Pathways between a polygenic index for education and years of completed schooling: the presentation of self and assessment of others.

Polygenic scores (PGS) are broadly misconstrued as reflecting direct causal genetic effects on their respective phenotypes. While this assumption might be accurate for some anthropometric traits like height, more complex traits such as educational attainment show very large indirect effects that stem from many sources. One unexplored source of confounding is the possibility of evocative gene-environment correlation (rGE). Using data from the National Longitudinal Study of Adolescent to Adult Health, we examine the relationship between interviewer assessments of respondent appearance as a function of education PGS. We show a bivariate association between educational PGS and 1) perceived grooming, 2) physical attractiveness, and 3) personality. We then regress years of education on the educational PGS and show that very little of the association (~1-2%) is mediated by attractiveness or personality but 7.5% of the baseline association is confounded with how others may perceive grooming. These results highlight the importance of social-behavioral mechanisms that may link specific genotypes to successful transitions through high school and college and continue to bridge research from the social and biological sciences.

Do Sheriff-Coroners Underreport Officer-Involved Homicides?

Introduction: In the United States, each state sets its own standards for its death investigation system. These may require independent medical examiners and coroners or allow for the sheriff to assume the role of coroner. Motivated by the well-established fact that counts of officer-involved homicides in official data sets grossly undercount the number of these incidents, we examine the possibility that different death investigation systems may lead to different death classification outcomes. Methods: To examine the potential differences in officer-involved homicide underreporting by presence of sheriff-coroner and violent death type (gunshot, intentional use of force, pursuit, or other vehicle accident), we compare ratios of incidents from both the Federal Bureau of Investigation's Supplementary Homicide Reports and the restricted Multiple-Cause of Death files from the National Vital Statistics System to the Fatal Encounters data across coroner contexts in California between 2000 and 2018; we quantify differences descriptively and examine bivariate tests of means. Results: We find significantly greater underreporting of officer-involved deaths in sheriff-coroner counties in both official data sets for all incidents compared with non-sheriff-coroner counties, independently of the period considered. These underreporting differences in the National Vital Statistics System are robust to restricting to gunshot and intentional use of force deaths, the type of incident expected to be less prone to misclassification in that data set. Conclusions: Officer-involved death underreporting in sheriff-coroner counties necessitates further scrutiny. Disparities in officer-involved death reporting suggest political pressure may play a role in classifying deaths.

Assessing Data Completeness, Quality, and Representativeness of Justifiable Homicides in the FBI's Supplementary Homicide Reports: A Research Note.

Introduction: The most widely used data set for studying police homicides-the Supplementary Homicide Reports (SHR) kept by the Federal Bureau of Investigation-is collected from a voluntary sample. Materials and Methods: Using a journalist-curated database of police-related deaths, we find the SHR police homicide data to be substantially incomplete. This is due to both non-reporting and substantial under-reporting by agencies. Further, our inquiry discloses a pattern of error in identifying "victims" and "offenders" in the data, and finds that investigating agencies are often incorrectly listed as the responsible agency, which seriously jeopardizes police department-level analyses. Finally, there is evidence of sample bias such that the SHR data system is not representative of all police departments, nor is it representative of large police departments. Conclusions: We conclude that the SHR data is of dubious value for assessing correlates of police homicides in the United States, as all analyses using it will reflect these widespread biases and significant undercounts. Analysis of SHR data for these purposes should cease.

The Impact of Residing in a Gang Territory on Adverse Birth Outcomes: Evidence from Los Angeles.

Gang violence remains an ongoing crisis in many communities in the United States. This paper assesses the potential association of gang-occupied neighborhoods with birth outcomes. Adverse birth outcomes serve as a "barometer" of population health, denoting both poor conditions for human development and portending future public health concerns. We draw upon (1) Los Angeles County Vital Statistics Birth Records (2008-2012), (2) GIS information on gang territory boundaries, (3) LA city geo-coded crime data, and (4) the 2010 U.S. Census and 2006-2010 American Community Survey. We find an association between gang-occupied neighborhoods and adverse birth outcomes; however, this association is largely explained by other neighborhood socio-demographic characteristics, crime notwithstanding. We also find that gangland neighborhoods tend to exacerbate the effects of crime for all birth outcomes, but only significantly so for small for gestational age births. Lastly, gang co-residence, crime, and other neighborhood demographics explain a substantial portion of socioeconomic and racial/ethnic disparities in adverse birth outcomes. Gangland neighborhoods appear to be a novel contributor to both population health and health disparities. Future studies should address these relationships in a broad range of metropolitan settings, paying careful attention to causal linkages and moderating effects of gangs and crime.

