Obesity prevention is a global public health priority as a result of the worldwide increase in obesity prevalence 1 and its associated chronic diseases 2 . Although genetic factors may underlie the propensity of individuals to become obese 3 , the pace at which obesity prevalence has grown at population level during recent decades points to social and environmental causes 4 5 . An individual’s body mass index (BMI) is mainly determined by energy intake (eating) and energy expenditure (physical activity/sedentary behaviour). These energy balance related behaviours (EBRBs) are influenced by a range of determinants 6 . One important category of determinants is the opportunities for calorie intake and calorie expenditure or a lack thereof in the physical environment. For example, dietary behaviour may be influenced by access to different foods through various types of outlets and services. Similarly, physical activity levels may be influenced by access to recreational or sports facilities, green spaces or parks, as well as transport infrastructure and land use. Certain environments may be more ‘obesogenic’ than others, such that they are more likely to promote weight gain and obesity in individuals or populations 5 , but it remains a challenge to identify the physical environmental factors with the greatest impacts on (the development of) overweight and obesity.

Following a steady increase in studies relating characteristics of the physical environment to overweight or obesity in the last decade, a number of reviews was published between 2005 and 2012 7 8 9 10 11 12 , showing mixed results. Among a large range of factors that have been examined, only two environmental correlates appeared to be consistently associated with weight status: indicators of urban sprawl (often based on population density, and positively associated with obesity) and measures of land use mix (negatively associated with obesity) 12 13 . However, there are numerous potential correlates of obesity from the physical environment and it is plausible that many other environmental factors such as access to recreation areas, proximity to fast food outlets or the presence of walking and cycling infrastructure might influence weight status through their links to food and physical activity behavior 14 15 16 17 . It may be that the heterogeneity in methods and measures used, or differences in contexts or location, has led to this lack of consistent results.

A recent review of reviews identified a number of gaps and areas for improvement that could explain some of the inconsistencies in the findings about obesogenic environments 12 . The authors evaluated the quality of previous literature reviews on built environment, physical activity and obesity based on: 1) the age and other demographic characteristics of the population, 2) the time frame for the literature search, 3) the total number of articles included, 4) data sources, 5) whether the methodological quality of the primary studies was assessed, 6) whether the measurement mode of the characteristics of the physical environment was reported, 7) whether the outcome was defined, and 8) whether the measurement mode of the outcome was reported. The methodological quality of the primary studies had been assessed in very few of the reviews identified 12 . Although quality assessment tools are rarely used in the evaluation of observational studies 18 , assessing the methodological quality of any included studies is an important element of systematic literature reviews.

In addition, previous reviews have generally not distinguished between objective and perceived measures of the environment. Aspects of the physical environment are considered to be measured objectively when assessed through street audits, virtual audits (using remote imaging data) or on the basis of Geographic Information Systems 19 20 . The agreement between these objectively measured aspects of physical environments and perceptions of these environments (as measured with interviews or questionnaires) is generally considered to be moderate or low 21 22 .

Consequently, we aim to provide an updated review of the literature on physical environmental correlates of adult weight status. We gave a detailed overview of the characteristics of the primary studies and assessed the methodological quality of the included articles. This quality assessment allowed comparison of results of studies that are methodologically strong with those that are methodologically weaker. On the basis that environments are likely to be very different in high income countries from those in middle or low income countries, in this review we have focused on studies that were conducted in high income countries. In addition, we stratified the included studies by mode of measurement and continent of origin.

