Wartime health shocks and the postwar socioeconomic status and mortality of union army veterans and their children.
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ABSTRACT:
SUBMITTER: Costa DL
PROVIDER: S-EPMC7096284 | biostudies-literature | 2020 Mar
REPOSITORIES: biostudies-literature
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Wartime health shocks and the postwar socioeconomic status and mortality of union army veterans and their children.
Costa Dora L DL Yetter Noelle N DeSomer Heather H
Journal of health economics 20191228
We investigate when and how health shocks reverberate across the life cycle and down to descendants in a manual labor economy by examining the association of war wounds with the socioeconomic status and older age mortality of US Civil War (1861-5) veterans and of their adult children. Younger veterans who had been severely wounded in the war left the farm sector, becoming laborers. Consistent with human capital and job matching models, older severely wounded men were unlikely to switch sectors a ...[more]
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Project description:This paper overviews the research opportunities made possible by a NIA-funded program project, Early Indicators, Intergenerational Processes, and Aging. Data collection began almost three decades ago on 40,000 soldiers from the Union Army in the US Civil War. The sample contains extensive demographic, economic, and medical data from childhood to death. In recent years, a large sample of African-American soldiers and an oversampling of soldiers from major US cities have been added. Hundreds of historical maps containing public health data have been geocoded to place soldiers and their family members in a geospatial context. With newly granted funding, thousands of veterans will be linked to the demographic information available from the census and vital records of their children.
| S-EPMC5501418 | biostudies-other
Project description:BackgroundThe VHA is the largest integrated US health system and is increasingly moving care into the communities where veterans reside. Veterans who utilize the VA for their care have worse health status than the general population. However, there is limited evidence about the association of neighborhood environment and health outcomes among veterans.ObjectivesThe primary aim of this study is to assess the relative contribution of neighborhood environment, health system, and individual characteristics to health status and mortality of veterans.MethodsInformation on personal socio-economic indicators, existing medical conditions and health status were obtained from baseline data from a multi-site, randomized trial of primary care patients (n = 15,889). The physical component scale (PCS) and mental component scale (MCS) summarized health status. Census tracts were used as proxies for neighborhoods. A summary score based on census tract data characterized the neighborhood socio-economic environment and walkability. Data were analyzed with multilevel hierarchical models. Analyses of health status were cross-sectional. Mortality analyses were longitudinal as participants were followed for an average of 722.5 days to ascertain vital status.ResultsNeighborhood SES was associated with PCS and MCS scores, controlling for individual socio-economic status, self-reported co-morbid disease, smoking status, and health care access. In the lowest versus highest quartiles of neighborhood SES, adjusted PCS scores were 34.4 vs. 35.4 (p < 0.05) and adjusted MCS scores were 46.2 versus 47.0 (p < 0.05). PCS score was also significantly associated with neighborhood walkability (p < 0.05). Mortality was lower for veterans living in neighborhoods with the highest decile neighborhood SES (HR 0.78, highest vs. lowest decile 95% CI 0.63, 0.97).ConclusionsVeterans living in lower SES neighborhoods have poorer health status and a higher risk of mortality, independent of individual characteristics and health care access. Neighborhood walkability was associated with higher PCS scores.
| S-EPMC3138994 | biostudies-literature
Project description:ImportanceSocioeconomic factors are associated with worse outcomes after hospitalization, but neither the Centers for Medicare & Medicaid Services (CMS) nor the Veterans Affairs (VA) health care system adjust for socioeconomic factors in profiling hospital mortality.ObjectiveTo evaluate changes in Veterans Affairs medical centers' (VAMCs') risk-standardized mortality rates among veterans hospitalized for heart failure and pneumonia after adjusting for socioeconomic factors.Design, setting, and participantsIn this cross-sectional study, retrospective data were used to assess 131 VAMCs' risk-standardized 30-day mortality rates with or without adjustment for socioeconomic covariates. The study population included 42 892 veterans hospitalized with heart failure and 39 062 veterans hospitalized with pneumonia from January 1, 2012, to December 31, 2014. Data were analyzed from March 1, 2019, to April 1, 2020.Main outcomes and measuresThe primary outcome was 30-day mortality after admission. Socioeconomic covariates included neighborhood disadvantage, race/ethnicity, homelessness, rurality, nursing home residence, reason for Medicare eligibility, Medicaid and Medicare dual eligibility, and VA priority.ResultsThe study population included 42 892 veterans hospitalized with heart failure (98.2% male; mean [SD] age, 71.9 [11.4] years) and 39 062 veterans hospitalized with pneumonia (96.8% male; mean [SD] age, 71.0 [12.4] years). The addition of socioeconomic factors to the CMS models modestly increased the C statistic from 0.77 (95% CI, 0.77-0.78) to 0.78 (95% CI, 0.78-0.78) for 30-day mortality after heart failure and from 0.73 (95% CI, 0.72-0.73) to 0.74 (95% CI, 0.73-0.74) for 30-day mortality after pneumonia. Mortality rates were highly correlated (Spearman correlations of ≥0.98) in models that included or did not include socioeconomic factors. With the use of the CMS model for heart failure, VAMCs in the lowest quintile had a mean (SD) mortality rate of 6.0% (0.4%), those in the middle 3 quintiles had a mean (SD) mortality rate of 7.2% (0.4%), and those in the highest quintile had a mean (SD) mortality rate of 8.8% (0.6%). After the inclusion of socioeconomic covariates, the adjusted mean (SD) mortality was 6.1% (0.4%) for hospitals in the lowest quintile, 7.2% (0.4%) for those in the middle 3 quintiles, and 8.6% (0.5%) for those in the highest quintile. The mean absolute change in rank after socioeconomic adjustment was 3.0 ranking positions (interquartile range, 1.0-4.0) among hospitals in the highest quintile of mortality after heart failure and 4.4 ranking positions (interquartile range, 1.0-6.0) among VAMCs in the lowest quintile. Similar findings were observed for mortality rankings in pneumonia and after inclusion of clinical covariates.Conclusions and relevanceThis study suggests that adjustments for socioeconomic factors did not meaningfully change VAMCs' risk-adjusted 30-day mortality rates for veterans hospitalized for heart failure and pneumonia. The implications of such adjustments should be examined for other quality measures and health systems.
