Faculty Bibliography

OBJECTIVES/OBJECTIVE:Some of the most pressing health problems are found in rural America. However, the surveillance needed to track and prevent disease in these regions is lacking. Our objective was to perform a comprehensive health survey of a single rural county to assess the validity of using emergency claims data to estimate rural disease prevalence at a sub-county level. DESIGN/METHODS:We performed a cross-sectional study of chronic disease prevalence estimates using emergency department (ED) claims data versus mailed health surveys designed to capture a substantial proportion of residents in New York's rural Sullivan County. SETTING/METHODS:Sullivan County, a rural county ranked second-to-last for health outcomes in New York State. PARTICIPANTS/METHODS:Adult residents of Sullivan County aged 25 years and older who responded to the health survey in 2017-2018 or had at least one ED visit in 2011-2015. OUTCOME MEASURES/METHODS:We compared age and gender-adjusted prevalence of hypertension, hyperlipidaemia, diabetes, cancer, asthma and chronic obstructive pulmonary disease/emphysema among nine sub-county areas. RESULTS:Our county-wide mailed survey obtained 6675 completed responses for a response rate of 30.4%. This sample represented more than 12% of the estimated 53 020 adults in Sullivan County. Using emergency claims data, we identified 34 576 adults from Sullivan County who visited an ED at least once during 2011-2015. At a sub-county level, prevalence estimates from mailed surveys and emergency claims data correlated especially well for diabetes (r=0.90) and asthma (r=0.85). Other conditions were not well correlated (range: 0.23-0.46). Using emergency claims data, we created more geographically detailed maps of disease prevalence using geocoded addresses. CONCLUSIONS:For select conditions, emergency claims data may be useful for tracking disease prevalence in rural areas and providing more geographically detailed estimates. For rural regions lacking robust health surveillance, emergency claims data can inform how to geographically target efforts to prevent chronic disease.

BACKGROUND:Although being employed during midlife is positively associated with cognitive function in later life, little is known with respect to cumulative trajectories or durations of time spent in different kinds of work. METHODS:We investigated the relationships between employment trajectory from ages 31 years to 50 years and cognitive skills at ages 50-78 years among 2521 adults in the US Panel Study of Income Dynamics from 1968 to 2016. Sequence analysis was used to identify prototypical employment trajectories, capturing employment status and high versus lower job skill level at each year of age from 31 years to 50 years. Adjusted and weighted logistic regression was used to estimate relationships between employment trajectory and performance on each of four cognitive tests representing numerical reasoning, verbal reasoning, health literacy and financial literacy. Dose-response relationships between the duration of high-skill employment and cognitive skills were examined. RESULTS:Seven prototypical employment trajectories were identified, the most common being consistently lower skill employment (44%; 1105/2521). Consistently high-skill and fluctuating skill trajectories were associated with high numerical reasoning scores (OR=1.54, 95% CI 0.99 to 2.40; OR=2.52, 95% CI 1.39 to 4.58, respectively), compared with consistently lower skill employment. There was a dose-response relationship between duration of high-skill employment and numerical reasoning (OR=1.17; 95% CI 1.06 to 1.28), plateauing after approximately 4 years of high-skill employment. CONCLUSIONS:Sequence analysis of exposure trajectories is a novel method for life course epidemiology that accounts for exposure timing, duration and ordering. Our results using this method indicate that the duration may be more important than the timing of high-skill midlife employment for later-life numerical reasoning skills.

OBJECTIVES/OBJECTIVE:To estimate the association between rates of police-related deaths and neighborhood residential segregation (by income, race/ethnicity, or both combined) in the United States. METHODS:We identified police-related deaths that occurred in the United States (2015-2016) using a data set from the Guardian newspaper. We used census data to estimate expected police-related death counts for all US census tracts and to calculate the Index of Concentration at the Extremes as a segregation measure. We used multilevel negative binomial models for the analyses. RESULTS:Overall, police-related death rates were highest in neighborhoods with the greatest concentrations of low-income residents (vs high-income residents) and residents of color (vs non-Hispanic White residents). For non-Hispanic Blacks, however, the risk was greater in the quintile of neighborhoods with the highest concentration of non-Hispanic White residents than in certain neighborhoods with relatively higher concentrations of residents of color (the third and fourth quintiles). CONCLUSIONS:Neighborhood context matters-beyond individual race/ethnicity-for understanding, preventing, and responding to the occurrence of police-related deaths. Public Health Implications. Efforts to monitor, prevent, and respond to police-related deaths should consider neighborhood context, including levels of segregation by income and race/ethnicity.

