Association Between Social Disadvantage and Otitis Media Treatment in US Children With Commercial Insurance.

Importance: It is well established that social disadvantage is associated with earlier, more frequent, and more severe otitis media in children. Appropriate medical and surgical treatment of otitis media can prevent hearing loss and other complications, which may affect future academic and employment opportunities in socially disadvantaged populations. Clinical treatment patterns for otitis media in the US are unclear. Objective: To describe and quantify social disparities in the treatment patterns of otitis media in children in the US. Design, Setting, and Participants: This cross-sectional study included claims data from the Optum Clinformatics Data Mart Database between January 1, 2003, and March 31, 2021, with linked inpatient, outpatient, and pharmaceutical claims for 4 831 408 children with otitis media. Exposures: Age at first otitis media diagnosis, sex, environmental allergies, gastroesophageal reflux, adenotonsillar hyperplasia, zip code, social deprivation index score, social vulnerability index score. Main Outcomes and Measures: Treatment of recurrent and suppurative otitis media in children, insertion of tympanostomy tubes, and treatment for severe complications of undertreated otitis media. The principal measure of social disadvantage was the social deprivation index. The social vulnerability index was used for sensitivity analyses to ensure external validity. Multiple logistic regression analyses were used to quantify the association of all projected variables with the study outcomes. Results: Among 4 831 408 US children with otitis media (median [IQR] age, 4 [1-8] years; 2 491 557 boys [51.57%]), 994 921 (20.59%) were treated for recurrent otitis media, 717 978 (14.86%) were treated for suppurative otitis media, 335 949 (6.95%) received tympanostomy tubes, and 10 975 (0.23%) had severe complications of otitis media. In multivariable regression models including patient factors and social indices, earlier age at diagnosis, male sex, environmental allergies, gastroesophageal reflux, and adenotonsillar hyperplasia were associated with increased treatment for otitis media, whereas social deprivation index was associated with lower odds of medical treatment for recurrent otitis media (odds ratio [OR], 0.86; 95% CI, 0.85-0.87), suppurative otitis media (OR, 0.61; 95% CI, 0.60-0.62), and insertion of tympanostomy tubes (OR, 0.76; 95% CI, 0.75-0.78) but higher odds of having severe complications (OR, 1.28; 95% CI, 1.19-1.37). Conclusions and Relevance: The findings of this cross-sectional study suggest that children with otitis media who were socially disadvantaged were less likely to receive treatment and more likely to experience complications for undertreated otitis media. As otitis media is a modifiable risk factor for hearing loss, efforts need to be made to ensure equitable access to treatment for all children.

Epigenome-wide association study and epigenetic age acceleration associated with cigarette smoking among Costa Rican adults.

Smoking-associated DNA methylation (DNAm) signatures are reproducible among studies of mostly European descent, with mixed evidence if smoking accelerates epigenetic aging and its relationship to longevity. We evaluated smoking-associated DNAm signatures in the Costa Rican Study on Longevity and Healthy Aging (CRELES), including participants from the high longevity region of Nicoya. We measured genome-wide DNAm in leukocytes, tested Epigenetic Age Acceleration (EAA) from five clocks and estimates of telomere length (DNAmTL), and examined effect modification by the high longevity region. 489 participants had a mean (SD) age of 79.4 (10.8) years, and 18% were from Nicoya. Overall, 7.6% reported currently smoking, 35% were former smokers, and 57.4% never smoked. 46 CpGs and five regions (e.g. AHRR, SCARNA6/SNORD39, SNORA20, and F2RL3) were differentially methylated for current smokers. Former smokers had increased Horvath's EAA (1.69-years; 95% CI 0.72, 2.67), Hannum's EAA (0.77-years; 95% CI 0.01, 1.52), GrimAge (2.34-years; 95% CI1.66, 3.02), extrinsic EAA (1.27-years; 95% CI 0.34, 2.21), intrinsic EAA (1.03-years; 95% CI 0.12, 1.94) and shorter DNAmTL (- 0.04-kb; 95% CI - 0.08, - 0.01) relative to non-smokers. There was no evidence of effect modification among residents of Nicoya. Our findings recapitulate previously reported and novel smoking-associated DNAm changes in a Latino cohort.

Explaining the Variance in Cardiovascular Disease Risk Factors: A Comparison of Demographic, Socioeconomic, and Genetic Predictors.

