In this study, we found that neighborhoods in Oslo have different obesogenic environments depending on their deprivation levels. In particular, deprived neighborhoods had greater availability of fast food restaurants and lower availability of indoor facilities compared to neighborhoods with low deprivation levels. In addition, we found in our sample of participants that children from deprived neighborhoods were more likely to have overweight/obesity than children from advantaged neighborhoods (low-deprived neighborhoods), even when accounting for individual-level sociodemographic characteristics, such as ethnicity and parental education. However, the association between neighborhood deprivation and overweight/obesity was not explained by the differences in the food and physical activity environments.
Living in deprived neighborhoods has been implied to increase the risk of unhealthy behaviors as a result of higher exposure to fast food restaurants (26, 58) and limited access to grocery stores (59–61). Our results support that high-deprived neighborhoods had more fast food restaurants than the low-deprived neighborhoods. However, we did not find significant differences in the number of grocery stores among the three neighborhood deprivation levels, which was not in line with the findings of previous studies that found greater availability of grocery stores in low-deprived neighborhoods (59–61). Variations in the types of grocery stores evaluated, neighborhood definitions, sample sizes, and the ecological study designs may explain the different results (62).
When food outlets were grouped by “healthy” and “unhealthy” food outlets, the availability of both groups was greater as the neighborhood deprivation score increased. This is partially in agreement with previous systematic reviews, indicating that deprived neighborhoods have greater availability of “unhealthy” food outlets, but generally a lower availability of “healthy” food outlets in such neighborhoods (16, 25, 28, 29). In our findings, the greater availability of “healthy” food outlets in the more deprived neighborhoods was mostly due to the higher presence of restaurants in those neighborhoods. However, we cannot assure that all restaurants across the neighborhoods were promoting the same food environment, and thus equally exposed the residents to healthy food choices. As evidenced by Saelens et al. (2007), the environment consumers’ experience within restaurants, even within the same type, varies considerably among restaurants (e.g., prices, food promotions, number of healthy food choices, etc.), and, hence, can rearrange individuals’ food choices patterns (41). Additionally, a recent study on obesogenic food environment and youth found that in socioeconomically deprived neighborhoods, full-service restaurants had greater promotion of unhealthy food options for their residents compared to restaurants in low-deprived neighborhoods (63), a previous paper had already observed the same pattern that unhealthy food options were strongly promoted in restaurants in deprived neighborhoods (64).
On the other hand, the greater availability of “unhealthy” food outlets in higher-deprived neighborhoods seen in this study was due to the greater number of fast food restaurants and convenience stores in these neighborhoods. This is consistent with studies from Canada and England showing a linear increase between neighborhood deprivation and the number of fast food outlets (26, 58), and with more convenience stores in the deprived neighborhoods found in other studies (59, 65). The implications of these characteristics of the food environment in the deprived neighborhoods, i.e., high exposure to fast food, which is not counterbalanced by higher exposure to grocery stores, are that residents from these neighborhoods can have more access to energy dense, nutrient-low, and highly processed food products.
Regarding the differences in the physical activity environment, in the current study a lower availability of indoor facilities was seen in the more deprived neighborhoods. The relation between neighborhood deprivation and the availability of recreational facilities in the neighborhoods has been demonstrated in some studies, but with contradictory findings (25, 66). In particular, some studies have outlined that higher deprived neighborhoods have fewer physical activity resources (including both indoor and outdoor facilities) than neighborhoods with lower deprivation levels (27, 67). Whereas, other studies reported no differences (68, 69), or even better access to both indoor and outdoor recreational facilities in high-deprived neighborhoods (66), or, similar to our findings, only inequalities in terms of the availability of indoor recreational facilities, with fewer opportunities for physical activity among the residents of deprived neighborhoods (70).
Conversely, we observed higher prevalence of public transportation stops in more deprived neighborhoods, contradicting previous research that found neighborhood deprivation to be linked with transport disadvantage (71). However, in our study, this observation may just reflect the urbanization plan connected to densely populated inner areas, regardless of the deprivation levels of the neighborhoods (47).
Overall, these inconsistent results may be related to the specificities of different urban designs, land use patterns, and neighborhood deprivation measurements (separate indicators versus composite scores) used in each study (72). In addition, despite the availability of physical activity resources being an important measure of the built environment, combined measures involving equally quantitative and qualitative aspects of the neighborhood physical activity environment can provide a more rigorous picture of the reality of deprivation neighborhoods contexts. Namely, neighborhood features perceived by the residents, like aesthetic appeal and safety, may be as relevant as availability, given the positive associations documented between these qualitative measures of the neighborhoods and the physical activity levels of their residents in low-deprived neighborhoods (73).
In our sample of participants, 29% of the children living in high-deprived neighborhoods had overweight/obesity, compared to only 6% in the low-deprived neighborhoods. Moreover, in this study, children living in high-deprived neighborhoods were two times more likely to have overweight/obesity than children from low-deprived neighborhoods, even when adjusting for ethnicity and parental education. This finding corroborates several other studies that have reported that childhood obesity affects unequally the more socioeconomically deprived areas, where children have a high BMI and an increased risk of obesity (13, 18, 19).
