Gender and Racial/Ethnic Disparities: Cumulative Screening of Health Risk Indicators in 20-50 Year Olds in the United States

This study explored potential gender and racial/ethnic disparities in overall health risk related to 24 health risk indicators selected across six domains: socioeconomic, health status and health care, lifestyle, nutritional, clinical, and environmental. Using the 2003-2006 National Health and Nutrition Examination Surveys (NHANES), it evaluated cross-sectional data for 5,024 adults in the United States. Logistic regression models were developed to estimate prevalence odds ratios (PORs) adjusted for smoking, health insurance status, and age. Analyses evaluated disparities associated with 24 indicator variables of health risk, comparing females to males and four racial/ethnic groups to non-Hispanic Whites. Non-Hispanic Blacks and Mexican Americans were at greater risk for at least 50% of the 24 health risk indicators, including measures of socioeconomic status, health risk behaviors, poor/fair self-reported health status, multiple nutritional and clinical indicators, and blood lead levels. This demonstrates that cumulative health risk is unevenly distributed across racial/ethnic groups. A similarly high percentage (46%) of the risk factors was observed in females. Females as compared to males were more likely to have lower income, lower blood calcium, poor/fair self-reported health, more poor mental health days/month, higher medication usage and hospitalizations, and higher serum levels of some clinical indicators and blood cadmium. This analysis of cumulative health risk is responsive to calls for broader-based, more integrated assessment of health disparities that can help inform community assessments and public health policy

Biological and behavioral factors modify urinary arsenic metabolic profiles in a U.S. population

Abstract Background Because some adverse health effects associated with chronic arsenic exposure may be mediated by methylated arsenicals, interindividual variation in capacity to convert inorganic arsenic into mono- and di-methylated metabolites may be an important determinant of risk associated with exposure to this metalloid. Hence, identifying biological and behavioral factors that modify an individual’s capacity to methylate inorganic arsenic could provide insights into critical dose-response relations underlying adverse health effects. Methods A total of 904 older adults (≥45 years old) in Churchill County, Nevada, who chronically used home tap water supplies containing up to 1850 μg of arsenic per liter provided urine and toenail samples for determination of total and speciated arsenic levels. Effects of biological factors (gender, age, body mass index) and behavioral factors (smoking, recent fish or shellfish consumption) on patterns of arsenicals in urine were evaluated with bivariate analyses and multivariate regression models. Results Relative contributions of inorganic, mono-, and di-methylated arsenic to total speciated arsenic in urine were unchanged over the range of concentrations of arsenic in home tap water supplies used by study participants. Gender predicted both absolute and relative amounts of arsenicals in urine. Age predicted levels of inorganic arsenic in urine and body mass index predicted relative levels of mono- and di-methylated arsenic in urine. Smoking predicted both absolute and relative levels of arsenicals in urine. Multivariate regression models were developed for both absolute and relative levels of arsenicals in urine. Concentration of arsenic in home tap water and estimated water consumption were strongly predictive of levels of arsenicals in urine as were smoking, body mass index, and gender. Relative contributions of arsenicals to urinary arsenic were not consistently predicted by concentrations of arsenic in drinking water supplies but were more consistently predicted by gender, body mass index, age, and smoking. Conclusions These findings suggest that analyses of dose-response relations in arsenic-exposed populations should account for biological and behavioral factors that modify levels of inorganic and methylated arsenicals in urine. Evidence of significant effects of these factors on arsenic metabolism may also support mode of action studies in appropriate experimental models

Biological and behavioral factors modify urinary arsenic metabolic profiles in a U.S. population

