Spatial accessibility and travel to pharmacy by type in the Detroit region.

BACKGROUND: Community pharmacies are a critical part of the health care provision system. Yet less is understood about the spatial accessibility to pharmacies and how people travel to reach these services. OBJECTIVES: This study compared spatial accessibility and actual travel to different types of pharmacies among selected neighborhoods in the Detroit region. METHODS: Three types of neighborhoods were selected and compared, including two lower income Black urban neighborhoods of high-density and four upper income White suburbs (two of low density and two of high density). Spatial accessibility was computed by pharmacy type and compared among neighborhoods using ANOVA. Pharmacy trips reported in a travel survey were geocoded and linked with community pharmacies in a list generated from ReferenceUSA business data. Destination choices were mapped and the relationship between spatial accessibility and actual distance traveled was examined using ordinary least squares regressions. RESULTS: On average, urban residents in Detroit had higher access to local independent pharmacies (0.74 miles to the nearest one) but relatively lower access to national chains (1.35 miles to the nearest one), which most residents relied on. Urban residents also tended to shop around more for services even among national chains. In fact, they bypassed nearby local independent pharmacies and traveled long distances to use farther pharmacies, primarily national chains. The average trip distance to pharmacy was 2.1 miles for urban residents, but only 1.1 miles and 1.5 miles for residents in high-density suburbs and low-density suburbs, respectively. CONCLUSION: Supposedly good spatial access considering all pharmacies together may mask excessive burden in reaching the pharmacy services needed in low-income minority urban communities, as shown in the case of Detroit. Thus, when mapping pharmacy deserts, it is important to distinguish spatial accessibility among different pharmacy types.

Explained and unexplained racial and regional inequality in obesity prevalence in the United States.

Objective: There are substantial racial and regional disparities in obesity prevalence in the United States. This study partitioned the mean Body Mass Index (BMI) and obesity prevalence rate gaps between non-Hispanic blacks and non-Hispanic whites into the portion attributable to observable obesity risk factors and the remaining portion attributable to unobservable factors at the national and the state levels in the United States (U.S.) in 2010. Design: This study used a simulated micro-population dataset combining common information from the Behavioral Risk Factor Surveillance System and the U.S. Census data to obtain a reliable, large sample representing the adult populations at the national and state levels. It then applied a reweighting decomposition method to decompose the black-white mean BMI and obesity prevalence disparities at the national and state levels into the portion attributable to the differences in distribution of observable obesity risk factors and the remaining portion unexplainable with risk factors. Results: We found that the observable differences in distribution of known obesity risk factors explain 18.5% of the mean BMI difference and 20.6% of obesity prevalence disparities between non-Hispanic blacks and non-Hispanic whites. There were substantial variations in how much the differences in distribution of known obesity risk factors can explain black-white gaps in mean BMI (-67.7% to 833.6%) and obesity prevalence (-278.5% to 340.3%) at the state level. Conclusion: The results from this study demonstrate that known obesity risk factors explain a small proportion of the racial, ethnic and between-state disparities in obesity prevalence in the United States. Future etiologic studies are required to further understand the causal factors underlying obesity and racial, ethnic and geographic disparities.

The dynamics of food shopping behavior: Exploring travel patterns in low-income Detroit neighborhoods experiencing extreme disinvestment using agent-based modeling.

