Exploring longitudinal associations between the food and physical activity environment and weight status: natural experiments around the residential address, the work address, the secondary school address, and the home-secondary school travel route.

Overweight and obesity are major risk factors for various chronic diseases1. Overweight and obesity are defined as having a Body Mass Index (BMI, weight in kilograms divided by square height in metres) of 25.0 or higher and 30.0 or higher, respectively. Currently, approximately half of Dutch adults are overweight or obese2. In absence of effective health policy, it is expected that 62% of Dutch adults will be overweight or obese by 20403. 
Overweight and obesity have a multifactorial and complex aetiology. Fundamentally, these are caused by an excess of energy intake relative to energy expenditure. Previously, energy intake and energy expenditure were considered as the result of individual determinants, yet individually-focused policies have been ineffective in reducing overweight and obesity. Nowadays, it has become widely acknowledged that environmental determinants also play an important role in the development of overweight and obesity4. 
Abundant access to fast-food outlets and a lack of access to physical activity facilities are considered among the most important environmental determinants of overweight and obesity. Fast-food outlets (e.g., snack bars) typically offer cheap, quickly served and high-calorie meals, and are easily accesible. Abundant access to fast-food outlets may provoke a high-calorie diet, resulting in a higher weight status. Fast-food outlets have increased in number in the Netherlands: for example, the number of fast-food outlets in the province of Groningen has increased with 33% between 2013 and 20185. Also, a lack of physical activity facilities (e.g. indoor gyms and outdoor sport fields) in the living environment may make it more difficult for individuals to be physically active, thereby affecting their weight status. 
Yet, evidence on the association between the food and physical activity environment and weight status is inconsistent and mainly comes from the United States6. There are several reasons for the inconsistency of the evidence. 
First, accurate measurement of the environmental exposure is a challenge7: it requires linkages between costly and computationally challenging geographic information systems, individual participant health data, and privacy-sensitive participant addresses. Alternatively, researchers rely on group-level exposure estimates (e.g. the number of fast-food outlets per zip-code unit7). Yet, this introduces the risk of misclassification since individuals within the same zip-code unit may differ in their food and physical activity environment. For example, physical activity facilities may be mostly present in one specific area within a zip code. Furthermore, studies typically measure food and physical activity environment either in terms of density (e.g., the amount of fast-food outlets within a certain range around the residential address) or proximity (e.g., the distance towards the nearest fast-food outlet from the residential address)8. These measures are correlated but conceptually distinct9: for example, a fast-food outlet may be nearby (high proximity) but still be the only one in the area (low density). Therefore, taking into account both measures provides a more comprehensive assessment of the food and physical activity environment10. 
Second, there is a lack of longitudinal studies on the association between the food and physical activity environment and weight status. Ideally, longitudinal designs should be enriched by natural experimental approaches, examining the effect of changes in the environment (e.g. by moving to a different address, or the openings or closings of fast-food outlets or physical activity facilities when staying at the same address) on weight status over time11. As trials with randomization of individuals to different environments are unfeasible, natural experiments with adequate confounder adjustment represent the highest form of evidence in this field. The few longitudinal studies on this topic yielded inconsistent results, and suffer from generalizability issues12, only assessed environmental exposure at baseline13–18, or used self-reported weight status as an outcome19. Furthermore, they typically did not adequately address confounding (e.g., they did not use using propensity scores20,21). 
Third, few studies have examined the role of the food and physical activity environment around areas other than around the residential address, such as around school and work addresses. Food and physical activity environments around secondary schools have received substantial media attention22, leading to a ban of fast-food outlets within the vicinity of schools in London23. Although studies point to the presence of an association, they were all cross-sectional in nature and conducted in the United States, where the structure of the built environment differs from Europe. Regarding exposure around the work address, a cross-sectional UK study suggested that the association between fast-food outlet density and BMI is equally strong around the residential address as around the work address24. Importantly, these exposures around the residential address home and around the work address shared little overlap25. This indicates that including both exposure around the residential address and around the work address provides a more comprehensive assessment of environmental exposure. However, the results of this UK study are based on cross-sectional data and the study sample was not a representative sample of the general popualtion. Besides exposure around the working address, assessing the food and physical activity environment around the travel routes, such as between school and home, may contribute towards a more comprehensive assessment of exposure. However, evidence on the role of exposure around the between school and home is inconsistent and comes from cross-sectional studies24,26. So, more research is needed to better understand the association between the food and physical activity environment and weight status around the school address, around the work address and along the home-school travel route. 
Fourth, potential effect modifiers in the association between the food and physical activity environment and weight status require further investigation. For example, the food and physical activity environment may be more influential in people who are genetically susceptible of developing an elevated weight status27. Investigating the modifying role of such genetic susceptibility in the association between food and physical activity environments and BMI is difficult, as it requires a linkage between environmental exposure data, genetic data, and individual health data. Such linkages are costly, computationally challenging, and rarely available worldwide. A UK Biobank study28 found that fast-food outlet exposure was only associated with BMI among individuals genetically susceptible of an elevated weight status29. However, this study was cross-sectional in nature and contained issues regarding misclassification of fast-food outlets. So, more rigorous research is needed to investigate the potentially modifying role of genetic susceptibility in the association between the food and physical activity environment and weight status. Furthermore, the food and physical activity environment may have a different influence in deprived neighbourhoods. For example, deprived neighbourhoods may be less safe, discouraging individuals make use of physical activity facilities30. Investigating to what extent the association between the food and physical activity environment and weight status differs by neighbourhood deprivation level would inform policy-makers to specifically target the food and physical activity environment in certain (deprived) neighbourhoods. Moreover, the food and physical activity environment may be more influential in certain age categories. Investigating age as an effect modifier offers a life-course perspective on this topic, and may point to ‘sensitive periods’ during which individuals are most susceptible to the environment. 
Fifth, it is unclear to what extent the association between the food environment and weight status is mediated through diet, and to what extent the association between the physical activity environment and weight status is mediated through physical activity. Although dietary intake and physical activity influence weight status31, few studies have investigated the potentially mediating role of diet and physical activity in the association between the food and physical activity environment and weights status. Such investigations may inform policies designed to reduce the potential effects of unfavourable food and physical activity environments (e.g., calorie-labelling). A European-wide study found that the association between fast-food outlet exposure and BMI was mediated through fast-food consumption32, but adopted a cross-sectional design and relied on self-reported BMI. So, more research is need to investigate the potentially mediating role of diet and physical activity in the association between the food and physical activity environment and weight status. 
Therefore, we aim firstly, to examine the association between changes in the food and physical activity environment around the residential address and the work address over time and changes in BMI in adults. Secondly, we will examine the association between changes in the food and physical activity environment around the residential address, the secondary school address, and the home-school travel route among children in the age of 8 to 18 years. 
Additionally, within these associations, we aim to investigate potential effect modifiers (i.e., genetic risk, neighbourhood deprivation, age) and changes in potential mediating factors (e.g., physical activity, diet).