Abstract Background Because some adverse health effects associated with chronic arsenic exposure may be mediated by methylated arsenicals, interindividual variation in capacity to convert inorganic arsenic into mono- and di-methylated metabolites may be an important determinant of risk associated with exposure to this metalloid. Hence, identifying biological and behavioral factors that modify an individual’s capacity to methylate inorganic arsenic could provide insights into critical dose-response relations underlying adverse health effects. Methods A total of 904 older adults (≥45 years old) in Churchill County, Nevada, who chronically used home tap water supplies containing up to 1850 μg of arsenic per liter provided urine and toenail samples for determination of total and speciated arsenic levels. Effects of biological factors (gender, age, body mass index) and behavioral factors (smoking, recent fish or shellfish consumption) on patterns of arsenicals in urine were evaluated with bivariate analyses and multivariate regression models. Results Relative contributions of inorganic, mono-, and di-methylated arsenic to total speciated arsenic in urine were unchanged over the range of concentrations of arsenic in home tap water supplies used by study participants. Gender predicted both absolute and relative amounts of arsenicals in urine. Age predicted levels of inorganic arsenic in urine and body mass index predicted relative levels of mono- and di-methylated arsenic in urine. Smoking predicted both absolute and relative levels of arsenicals in urine. Multivariate regression models were developed for both absolute and relative levels of arsenicals in urine. Concentration of arsenic in home tap water and estimated water consumption were strongly predictive of levels of arsenicals in urine as were smoking, body mass index, and gender. Relative contributions of arsenicals to urinary arsenic were not consistently predicted by concentrations of arsenic in drinking water supplies but were more consistently predicted by gender, body mass index, age, and smoking. Conclusions These findings suggest that analyses of dose-response relations in arsenic-exposed populations should account for biological and behavioral factors that modify levels of inorganic and methylated arsenicals in urine. Evidence of significant effects of these factors on arsenic metabolism may also support mode of action studies in appropriate experimental models

Evaluation of genetic susceptibility to childhood allergy and asthma in an African American urban population

<p>Abstract</p> <p>Background</p> <p>Asthma and allergy represent complex phenotypes, which disproportionately burden ethnic minorities in the United States. Strong evidence for genomic factors predisposing subjects to asthma/allergy is available. However, methods to utilize this information to identify high risk groups are variable and replication of genetic associations in African Americans is warranted.</p> <p>Methods</p> <p>We evaluated 41 single nucleotide polymorphisms (SNP) and a deletion corresponding to 11 genes demonstrating association with asthma in the literature, for association with asthma, atopy, testing positive for food allergens, eosinophilia, and total serum IgE among 141 African American children living in Detroit, Michigan. Independent SNP and haplotype associations were investigated for association with each trait, and subsequently assessed in concert using a genetic risk score (GRS).</p> <p>Results</p> <p>Statistically significant associations with asthma were observed for SNPs in <it>GSTM1, MS4A2</it>, and <it>GSTP1 </it>genes, after correction for multiple testing. Chromosome 11 haplotype CTACGAGGCC (corresponding to <it>MS4A2 </it>rs574700, rs1441586, rs556917, rs502581, rs502419 and <it>GSTP1 </it>rs6591256, rs17593068, rs1695, rs1871042, rs947895) was associated with a nearly five-fold increase in the odds of asthma (Odds Ratio (OR) = 4.8, <it>p </it>= 0.007). The GRS was significantly associated with a higher odds of asthma (OR = 1.61, 95% Confidence Interval = 1.21, 2.13; <it>p </it>= 0.001).</p> <p>Conclusions</p> <p>Variation in genes associated with asthma in predominantly non-African ethnic groups contributed to increased odds of asthma in this African American study population. Evaluating all significant variants in concert helped to identify the highest risk subset of this group.</p

Environmental risk factors for Toxoplasma gondii infections and the impact of latent infections on allostatic load in residents of Central North Carolina