Perceived Discrimination and Mental Distress Amid the COVID-19 Pandemic: Evidence From the Understanding America Study.

INTRODUCTION: This study examines COVID-19-associated discrimination regardless of infection status. It evaluates the contribution of various risk factors (e.g., race/ethnicity and wearing a face mask) and the relationship with mental distress among U.S. adults in March and April 2020, when the pandemic escalated across the country. METHODS: Participants consisted of a probability-based, nationally representative sample of U.S. residents aged ≥18 years who completed COVID-19-related surveys online in March and April (n=3,665). Multivariable logistic regression was used to predict the probability of a person perceiving COVID-19-associated discrimination. Linear regression was used to analyze the association between discrimination and mental distress. Analyses were conducted in May 2020. RESULTS: Perception of COVID-19-associated discrimination increased from March (4%) to April (10%). Non-Hispanic Black (absolute risk from 0.09 to 0.15 across months) and Asians (absolute risk from 0.11 to 0.17) were more likely to perceive discrimination than other racial/ethnic groups (absolute risk from 0.03 to 0.11). Individuals who wore face masks (absolute risk from 0.11 to 0.14) also perceived more discrimination than those who did not (absolute risk from 0.04 to 0.11). Perceiving discrimination was subsequently associated with increased mental distress (from 0.77 to 1.01 points on the 4-item Patient Health Questionnaire score). CONCLUSIONS: Perception of COVID-19-associated discrimination was relatively low but increased with time. Perceived discrimination was associated with race/ethnicity and wearing face masks and may contribute to greater mental distress during early stages of the pandemic. The long-term implications of this novel form of discrimination should be monitored.

Geographic Heterogeneity in Otolaryngology Medicare New Patient Visits.

OBJECTIVE: To analyze the spatial variation of sociodemographic factors associated with the geographic distribution of new patient visits to otolaryngologists. STUDY DESIGN: Retrospective cross-sectional analysis. SETTING: United States. SUBJECT AND METHODS: Medicare new patient visits pooled from 2012 to 2016 to otolaryngology providers were obtained from the Centers for Medicare and Medicaid Services, and county-level sociodemographic data were obtained from the 2012-2016 American Community Survey. The mean number of new patient visits per otolaryngology provider by county was calculated. The spatial variation was analyzed with negative binomial and geographically weighted regression. Predictors included various neighborhood characteristics. RESULTS: There were 7,199,129 Medicare new patient visits to otolaryngology providers from 2012 to 2016. A 41.7-fold difference in new patient evaluation rates was observed across US counties (range, 11-458.8 per otolaryngology provider). On multivariable regression analysis, median age, sex, work commute time, percentage insured, and the advantage index of a county were predictors for the rate of new patient visits to otolaryngology providers. However, geographically weighted regression demonstrated that the association of a county's disadvantage index, advantage index, percentage insured, and work commute times with new patient visits per provider varied across space. CONCLUSIONS: There are wide geographic differences in the number of new Medicare patients seen by otolaryngologists, and the influence of county sociodemographic factors varied regionally. Further research to analyze the variations in practice patterns of otolaryngologists is warranted to predict future public health needs.

The Great Recession and adverse birth outcomes: Evidence from California, USA.

OBJECTIVES: Prior studies of the health effects of recessions have shown mixed results. Ecological studies often report a positive relationship between economic downturns and population health while individual-level studies often show that conditions related to recessions are deleterious. Our study examines the spatially and temporally heterogenous effects of the Great Recession (TGR) on adverse birth outcomes, a contemporaneous measure of population health that is highly responsive to changing social conditions. METHODS: We use restricted birth cohort data from California (2004-2012) merged with both county- and tract-level socio-demographic data, to explore birth selectivity and temporal and unemployment effects during TGR on adverse birth outcomes. RESULTS: We find that gestational exposure - more specifically, second trimester exposure - during or adjacent to the months of TGR was generally deleterious for birth outcomes, more so, in some cases, for mothers with lower levels of education, and that increases in county-level unemployment were generally deleterious for birth outcomes. CONCLUSIONS: Although recessionary effects on population health are problematic and may have far-reaching effects, it appears that these effects may be largely universal, even given potential selective fertility favoring advantaged groups.

