Outcome of pregnancy oral glucose tolerance test and preterm birth.

BACKGROUND: Gestational diabetes is associated with adverse outcomes such as preterm birth (<37 weeks). However, there is no international consensus on screening criteria or diagnostic levels for gestational diabetes, and it is unknown whether body mass index (BMI) or obesity modifies the relation between glucose level and preterm birth. METHODS: We studied a pregnancy cohort restricted to two Danish regions from the linked Danish Medical Birth Register to study associations between glucose measurements from the 2-hour post-load 75-gram oral glucose tolerance test (one-step approach) and preterm birth from 2004-2018. In Denmark, gestational diabetes screening is a targeted strategy for mothers with identified risk factors. We used Poisson regression to estimate rate ratios (RR) of preterm birth with z-standardized glucose measurements. We assessed effect measure modification by stratifying analyses and testing for heterogeneity. RESULTS: Among 11,337 pregnancies (6.2% delivered preterm), we observed an adjusted preterm birth RR of 1.2 (95% CI: 1.1-1.3) for a 1 standard deviation glucose increase of 1.4 mmol/L from the mean 6.7 mmol/L. There was evidence for effect measure modification by obesity, e.g., adjusted RR for non-obese (BMI <30): 1.2 (95%CI: 1.1-1.3) vs. obese (BMI ≥30): 1.3 (95%CI: 1.2-1.5), P=0.05 for heterogeneity. CONCLUSIONS: Among mothers screened for gestational diabetes, increased glucose levels, even those below the diagnostic level for gestational diabetes in Denmark, were associated with increased preterm birth risk. Obesity (BMI ≥30) may be an effect measure modifier, not just a confounder, of the relation between blood glucose and preterm birth risk.

Underlying Reasons for Primary Care Visits Where Chlamydia Testing Was Performed in the United States, 2019 to 2022.

BACKGROUND: In the United States, most chlamydia cases are reported from non-sexually transmitted disease clinics, and there is limited information focusing on the reasons for chlamydia testing in private settings. These analyses describe clinical visits to primary care providers where chlamydia testing was performed to help discern between screening and diagnostic testing for chlamydia. METHODS: Using the largest primary care clinical registry in the United States, the PRIME registry, chlamydia tests were identified using Current Procedural Terminology procedure codes and categorized as diagnostic testing for sexually transmitted infection (STI)-related symptoms, screening for chlamydia, or "other," based on Classification of Diseases, Tenth Revision Evaluation and Management codes selected for visits. RESULTS: Of 120,013 clinical visits with chlamydia testing between January 1, 2019, and December 31, 2022, 70.4% were women; 20.6% were with STI-related symptoms, 59.9% were for screening, and 19.5% for "other" reasons. Of those 120,013 clinical visits with chlamydia testing, the logit model showed that patients were significantly more likely to have STI-related symptoms if they were female than male, non-Hispanic Black than non-Hispanic White, aged 15 to 24 years than aged ≥45 years, and resided in the South than in the Northeast. CONCLUSION: It is important to know what proportion of chlamydial infections is identified through screening programs and to have this information stratified by demographics. The inclusion of laboratory results could further facilitate a better understanding of the impact of chlamydia screening programs on the identification and treatment of chlamydia in private office settings in the United States.

Groundwater constituents and the incidence of kidney cancer.

BACKGROUND: Kidney cancer incidence demonstrates significant geographic variation suggesting a role for environmental risk factors. This study sought to evaluate associations between groundwater exposures and kidney cancer incidence. METHODS: The authors identified constituents from 18,506 public groundwater wells in all 58 California counties measured in 1996-2010, and obtained county-level kidney cancer incidence data from the California Cancer Registry for 2003-2017. The authors developed a water-wide association study (WWAS) platform using XWAS methodology. Three cohorts were created with 5 years of groundwater measurements and 5-year kidney cancer incidence data. The authors fit Poisson regression models in each cohort to estimate the association between county-level average constituent concentrations and kidney cancer, adjusting for known risk factors: sex, obesity, smoking prevalence, and socioeconomic status at the county level. RESULTS: Thirteen groundwater constituents met stringent WWAS criteria (a false discovery rate <0.10 in the first cohort, followed by p values <.05 in subsequent cohorts) and were associated with kidney cancer incidence. The seven constituents directly related to kidney cancer incidence (and corresponding standardized incidence ratios) were chlordane (1.06; 95% confidence interval [CI], 1.02-1.10), dieldrin (1.04; 95% CI, 1.01-1.07), 1,2-dichloropropane (1.04; 95% CI, 1.02-1.05), 2,4,5-TP (1.03; 95% CI, 1.01-1.05), glyphosate (1.02; 95% CI, 1.01-1.04), endothall (1.02; 95% CI, 1.01-1.03), and carbaryl (1.02; 95% CI, 1.01-1.03). Among the six constituents inversely related to kidney cancer incidence, the standardized incidence ratio furthest from the null was for bromide (0.97; 95% CI, 0.94-0.99). CONCLUSIONS: This study identified several groundwater constituents associated with kidney cancer. Public health efforts to reduce the burden of kidney cancer should consider groundwater constituents as environmental exposures that may be associated with the incidence of kidney cancer.

