Mapping the results of local statistics

The application of geographically weighted regression (GWR) – a local spatial statistical technique used to test for spatial nonstationarity – has grown rapidly in the social, health and demographic sciences. GWR is a useful exploratory analytical tool that generates a set of location-specific parameter estimates which can be mapped and analysed to provide information on spatial nonstationarity in relationships between predictors and the outcome variable. A major challenge to GWR users, however, is how best to map these parameter estimates. This paper introduces a simple mapping technique that combines local parameter estimates and local t-values on one map. The resultant map can facilitate the exploration and interpretation of nonstationarity.geographically weighted regression, local statistics, mapping, nonstationarity

Income Inequality and Opioid Prescribing Rates: Exploring Rural/Urban Differences in Pathways via Residential Stability and Social Isolation

While opioid prescribing rates have drawn researchers’ attention, little is known about the mechanisms through which income inequality affects opioid prescribing rates and even less focuses on whether there is a rural/urban difference in mediating pathways. Applying mediation analysis techniques to a unique ZIP code–level dataset from several sources maintained by the Centers for Medicare and Medicaid Services, we explicitly examine two mechanisms through residential stability and social isolation by rural/urban status and find that (1) income inequality is not directly related to opioid prescribing rates, but it exerts its influence on opioid prescribing via poor residential stability and elevated social isolation; (2) social isolation accounts for two-thirds of the mediating effect of income inequality on opioid prescribing rates among urban ZIP codes, but the proportion halves among rural ZIP codes; (3) residential stability plays a larger role in understanding how income inequality matters in rural than in urban ZIP codes; and (4) beneficiary characteristics matter only in urban ZIP codes. These findings offer nuanced insight into how income inequality affects opioid prescribing rates and suggests that the determinants of opioid prescribing rates vary by rural/urban status. Future research may benefit from identifying place-specific factors for opioid prescribing rates

Spatial Non‑stationarity in Opioid Prescribing Rates: Evidence from Older Medicare Part D Beneficiaries

Previous research that examined spatial patterns of opioid prescribing rates and factors associated with them has mainly relied on a global modeling perspective, overlooking the potential spatial non-stationarity embedded in these associations. In this study, we investigate whether there are spatially non-stationary associations between opioid prescribing rates and key characteristics of older Medicare Part D beneficiaries and their prescribers using several data sources from the Centers for Medicare and Medicaid Services. All measures are aggregated to the ZIP code level, and a total sample size of 18,126 ZIP codes is included in the analyses. Our descriptive results from geographically weighted regression and the Monte Carlo significance test suggest that most of the associations between the characteristics of beneficiaries and prescribers and opioid prescribing rates are spatially non-stationary. Our findings not only challenge the conventional analytic approach by highlighting the importance of a local modeling perspective in opioid prescribing research but also offer nuanced insight into how opioid prescribing rates are related to possible determinants across space

Social Isolation, Residential Stability, and Opioid Use Disorder among Older Medicare Beneficiaries: Metropolitan and Non-Metropolitan County Comparison

Research has shown that the prevalence of opioid use disorder (OUD) may rise substantially as society ages, but this issue receives the least attention in the literature. To address this gap, this study utilizes county-level data from multiple data sources (1) to investigate whether social isolation is associated with OUD prevalence among older Medicare beneficiaries, (2) to examine whether and how residential stability moderates the association between social isolation and OUD prevalence in US counties, and (3) to determine if there are any differences in these associations between metropolitan and nonmetropolitan counties. The results show that social isolation is a significant factor for county-level OUD prevalence, regardless of metropolitan status. In addition, counties with high residential stability have low prevalence of OUD among older adults and this association is stronger in metropolitan than in nonmetropolitan counties. Nonetheless, high levels of residential stability reinforce the positive relationship between social isolation and OUD prevalence. As a result, when developing policies and interventions aimed at reducing OUD among older adults, place of residence must be taken into account

Rural/Urban Differences in the Predictors of Opioid Prescribing Rates among Medicare Part D Beneficiaries 65 Years of Age and Older

Purpose: While research has been done comparing rural/urban differences in opioid prescribing to the disabled Medicare Part D population, research on opioid prescribing among the aged Medicare Part D population is lacking. This study aims to fill this gap by exploring the predictors of opioid prescribing to aged Medicare Part D beneficiaries and investigating whether these predictors vary across rural and urban areas. Methods: This is an analysis of ZIP Codes in the continental United States (18,126 ZIP Codes) utilizing 2017 data from Centers for Medicare & Medicaid Services. The analytic approach includes aspatial descriptive analysis, exploratory spatial analysis with geographically weighted regression, and explanatory analysis with spatial error regime modeling. Findings: Both beneficiary and prescriber characteristics play an important role in determining opioid prescribing rates in urban ZIP Codes, but most of them fail to explain the opioid prescribing rates in rural ZIP Codes. Conclusion: We identify potential spatial nonstationarity in opioid prescribing rates, indicating the complex nature of opioid-related issues. This means that the same stimulus may not lead to the same change in opioid prescribing rates because the change may be place specific. By understanding the rural/urban differences in the predictors of opioid prescribing, place-specific policies can be developed that can guide more informed opioid prescribing practices and necessary interventions

Face Masking Violations, Policing, and COVID-19 Death Rates: A Spatial Analysis in New York City ZIP Codes