BACKGROUND: Efforts to explain the burden of cardiovascular disease (CVD) often focus on genetic factors or social determinants of health. There is little evidence on the comparative predictive value of each, which could guide clinical and public health investments in measuring genetic versus social information. We compared the variance in CVD-related outcomes explained by genetic versus socioeconomic predictors. METHODS: Data were drawn from the Health and Retirement Study (N = 8,720). We examined self-reported diabetes, heart disease, depression, smoking, and body mass index, and objectively measured total and high-density lipoprotein cholesterol. For each outcome, we compared the variance explained by demographic characteristics, socioeconomic position (SEP), and genetic characteristics including a polygenic score for each outcome and principal components (PCs) for genetic ancestry. We used R-squared values derived from race-stratified multivariable linear regressions to evaluate the variance explained. RESULTS: The variance explained by models including all predictors ranged from 3.7% to 14.3%. Demographic characteristics explained more than half this variance for most outcomes. SEP explained comparable or greater variance relative to the combination of the polygenic score and PCs for most conditions among both white and Black participants. The combination of SEP, polygenic score, and PCs performed substantially better, suggesting that each set of characteristics may independently contribute to the prediction of CVD-related outcomes. Philip R. Lee Institute for Health Policy Studies, Department of Family & Community Medicine, UCSF. CONCLUSIONS: Focusing on genetic inputs into personalized medicine predictive models, without considering measures of social context that have clear predictive value, needlessly ignores relevant information that is more feasible and affordable to collect on patients in clinical settings. See video abstract at, http://links.lww.com/EDE/B879.

Public health impacts of an imminent Red Sea oil spill.

The possibility of a massive oil spill in the Red Sea is increasingly likely. The Safer, a deteriorating oil tanker containing 1.1 million barrels of oil, has been deserted near the coast of Yemen since 2015 and threatens environmental catastrophe to a country presently in a humanitarian crisis. Here, we model the immediate public health impacts of a simulated spill. We estimate that all of Yemen's imported fuel through its key Red Sea ports would be disrupted and that the anticipated spill could disrupt clean-water supply equivalent to the daily use of 9.0-9.9 million people, food supply for 5.7-8.4 million people and 93-100% of Yemen's Red Sea fisheries. We also estimate an increased risk of cardiovascular hospitalization from pollution ranging from 5.8 to 42.0% over the duration of the spill. The spill and its potentially disastrous impacts remain entirely preventable through offloading the oil. Our results stress the need for urgent action to avert this looming disaster.

Using an Automated Electronic Health Record Score To Estimate Life Expectancy In Men Diagnosed With Prostate Cancer In The Veterans Health Administration.

OBJECTIVES: To determine if an automatically calculated electronic health record score can estimate intermediate-term life expectancy in men with prostate cancer to provide guideline concordant care. METHODS: We identified all men (n = 36,591) diagnosed with prostate cancer in 2013-2015 in the VHA. Of the 36,591, 35,364 (96.6%) had an available Care Assessment Needs (CAN) score (range: 0-99) automatically calculated in the 30 days prior to the date of diagnosis. It was designed to estimate short-term risks of hospitalization and mortality. We fit unadjusted and multivariable Cox proportional hazards regression models to determine the association between the CAN score and overall survival among men with prostate cancer. We compared CAN score performance to two established comorbidity measures: The Charlson Comorbidity Index and Prostate Cancer Comorbidity Index (PCCI). RESULTS: Among 35,364 men, the CAN score correlated with overall stage, with mean scores of 46.5 ( ± 22.4), 58.0 ( ± 24.4), and 68.1 ( ± 24.3) in localized, locally advanced, and metastatic disease, respectively. In both unadjusted and adjusted models for prostate cancer risk, the CAN score was independently associated with survival (HR = 1.23 95%CI 1.22-1.24 & adjusted HR = 1.17 95%CI 1.16-1.18 per 5-unit change, respectively). The CAN score (overall C-Index 0.74) yielded better discrimination (AUC = 0.76) than PCCI (AUC = 0.65) or Charlson Comorbidity Index (AUC = 0.66) for 5-year survival. CONCLUSION: The CAN score is strongly associated with intermediate-term survival following a prostate cancer diagnosis. The CAN score is an example of how learning health care systems can implement multi-dimensional tools to provide fully automated life expectancy estimates to facilitate patient-centered cancer care.