Trends and inequities in the diagnosis and treatment of poststroke depression: a retrospective cohort study of privately insured patients in the USA, 2003-2020.

BACKGROUND: Depression is a common neuropsychiatric consequence of stroke, but there is little empiric evidence regarding clinical diagnosis and management of poststroke depression. METHODS: Retrospective cohort study among 831 471 privately insured patients with first stroke in the USA from 2003 to 2020. We identified diagnoses of poststroke depression using codes from the International Classification of Diseases. We identified treatment based on prescriptions for antidepressants. We used Cox proportional hazards regression analysis to examine rates of poststroke depression diagnosis by gender, age and race/ethnicity. Among individuals who received a diagnosis of poststroke depression, we estimated treatment rates by gender, race/ethnicity and age using negative binomial regression analysis. RESULTS: Annual diagnosis and treatment rates for poststroke depression increased from 2003 to 2020 (both p for trend<0.001). Diagnosis rates were higher in women than men (HR 1.53, 95% CI 1.51 to 1.55), lower among members of racial/ethnic minorities (vs white patients: Asian HR 0.63, 95% CI 0.60 to 0.66; Black HR 0.76, 95% CI 0.74 to 0.78; Hispanic HR 0.88, 95% CI 0.86 to 0.90) and varied by age. Among individuals diagnosed with poststroke depression, 69.8% were prescribed an antidepressant. Rates of treatment were higher in women vs men (rate ratio, RR=1.19, 95% CI: 1.17 to 1.21), lower among members of racial/ethnic minorities (vs white patients: Asian RR 0.85, 95% CI 0.80 to 0.90; Black RR 0.92, 95% CI 0.89 to 0.94; Hispanic RR 0.96, 95% CI 0.93 to 0.99) and higher among older patients. CONCLUSIONS: In this insured population, we identify potential inequities in clinical management of poststroke depression by gender, race/ethnicity and age that may reflect barriers other than access to healthcare.

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.

What to Do When Everything Happens at Once: Analytic Approaches to Estimate the Health Effects of Co-Occurring Social Policies.

Social policies have great potential to improve population health and reduce health disparities. Increasingly, those doing empirical research have sought to quantify the health effects of social policies by exploiting variation in the timing of policy changes across places. Multiple social policies are often adopted simultaneously or in close succession in the same locations, creating co-occurrence that must be handled analytically for valid inferences. Although this is a substantial methodological challenge for researchers aiming to isolate social policy effects, only in a limited number of studies have researchers systematically considered analytic solutions within a causal framework or assessed whether these solutions are being adopted. We designated 7 analytic solutions to policy co-occurrence, including efforts to disentangle individual policy effects and efforts to estimate the combined effects of co-occurring policies. We used an existing systematic review of social policies and health to evaluate how often policy co-occurrence is identified as a threat to validity and how often each analytic solution is applied in practice. Of the 55 studies, only in 17 (31%) did authors report checking for any co-occurring policies, although in 36 studies (67%), at least 1 approach was used that helps address policy co-occurrence. The most common approaches were adjusting for measures of co-occurring policies; defining the outcome on subpopulations likely to be affected by the policy of interest (but not other co-occurring policies); and selecting a less-correlated measure of policy exposure. As health research increasingly focuses on policy changes, we must systematically assess policy co-occurrence and apply analytic solutions to strengthen studies on the health effects of social policies.

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.

A US State Index of Successful Aging: Differences Between States and Over Time.

