Business Data Categorization and Refinement for Application in Longitudinal Neighborhood Health Research: a Methodology.

Retail environments, such as healthcare locations, food stores, and recreation facilities, may be relevant to many health behaviors and outcomes. However, minimal guidance on how to collect, process, aggregate, and link these data results in inconsistent or incomplete measurement that can introduce misclassification bias and limit replication of existing research. We describe the following steps to leverage business data for longitudinal neighborhood health research: re-geolocating establishment addresses, preliminary classification using standard industrial codes, systematic checks to refine classifications, incorporation and integration of complementary data sources, documentation of a flexible hierarchical classification system and variable naming conventions, and linking to neighborhoods and participant residences. We show results of this classification from a dataset of locations (over 77 million establishment locations) across the contiguous U.S. from 1990 to 2014. By incorporating complementary data sources, through manual spot checks in Google StreetView and word and name searches, we enhanced a basic classification using only standard industrial codes. Ultimately, providing these enhanced longitudinal data and supplying detailed methods for researchers to replicate our work promotes consistency, replicability, and new opportunities in neighborhood health research.

Patterns in Geographic Access to Health Care Facilities Across Neighborhoods in the United States Based on Data From the National Establishment Time-Series Between 2000 and 2014.

Importance: The association between proximity to health care facilities and improved disease management and population health has been documented, but little is known about small-area health care environments and how the presence of health care facilities has changed over time during recent health system and policy change. Objective: To examine geographic access to health care facilities across neighborhoods in the United States over a 15-year period. Design, Setting, and Participants: Using longitudinal business data from the National Establishment Time-Series, this cross-sectional study examined the presence of and change in ambulatory care facilities and pharmacies and drugstores in census tracts (CTs) throughout the continental United States between 2000 and 2014. Between January and April 2019, multinomial logistic regression was used to estimate associations between health care facility presence and neighborhood sociodemographic characteristics over time. Main Outcomes and Measures: Change in health care facility presence was measured as never present, lost, gained, or always present between 2000 and 2014. Neighborhood sociodemographic characteristics (ie, CTs) and their change over time were measured from US Census reports (2000 and 2010) and the American Community Survey (2008-2012). Results: Among 72 246 included CTs, the percentage of non-US-born residents, residents 75 years or older, poverty status, and population density increased, and 8.1% of CTs showed a change in the racial/ethnic composition of an area from predominantly non-Hispanic (NH) white to other racial/ethnic composition categories between 2000 and 2010. The presence of ambulatory care facilities increased from a mean (SD) of 7.7 (15.9) per CT in 2000 to 13.0 (22.9) per CT in 2014, and the presence of pharmacies and drugstores increased from a mean (SD) of 0.6 (1.0) per CT in 2000 to 0.9 (1.4) per CT in 2014. Census tracts with predominantly NH black individuals (adjusted odds ratio [aOR], 2.37; 95% CI, 2.03-2.77), Hispanic/Latino individuals (aOR 1.30; 95% CI, 1.00-1.69), and racially/ethnically mixed individuals (aOR, 1.53; 95% CI, 1.33-1.77) in 2000 had higher odds of losing health care facilities between 2000 and 2014 compared with CTs with predominantly NH white individuals, after controlling for other neighborhood characteristics. Census tracts of geographic areas with higher levels of poverty in 2000 also had higher odds of losing health care facilities between 2000 and 2014 (aOR, 1.12; 95% CI, 1.05-1.19). Conclusions and Relevance: Differential change was found in the presence of health care facilities across neighborhoods over time, indicating the need to monitor and address the spatial distribution of health care resources within the context of population health disparities.

Process of care compliance is associated with fewer diabetes complications.

OBJECTIVE: To examine the association between processes measures of diabetes care and time to progression for 4 diabetes complications: coronary artery disease (CAD), stroke, heart failure (HF), and renal disease (RD). STUDY DESIGN: This retrospective study followed outcomes from 2003 through 2009 in a cohort of 1797 employees with diabetes who worked for a large US manufacturer and were enrolled in the same health insurance plan. METHODS: Quality of care was measured by consensus standards for testing glycated hemoglobin, lipids, and microalbuminuria. Employees with diabetes who received all 3 measures of care in the baseline year (2003) were compared with those who received less complete testing. Cox proportional hazard regression models were used to assess potential associations between diabetes care and time to complications, controlling for potential confounders. RESULTS: Observed differences between the 2 groups in time to event were significant for 2 of the 4 complications: HF (hazard ratio [HR] = 0.39, 95% confidence interval [CI], 0.19-0.81; P = .0117) and RD (HR = 0.48, 95% CI, 0.24-0.95; P = .0339) and any of the 4 complications (HR = 0.66, 95% CI, 0.48-0.91; P = .0101). Differences in time to complication for CAD (HR = 0.70, 95% CI, 0.49-1.02; P = .0635) and stroke (HR = 0.63, 95% CI, 0.38-1.07; P = .0891) showed the same trend but were not significant. CONCLUSIONS: Employees with diabetes who received all 3 quality measures experienced fewer complications, risk-adjusting for other factors. These results provide support for the importance of care quality.

Beryllium sensitization in aluminum smelter workers.

OBJECTIVE: To determine whether beryllium-related disease exists among aluminum smelter workers. METHODS: A total of 1278 employees from four aluminum smelters determined to have significant beryllium exposure based on 5 years of sampling were invited to participate in medical surveillance that included a respiratory symptoms questionnaire, spirometry, and blood beryllium lymphocyte proliferation test. RESULTS: Of these, 734 employees participated in the program. Beryllium exposure from 965 personal samples ranged from 0.002 to 13.00 microg/m time-weighted average, with a median of 0.05 microg/m, geometric mean of 0.05 microg/m, and arithmetic mean of 0.22 microg/m. Only two employees had confirmed beryllium sensitization (0.27%). CONCLUSION: There is evidence of beryllium sensitization among aluminum smelter workers. When compared with beryllium-exposed workers in other industries, aluminum smelter workers had lower rates of sensitization. The low beryllium sensitization rate observed may be related to work practices and the properties of the beryllium found in this work environment.