The use of face masks during a pandemic and compliance with state and local mandates has been a divisive issue in the United States. We document variation in face masking violation rates involving police enforcement in New York City and examine the association between police-enforced face masking violations and COVID-19-related death rates. We assemble a Zone Improvement Plan (ZIP) code–level data set from the New York City Open Data, Department of Health, and the American Community Survey (2014–2018). We use maps to demonstrate the spatial patterning of police-enforced face masking violation rates and COVID-19-related death rates. Using a Bayesian spatial analysis approach to model police-enforced face masking violations, we find considerable variation in police-enforced face masking violation rates and COVID-19-related death rates across New York City and similarities in their spatial distribution, with higher rates for both measures found in Brooklyn and the Bronx. The positive association between police-enforced face masking violation rates and COVID-19-related death rates holds after including other covariates. The percentage of non-Hispanic Blacks, Hispanics, and households with limited English proficiency are positively associated with police-enforced face masking violations. This study extends the COVID-19 literature by reporting more aggressive enforcement of face masking rules in minority and limited-English-proficiency communities

Unemployment and Opioid-Related Mortality Rates in U.S. Counties: Investigating Social Capital and Social Isolation–Smoking Pathways

We examine two mechanisms—social capital and sociobehavior—potentially linking unemployment rates to opioid-related mortality and investigate whether the mechanisms differ geographically by the pace of the opioid crisis. Applying path analysis techniques to 2015–2017 opioid-related mortality in U.S. counties (N = 2,648), we find that (1) high unemployment rates are not directly associated with opioid-related mortality rates; (2) high unemployment rates are negatively associated with social capital, and low social capital contributes to high opioid-related mortality; (3) high unemployment rates increase social isolation and the prevalence of smoking, which is positively related to opioid-related mortality; and (4) the pathways are stronger among counties in the states experiencing a rapid growth in opioid-related mortality rates than among those states that are not. Our findings offer insight into how unemployment rates shape the opioid crisis and suggest that the relationship between unemployment and opioid-related mortality is complex

County Social Isolation and Opioid Use Disorder among Older Adults: A Longitudinal Analysis of Medicare Data, 2013–2018

This study aims to fill three knowledge gaps: (1) unclear role of ecological factors in shaping older adults’ risk of opioid use disorder (OUD), (2) a lack of longitudinal perspective in OUD research among older adults, and (3) underexplored racial/ethnic differences in the determinants of OUD in older populations. This study estimates the effects of county-level social isolation, concentrated disadvantage, and income inequality on older adults’ risk of OUD using longitudinal data analysis. We merged the 2013–2018 Medicare population (aged 65+) data to the American Community Survey 5-year county-level estimates to create a person-year dataset (N = 47,291,217 person-years) and used conditional logit fixed-effects modeling to test whether changes in individual- and county-level covariates alter older adults’ risk of OUD. Moreover, we conducted race/ethnicity-specific models to compare how these associations vary across racial/ethnic groups. At the county level, a one-unit increase in social isolation (mean = –0.197, SD = 0.511) increased the risk of OUD by 5.5 percent (OR = 1.055; 95% CI = [1.018, 1.094]) and a one-percentage-point increase in the working population employed in primary industry decreases the risk of OUD by 1 percent (OR = 0.990; 95% CI = [0.985, 0.996]). At the individual-level, increases in the Medicare Hierarchical Condition Categories risk score, physical comorbidity, and mental comorbidity all elevate the risk of OUD. The relationship between county-level social isolation and OUD is driven by non-Hispanic whites, while Hispanic beneficiaries are less sensitive to the changes in county-level factors than any other racial ethnic groups. Between 2013 and 2018, US older adults’ risk of OUD was associated with both ecological and individual factors, which carries implications for intervention. Further research is needed to understand why associations of individual factors with OUD are comparable across racial/ethnic groups, but county-level social isolation is associated only with OUD among non-Hispanic white beneficiaries

Social Vulnerability and the Prevalence of Opioid Use Disorder among Older Medicare Beneficiaries in U.S. Counties

Objectives: Recent research has investigated the factors associated with the prevalence of opioid use disorder (OUD) among older adults (65+), which has rapidly increased in the past decade. However, little is known about the relationship between social vulnerability and the prevalence of OUD, and even less about whether the correlates of the prevalence of OUD vary across the social vulnerability spectrum. This study aims to fill these gaps. Methods: We assemble a county-level data set in the contiguous United States (U.S.) by merging 2021 Medicare claims with the CDC’s social vulnerability index and other covariates. Using the total number of older beneficiaries with OUD as the dependent variable and the total number of older beneficiaries as the offset, we implement a series of nested negative binomial regression models and then analyze by social vulnerability quartiles. Results: Higher social vulnerability is associated with higher prevalence of OUD in U.S. counties. This association cannot be fully explained by the differences in the characteristics of older Medicare beneficiaries (e.g., average age) and/or other social conditions (e.g., social capital) across counties. Moreover, the group comparison tests indicate correlates of the prevalence of OUD vary across social vulnerability quartiles in that the average number of mental disorders is positively related to OUD prevalence in the least and the most vulnerable counties and social capital benefits the less vulnerable counties. Discussion: A perspective drawing upon contextual factors, especially social vulnerability, may be more effective in reducing OUD among older adults in U.S. counties than a one-size-fits-all approach

Contextual Despair

This document provides a summary of contextual variables at the tract, county, and state level that may be relevant to operationalizing different dimensions of “despair” in Add Health respondents’ environment, per the “deaths of despair” hypothesis advanced by Case and Deaton (2015; 2020)