Leisure time activities and biomarkers of chronic stress: The mediating roles of alcohol consumption and smoking.

AIMS: Previous research found an association between leisure time activities such as arts and cultural activities and self-reported health over the life course-a measure prone to response bias. This study tested the relationship between arts and cultural activities and allostatic load, a biomarker of chronic stress, and examined risky health behaviors, including alcohol consumption and smoking, as possible mediators. METHODS: The sample consists of 8948 adults from the second wave of the United Kingdom Household Longitudinal Study, which is representative of the British population. The cross-sectional association between arts and cultural activities and allostatic load was tested with negative binomial models, and the mediation roles of alcohol consumption and smoking in the association was tested with the Karlson-Holm-Breen (KHB) decomposition method. RESULTS: Frequent participation in arts, frequent attendance of cultural events, visits to museums or galleries, and visits to historical sites have negative associations with allostatic load. The associations are mediated by lower frequency of alcohol drinking and smoking. CONCLUSIONS: Cultural capital may promote health by reducing the frequency of health risk behaviors such as drinking alcohol and smoking. Future research and public health policies should consider whether cultural capital acts as a social determinant of health to promote healthy leisure activities over the life course.

Income, inflammation and cancer mortality: a study of U.S. National Health and Nutrition Examination Survey mortality follow-up cohorts.

BACKGROUND: To estimate the relationship between inflammatory biomarkers and cancer mortality in a nationally representative sample of the U.S. population while controlling for education, occupation, and income. METHODS: Data were obtained from the U.S. National Health and Nutrition Examination Survey from 1988 to 1994 (N = 7817) and 1999-2002 (N = 2344). We fit Cox proportional hazard models to examine the relationship between C-reactive protein (CRP) and fibrinogen with cancer mortality. RESULTS: In the full Cox multivariate model, clinically raised CRP was associated with cancer mortality in NHANES 1988-1994 (> 0.99 mg/dL: 95%CI: 1.04-2.13). However, across two inflammatory biomarkers (CRP and Fibrinogen), two NHANES time periods (1998-1994 and 1999-2002) and three income levels (12 strata in total), Hazard ratio confidence intervals did not include the null only for one association: CRP and cancer mortality among low income participants from 1988 to 1994 (HR = 1.83, 95% CI: 1.10-3.04). CONCLUSIONS: We find evidence that only in one unique stratum is earlier life CRP, and not fibrinogen, associated with prospective cancer mortality. After more complete control for socioeconomic confounding, CRP and fibrinogen do not predict cancer mortality in most subpopulations.

Short-term effects of the earned income tax credit on mental health and health behaviors.

Poverty has consistently been linked to poor mental health and risky health behaviors, yet few studies evaluate the effectiveness of programs and policies to address these outcomes by targeting poverty itself. We test the hypothesis that the earned income tax credit (EITC)-the largest U.S. poverty alleviation program-improves short-term mental health and health behaviors in the months immediately after income receipt. We conducted parallel analyses in two large longitudinal national data sets: the National Health Interview Survey (NHIS, 1997-2016, N = 379,603) and the Panel Study of Income Dynamics (PSID, 1985-2015, N = 29,808). Outcomes included self-rated health, psychological distress, tobacco use, and alcohol consumption. We employed difference-in-differences analysis, a quasi-experimental technique. We exploited seasonal variation in disbursement of the EITC, which is distributed as a tax refund every spring: we compared outcomes among EITC-eligible individuals interviewed immediately after refund receipt (Feb-Apr) with those interviewed in other months more distant from refund receipt (May-Jan), "differencing out" seasonal trends among non-eligible individuals. For most outcomes, we were unable to rule out the null hypothesis that there was no short-term effect of the EITC. Findings were cross-validated in both data sets. The exception was an increase in smoking in PSID, although this finding was not robust to sensitivity analyses. While we found no short-term "check effect" of the EITC on mental health and health behaviors, others have found long-term effects on these outcomes. This may be because recipients anticipate EITC receipt and smooth their income accordingly.

A Complex Systems Model of Breast Cancer Etiology: The Paradigm II Conceptual Model.