Background/UNASSIGNED:Metrics that quantify economic and social spatial polarization at multiple geographical levels are not routinely used by health agencies, despite rising inequalities. Methods/UNASSIGNED:We employed the Index of Concentration at the Extremes (ICE), which quantifies how persons in a specified area are concentrated into the top vs bottom of a specified societal distribution, to examine associations with Massachusetts mortality data (2010-14). Our a priori hypotheses were that these associations would: be greater at the local [census tract (CT)] compared with city/town level; vary by race/ethnicity but not gender; and be greatest for our new ICE for racialized economic segregation. Mortality outcomes comprised: child (< 5 years); premature (< 65 years); and cause-specific (cancer; cardiovascular; diabetes; suicide; HIV/AIDS; accidental poisoning; smoking-attributable). Results/UNASSIGNED:As illustrated by child mortality, in multilevel models jointly including CT and city/town metrics, the rate ratio comparing the worst to best-off ICE quintile for the total population ranged from 2.2 [95% confidence interval (CI) 1.6, 3.0] for the CT-level ICE for racialized economic segregation down to 1.1 (95% CI 0.8, 1.7) for the city/town-level ICE for racial segregation; similar patterns occurred by gender and for the non-Hispanic White population. Larger associations for the ICE for racialized economic segregation were at the CT-level for the Black non-Hispanic population (6.9; 95% CI 1.3, 36.9) and at the city/town level for the Hispanic population (6.4; 95% CI 1.2, 35.4). Conclusions/UNASSIGNED:Results indicate that health agencies should employ measures of spatial social polarization at multiple levels to monitor health inequities.

BACKGROUND:Prior research suggests that United States governmental sources documenting the number of law-enforcement-related deaths (i.e., fatalities due to injuries inflicted by law enforcement officers) undercount these incidents. The National Vital Statistics System (NVSS), administered by the federal government and based on state death certificate data, identifies such deaths by assigning them diagnostic codes corresponding to "legal intervention" in accordance with the International Classification of Diseases-10th Revision (ICD-10). Newer, nongovernmental databases track law-enforcement-related deaths by compiling news media reports and provide an opportunity to assess the magnitude and determinants of suspected NVSS underreporting. Our a priori hypotheses were that underreporting by the NVSS would exceed that by the news media sources, and that underreporting rates would be higher for decedents of color versus white, decedents in lower versus higher income counties, decedents killed by non-firearm (e.g., Taser) versus firearm mechanisms, and deaths recorded by a medical examiner versus coroner. METHODS AND FINDINGS/RESULTS:We created a new US-wide dataset by matching cases reported in a nongovernmental, news-media-based dataset produced by the newspaper The Guardian, The Counted, to identifiable NVSS mortality records for 2015. We conducted 2 main analyses for this cross-sectional study: (1) an estimate of the total number of deaths and the proportion unreported by each source using capture-recapture analysis and (2) an assessment of correlates of underreporting of law-enforcement-related deaths (demographic characteristics of the decedent, mechanism of death, death investigator type [medical examiner versus coroner], county median income, and county urbanicity) in the NVSS using multilevel logistic regression. We estimated that the total number of law-enforcement-related deaths in 2015 was 1,166 (95% CI: 1,153, 1,184). There were 599 deaths reported in The Counted only, 36 reported in the NVSS only, 487 reported in both lists, and an estimated 44 (95% CI: 31, 62) not reported in either source. The NVSS documented 44.9% (95% CI: 44.2%, 45.4%) of the total number of deaths, and The Counted documented 93.1% (95% CI: 91.7%, 94.2%). In a multivariable mixed-effects logistic model that controlled for all individual- and county-level covariates, decedents injured by non-firearm mechanisms had higher odds of underreporting in the NVSS than those injured by firearms (odds ratio [OR]: 68.2; 95% CI: 15.7, 297.5; p < 0.01), and underreporting was also more likely outside of the highest-income-quintile counties (OR for the lowest versus highest income quintile: 10.1; 95% CI: 2.4, 42.8; p < 0.01). There was no statistically significant difference in the odds of underreporting in the NVSS for deaths certified by coroners compared to medical examiners, and the odds of underreporting did not vary by race/ethnicity. One limitation of our analyses is that we were unable to examine the characteristics of cases that were unreported in The Counted. CONCLUSIONS:The media-based source, The Counted, reported a considerably higher proportion of law-enforcement-related deaths than the NVSS, which failed to report a majority of these incidents. For the NVSS, rates of underreporting were higher in lower income counties and for decedents killed by non-firearm mechanisms. There was no evidence suggesting that underreporting varied by death investigator type (medical examiner versus coroner) or race/ethnicity.