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Project description:Previous research finds that marriage is associated with better health and lower mortality, and one of the mechanisms underlying this association is health-related selection out of marriage. Using longitudinal survey data from 2,348 couples from the Fragile Families and Child Wellbeing Study, we examine whether certain health behaviors-smoking and binge drinking-are associated with risk of union dissolution among couples with young children. We use discrete time hazard models to test whether associations between health behaviors and union dissolution differ between married and cohabiting parents. We find no statistically significant association between binge drinking and union dissolution for either cohabiting or married couples. Parental smoking, however, is associated with union dissolution. On average, married and cohabiting couples in which both parents smoke have a higher risk of union dissolution than couples in which neither parent smokes. Additionally, father's smoking (in couples in which the mother does not smoke) is associated with union dissolution, but only for married couples. These findings illustrate the importance of considering the health behaviors of both partners and provide further evidence of differences in union dissolution dynamics between married and cohabiting couples.
| S-EPMC5552162 | biostudies-literature
Project description:ObjectiveApproximately three to six months after returning from deployment, military service members complete the Post-Deployment Health Reassessment (PDHRA), which includes screens for alcohol misuse, depression, and posttraumatic stress disorder (PTSD). To determine whether Army Reserve Component (RC) members (Army National Guard and Army Reserve) with positive screening scores on the PDHRA receive needed care, the investigators examined the association between positive scores and enrollment and utilization of care ("linkage") in the Veterans Health Administration (VHA), as well as rescreening scores, diagnosis, and behavioral treatment in VHA.MethodsMixed-effects regression models were used to predict linkage to VHA within six months after RC members (N=73,164) completed the PDHRA, with alcohol misuse, depression, and PTSD screen scores as key independent variables. Regression models were stratified by gender and National Guard versus Reserve status. Among those who linked to VHA (N=25,168), screening scores and subsequent diagnosis and treatment in VHA were also examined.ResultsArmy RC members with positive PTSD and depression screening scores were more likely than those with negative screens to link to VHA, and most (54%-84%) received VHA treatment once diagnosed. Positive screens for alcohol misuse were associated with linkage to VHA for men but not for women, and treatment rates for alcohol use disorders were relatively low (0%-25%) for both men and women diagnosed as having an alcohol use disorder.ConclusionsThe finding that Army RC members with greater indications of behavioral health problems linked to VHA is encouraging. However, more outreach and treatment engagement strategies could be directed to those with alcohol use disorder, particularly women.
| S-EPMC5697977 | biostudies-literature
Project description:BackgroundThe dimensions along which mortality is patterned in India remains unclear. We examined the specific contribution of social castes, household income, assets, and monthly per capita consumption to mortality differentials in India.Methods and findingsCross-sectional data on 217,363 individuals from 41,554 households from the 2004-2005 India Human Development Survey was analyzed using multiple logistic regressions. Mortality differentials across social castes were attenuated after adjusting for household economic factors such as income and assets. Individuals living in the lowest income and assets quintiles had an increased risk of mortality with odds ratio (OR) of 1.66 (95% CI ?=? 1.23-2.24) in the bottom income quintile and OR of 2.94 (95% CI ?=? 1.66-5.22) in the bottom asset quintile. Counter-intuitively, individuals living in households with lowest monthly consumption per capita had significantly lower probability of death (OR ?= ?0.27, 95% CI ?= ?0.20-0.38).ConclusionsMortality burden in India is largely patterned on economic dimensions as opposed to caste dimensions, though caste may play an important role in predicting economic opportunities.
