Health care utilization among women of reproductive age living in public housing: Associations across six public housing sites in San Francisco.

Housing is a key social determinant of health and health care utilization. Although stigmatized due to poor quality, public housing may provide stability and affordability needed for individuals to engage in health care utilization behaviors. For low-income women of reproductive age (15-44 y), this has implications for long-term reproductive health trajectories. In a sample of 5,075 women, we used electronic health records (EHR) data from 2006 to 2011 to assess outpatient and emergency department (ED) visits across six public housing sites in San Francisco, CA. Non-publicly housed counterparts were selected from census tracts surrounding public housing sites. Multivariable regression models adjusted for age and insurance status estimated incidence rate ratios (IRR) for outpatient visits (count) and odds ratios (OR) for ED visit (any/none). We obtained race/ethnicity-specific associations overall and by public housing site. Analyses were completed in December 2020. Public housing was consistently associated with health care utilization among the combined Asian, Alaskan Native/Native American, Native Hawaiian/Pacific Islander, and Other (AANHPI/Other) group. Public housing residents had fewer outpatient visits (IRR: 0.86; 95% Confidence Interval [CI]: 0.81, 0.93) and higher odds of an ED visit (OR: 1.81; 95% CI: 1.32, 2.48). Black women had higher odds of an ED visits (OR: 1.32; 95% CI: 1.07, 1.63), but this was driven by one public housing site (site-specific OR: 2.34; 95% CI: 1.12, 4.88). Variations by race/ethnicity and public housing site are integral to understanding patterns of health care utilization among women of reproductive age to potentially improve women's long-term health trajectories.

Neighborhood Child Opportunity and Individual-Level Pediatric Acute Care Use and Diagnoses.

: media-1vid110.1542/5751513300001PEDS-VA_2017-2309Video Abstract OBJECTIVES: Although health care providers and systems are increasingly interested in patients' nonmedical needs as a means to improve health, little is known about neighborhood conditions that contribute to child health problems. We sought to determine if a novel, publicly available measure of neighborhood context, the Child Opportunity Index, was associated with pediatric acute care visit frequency and diagnoses. METHODS: This cross-sectional study included San Francisco residents <18 years of age with an emergency department and/or urgent care visit to any of 3 medical systems (N = 47 175) between 2007 and 2011. Hot-spot analysis was used to compare the spatial distribution of neighborhood child opportunity and income. Generalized estimating equation logistic regression models were used to examine independent associations between neighborhood child opportunity and frequent acute care use (≥4 visits per year) and diagnosis group after adjusting for neighborhood income and patient age, sex, race and/or ethnicity, payer, and health system. RESULTS: Neighborhood child opportunity and income had distinct spatial distributions, and we identified different clusters of high- and low-risk neighborhoods. Children living in the lowest opportunity neighborhoods had significantly greater odds of ≥4 acute care visits per year (odds ratio 1.33; 95% confidence interval 1.03-1.73) compared with those in the highest opportunity neighborhoods. Neighborhood child opportunity was negatively associated with visits for respiratory conditions, asthma, assault, and ambulatory care-sensitive conditions but positively associated with injury-related visits. CONCLUSIONS: The Child Opportunity Index could be an effective tool for identifying neighborhood factors beyond income related to child health.

San Francisco children living in redeveloped public housing used acute services less than children in older public housing.

Understanding the links between housing and health is increasingly important. Poor housing quality is a predictor of poor health and developmental problems in low-income children. We examined associations between public housing type and recurrent pediatric emergency and urgent care hospital visits. Children ages 0-18 with public insurance who sought emergency care from any of three large medical systems in San Francisco were categorized by whether they lived in public housing redeveloped through the federal HOPE VI program, nonredeveloped public housing, or nonpublic housing in a census tract that also contained public housing. After we adjusted for potential confounding characteristics, we found that children living in nonredeveloped public housing were 39 percent more likely to have one or more repeat visits within one year for acute health care services unrelated to the initial visit, compared to children who lived in redeveloped HOPE VI housing. We observed no differences in repeat visits between children in redeveloped HOPE VI housing and those in nonpublic housing. These findings support the continued redevelopment of public housing as a means of both improving the health of vulnerable high-risk children from low-income neighborhoods and reducing health care costs.

Spatial pattern of body mass index among adults in the diabetes study of Northern California (DISTANCE).