BACKGROUND: The etiology of breast cancer is a complex system of interacting factors from multiple domains. New knowledge about breast cancer etiology continues to be produced by the research community, and the communication of this knowledge to other researchers, practitioners, decision makers, and the public is a challenge. METHODS: We updated the previously published Paradigm model (PMID: 25017248) to create a framework that describes breast cancer etiology in four overlapping domains of biologic, behavioral, environmental, and social determinants. This new Paradigm II conceptual model was part of a larger modeling effort that included input from multiple experts in fields from genetics to sociology, taking a team and transdisciplinary approach to the common problem of describing breast cancer etiology for the population of California women in 2010. Recent literature was reviewed with an emphasis on systematic reviews when available and larger epidemiologic studies when they were not. Environmental chemicals with strong animal data on etiology were also included. RESULTS: The resulting model illustrates factors with their strength of association and the quality of the available data. The published evidence supporting each relationship is made available herein, and also in an online dynamic model that allows for manipulation of individual factors leading to breast cancer (https://cbcrp.org/causes/). CONCLUSIONS: The Paradigm II model illustrates known etiologic factors in breast cancer, as well as gaps in knowledge and areas where better quality data are needed. IMPACT: The Paradigm II model can be a stimulus for further research and for better understanding of breast cancer etiology.

Predicting mortality from 57 economic, behavioral, social, and psychological factors.

Behavioral and social scientists have identified many nonbiological predictors of mortality. An important limitation of much of this research, however, is that risk factors are not studied in comparison with one another or from across different fields of research. It therefore remains unclear which factors should be prioritized for interventions and policy to reduce mortality risk. In the current investigation, we compare 57 factors within a multidisciplinary framework. These include (i) adverse socioeconomic and psychosocial experiences during childhood and (ii) socioeconomic conditions, (iii) health behaviors, (iv) social connections, (v) psychological characteristics, and (vi) adverse experiences during adulthood. The current prospective cohort investigation with 13,611 adults from 52 to 104 y of age (mean age 69.3 y) from the nationally representative Health and Retirement Study used weighted traditional (i.e., multivariate Cox regressions) and machine-learning (i.e., lasso, random forest analysis) statistical approaches to identify the leading predictors of mortality over 6 y of follow-up time. We demonstrate that, in addition to the well-established behavioral risk factors of smoking, alcohol abuse, and lack of physical activity, economic (e.g., recent financial difficulties, unemployment history), social (e.g., childhood adversity, divorce history), and psychological (e.g., negative affectivity) factors were also among the strongest predictors of mortality among older American adults. The strength of these predictors should be used to guide future transdisciplinary investigations and intervention studies across the fields of epidemiology, psychology, sociology, economics, and medicine to understand how changes in these factors alter individual mortality risk.

Quality and quantity: The association of state-level educational policies with later life cardiovascular disease.

Education is a powerful predictor of cardiovascular morbidity and mortality. While the majority of the literature has focused on years of educational attainment or degree attainment, fewer studies examine the role of educational quality in the prevention of cardiovascular disease (CVD). We tested the hypothesis that average state-level educational quality was associated with CVD, linking state-level data on educational quality with individual demographic and health data from multiple waves of the National Health and Nutrition Examination Survey (N = 34,770). We examined thirteen CVD-related outcomes-including blood pressure, cholesterol, and heart attack-to understand the multiple pathways through which educational quality may influence CVD. The primary predictor was a composite index of educational quality, combining state-level measures of student-teacher ratios, per-pupil expenditures, and school term length. We fit multivariable models, regressing each outcome on the educational quality composite index and adjusting for individual- and state-level covariates. We also assessed whether the association between state educational quality and CVD differed for less educated individuals. Overall, higher educational quality was associated with less smoking (OR = 0.86, 95%CI: 0.77, 0.97), but there was no statistically significant association for the other 12 outcomes. Interaction tests indicated that less educated individuals benefited less from higher educational quality relative to those with more education for several outcomes. Our study suggests that state-level educational quality is not strongly associated with CVD, and that this null association overall may mask heterogeneous benefits that accrue disproportionately to those with higher levels of education.

Educational attainment and cardiovascular disease in the United States: A quasi-experimental instrumental variables analysis.

