevalence (chapter 4). In each chapter, I formed a conceptual model of independent and control variables on one side and the dependent variable on the other. I drew on the socioecological framework and place-based perspective that includes demographic, social, cultural, and economic factors as well as the built-environmental or structural/infrastructural conditions of the place as possible determinants of population health. My broader goal was to investigate and understand the potential roles of built environment factors from the smart growth perspective. Therefore, I controlled other socioecological factors to isolate their roles and examine the specific relationships of the built environment in each study. In chapter 2, I examined whether and what aspects of local built-environment factors (independent variables) have relationships with dietary-intake standards in the counties of the USA (insufficient consumption of fruits and vegetables) (dependent variable). I investigated whether the availability and accessibility of different built-environment structures and infrastructures, i.e. different types of food outlets, have relationships with the local populations insufficient consumption of fruits and vegetables in the counties of the USA when other socioecological factors are controlled. I also investigated whether the built environment features that form the local commuting environment have relationships with the local populations dietary intake standards (insufficient consumption of fruits and vegetables) in the counties of the USA, controlling for other socioecological factors. I measured the local commuting environment as distances to workplaces, and the availability of transportation facilities in the counties of the USA. In chapter 3, I examined the relationships between the built environment factors (independent variables) and physical inactivity prevalence in the county (dependent variable). More specifically, I examined the relationships of the built environment for the availability of physical activity facilities and access to these facilities with physical inactivity rates in the counties of the USA. I also included the neighborhood crime rate as a measure of safe neighborhoods to examine its relationships with physical inactivity prevalence. I also examined built environment variables for local commuting environments to examine their relationships with physical inactivity prevalence in the counties of the USA. I used distances to workplaces and the availability of transportation facilities as measures of the local commuting environment. Chapter 4 provides a comprehensive study that examines the direct relationships between built environment factors (independent variables) and obesity rates in the counties of the USA (dependent variable). My conceptual model describes that shortcomings in the food environment, physical activity environment, and commuting environment together may lead to obesity prevalence. I formulated my questions accordingly to examine the relationships of these environments with obesity prevalence in the counties of the USA. I used all factors studied in chapters 2 and 3 to examine the direct relationship of these factors with obesity prevalence. This is a county-level national study. The data on all my variables were collected, compiled, or computed at the county-level. These are cross-sectional data and are publicly available from official websites and used by government agencies for national reports. I used county-data for 48 contiguous states in the USA. I excluded Alaska and Hawaii due to large missing data for many variables included in the study. In each chapter, I used multiple regression analyses and examined these relationships at the national level and within different county-types and county-groups. Specifically, I used ordinary least squares (OLS) regression to test my model for each chapter on the data of (1) all counties in the USA included in this study (main analyses at national level); (2) 9 county-types formed based on the characteristics given under rural-urban continuum codes (RUCC); and (3) county-groups based on similarities in characteristics such as size, metropolitan-nonmetropolitan status, rurality/urbanicity, and socioecological factors. The purpose of conducting multiple analyses was to find out if the variables in my models had similar relationships in counties having similar or different characteristics mentioned above and whether the findings at the national level were consistent for county-types and their groups. For each case, I developed specified models in multiple steps. I conducted regression analyses with control variables, with independent variables, and combined analyses with control and independent variables. The results of the three studies in this dissertation show that most of the built environment factors included in the study are important and they have significant relationships with the dependent variable in each study. The built environments for food, physical activity, and local commuting environments variables pertaining to the built environments for food, physical activity, and local commuting environments have significant relationships with the dependent variables at the national level and for different county-groups and county-types. The demographic/socioeconomic variables i.e. the control variables turn out to be important variables. Their beta values are high, generally higher than the beta values for built environment variables. However, some built-environment variables also turn out to be quite important. Their beta values are also high in all models. The results further show that some built environment variables are more important than others as they are present in most of the models. The results of this dissertation have some important policy implications. These results show that different socioecological factors, particularly the built environment factors that I included for examination can influence dietary-intake, physical inactivity and, subsequently, obesity prevalence among populations. These factors that form food and physical activity environments can create obesogenic environments. These factors pertain to different fields including the organizations and agencies engaged in urban-rural development, infrastructural design, housing, transportation, and so on. Private businesses form an important component of the population-health domain, and their role is important for any change/modifications in the structural/infrastructural design of the built environments. Therefore, an intergovernmental, inter-organizational, and intersectoral collaboration is required for policy formulation and implementation to control the obesity epidemic.