159 research outputs found

    Social disparities in heart disease risk and survivor bias among autoworkers: an examination based on survival models and g-estimation.

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    ObjectivesTo examine gender and racial disparities in ischaemic heart disease (IHD) mortality related to metalworking fluid exposures and in the healthy worker survivor effect.MethodsA cohort of white and black men and women autoworkers in the USA was followed from 1941 to 1995 with quantitative exposure to respirable particulate matter from water-based metalworking fluids. Separate analyses used proportional hazards models and g-estimation.ResultsThe HR for IHD among black men was 3.29 (95% CI 1.49 to 7.31) in the highest category of cumulative synthetic fluid exposure. The HR for IHD among white women exposed to soluble fluid reached 2.44 (95% CI 0.96 to 6.22). However, no increased risk was observed among white men until we corrected for the healthy worker survivor effect. Results from g-estimation indicate that if white male cases exposed to soluble or synthetic fluid had been unexposed to that fluid type, then 1.59 and 1.20 years of life would have been saved on average, respectively.ConclusionsWe leveraged the strengths of two different analytic approaches to examine the IHD risks of metalworking fluids. All workers may have the same aetiological risk; however, black and female workers may experience more IHD from water-based metalworking fluid exposure because of a steeper exposure-response or weaker healthy worker survivor effect

    Socioeconomic disadvantage in childhood as a predictor of excessive gestational weight gain and obesity in midlife adulthood.

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    BackgroundLower childhood socioeconomic position is associated with greater risk of adult obesity among women, but not men. Pregnancy-related weight changes may contribute to this gender difference. The objectives of this study were to determine the associations between: 1. childhood socioeconomic disadvantage and midlife obesity; 2. excessive gestational weight gain (GWG) and midlife obesity; and 3. childhood socioeconomic disadvantage and excessive GWG, among a representative sample of childbearing women.MethodsWe constructed marginal structural models for seven measures of childhood socioeconomic position for 4780 parous women in the United States, using National Longitudinal Survey of Youth (1979-2010) data. Institute of Medicine definitions were used for excessive GWG; body mass index ≥30 at age 40 defined midlife obesity. Analyses were separated by race/ethnicity. Additionally, we estimated controlled direct effects of childhood socioeconomic disadvantage on midlife obesity under a condition of never gaining excessively in pregnancy.ResultsLow parental education, but not other measures of childhood disadvantage, was associated with greater midlife obesity among non-black non-Hispanic women. Among black and Hispanic mothers, childhood socioeconomic disadvantage was not consistently associated with midlife obesity. Excessive GWG was associated with greater midlife obesity in all racial/ethnic groups. Childhood socioeconomic disadvantage was not statistically significantly associated with excessive GWG in any group. Controlled direct effects were not consistently weaker than total effects.ConclusionsChildhood socioeconomic disadvantage was associated with adult obesity, but not with excessive gestational weight gain, and only for certain disadvantage measures among non-black non-Hispanic mothers. Prevention of excessive GWG may benefit all groups through reducing obesity, but excessive GWG does not appear to serve as a mediator between childhood socioeconomic position and adult obesity in women

    Differences in the association of cardiovascular risk factors with education: a comparison of Costa Rica (CRELES) and the USA (NHANES)

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    artículo (arbitrado)--Universidad de Costa Rica. Instituto de Investigaciones en Salud, 2009Background Despite different levels of economic development, Costa Rica and the USA have similar mortalities among adults. However, in the USA there are substantial differences in mortality by educational attainment, and in Costa Rica there are only minor differences. This contrast motivates an examination of behavioural and biological correlates underlying this difference. Methods The authors used data on adults aged 60 and above from the Costa Rican Longevity and Healthy Ageing Study (CRELES) (n¼2827) and from the US National Health and Nutrition Examination Survey (NHANES) (n¼5607) to analyse the cross-sectional association between educational level and the following risk factors for cardiovascular disease (CVD): ever smoked, current smoker, sedentary, high saturated fat, high carbohydrates, high calorie diet, obesity, severe obesity, large waist circumference, HDL cholesterol, LDL cholesterol, triglycerides, hemoglobin A1c, fasting glucose, C-reactive protein, systolic blood pressure and BMI. Results There were significantly fewer hazardous levels of risk biomarkers at higher levels of education for more than half (10 out of 17) of the risk factors in the USA, but for less than a third of the outcomes in Costa Rica (five out of 17). Conclusions These results are consistent with the context-specific nature of educational differences in risk factors for CVD and with a non-uniform nature of association of CVD risk factors with education within countries. Our results also demonstrate that social equity in mortality is achieved without uniform equity in all risk factors.Universidad de Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias de la Salud::Instituto de Investigaciones en Salud (INISA

    The Fall and Rise of US Inequities in Premature Mortality: 1960–2002

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    Nancy Krieger and colleagues found evidence of decreasing, and then increasing or stagnating, socioeconomic and racial inequities in US premature mortality and infant death from 1960 to 2002

    Genetic vulnerability to diabetes and obesity: does education offset the risk?

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    The prevalence of type 2 diabetes (T2D) and obesity has recently increased dramatically. These common diseases are likely to arise from the interaction of multiple genetic, socio-demographic and environmental risk factors. While previous research has found genetic risk and education to be strong predictors of these diseases, few studies to date have examined their joint effects. This study investigates whether education modifies the association between genetic background and risk for type 2 diabetes (T2D) and obesity. Using data from non-Hispanic Whites in the Health and Retirement Study (HRS, n = 8398), we tested whether education modifies genetic risk for obesity and T2D, offsetting genetic effects; whether this effect is larger for individuals who have high risk for other (unobserved) reasons, i.e., at higher quantiles of HbA1c and BMI; and whether effects differ by gender. We measured T2D risk using Hemoglobin A1c (HbA1c) level, and obesity risk using body-mass index (BMI). We constructed separate genetic risk scores (GRS) for obesity and diabetes respectively based on the most current available information on the single nucleotide polymorphism (SNPs) confirmed as genome-wide significant predictors for BMI (29 SNPs) and diabetes risk (39 SNPs). Linear regression models with years of schooling indicate that the effect of genetic risk on HbA1c is smaller among people with more years of schooling and larger among those with less than a high school (HS) degree compared to HS degree-holders. Quantile regression models show that the GRS × education effect systematically increased along the HbA1c outcome distribution; for example the GRS × years of education interaction coefficient was −0.01 (95% CI = −0.03, 0.00) at the 10th percentile compared to −0.03 (95% CI = −0.07, 0.00) at the 90th percentile. These results suggest that education may be an important socioeconomic source of heterogeneity in responses to genetic vulnerability to T2D

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

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    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

    Potential for allocative harm in an environmental justice data tool

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    Neighborhood-level screening algorithms are increasingly being deployed to inform policy decisions. We evaluate one such algorithm, CalEnviroScreen - designed to promote environmental justice and used to guide hundreds of millions of dollars in public funding annually - assessing its potential for allocative harm. We observe the model to be sensitive to subjective model decisions, with 16% of tracts potentially changing designation, as well as financially consequential, estimating the effect of its positive designations as a 104% (62-145%) increase in funding, equivalent to \$2.08 billion (\$1.56-2.41 billion) over four years. We also observe allocative tradeoffs and susceptibility to manipulation, raising ethical concerns. We recommend incorporating sensitivity analyses to mitigate allocative harm and accountability mechanisms to prevent misuse
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