BACKGROUND: There is ongoing debate about whether education or socioeconomic status (SES) should be inputs into cardiovascular disease (CVD) prediction algorithms and clinical risk adjustment models. It is also unclear whether intervening on education will affect CVD, in part because there is controversy regarding whether education is a determinant of CVD or merely correlated due to confounding or reverse causation. We took advantage of a natural experiment to estimate the population-level effects of educational attainment on CVD and related risk factors. METHODS AND FINDINGS: We took advantage of variation in United States state-level compulsory schooling laws (CSLs), a natural experiment that was associated with geographic and temporal differences in the minimum number of years that children were required to attend school. We linked census data on educational attainment (N = approximately 5.4 million) during childhood with outcomes in adulthood, using cohort data from the 1992-2012 waves of the Health and Retirement Study (HRS; N = 30,853) and serial cross-sectional data from 1971-2012 waves of the National Health and Nutrition Examination Survey (NHANES; N = 44,732). We examined self-reported CVD outcomes and related risk factors, as well as relevant serum biomarkers. Using instrumental variables (IV) analysis, we found that increased educational attainment was associated with reduced smoking (HRS ß -0.036, 95%CI: -0.06, -0.02, p < 0.01; NHANES ß -0.032, 95%CI: -0.05, -0.02, p < 0.01), depression (HRS ß -0.049, 95%CI: -0.07, -0.03, p < 0.01), triglycerides (NHANES ß -0.039, 95%CI: -0.06, -0.01, p < 0.01), and heart disease (HRS ß -0.025, 95%CI: -0.04, -0.002, p = 0.01), and improvements in high-density lipoprotein (HDL) cholesterol (HRS ß 1.50, 95%CI: 0.34, 2.49, p < 0.01; NHANES ß 0.86, 95%CI: 0.32, 1.48, p < 0.01), but increased BMI (HRS ß 0.20, 95%CI: 0.002, 0.40, p = 0.05; NHANES ß 0.13, 95%CI: 0.01, 0.32, p = 0.05) and total cholesterol (HRS ß 2.73, 95%CI: 0.09, 4.97, p = 0.03). While most findings were cross-validated across both data sets, they were not robust to the inclusion of state fixed effects. Limitations included residual confounding, use of self-reported outcomes for some analyses, and possibly limited generalizability to more recent cohorts. CONCLUSIONS: This study provides rigorous population-level estimates of the association of educational attainment with CVD. These findings may guide future implementation of interventions to address the social determinants of CVD and strengthen the argument for including educational attainment in prediction algorithms and primary prevention guidelines for CVD.

Socioeconomic gradients in cancer incidence by race and ethnicity in California, 2008-2012: the influence of tobacco use or screening detectable cancers.

PURPOSE: There are clearly documented inequalities in cancer incidence by socioeconomic position, but it is unclear whether this is due primarily to differences in tobacco exposure and screening practices or to other factors. METHODS: Our study included 741,373 incident cases of invasive cancer from 2008 to 2012 in California. We calculated age-standardized incidence rates across twelve categories of census tract poverty as a measure of socioeconomic position (SEP) for (1) all cancer sites combined, (2) sites not strongly related to tobacco use, (3) sites not related to screening, and (4) sites not related to tobacco use or screening. RESULTS: There was higher cancer incidence among those living in areas with higher levels of poverty for sites not strongly related to tobacco use or screening, among Whites, Blacks, and Asians, but not among Latinos. Among Whites there was no relationship with census tract poverty at lower levels of poverty-the relationship with cancer incidence was primarily among those in higher poverty. For Blacks and Asians, there is a more linear relationship with cancer incidence across levels of poverty. CONCLUSIONS: SEP gradients in cancer incidence remain after exclusion of cancer sites strongly related to tobacco use and screening. Our findings demonstrate a need for research on other environmental and social causes of cancer where exposures are differentially distributed by SEP.

Gender, Depression, and Blue-collar Work: A Retrospective Cohort Study of US Aluminum Manufacturers.