Policy Points The focus of successful aging is on the social contexts that enable individuals to be productively engaged and secure, with an emphasis on equity. There is currently no index to measure progress towards this goal at the US state level. We developed an empirical index for the evaluation of US state adaptation to societal aging across five critical domains that support successful population aging: (1) productivity and engagement, (2) security, (3) equity, (4) cohesion, and (5) well-being. Our index shows substantial variability over time and is not overly influenced by the performance of an individual domain. This suggests that it can be used to monitor state progress over time toward the goal of supporting successful aging. Rather than a major national trend, there are large between-state differences and changes in our index over time. This suggests individual US state policies and programs, as well as local economic conditions, may have a substantial impact on adaptations to societal aging. CONTEXT: Although it is recognized that aspects of US state environments impact the likelihood that older adults age successfully, there is currently no reliable and comprehensive measure of contexts that best support successful aging at a state level. The current project adapts a multidimensional index previously used to assess adaptation to successful aging in developed countries and applies it to the 50 US states and the District of Columbia. METHODS: We obtained data from multiple sources for all 50 US states and the District of Columbia from 2003 to 2017 in order to measure five distinct domains that define successful population aging: (1) productivity and engagement, (2) security, (3) equity, (4) cohesion, and (5) well-being. We created a ranking of states for the year 2017 based on these domains, and also examined how individual US state rankings changed over time from 2003 to 2017. FINDINGS: The level of adaptation to successful aging varied substantially between states and over time. The highest-ranked states in 2017 were Vermont, Hawaii, Iowa, Colorado, and New Hampshire, and the lowest-ranked states were Louisiana, Arkansas, Kentucky, West Virginia, and Mississippi. Mississippi, South Carolina, Iowa, Arizona, and Delaware had the greatest improvement in their ranking over the period of 2003 to 2017. Our findings were generally robust to the weighting scheme used and were not overly influenced by any particular domain. CONCLUSIONS: The US State Index of Successful Aging can be used to monitor US state progress in promoting the well-being and health of aging populations. Factors driving the changes in the index remain to be elucidated.

Long-Term Effects of Local-Area New Deal Work Relief in Childhood on Educational, Economic, and Health Outcomes Over the Life Course: Evidence From the Wisconsin Longitudinal Study.

The economic characteristics of one's childhood neighborhood have been found to determine long-term well-being. Policies enacted during childhood may change neighborhood trajectories and thus impact long-term outcomes for children. We use individual-level data from the Wisconsin Longitudinal Study to examine the enduring consequences of childhood exposure to local-area New Deal emergency employment work-relief activity. Our outcomes include adolescent cognition, educational attainment, midlife income, health behaviors, late-life cognition, and mortality. We find that children (ages 0-3) living in neighborhoods with moderate work-relief activity in 1940 had higher adolescent IQ scores, had higher class rank, and were more likely to obtain at least a bachelor's degree. We find enduring benefits for midlife income and late-life cognition for males who grew up in areas with a moderate amount of work relief. We find mixed results for males who grew up in the most disadvantaged areas with the highest levels of work-relief activity. These children had similar educational outcomes as those in the most advantaged districts with the lowest work-relief activity but had higher adult smoking rates. Our findings provide some of the first evidence of the long-term consequences of New Deal policies on children's long-term life course outcomes.

Anomalously warm weather and acute care visits in patients with multiple sclerosis: A retrospective study of privately insured individuals in the US.

BACKGROUND: As the global climate changes in response to anthropogenic greenhouse gas emissions, weather and temperature are expected to become increasingly variable. Although heat sensitivity is a recognized clinical feature of multiple sclerosis (MS), a chronic demyelinating disorder of the central nervous system, few studies have examined the implications of climate change for patients with this disease. METHODS AND FINDINGS: We conducted a retrospective cohort study of individuals with MS ages 18-64 years in a nationwide United States patient-level commercial and Medicare Advantage claims database from 2003 to 2017. We defined anomalously warm weather as any month in which local average temperatures exceeded the long-term average by ≥1.5°C. We estimated the association between anomalously warm weather and MS-related inpatient, outpatient, and emergency department visits using generalized log-linear models. From 75,395,334 individuals, we identified 106,225 with MS. The majority were women (76.6%) aged 36-55 years (59.0%). Anomalously warm weather was associated with increased risk for emergency department visits (risk ratio [RR] = 1.043, 95% CI: 1.025-1.063) and inpatient visits (RR = 1.032, 95% CI: 1.010-1.054). There was limited evidence of an association between anomalously warm weather and MS-related outpatient visits (RR = 1.010, 95% CI: 1.005-1.015). Estimates were similar for men and women, strongest among older individuals, and exhibited substantial variation by season, region, and climate zone. Limitations of the present study include the absence of key individual-level measures of socioeconomic position (i.e., race/ethnicity, occupational status, and housing quality) that may determine where individuals live-and therefore the extent of their exposure to anomalously warm weather-as well as their propensity to seek treatment for neurologic symptoms. CONCLUSIONS: Our findings suggest that as global temperatures rise, individuals with MS may represent a particularly susceptible subpopulation, a finding with implications for both healthcare providers and systems.

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.

The role of cortisol in ischemic heart disease, ischemic stroke, type 2 diabetes, and cardiovascular disease risk factors: a bi-directional Mendelian randomization study.