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Project description:Cancer mortality is higher among residents of low-socioeconomic status (SES) areas than those of high-SES areas; however, the contribution of modifiable risk factors to this disparity is not known. We used data from 54,737 participants in the VITamins And Lifestyle (VITAL) Study, aged 50-76 with no history of cancer at baseline (2000-2002). Of these, 1488 died of cancer over an average of 7.7 years of follow-up. Data on modifiable risk factors including body mass index (BMI), physical activity, diet, alcohol, smoking and screening were taken from baseline questionnaires. We constructed a block group-level SES index using data from the 2000 United States Census and fit Cox proportional hazards models estimating the association between area-level SES and total cancer mortality with and without control for modifiable risk factors. All statistical tests are 2-sided. Cancer mortality was 77% (95% CI: 50%, 111%) higher in the lowest-SES areas compared with the highest. Modifiable risk factors accounted for 45% (95% CI: 34%, 62%) of this association. Smoking explained the greatest proportion (29%; 95% CI: 22%, 40%) of the observed association, followed by diet (11%; 95% CI: 7%, 17%), physical activity (10%; 95% CI: 7%, 16%), screening (9%; 6%, 13%), and BMI (5%; 95% CI: 1%, 10%). Results were similar in models controlling for individual education and income. The association between area-level SES and cancer mortality is partially explained by modifiable risk factors, which could suggest the appropriate targets to reduce socioeconomic disparities.
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Project description:Studies extending across multiple life stages promote an understanding of factors influencing health across the life span. Existing work has largely focused on individual-level rather than area-level early life determinants of health. In this study, we linked multiple data sets to examine whether early life state-level characteristics were predictive of health and mortality decades later. The sample included 143,755 U.S. employees, for whom work life claims and administrative data were linked with early life state-of-residence and mortality. We first created a "state health risk score" (SHRS) and "state mortality risk score" (SMRS) by modeling state-level contextual characteristics with health status and mortality in a randomly selected 30% of the sample (the "training set"). We then examined the association of these scores with objective health status and mortality in later life in the remaining 70% of the sample (the "test set") using multivariate linear and Cox regressions, respectively. The association between the SHRS and adult health status was β=0.14 (95%CI: 0.084, 0.20), while the hazard ratio for the SMRS was 0.96 (95%CI: 0.93, 1.00). The association between the SHRS and health was not statistically significant in older age groups at a p-level of 0.05, and there was a statistically significantly different association for health status among movers compared to stayers. This study uses a life course perspective and supports the idea of "sensitive periods" in early life that have enduring impacts on health. It adds to the literature examining populations in the U.S. where large linked data sets are infrequently available.
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Project description:Our study aims to investigate the association between SRH and all-cause mortality, and to investigate whether the SRH-mortality association varies across different socioeconomic status (SES) groups among middle-aged and older Chinese adults. We used data from China Health and Retirement Longitudinal Study (CHARLS), including 11,762 participants for the final analysis. Cox proportional hazards regression was conducted to investigate the association between SRH status and subsequent mortality. There were 724 death events occurred. The results were shown that fair/poor SRH participants tend to die than better SRH peers (HR 1.46, 95% CI 1.12-1.91). The association only occurred in those with rural residency (HR 1.46, 95% CI 1.05-2.04), those who were literate (HR 1.65, 95% CI 1.17-2.33), those with above-average household income (HR 1.95, 95% CI 1.15-3.29) and those working in agriculture and below (HR 1.38, 95% CI 1.02-1.88). In conclusion, worse SRH may be a predictor of all-cause mortality among middle-aged and elderly Chinese, especially in people with rural residency, literacy, above-average household income and working in agriculture and below.
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Project description:Bangladesh has achieved remarkable gains in health indicators during the last four decades despite low levels of economic development. However, the persistence of inequities remains disturbing. This success was also accompanied by health and demographic transitions, which in turn brings new challenges for a nation that has yet to come to terms with pre-transition health challenges. It is therefore important to understand the causes of death and their relationship with socioeconomic status (SES).The paper aims to assess the causes of death by SES based on surveillance data from a rural area of Bangladesh, in order to understand the situation and inform policy makers and programme leaders.We analysed population-based mortality data collected from the Chakaria Health and Demographic Surveillance System in Bangladesh. The causes of death were determined by using a Bayesian-based programme for interpreting verbal autopsy findings (InterVA-4). The data included 1,391 deaths in 217,167 person-years of observation between 2010 and 2012. The wealth index constructed using household assets was used to assess the SES, and disease burdens were compared among the wealth quintiles.Analysing cause of death (CoD) revealed that non-communicable diseases (NCDs) were the leading causes of deaths (37%), followed by communicable diseases (CDs) (22%), perinatal and neonatal conditions (11%), and injury and accidents (6%); the cause of remaining 24% of deaths could not be determined. Age-specific mortality showed premature birth, respiratory infections, and drowning were the dominant causes of death for childhood mortality (0-14 years), which was inversely associated with SES (p<0.04). For adult and the elderly (15 years and older), NCDs were the leading cause of death (51%), followed by CDs (23%). For adult and the elderly, NCDs concentrated among the population from higher SES groups (p<0.005), and CDs among the lower SES groups (p<0.001).Epidemiologic transition is taking place with a shift from the dominance of CDs to NCDs. SES inequity in mortality still persists--the poor suffer from CDs in all age groups, whereas those better off suffer more from NCDs than CDs. Policy makers thus need to consider the social distribution of diseases before developing any public health action targeted towards reducing mortality and the extent of disease burden in an equitable manner.
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