Neighbourhood food‐related physical characteristics may influence food choices, and hence obesity risk. Yet, it can be argued that higher SES individuals are more likely to own cars and are hence less dependent on neighbourhood stores for food, whereas the reverse is true for individuals with lower SES. (According to the 1990 US census, nearly 30% of adults from poor households did not own a car compared with 10% of the overall population.)35
In our study, we observed that proximity to various types of food stores was associated with neighbourhood SES. Residents of low socioeconomic neighbourhoods lived closest to small grocery stores and convenience stores, and residents of middle socioeconomic neighbourhoods lived closest to supermarkets and fast food restaurants, as well as ethnic markets, compared with residents of other neighbourhoods. Others have reported that there are relatively more fast food restaurants, small grocery stores and convenience stores in poor neighbourhoods.16,18,36,37
In our study, differences in store density by neighbourhood SES were significant only for ethnic markets—the density of ethnic markets was highest in low socioeconomic neighbourhoods. As we also noted that residents of middle socioeconomic neighbourhoods lived closest to ethnic markets, we speculate that ethnic markets may be located in areas straddling low and middle socioeconomic neighbourhoods, near to where ethnic minority populations live.
In examining the contributions of neighbourhood social characteristics to BMI, we found, as reported by others,5,6,7,8,9
higher BMI among residents of low socioeconomic neighbourhoods after adjusting for individual‐level factors. Since individual‐level behavioural factors may be intervening rather than confounding variables, the magnitude of the neighbourhood socioeconomic effect may actually be greater than that reported in this study.
Our findings regarding associations between neighbourhood physical characteristics and BMI varied depending on the measure (proximity or density) used. We hypothesised that living close to ethnic markets, small grocery stores and convenience stores would be associated with higher BMI. We found such an association only with ethnic markets, and only among women. Based on work by others,12,14,15
we had further hypothesised that living close to supermarkets would be associated with lower BMI. Instead, we found the opposite. Given the wide availability of heavily marketed high‐fat and high‐sugar processed foods,38
it could be inferred that living close to retail food stores of any kind, including supermarkets, implies greater exposure to these foods, and that nutrition knowledge, while not sufficient to initiate behavioural change, is important for helping individuals make healthy food choices. Indeed, we observed an association between increased nutrition knowledge and lower BMI. In our examination of the relationships between store density and BMI, we found that only density of small grocery stores was associated with BMI in women. We conclude that living in neighbourhoods with a higher density of small grocery stores is associated with increased overweight risk in women.
The gender differences in the associations between neighbourhood physical characteristics and BMI parallel the observations of researchers in the UK22
; several explanations are plausible. Women may depend more on neighbourhood goods, services and resources than men do, and hence be exposed to the effects of the neighbourhood to a greater extent.22
Also, women may perceive the neighbourhood environment differently from men39
; perceptions of neighbourhood environment have been observed to be associated with health.40
This study has several limitations. First, owing to the historical nature of the food store data collected, we were unable to verify that the food stores were accurately classified—for example, ethnic stores may include stores that sell mostly convenience foods and those that sell fruits and vegetables. Second, over the course of the SHDPP study, it is likely that the mix of foods offered by the different types of food stores changed. Between 1972 and 1992, processed food sales increased from $242 to $342 billion.41
To address this limitation, survey year was included as a term in the statistical models. Third, despite the large sample size, our findings relate to small to mid‐sized cities in agricultural regions in ethnically diverse California. In less ethnically diverse regions, ethnic markets may play a lesser role. In large cities, where different socioeconomic groups may live closer to each other, factors other than proximity to various types of retail food stores may influence food purchasing and consumption patterns. Fourth, the cross‐sectional nature of our data precludes a conclusion regarding causal relationships. Further, other factors that may influence where people shop for food—such as transportation—need to be examined.42
Finally, several multilevel regression models were analysed, but adjustment for multiple comparisons was not made. Rothman43
has argued that adjustments for multiple comparisons are not always necessary for large bodies of data involving actual observations.
To our knowledge, this is one of the first studies in the US to simultaneously document the contributions of both social and physical aspects of the neighbourhood environment to obesity risk. Although these two aspects of the neighbourhood environment are inter‐related, they seem to show independent associations with BMI.
- In the US, local efforts are being made to develop environment‐based programmes that aim to increase access to fresh fruits and vegetables, especially in low‐income neighbourhoods.
- Our findings suggest that changing behaviour may involve more than just removing environmental barriers to behavioural change. While education‐based intervention efforts have mostly proven ineffective in changing food behaviour,28,44 education may continue to play an important role in the development of environment‐based interventions.
- Our findings also suggest that women may be more sensitive to the effects of the neighbourhood environment; it may be worthwhile to explore the effectiveness of interventions that incorporate environmental approaches and educational strategies tailored to women, who often influence food consumption of the family.
What this paper adds
- Residents of low socioeconomic neighbourhoods have increased obesity risk.
- In the US, there is a higher density of small grocery and convenience stores in low socioeconomic neighbourhoods. As these stores seldom carry fresh and healthy foods, the assumption is that living close to these stores increases obesity risk, and, conversely, living close to supermarkets, which invariably carry fresh produce and healthy foods, lowers obesity risk.
- Our findings suggest that living in neighbourhoods with a high density of small grocery stores is associated with increased BMI. However, living close to supermarkets is not associated with a lower risk of obesity.
- We conclude that living in an environment where healthy food is not readily available is associated with increased obesity risk. The mechanisms by which the food‐related characteristics of the neighbourhood environment influence obesity risk should be further examined and elucidated.