Adverse Childhood Experiences, Early and Nonmarital Fertility, and Women's Health at Midlife.

Adverse childhood experiences (ACEs) have powerful consequences for health and well-being throughout the life course. We draw on evidence that exposure to ACEs shapes developmental processes central to emotional regulation, impulsivity, and the formation of secure intimate ties to posit that ACEs shape the timing and context of childbearing, which in turn partially mediate the well-established effect of ACEs on women's later-life health. Analysis of 25 years of nationally representative panel data from the National Longitudinal Study of Youth (NLSY79; n = 3,893) indicates that adverse childhood experiences predict earlier age at first birth and greater odds of having a nonmarital first birth. Age and marital status at first birth partially mediate the effect of ACEs on women's health at midlife. Implications for public health and family policy aimed at improving maternal and child well-being are discussed.

The impact of perceived discrimination on depressive symptoms and the role of differentiated social support among immigrant populations in South Korea.

BACKGROUND: Previous studies demonstrated a positive association between perceived discrimination and mental health problems among immigrants in countries that traditionally host immigrants. Recent trends in international migration show that there has been a significant increase in immigrant populations in East Asian countries. These newer host countries have different social contexts from traditional ones, yet mental health among these immigrants and its relationship to discrimination are under-researched. Thus, this study aimed to examine the association between perceived discrimination and depressive symptoms among immigrants in one of the newer host countries, South Korea. Moreover, we investigated if differentiated social support (ethnic, host or other support) serves as a moderator of discrimination for depressive symptoms. METHODS: This study used survey data from the 2012 Korean Social Survey on Foreign Residents (N = 1068), restricted to adults 20 years or older. Multiple linear regression models were conducted to estimate the association between perceived discrimination, social support, and depressive symptoms among immigrants in South Korea. RESULTS: Perceived discrimination showed a strong positive association with depressive symptoms among immigrants, and ethnic and host support was directly positively associated with depressive symptoms. Furthermore, ethnic support moderated the effects of perceived discrimination on depressive symptoms. CONCLUSION: Community-level interventions providing immigrants opportunities to increase social networking members from the same country as well as the native-born in a host country may be helpful resources for improving mental health among immigrants in South Korea. Also, raising awareness of racial discrimination among members in South Korea would be crucial.

"Using Crowd-Sourced Data to Explore Police-Related-Deaths in the United States (2000-2017): The Case of Fatal Encounters".

Objectives: We evaluated the Fatal Encounters (FE) database as an open-source surveillance system for tracking police-related deaths (PRDs). Methods: We compared the coverage of FE data to several known government sources of police-related deaths and police homicide data. We also replicated incident selection from a recent review of the National Violent Death Reporting System. Results: FE collected data on n = 23,578 PRDs from 2000-2017. A pilot study and ongoing data integration suggest greater coverage than extant data sets. Advantages of the FE data include circumstance of death specificity, incident geo-locations, identification of involved police-agencies, and near immediate availability of data. Disadvantages include a high rate of missingness for decedent race/ethnicity, potentially higher rates of missing incidents in older data, and the exclusion of more comprehensive police use-of-force and nonlethal use-of-force data-a critique applicable to all extant data sets. Conclusions: FE is the largest collection of PRDs in the United States and remains as the most likely source for historical trend comparisons and police-department level analyses of the causes of PRDs.

Long-term trends in adult mortality for U.S. Blacks and Whites: an examination of period- and cohort-based changes.

Black-white differences in U.S. adult mortality have narrowed over the past five decades, but whether this narrowing unfolded on a period or cohort basis is unclear. The distinction has important implications for understanding the socioeconomic, public health, lifestyle, and medical mechanisms responsible for this narrowing. We use data from 1959 to 2009 and age-period-cohort (APC) models to examine period- and cohort-based changes in adult mortality for U.S. blacks and whites. We do so for all-cause mortality among persons aged 15-74 as well as for several underlying causes of death more pertinent for specific age groups. We find clear patterns of cohort-based reductions in mortality for both black men and women and white men and women. Recent cohort-based reductions in heart disease, stroke, lung cancer, female breast cancer, and other cancer mortality have been substantial and, save for breast cancer, have been especially pronounced for blacks. Period-based changes have also occurred and are especially pronounced for some causes of death. Period-based reductions in blacks' and whites' heart disease and stroke mortality are particularly impressive, as are recent period-based reductions in young men's and women's mortality from infectious diseases and homicide. These recent period changes are more pronounced among blacks. The substantial cohort-based trends in chronic disease mortality and recent period-based reductions for some causes of death suggest a continuing slow closure of the black-white mortality gap. However, we also uncover troubling signs of recent cohort-based increases in heart disease mortality for both blacks and whites.