Previous evidence has suggested that residents from deprived neighborhoods tend to have a higher BMI where their neighborhoods are characterized by relative prevalence of fast food outlets and constraints on physical activity resources (17, 28, 30). In the present study, when the neighborhood built environment was compared between the two BMI groups (non-overweight/-obesity vs overweight/obesity), we only found differences in the food environment characteristics, where there was greater availability of both grocery and convenience stores in the neighborhoods of the children with overweight/obesity than in the neighborhoods of the children without overweight/obesity. Further, in this study, the built environment features studied did not seem to drive the relationship between neighborhood deprivation and children’s overweight/obesity.
This is not to say that food and physical activity environments are not important for children's development, given the increasing influence that environmental characteristics have as children age and become more independent from their families in their interactions with the built environment (72). Accordingly, maybe the children of our sample were not yet old enough to be influenced by the food and physical activity resources in their neighborhoods. In this regard, this suggests that perhaps other factors that we were unable to adjust for, such as parents‘ lifestyle and household income, could have acted as mediators between the built environment and children’s weight-status (74, 75). Longitudinal studies with repeated measurements of neighborhood socioeconomic conditions, built environment, and childhood obesity are needed to disentangle these complex causal relationships.
Nevertheless, if nothing changes in the neighborhood context of these children, growing up in more deprived neighborhoods, and thus being exposed in the long-term to a more favorable obesogenic environment, the risk of obesity incidence in early adulthood is increased (76).
In addition, the residents of deprived neighborhoods may also be deprived of their social and political influence to demand for better and protective live conditions, and to oppose for unwanted unhealthy built environments. Municipalities and decision-makers, who can influence the number and types of goods and resources allocated, in favor of these populations, are therefore essential to tailor the neighborhood built environment. For example, governmental decisions such as zoning laws that can limit the amount of fast food outlets in the high-deprived neighborhoods, along with investments to develop recreational facilities for children, involving community participation in identifying relevant barriers and facilitators that may influence their children's physical activity opportunities in the high-deprived neighborhoods.
This study has several strengths. We considered a wide range of built environment characteristics, including a variety of both food outlets and physical activity resources, in contrast to most studies (15). Additionally, the built environment variables were objectively measured using ArcGIS Pro software. Besides, we were able to capture different nuances of the children's built environment context, by including both availability and accessibility measures. For instance, the presence of one fast food restaurant in the neighborhood could reflect poor availability. However, it could still represent high proximity if this fast food restaurant was close to the participant’s residential address. Finally, although the neighborhood deprivation construct used in this study did not exhaust the domain of all socioeconomic indicators, a composite neighborhood deprivation score comprising three sociodemographic parameters was used to assess the neighborhood deprivation levels, as opposed to use a single measure representing neighborhood income or employment distributions or educational compositions. However, this study also has some limitations. Similar to many studies in the field, a cross-sectional design was used; hence, it has a limited understanding about the relationship between neighborhoods and childhood obesity, and little can be said about how children interact with their neighborhoods. Also, we did not account for additional features to assess the built environment, such as price or nutritional value of food products, within each food outlet, or alternatives to food shopping, such as home food delivery, or prices connected to gyms or other recreational facilities, or perceived neighborhood features, like aesthetic appeal and safety. These factors may be more important to consider in understanding the relationship between obesity and the built environment than simply counting food outlets or physical activity resources. Moreover, while street network buffers compared to census tracts are considered a more accurate representation of a person’s neighborhood, they must still be considered artificial neighborhoods, given they may not reflect the actual space children use, which in turn could underestimate the impact of the built environment (77). Furthermore, we relied on secondary data sources to collect the built environment features. These databases are rarely perfect, and limit our ability to ensure the rigidity of the data collection and the completeness of the data. Nevertheless, with the exception of small outdoor and indoor recreational facilities, we were able to validate the existence of the environmental features through GSV or satellite imaging, which can be considered a strength (78). Further, although some sociodemographic variables were included as covariates in the analyses, potential biases associated with neighborhood self-selection cannot be dismissed. Namely, in our analyses indicators of socioeconomic position such as household income were not accounted for. Still, even though each indicator of socioeconomic position has a unique contribution in capturing aspects of socioeconomic context, parental education has been shown to have the greatest influence on children’s health (18, 79). Furthermore, due to Covid-19 restrictions, one of the rounds of anthropometric measurements was evaluated by self-report, and although reported weight/height data are a reasonably valid alternative to measure children’s BMI (80), errors of measurement cannot be excluded. Because this was an exploratory study, and data concerning rates of childhood obesity at the neighborhood level were not included, no conclusions concerning the actual impact of neighborhood built environment on obesity can be outlined. Finally, no adjustments were made for multiple comparisons, though several multilevel regression models were performed. However, it has been argued that for large samples involving objective observations, adjustments for multiple comparisons are not always required (81).