BACKGROUND: Industrial blue-collar workers face multiple work-related stressors, but evidence regarding the burden of mental illness among today's blue-collar men and women remains limited. METHODS: In this retrospective cohort study, we examined health and employment records for 37,183 blue- and white-collar workers employed by a single US aluminum manufacturer from 2003 to 2013. Using Cox proportional hazards regression, we modeled time to first episode of treated depression by gender and occupational class. Among cases, we modeled rates of depression-related service utilization with generalized gamma regression. RESULTS: Compared with their white-collar counterparts, blue-collar men were more likely to be treated for depression (hazard ratio [HR] = 1.3; 95% confidence interval [CI] = 1.1, 1.4) as were blue-collar women (HR = 1.4; 1.2, 1.6). Blue-collar women were most likely to be treated for depression as compared with white-collar men (HR = 3.2; 95% CI = 2.1, 5.0). However, blue-collar workers used depression-related services less frequently than their white-collar counterparts among both men (rate ratio = 0.91; 95% CI = 0.84, 0.98) and women (rate ratio = 0.82; 95% CI = 0.77, 0.88). CONCLUSIONS: Blue-collar women were more likely to be treated for depression than white-collar workers, and blue-collar women were most likely to be treated for depression compared with white-collar men. However, blue-collar men and women used depression-related healthcare services less frequently than white-collar workers. These findings underscore that blue-collar women may be uniquely susceptible to depression, and suggest that blue-collar workers may encounter barriers to care-seeking related mental illness other than their insurance status.

Socioeconomic Differences in the Epidemiologic Transition From Heart Disease to Cancer as the Leading Cause of Death in the United States, 2003 to 2015: An Observational Study.

Background: Recent data suggest that the United States is in the midst of an epidemiologic transition in the leading cause of death. Objective: To examine county-level sociodemographic differences in the transition from heart disease to cancer as the leading cause of death in the United States. Design: Observational study. Setting: U.S. death records, 2003 to 2015. Participants: Decedents aged 25 years or older, classified by racial/ethnic group. Measurements: All-cause, heart disease, and cancer mortality stratified by quintiles of county median household income. Age- and sex-adjusted mortality rates and average annual percentage of change were calculated. Results: Heart disease was the leading cause of death in 79% of counties in 2003 and 59% in 2015. Cancer was the leading cause of death in 21% of counties in 2003 and 41% in 2015. The shift to cancer as the leading cause of death was greatest in the highest-income counties. Overall, heart disease mortality rates decreased by 28% (30% in high-income counties vs. 22% in low-income counties) from 2003 to 2015, and cancer mortality rates decreased by 16% (18% in high-income counties vs. 11% in low-income counties). In the lowest-income counties, heart disease remained the leading cause of death among all racial/ethnic groups, and improvements were smaller for both heart disease and cancer. Limitation: Use of county median household income as a proxy for socioeconomic status. Conclusion: Data show that heart disease is more likely to be the leading cause of death in low-income counties. Low-income counties have not experienced the same decrease in mortality rates as high-income counties, which suggests a later transition to cancer as the leading cause of death in low-income counties. Primary Funding Source: National Institute on Minority Health and Health Disparities.

How and why studies disagree about the effects of education on health: A systematic review and meta-analysis of studies of compulsory schooling laws.

Rich literatures across multiple disciplines document the association between increased educational attainment and improved health. While quasi-experimental studies have exploited variation in educational policies to more rigorously estimate the health effects of education, there remains disagreement about whether education and health are causally linked. The aim of this study was to conduct a systematic review and meta-analysis to characterize this literature, with a focus on quasi-experimental studies of compulsory schooling laws (CSLs). Articles from 1990 to 2015 were obtained through electronic searches and manual searches of reference lists. We searched for English-language studies and included manuscripts if: (1) they involved original data analysis; (2) outcomes were health-related; and (3) the primary predictor utilized variation in CSLs. We identified 89 articles in 25 countries examining over 25 health outcomes, with over 600 individual point estimates. We systematically characterized heterogeneity on key study design features and conducted a meta-analysis of studies with comparable health outcome and exposure variables. Within countries, studies differed in terms of birth cohorts included, the measurement of health outcomes within a given category, and the type of CSL variation examined. Over 90% of manuscripts included multiple analytic techniques, such as econometric and standard regression methods, with as many as 31 "primary" models in a single study. A qualitative synthesis of study findings indicated that educational attainment has an effect on the majority of health outcomes-most beneficial, some negative-while the meta-analysis demonstrated small beneficial effects for mortality, smoking, and obesity. Future work could focus on inconsistent findings identified by this study, or review the health effects of other types of educational policies.

The association of early life socioeconomic position on breast cancer incidence and mortality: a systematic review.