BACKGROUND: The role that environmental factors, such as neighborhood socioeconomics, food, and physical environment, play in the risk of obesity and chronic diseases is not well quantified. Understanding how spatial distribution of disease risk factors overlap with that of environmental (contextual) characteristics may inform health interventions and policies aimed at reducing the environment risk factors. We evaluated the extent to which spatial clustering of extreme body mass index (BMI) values among a large sample of adults with diabetes was explained by individual characteristics and contextual factors. METHODS: We quantified spatial clustering of BMI among 15,854 adults with diabetes from the Diabetes Study of Northern California (DISTANCE) cohort using the Global and Local Moran's I spatial statistic. As a null model, we assessed the amount of clustering when BMI values were randomly assigned. To evaluate predictors of spatial clustering, we estimated two linear models to estimate BMI residuals. First we included individual factors (demographic and socioeconomic characteristics). Then we added contextual factors (neighborhood deprivation, food environment) that may be associated with BMI. We assessed the amount of clustering that remained using BMI residuals. RESULTS: Global Moran's I indicated significant clustering of extreme BMI values; however, after accounting for individual socioeconomic and demographic characteristics, there was no longer significant clustering. Twelve percent of the sample clustered in extreme high or low BMI clusters, whereas, only 2.67% of the sample was clustered when BMI values were randomly assigned. After accounting for individual characteristics, we found clustering of 3.8% while accounting for neighborhood characteristics resulted in 6.0% clustering of BMI. After additional adjustment of neighborhood characteristics, clustering was reduced to 3.4%, effectively accounting for spatial clustering of BMI. CONCLUSIONS: We found substantial clustering of extreme high and low BMI values in Northern California among adults with diabetes. Individual characteristics explained somewhat more of clustering of the BMI values than did neighborhood characteristics. These findings, although cross-sectional, may suggest that selection into neighborhoods as the primary explanation of why individuals with extreme BMI values live close to one another. Further studies are needed to assess causes of extreme BMI clustering, and to identify any community level role to influence behavior change.

Obesity and the food environment: income and ethnicity differences among people with diabetes: the Diabetes Study of Northern California (DISTANCE).

OBJECTIVE: It is unknown whether any association between neighborhood food environment and obesity varies according to individual income and/or race/ethnicity. The objectives of this study were to test whether there was an association between food environments and obesity among adults with diabetes and whether this relationship differed according to individual income or race/ethnicity. RESEARCH DESIGN AND METHODS: Subjects (n = 16,057) were participants in the Diabetes Study of Northern California survey. Kernel density estimation was used to create a food environment score for each individual's residence address that reflected the mix of healthful and unhealthful food vendors nearby. Logistic regression models estimated the association between the modeled food environment and obesity, controlling for confounders, and testing for interactions between food environment and race/ethnicity and income. RESULTS: The authors found that more healthful food environments were associated with lower obesity in the highest income groups (incomes 301-600% and >600% of U.S. poverty line) among whites, Latinos, and Asians. The association was negative, but smaller and not statistically significant, among high-income blacks. On the contrary, a more healthful food environment was associated with higher obesity among participants in the lowest-income group (<100% poverty threshold), which was statistically significant for black participants in this income category. CONCLUSIONS: These findings suggest that the availability of healthful food environments may have different health implications when financial resources are severely constrained.

Small food stores and availability of nutritious foods: a comparison of database and in-store measures, Northern California, 2009.

INTRODUCTION: Small food stores are prevalent in urban neighborhoods, but the availability of nutritious food at such stores is not well known. The objective of this study was to determine whether data from 3 sources would yield a single, homogenous, healthful food store category that can be used to accurately characterize community nutrition environments for public health research. METHODS: We conducted in-store surveys in 2009 on store type and the availability of nutritious food in a sample of nonchain food stores (n = 102) in 6 predominantly urban counties in Northern California (Alameda, Contra Costa, Marin, Sacramento, San Francisco, and Santa Clara). We compared survey results with commercial database information and neighborhood sociodemographic data by using independent sample t tests and classification and regression trees. RESULTS: Sampled small food stores yielded a heterogeneous group of stores in terms of store type and nutritious food options. Most stores were identified as convenience (54%) or specialty stores (22%); others were small grocery stores (19%) and large grocery stores (5%). Convenience and specialty stores were smaller and carried fewer nutritious and fresh food items. The availability of nutritious food and produce was better in stores in neighborhoods that had a higher percentage of white residents and a lower population density but did not differ significantly by neighborhood income. CONCLUSION: Commercial databases alone may not adequately categorize small food stores and the availability of nutritious foods. Alternative measures are needed to more accurately inform research and policies that seek to address disparities in diet-related health conditions.