Original studies that examined associations between physical environmental characteristics and adult weight status were reviewed. The physical environment was defined as all built environmental and transport related factors 5 . A literature search, using five electronic databases (PubMed, EMBASE, Web of Science, Cochrane Library and PsychInfo), was conducted in May 2013. Studies relating a physical environmental factor to BMI, overweight or obesity in adults were considered if published between January 1995 and May 2013 in Dutch, English, French or German language. A full description of search terms and search strategy is provided in Additional file 1. Articles were included if weight status in adults was one of the main outcomes. Furthermore, we included articles that focused on macro environmental correlates (i.e. environmental factors measured at the neighbourhood, province or national level) of weight status. Articles of studies were excluded if they:

● focused primarily on socioeconomic characteristics or the social environment of a geographic area

● assessed a physical environmental factor only as a potential confounder

● had a very specific target population that would lead to non-generalizable results (e.g. senior citizens, pregnant women, particular ethnic groups in specific locations, etc.)

● were conducted in low or middle income countries or regions

● did not present original research (e.g. reviews, case reports, editorials, commentaries, discussions or letters)

After duplicates were removed, 5,642 articles were screened on title and abstract by the first author. Subsequently, a random sample of 500 titles and abstracts was also screened by the second author; 212 full articles were read by the first and second author. Of these articles, 92 were included in the review (see Flow chart in Additional file 3). Characteristics of the studies are shown on Table 1.

† CS = cross-sectional, LG = longitudinal.

‡ x = association was statistically significant in this direction.

¥ Measures of the Physical Environment (PE): O = objective, P = perceived. Measures of weight status: M = objectively measured, S = self-reported.

Ω PA = physical activity, nbh = neighbourhood.

§ nbh = neighbourhood, km = kilometer, m = meter, LSOA/MSOA = lower/middle statistical output area, ZCTA = Zip Code Tabulation Area.

A large majority of studies (74) was conducted in North America (USA: 66, Canada: 8), 12 were conducted in Europe (half in the UK) and six were conducted in Australasia. Half the studies (45) were published from 2010 onwards, with seven in 2013. Before 2010, 47 studies were published. Most studies (75) used exclusively objective measures of the physical environment, while 17 studies used perceived measures to link physical environmental characteristics to weight status. Of these 17 studies, nine studies examined both the objective and the perceived environment.

There was great heterogeneity across studies in the use and definition of physical environmental factors. Fifty-three studies investigated the association between an environmental factor that was presumed to affect obesity through physical activity (such as parks or sports facilities), thirty-six studies assessed the association of the food related environment (such as the density of fast-food restaurants) and six studies assessed the transport-related environment (such as proximity to public transport amenities). Thirty-one studies assessed urban form characteristics such as street connectivity, urban sprawl and land use mix, and twenty studies investigated other types of environmental factors such as graffiti or crime. Fifteen studies assessed associations between both food related and physical activity related environments and obesity. It goes beyond the scope of this review to present all the different metrics used, but an overview of the different metrics and associated operationalization of physical environmental factors used in these kind of studies has been provided elsewhere 9 . As an example of the heterogeneity between studies, while fifty-three studies investigated a physical activity related environmental factor, none of the seven 79 89 104 111 115 116 119 studies examining green space used the same definition of this metric. Tilt et al. calculated greenness with NDVI (normalized difference vegetation index; the amount of photosynthetically active light as measured with infrared light) 89 , while West et al. defined green space as all publicly owned and operated green spaces 79 . Toftager et al. included beaches, seas, forests and lakes but no agricultural fields 118 , while Cummins et al. included agricultural land but excluded domestic gardens 116 . The remaining three studies also used different definitions of green space.

There was no consistent pattern of associations between physical environmental factors and weight status. For example, nineteen studies assessed the association between walkability (often a combination of three factors: intersection density, land use mix and population density) and overweight or obesity – one study from Europe and 18 studies from North America. The European study did not find an association between walkability and obesity, although there was an association between walkability and several domains of physical activity 109 . Of the other 18 studies, eight found associations that were in line with the hypothesis (i.e. higher walkable areas are associated with lower BMI or overweight prevalence). Three studies did not find statistically significant associations and five studies found inconsistent results. Inconsistencies arose from results that indicated that associations were only present in men versus women, only present in disadvantaged areas versus higher SES neighbourhoods, or only present for BMI versus overweight/obesity as outcome.