Does SES explain more of the black/white health gap than we thought? Revisiting our approach toward understanding racial disparities in health.

Studies of racial health gaps often find that disparities persist even after adjusting for socioeconomic status (SES). We contend that the persistent residual variation may, in part, be the result of conceptual and methodological problems in the operationalization of SES. These include inadequate attention to the content validity of SES measures and insufficient adjustments for SES differences across racial groups. Using data from the 1997-2007 U.S. Panel Study of Income Dynamics (N = 9932), we use longitudinal and multi-level measures of SES and apply a propensity score adjustment strategy to examine the black/white disparity in self-rated health. Compared to conventional regression estimates that yield unexplained racial health gaps, propensity score adjustment accounts for the entire racial disparity in self-rated health. Results suggest that previous studies may have inadequately adjusted for differences in SES across racial groups, that social factors should be carefully and conscientiously considered, and that acknowledgment of the possibility of incomplete SES adjustments should be weighed before any inferences to non-SES etiology can be made.

Assessing the Utility of Satellite Imagery with Differing Spatial Resolutions for Deriving Proxy Measures of Slum Presence in Accra, Ghana.

Little research has been conducted on how differing spatial resolutions or classification techniques affect image-driven identification and categorization of slum neighborhoods in developing nations. This study assesses the correlation between satellite-derived land cover and census-derived socioeconomic variables in Accra, Ghana to determine whether the relationship between these variables is altered with a change in spatial resolution or scale. ASTER and Landsat TM satellite images are each used to classify land cover using spectral mixture analysis (SMA), and land cover proportions are summarized across Enumeration Areas in Accra and compared to socioeconomic data for the same areas. Correlation and regression analyses compare the SMA results with a Slum Index created from various socio-economic data taken from the Census of Ghana, as well as to data derived from a "hard" per-pixel classification of a 2.4 m Quickbird image. Results show that the vegetation fraction is significantly correlated with the Slum Index (Pearson's r ranges from -0.33 to -0.51 depending on which image-derived product is compared), and the use of a spatial error model improves results (multivariate model pseudo-R2 ranges from 0.37 to 0.40 by image product). We also find that SMA products derived from ASTER are a sufficient substitute for classification products derived from higher spatial resolution QB data when using land cover fractions as a proxy for slum presence, suggesting that SMA might be more cost-effective for deriving land cover fractions than the use of high-resolution imagery for this type of demographic analysis.

Socio-economic status and z-score standardized height-for-age of U.S.-born children (ages 2-6).

This study explores socio-economic gradients in height (stature-for-age) among a nationally representative sample of 2-6 year old children in the United States. We use NHANES III (1988-1994) Youth data linked with a special Natality Data supplement which contains information from birth certificates among sampled NHANES III Youth who are < 7 years of age. Our results indicate significant socio-economic gradients for both maternal education and family income, net of controls for confounders, including: birth weight, gestational age, family size, and parental heights. These results are in stark contrast to those from other developed countries that seem to indicate diminished or eliminated socio-economic disparities, net of known confounders. In the United States, it appears that socio-economic gradients have an effect on birth outcomes, and continue to have an additional direct and independent effect on height, even in early childhood.

The link between neighborhood poverty and health: context or composition?

Cross-sectional studies of neighborhood context and health are subject to upward bias due to unobserved heterogeneity and to downward bias due to overadjustment for potential mediators in the pathway between neighborhood context and health. In this study, the authors employed two strategies that addressed these two sources of bias. First, to mitigate overadjustment of mediators, they adjusted for baseline characteristics observed just prior to the measurement of neighborhood context, using a combined propensity score and regression strategy. Second, to mitigate underadjustment of unmeasured confounders, they employed a fixed-effects modeling strategy to account for unobserved non-time-varying heterogeneity. Analyses were based on a nationally representative sample of the nonimmigrant US population from the Panel Study of Income Dynamics (1980-1997) in which respondent-rated health was regressed on neighborhood poverty. The samples consisted of approximately 6,000 respondents for the propensity score/regression models and 45,000 person-years for the fixed-effects models. Both modeling strategies yielded significant estimates of neighborhood poverty and supported a causal link between neighborhood context and health.