OBJECTIVES: We conducted a systematic review of the literature relating early life socioeconomic position (SEP) to breast cancer incidence and mortality from a critical period and life-course trajectory perspective. METHODS: PubMed, EMBASE and Web of Science were searched to identify cohort studies that evaluated the impact of early life SEP indicators on the incidence and/or mortality from breast cancer in adulthood. RESULTS: Nine distinct studies evaluated the relationship between early life SEP and breast cancer between 1990 and 2016. Five reports assessed breast cancer incidence and five assessed breast cancer mortality as outcomes; one study assessed both incidence and mortality. While lower early life SEP was associated with reduced breast cancer incidence and increased breast cancer mortality in the US, studies conducted in Europe were unable to establish a consistent association. CONCLUSIONS: We found moderate support for the association between early life SEP and incidence and mortality from breast cancer. The impact of early life SEP on breast cancer incidence and mortality appeared to vary between countries. We urge further investigation of the role of lifelong SEP trajectories in breast cancer outcomes.

Geographic Clustering of Polygenic Scores at Different Stages of the Life Course.

We interrogate state-level clustering of polygenic scores at different points in the life course and variation in the association of mean polygenic scores in a respondent's state of birth with corresponding phenotypes. The polygenic scores for height and smoking show the most state-level clustering (2 to 4 percent) with relatively little clustering observed for the other scores. However, even the small amounts of observed clustering are potentially meaningful. The state-mean polygenic score for educational attainment is strongly associated with an individual's educational attainment net of that person's polygenic score. The ecological clustering of polygenic scores may denote a new environmental factor in gene-environment research. We conclude by discussing possible mechanisms that underlie this association and the implications of our findings for social and genetic research.

Leukocyte Telomere Length in Relation to 17 Biomarkers of Cardiovascular Disease Risk: A Cross-Sectional Study of US Adults.

BACKGROUND: Leukocyte telomere length (LTL) is a putative biological marker of immune system age, and there are demonstrated associations between LTL and cardiovascular disease. This may be due in part to the relationship of LTL with other biomarkers associated with cardiovascular disease risk. However, the strength of associations between LTL and adiposity, metabolic, proinflammatory, and cardiovascular biomarkers has not been systematically evaluated in a United States nationally representative population. METHODS AND FINDINGS: We examined associations between LTL and 17 cardiovascular biomarkers, including lipoproteins, blood sugar, circulatory pressure, proinflammatory markers, kidney function, and adiposity measures, in adults ages 20 to 84 from the cross-sectional US nationally representative 1999-2002 National Health and Nutrition Examination Survey (NHANES) (n = 7,252), statistically adjusting for immune cell type distributions. We also examine whether these associations differed systematically by age, race/ethnicity, gender, education, and income. We found that a one unit difference in the following biomarkers were associated with kilobase pair differences in LTL: BMI -0.00478 (95% CI -0.00749--0.00206), waist circumference -0.00211 (95% CI -0.00325--0.000969), percentage of body fat -0.00516 (95% CI -0.00761--0.0027), high density lipoprotein (HDL) cholesterol 0.00179 (95% CI 0.000571-0.00301), triglycerides -0.000285 (95% CI -0.000555--0.0000158), pulse rate -0.00194 (95% CI -0.00317--0.000705), C-reactive protein -0.0363 (95% CI 0.0601--0.0124), cystatin C -0.0391 (95% CI -0.0772--0.00107). When using clinical cut-points we additionally found associations between LTL and insulin resistance -0.0412 (95% CI -0.0685--0.0139), systolic blood pressure 0.0455 (95% CI 0.00137-0.0897), and diastolic blood pressure -0.0674 (95% CI -0.126--0.00889). These associations were 10%-15% greater without controlling for leukocyte cell types. There were very few differences in the associations by age, race/ethnicity, gender, education, or income. Our findings are relevant to the relationships between these cardiovascular biomarkers in the general population but not to cardiovascular disease as a clinical outcome. CONCLUSIONS: LTL is most strongly associated with adiposity, but is also associated with biomarkers across several physiological systems. LTL may thus be a predictor of cardiovascular disease through its association with multiple risk factors that are physiologically correlated with risk for development of cardiovascular disease. Our results are consistent with LTL being a biomarker of cardiovascular aging through established physiological mechanisms.