Only eight studies used longitudinal data. The follow-up time ranged from four to 25 years. Sixty-six studies defined the geographical scale of study (‘neighbourhood’ or ‘environment’) based on administrative boundaries (for example: county or census tract). The remaining studies used ‘buffers’ (network or Euclidian) with varying radius, with the exception of one study that used limits of activity-space. Of the 93 included studies, 36 presented results that broadly corresponded with the hypothesis in the study (i.e. the results were according to what was expected). Fourteen studies reported that they did not find statistically significant results and 5 studies reported unexpected results, i.e. opposite to the hypothesised direction. Another 38 studies reported on a mixture of expected, unexpected and/or non-significant results.

We systematically reviewed the published scientific literature on associations between physical environmental factors and weight status in adults. The results showed a great heterogeneity in findings. In line with previous results 4 7 9 10 12 , two environmental variables appeared to be more consistently associated with overweight or obesity than other factors: ‘urban sprawl’ and ‘land use mix’. Of note, these two factors have been widely studied in North America, but not in Europe or Australasia. For other environmental variables, there was great variation in the metrics used, the number of features studied and the different contexts of the studies. The current evidence base therefore provides inconsistent results about associations between the physical environment and overweight or obesity in adults.

Previous literature reviews have generally shown a positive association between the physical (or built) environment and obesity. For example, Booth et al. concluded that there was ‘strong preliminary evidence of a relationship between built environment features and the prevalence of obesity’. However, the authors only included 9 papers 4 . Papas et al. included 20 studies, and stated that ‘17 found a statistically significant relation between some aspect of the built environment and risk of obesity’ 7 . Feng et al. included 63 studies, and were cautious in drawing their conclusions: ‘While there is strong intuitive appeal to the notion that the built environment must be contributing to the obesity epidemic, existing scientific evidence does not provide consistent or convincing support for this hypothesis’ 9 .

We hypothesized that this lack of apparent inconsistent results was due to heterogeneity in the measures and methods used in primary studies. We therefore conducted stratified analyses, grouping homogeneous studies together in order to identify any patterns that might emerge if we reduced heterogeneity. Although some authors stated that there was limited generalizability of North American results to European settings 7 116 , findings remained heterogeneous. As there were not enough studies taking into account similar physical environmental factors between North America, Australia and Europe, it was not possible to make intercontinental comparisons. It may well be that in developed societies, the differences between physical environments within one country or city are not large enough to create measurable differences in impact on outcomes.

Stratification by mode of measurement did not reveal consistent differences between studies that used objective measures versus perceptions of the environment. Although a number of tools to measure perceptions of the environment are available (for example: NEWS 120 , ALPHA 121 , NWS 122 , PANES 123 ), many authors used a self-developed instrument, making it difficult to compare results between studies. Comparison of studies that used both objective measures and perceptions of the environment was hampered by to the fact that different dimensions are assessed with these measurement modes. While researchers often objectively assessed distance to a specific facility, they tended to ask for general perceptions of distance: for example ‘is this facility present in your neighbourhood’ instead of ‘do you think this facility is present within 2.5 kilometres. It was noteworthy that no studies reporting on perceptions of the environment found associations that were contrary to the author’s prior hypotheses. This might indicate that unexpected associations were not found, that unexpected associations were not reported (or published), or that prior hypotheses were not tightly defined.

Taking into account the methodological quality of the primary studies did not lead to different results from previous reviews. This may, however, be a function of the approach taken by the tool: it is possible that the determining factor is not the quality of the study, but rather the conceptual model it is based on. As Ding and Gebel 12 describe, we should look for more complex conceptual and statistical models, taking into account innovative analyses and distinguishing between objective and subjective measures of the environment. A relatively simple quality assessment may not be capable of discerning the factors that differentiate these more sophisticated approaches.