BACKGROUND: Cortisol, a steroid hormone frequently used as a biomarker of stress, is associated with cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM). To clarify whether cortisol causes these outcomes, we assessed the role of cortisol in ischemic heart disease (IHD), ischemic stroke, T2DM, and CVD risk factors using a bi-directional Mendelian randomization (MR) study. METHODS: Single nucleotide polymorphisms (SNPs) strongly (P < 5 × 10-6) and independently (r2 < 0.001) predicting cortisol were obtained from the CORtisol NETwork (CORNET) consortium (n = 12,597) and two metabolomics genome-wide association studies (GWAS) (n = 7824 and n = 2049). They were applied to GWAS of the primary outcomes (IHD, ischemic stroke and T2DM) and secondary outcomes (adiposity, glycemic traits, blood pressure and lipids) to obtain estimates using inverse variance weighting, with weighted median, MR-Egger, and MR-PRESSO as sensitivity analyses. Conversely, SNPs predicting IHD, ischemic stroke, and T2DM were applied to the cortisol GWAS. RESULTS: Genetically predicted cortisol (based on 6 SNPs from CORNET; F-statistic = 28.3) was not associated with IHD (odds ratio (OR) 0.98 per 1 unit increase in log-transformed cortisol, 95% confidence interval (CI) 0.93-1.03), ischemic stroke (0.99, 95% CI 0.91-1.08), T2DM (1.00, 95% CI 0.96-1.04), or CVD risk factors. Genetically predicted IHD, ischemic stroke, and T2DM were not associated with cortisol. CONCLUSIONS: Contrary to observational studies, genetically predicted cortisol was unrelated to IHD, ischemic stroke, T2DM, or CVD risk factors, or vice versa. Our MR results find no evidence that cortisol plays a role in cardiovascular risk, casting doubts on the cortisol-related pathway, although replication is warranted.

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.

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.

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.

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.

Life-course BMI and biomarkers in persons aged 60 years or older: a comparison of the USA and Costa Rica.

OBJECTIVE: There is a large literature linking current BMI to levels of cardiovascular risk biomarkers, but it is unknown whether measures of BMI earlier in the life course and maximum BMI are predictive of current levels of biomarkers. The objective of the current study was to determine how current, maximum and age-25 BMI among individuals over the age of 60 years are associated with their current levels of cardiovascular risk biomarkers. DESIGN: Cross-sectional study with retrospective recall. SETTING: Costa Rica (n 821) and the USA (n 4110). SUBJECTS: Nationally representative samples of adults aged 60 years or over. RESULTS: We used regression models to examine the relationship between multiple meaures of BMI with four established cardiovascular risk biomarkers. The most consistent predictor of current levels of systolic blood pressure, TAG and HDL-cholesterol was current BMI. However, maximum BMI was the strongest predictor of glycosylated Hb (HbA1c) and was also related to HDL-cholesterol and TAG. HbA1c was independent of current BMI. We found that these relationships are consistent between Costa Rica and the USA for HbA1c and for HDL-cholesterol. CONCLUSIONS: Current levels of cardiovascular risk biomarkers are not only the product of current levels of BMI, but also of maximum lifetime BMI, particularly for levels of HbA1c and for HDL-cholesterol. Managing maximum obtained BMI over the life course may be most critical for maintaining the healthiest levels of cardiovascular risk.

Similarities in Maternal Weight and Birth Weight Across Pregnancies and Across Sisters.

Objectives The current study examined how prepregnancy body mass index (BMI), gestational weight gain, and birth weight cluster between births within women and between women who are sisters. Methods Using data from the National Longitudinal Survey of Youth 1979 cohort, we utilized nested, multivariable hierarchical linear models to examine the correlation of these three outcomes between births (n = 6006) to women (n = 3605) and sisters (n = 3170) so that we can quantify the clustering by sibship and by woman for these three pregnancy-related outcomes. Results After controlling for confounding covariates, prepregnancy BMI (intraclass correlation (ICC) 0.24, 95% CI 0.16, 0.32), gestational weight gain (ICC 0.23, 95% CI 0.16, 0.31), and infant's birthweight (ICC 0.07, 95% CI 0.003, 0.13) were correlated between sisters. Additionally, all three outcomes were significantly correlated between births for each sister, suggesting that prepregnancy BMI (ICC 0.82, 95% CI 0.81, 0.83), gestational weight gain (ICC 0.45, 95% CI 0.42, 0.49), and birth weight (ICC 0.31, 95% CI 0.28, 0.35) track between pregnancies in the same woman. Conclusions for Practice The observed clustering both within women and between sisters suggests that shared genetic and environmental factors among sisters play a role in pregnancy outcomes above and beyond that of women's own genetic and environmental factors. Findings suggest that asking a woman about her sisters' pregnancy outcomes could provide insight into the possible outcomes for her current pregnancy. Future research should test if collecting such a family history and providing tailored clinical recommendations accordingly would be useful.