Abstract Background Toxoplasma gondii infection can be acquired through ingestion of infectious tissue cysts in undercooked meat or environmental oocysts excreted by cats. This cross-sectional study assessed environmental risk factors for T. gondii infections and an association between latent infections and a measure of physiologic dysregulation known as allostatic load. Methods Serum samples from 206 adults in the Durham-Chapel Hill, North Carolina area were tested for immunoglobulin (IgG) responses to T. gondii using commercial ELISA kits. Allostatic load was estimated as a sum of 15 serum biomarkers of metabolic, neuroendocrine and immune functions dichotomized at distribution-based cutoffs. Vegetated land cover within 500 m of residences was estimated using 1 m resolution data from US EPA’s EnviroAtlas. Results Handling soil with bare hands at least weekly and currently owning a cat were associated with 5.3 (95% confidence limits 1.4; 20.7) and 10.0 (2.0; 50.6) adjusted odds ratios (aOR) of T. gondii seropositivity, respectively. There was also a significant positive interaction effect of handling soil and owning cats on seropositivity. An interquartile range increase in weighted mean vegetated land cover within 500 m of residence was associated with 3.7 (1.5; 9.1) aOR of T. gondii seropositivity. Greater age and consumption of undercooked pork were other significant predictors of seropositivity. In turn, T. gondii seropositivity was associated with 61% (13%; 130%) greater adjusted mean allostatic load compared to seronegative individuals. In contrast, greater vegetated land cover around residence was associated with significantly reduced allostatic load in both seronegative (p < 0.0001) and seropositive (p = 0.004) individuals. Conclusions Residents of greener areas may be at a higher risk of acquiring T. gondii infections through inadvertent ingestion of soil contaminated with cat feces. T. gondii infections may partially offset health benefits of exposure to the natural living environment

Factors associated with self-reported health: implications for screening level community-based health and environmental studies

Abstract Background Advocates for environmental justice, local, state, and national public health officials, exposure scientists, need broad-based health indices to identify vulnerable communities. Longitudinal studies show that perception of current health status predicts subsequent mortality, suggesting that self-reported health (SRH) may be useful in screening-level community assessments. This paper evaluates whether SRH is an appropriate surrogate indicator of health status by evaluating relationships between SRH and sociodemographic, lifestyle, and health care factors as well as serological indicators of nutrition, health risk, and environmental exposures. Methods Data were combined from the 2003–2006 National Health and Nutrition Examination Surveys for 1372 nonsmoking 20–50 year olds. Ordinal and binary logistic regression was used to estimate odds ratios and 95 % confidence intervals of reporting poorer health based on measures of nutrition, health condition, environmental contaminants, and sociodemographic, health care, and lifestyle factors. Results Poorer SRH was associated with several serological measures of nutrition, health condition, and biomarkers of toluene, cadmium, lead, and mercury exposure. Race/ethnicity, income, education, access to health care, food security, exercise, poor mental and physical health, prescription drug use, and multiple health outcome measures (e.g., diabetes, thyroid problems, asthma) were also associated with poorer SRH. Conclusion Based on the many significant associations between SRH and serological assays of health risk, sociodemographic measures, health care access and utilization, and lifestyle factors, SRH appears to be a useful health indicator with potential relevance for screening level community-based health and environmental studies

Sustainability, Health and Environmental Metrics: Impact on Ranking and Associations with Socioeconomic Measures for 50 U.S. Cities

Waste and materials management, land use planning, transportation and infrastructure including water and energy can have indirect or direct beneficial impacts on the environment and public health. The potential for impact, however, is rarely viewed in an integrated fashion. To facilitate such an integrated view in support of community-based policy decision making, we catalogued and evaluated associations between common, publically available, Environmental (e), Health (h), and Sustainability (s) metrics and sociodemographic measurements (n = 10) for 50 populous U.S. cities. E, H, S indices combined from two sources were derived from component (e) (h) (s) metrics for each city. A composite EHS Index was derived to reflect the integration across the E, H, and S indices. Rank order of high performing cities was highly dependent on the E, H and S indices considered. When viewed together with sociodemographic measurements, our analyses further the understanding of the interplay between these broad categories and reveal significant sociodemographic disparities (e.g., race, education, income) associated with low performing cities. Our analyses demonstrate how publically available environmental, health, sustainability and socioeconomic data sets can be used to better understand interconnections between these diverse domains for more holistic community assessments