Although there is a general consensus that the physical environment has an important influence on individuals’ weight status (in environments where there is no food, one cannot eat; in environments where there are no cars, public transport or machines, one cannot avoid being more physically active for transport, daily activities or work), a large body of research has failed robustly to identify direct causal pathways between the physical environment and weight status. We found no evidence that continent, mode of measurement of the physical environmental correlates, or the methodological quality of primary studies affected the consistency of the results. There may, however, be a number of additional explanations for this lack of consistent associations.

An extra set of quality criteria – specific for studies relating environmental factors to health or weight status – could therefore be defined. This could include taking into account interactions of objective measures and perceptions, the effect of mediators and moderators, and the complexity of conceptual models. Crucial mediators obviously include energy balance related behaviours (EBRBs) such as dietary habits and levels of physical activity, and future studies would benefit from including these kinds of intermediate outcomes. While physical activity mediators have been examined in some studies 36 45 117 118 , only two of the reviewed studies took into account food related mediators 86 113 . Furthermore, different environmental variables may moderate each other’s influences or may be moderated by individual level determinants. For example, people with high self- efficacy for physical activity or who perceive strong social support or social pressure to be physical active, may be less influenced by physical environments that do not support physical activity 124 than those with lower levels of such factors. A number of studies that have recently explored mediation and moderation between individual level and family and neighbourhood environmental level determinants have been conducted recently, and indeed suggest such relationships in their associations with EBRB and weight status (i.e. 125 . It may also be necessary to more critically assess the methods used for assessing objective and subjective measures of the environment. Even objective measures are only able to capture part of the ‘true’ physical environment, and perceptions of the environment may be heavily influenced by demographic or lifestyle factors.

Then, it may be that the areas in which the included studies were conducted do not provide adequate variety in exposure to result in measurable differences in outcomes. Indeed, many studies were conducted in only a single city or region. It may be valuable to assess physical environmental factors in a wider region (for example; the approach taken by the SPOTLIGHT project 126 ). Additionally, the use of administrative units may be ill-suited to examine environmental effects on health. The impact of exposure to environmental variables in a neighbourhood, area or place may differ between individuals 127 128 , so previous studies might have misclassified relevant study areas. Furthermore, it would advance the field if more emphasis were placed on the difference between causation and correlation. Longitudinal observational studies and natural experiments have the advantage of allowing for temporal associations, while accounting for residential self-selection (endogeneity) 73 may also be possible in cross-sectional study designs.

Future researchers should consider the complexity of the relations with individual weight status, as simplistic interventions aimed at limited aspects of the physical environment may not provide the desired changes in obesity-related behaviours, let alone outcomes such as weight status. There is, for example, the potential for compensatory behaviours: more active people might consume more food, or people who use active transport may reduce physical activity in other domains of their lives. It needs to be understood which health-related activities people conduct where, when, for how long, with whom and so on, and also to include thorough appraisal of the different tools that measure perceptions of the environment in terms of validity, reliability and applicability.

We systematically assessed the methodological quality of the included studies and took this quality into account in the review and interpretation of the evidence. The results of the present review remain in line with previous literature reviews 4 7 9 12 , indicating that this additional step did not lead to different conclusions.

This systematic review provides an updated overview of the studies examining associations between the physical environment and weight status. We add to the existing literature by stratifying articles by continent and mode of measurement. The fact that this extensive review showed minimal evidence for an association between characteristics of the built environment and weight status indicates that we still do not fully understand the complex relations involved.

Although land use mix and urban sprawl were more consistently associated with overweight or obesity than other physical environmental factors, the evidence remains weak and the nature of associations between the physical environment and weight status needs further study.

BMI: Body mass index; EBRB: Energy balance related behaviour.

The authors declare that they have no competing interest.

JDM carried out the literature search, performed the quality assessment of included articles and drafted the manuscript. HR and JL helped draft the manuscript. KG performed the quality assessment as second reviewer. All authors commented on and approved the final manuscript.