OBJECTIVES/OBJECTIVE:To assess the validity of demographic data reported in news media-based data sets for persons killed by police in Massachusetts (2004-2016) and to evaluate misclassification of these deaths in vital statistics mortality data. METHODS:We identified 84 deaths resulting from police intervention in 4 news media-based data sources (WGBH News, Fatal Encounters, The Guardian, and The Washington Post) and, via record linkage, conducted matched-pair analyses with the Massachusetts mortality data. RESULTS:Compared with death certificates, there was near-perfect correlation for age in all sources (Pearson r > 0.99) and perfect concordance for gender. Agreement for race/ethnicity ranged from perfect (The Counted and The Washington Post) to high (Fatal Encounters Cohen's κ = 0.92). Among the 78 decedents for whom finalized International Classification of Diseases, 10th Revision (ICD-10), codes were available, 59 (75.6%) were properly classified as "deaths due to legal intervention." CONCLUSIONS:In Massachusetts, the 4 media-based sources on persons killed by police provide valid demographic data. Misclassification of deaths due to legal intervention in the mortality data does, however, remain a problem. Replication of the study in other states and nationally is warranted.

Research on residential segregation and health, primarily conducted in the USA, has chiefly employed city or regional measures of racial segregation. To test our hypothesis that stronger associations would be observed using local measures, especially for racialized economic segregation, we analyzed risk of fatal and non-fatal assault in Massachusetts (1995-2010), since this outcome is strongly associated with residential segregation. The segregation metrics comprised the Index of Concentration at the Extremes (ICE), the Index of Dissimilarity, and poverty rate, with measures computed at both the census tract and city/town level. Key results were that larger associations between fatal and non-fatal assaults and residential segregation occurred for models using the census tract vs. city/town measures, with the greatest associations observed for racialized economic segregation. For fatal assaults, comparing the bottom vs. top quintiles, the incidence rate ratio (and 95% confidence interval (CI)) in models using the census tract measures equaled 3.96 (95% CI 3.10, 5.06) for the ICE for racialized economic segregation, 3.26 (95% CI 2.58, 4.14) for the ICE for income, 3.14 (95% CI 2.47, 3.99) for poverty, 2.90 (95% CI 2.21, 3.81) for the ICE for race/ethnicity, and only 0.93 (95% CI 0.79, 1.11) for the Index of Dissimilarity; in models that included both census tract and city/town ICE measures, this risk ratio for the ICE for racialized economic segregation was higher at the census tract (3.29; 95% CI 2.43, 4.46) vs. city/town level (1.61; 95% CI 1.12, 2.32). These results suggest that, at least in the case of fatal and non-fatal assaults, research on residential segregation should employ local measures, including of racialized economic segregation, to avoid underestimating the adverse impact of segregation on health.

BACKGROUND:Growing spatial social and economic polarisation may be an important societal determinant of health, but only a few studies have used the recently developed Index of Concentration at the Extremes (ICE) to analyse the impact of joint concentrations of privilege and privation on health outcomes. We explore use of the ICE to investigate risk of hypertension in an urban, multiracial/ethnic, and predominantly working-class study population of US adults. METHODS:We generated novel ICE measures at the census tract level that jointly assess extreme concentrations of both income and racial/ethnic composition. We then linked the ICE measures to data from two observational, cross-sectional studies conducted in the Boston metropolitan area (2003-2004; 2008-2010; N=2145). RESULTS:The ICE measure for extreme concentrations of white compared with black residents was independently associated with lower odds of hypertension (OR=0.76; 95% CI 0.62 to 0.93), controlling for race/ethnicity, age, gender, smoking, body mass index, household income, education and self-reported exposure to racial discrimination. Even stronger associations were observed for the ICE measures that compared concentrations of high-income white residents versus low-income residents of colour (OR=0.61; 95% CI 0.40 to 0.96) and high-income white versus low-income black residents (OR=0.48; 95% CI 0.29 to 0.81). CONCLUSIONS:Results suggest public health studies should explore the joint impact of racial/ethnic and economic spatial polarisation on population health.