Does place explain racial health disparities? Quantifying the contribution of residential context to the Black/white health gap in the United States.

The persistence of the black health disadvantage has been a puzzling component of health in the United States in spite of general declines in rates of morbidity and mortality over the past century. Studies that have focused on well-established individual-level determinants of health such as socio-economic status and health behaviors have been unable to fully explain these disparities. Recent research has begun to focus on other factors such as racism, discrimination, and segregation. Variation in neighborhood context-socio-demographic composition, social aspects, and built environment-has been postulated as an additional explanation for racial disparities, but few attempts have been made to quantify its overall contribution to the black/white health gap. This analysis is an attempt to generate an estimate of place effects on explaining health disparities by utilizing data from the U.S. National Health Interview Survey (NHIS) (1989-1994), combined with a methodology for identifying residents of the same blocks both within and across NHIS survey cross-sections. Our results indicate that controlling for a single point-in-time measure of residential context results in a roughly 15-76% reduction of the black/white disparities in self-rated health that were previously unaccounted for by individual-level controls. The contribution of residential context toward explaining the black/white self-rated health gap varies by both age and gender such that contextual explanations of disparities decline with age and appear to be smaller among females.

You are where you shop: grocery store locations, weight, and neighborhoods.

BACKGROUND: Residents in poor neighborhoods have higher body mass index (BMI) and eat less healthfully. One possible reason might be the quality of available foods in their area. Location of grocery stores where individuals shop and its association with BMI were examined. METHODS: The 2000 U.S. Census data were linked with the Los Angeles Family and Neighborhood Study (L.A.FANS) database, which consists of 2620 adults sampled from 65 neighborhoods in Los Angeles County between 2000 and 2002. In 2005, multilevel linear regressions were used to estimate the associations between BMI and socioeconomic characteristics of grocery store locations after adjustment for individual-level factors and socioeconomic characteristics of residential neighborhoods. RESULTS: Individuals have higher BMI if they reside in disadvantaged areas and in areas where the average person frequents grocery stores located in more disadvantaged neighborhoods. Those who own cars and travel farther to their grocery stores also have higher BMI. When controlling for grocery store census tract socioeconomic status (SES), the association between residential census tract SES and BMI becomes stronger. CONCLUSIONS: Where people shop for groceries and distance traveled to grocery stores are independently associated with BMI. Exposure to grocery store mediates and suppresses the association of residential neighborhoods with BMI and could explain why previous studies may not have found robust associations between residential neighborhood predictors and BMI.

Los Años de la Crisis: an examination of change in differential infant mortality risk within Mexico.

The main aim of the present analysis is to test the possibility that the period of economic hardship characterizing Mexico over the decade 1986-1996 has negatively influenced infant health outcomes. Data on births from two installments of the Encuesta Nacional de la Dinámica Demográfica, a nationally representative demographic survey, are used to determine whether a reduction in mortality differentials has paralleled the overall drop in the national infant mortality rate. The findings indicate that the decrease observed in the overall infant mortality rate has been matched by decreases in several disparities at the same time that it has been marred by increases in others. The data support the possibility that where you live has become an increasingly salient factor in determining the odds of infant mortality. High parity, low education and unemployment status have also become more salient factors in predicting post neonatal infant mortality risk in the more recent period as compared to the earlier period. As Mexico's infant mortality rate begins to stabilize in the near future, this research highlights the need to re-focus our research efforts on the causes and consequences of differential mortality trends.

Early origins of the gradient: the relationship between socioeconomic status and infant mortality in the United States.

Although relationships between social conditions and health have been documented for centuries, the past few decades have witnessed the emergence of socioeconomic gradients in health and mortality in most developed countries. These gradients indicate that health improves, although decreasingly so, at higher levels of socioeconomic status. To minimize problems with reverse causality, I tested competing hypotheses for observed socioeconomic gradients for infant mortality outcomes. I found no support for the income-inequality hypothesis and negligible support for the occupational-grade hypothesis. The results indicate that absolute material conditions are the most important determinants of socioeconomic effects on the risk of infant mortality and that while poverty has the most pronounced effect on risk, income is decreasingly salutary across the majority of the mortality gradient.