Only a handful of studies have leveraged agent-based models (ABMs) to examine public health outcomes and policy interventions associated with uneven urban food environments. While providing keen insights about the role of ABMs in studying urban food environments, these studies underutilize real-world data on individual behavior in their models. This study provides a unique contribution to the ABM and food access literature by utilizing survey data to develop an empirically-rich spatially-explicit ABM of food access. This model is used to simulate and scrutinize individual travel behavior associated with accessing food in low-income neighborhoods experiencing disinvestment in Detroit (Michigan), U.S. In particular, the relationship between trip frequencies, mode of travel, store choice, and distances traveled among individuals grouped into strata based on selected sociodemographic characteristics, including household income and age, is examined. Results reveal a diversified picture of not only how income and age shape food shopping travel but also the different thresholds of tolerance for non-motorized travel to stores. Younger and poorer population subgroups have a higher propensity to utilize non-motorized travel for shopping than older and wealthier subgroups. While all groups tend to travel considerable distances outside their immediate local food environment, different sociodemographic groups maintain unique spatial patterns of grocery-shopping behavior throughout the city and the suburbs. Overall, these results challenge foundational tenets in urban planning and design, regarding the specific characteristics necessary in the built environment to facilitate accessibility to urban amenities, such as grocery stores. In neighborhoods experiencing disinvestment, sociodemographic conditions play a more important role than the built environment in shaping food accessibility and ultimately travel behavior.

Impacts of Federally Funded State Obesity Programs on Adult Obesity Prevalence in the United States, 1998-2010.

OBJECTIVES: From 2000 to 2010, the Division of Nutrition, Physical Activity, and Obesity (DNPAO) at the Centers for Disease Control and Prevention (CDC) funded 37 state health departments to address the obesity epidemic in their states through various interventions. The objective of this study was to investigate the overall impacts of CDC-DNPAO statewide intervention programs on adult obesity prevalence in the United States. METHODS: We used a set of an individual-level, interrupted time-series regression and a quasi-experimental analysis to evaluate the overall effect of CDC-DNPAO intervention programs before (1998-1999) and after (2010) their implementation by using data from CDC's Behavioral Risk Factor Surveillance System. RESULTS: States that implemented the CDC-DNPAO program had a 2.4% to 3.8% reduction in the odds of obesity during 2000-2010 compared with states without the program. The effect of the CDC-DNPAO program varied by length of program implementation. A quasi-experimental analysis found that states with longer program implementation did not necessarily have lower odds of obesity than states with shorter program implementation. CONCLUSIONS: Statewide obesity interventions can contribute to reduced odds of obesity in the United States. Future research should evaluate the CDC-DNPAO programs in relation to their goals, objectives, and other environmental obesity risk factors to inform future interventions.

Adult obesity prevalence at the county level in the United States, 2000-2010: Downscaling public health survey data using a spatial microsimulation approach.

Obesity is a growing public health concern in the United States. There is a need to monitor obesity prevalence at the local level to intervene in place-specific ways. However, national public health surveys suppress the local geographic information of respondents due to small sample sizes and the protection of confidentiality. This study therefore, uses a spatial microsimulation approach to estimate obesity prevalence rates at the county level across the United States to visualize temporal, spatial and spatio-temporal changes from 2000 to 2010 for use in the monitoring of obesity prevalence. This method iteratively replicates the demographic characteristics of public health survey respondents with census data for those areas. Following, Local Moran's I was used to identify clusters of high and low obesity prevalence. The findings showed that obesity prevalence rose dramatically over the last decade with substantial variation across counties and states. Counties in Southern states, especially along the Mississippi River and Appalachian Mountains and counties containing or in proximity to Native American reservation sites showed elevated obesity prevalence rates across the decade. Counties in Midwestern states had higher obesity prevalence rates compared to counties in Western and Northeastern states. This study demonstrated the use of spatial microsimulation modeling as an alternative method to obtain reliable obesity prevalence rates at the local-level using existing health survey and census data.

Going outside the neighborhood: the shopping patterns and adaptations of disadvantaged consumers living in the lower eastside neighborhoods of Detroit, Michigan.

This research employs household survey data and Geographic Information Systems (GIS) to explore the core assumption underlying much of the food desert discourse that socially and economically disadvantaged residents shop in their immediate neighborhood food environment. Findings indicate that disadvantaged consumers living on the lower eastside of Detroit, Michigan bypass their neighborhood food environments, which are disproportionately composed of convenience and party stores, to shop at independent, discount and regional supermarkets located in other parts of the city and in the suburbs. These trends hold despite various economic and physical constraints to their mobility. These findings complicate past assumptions that socially and economically disadvantaged residents living in a food desert shop within their neighborhood environment.