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Background: Comparisons of incidence and mortality rates are the metrics used most commonly to define cancer-related racial disparities. In the US, and particularly in South Carolina, these largely disfavor African Americans (AAs). Computed from readily available data sources, the mortality-to-incidence rate ratio (MIR) provides a population-based indicator of survival.Methods: South Carolina Central Cancer Registry incidence data and Vital Registry death data were used to construct MIRs. ArcGIS 9.2 mapping software was used to map cancer MIRs by sex and race for 8 Health Regions within South Carolina for all cancers combined and for breast, cervical, colorectal, lung, oral, and prostate cancers.Results: Racial differences in cancer MIRs were observed for both sexes for all cancers combined and for most individual sites. The largest racial differences were observed for female breast, prostate, and oral cancers, and AAs had MIRs nearly twice those of European Americans (EAs).Conclusions: Comparing and mapping race- and sex-specific cancer MIRs provides a powerful way to observe the scope of the cancer problem. By using these methods, in the current study, AAs had much higher cancer MIRs compared with EAs for most cancer sites in nearly all regions of South Carolina. Future work must be directed at explaining and addressing the underlying differences in cancer outcomes by region and race. MIR mapping allows for pinpointing areas where future research has the greatest likelihood of identifying the causes of large, persistent, cancer-related disparities. Other regions with access to high-quality data may find it useful to compare MIRs and conduct MIR mapping. [ABSTRACT FROM AUTHOR]

Child sexual abuse (CSA) is a widespread problem that has been associated with a variety of negative health outcomes. There has been a call for prevention of first occurrences of CSA. Public health provides a unique framework for conceptualizing and implementing these prevention efforts. This article explains a model of the public health approach to prevention and illustrates the applicability of this model to CSA. The Centers for Disease Control and Prevention convened a panel of experts to advise the agency about raising awareness of CSA as a public health problem. A summary of the recommendations developed by this expert panel is presented. [ABSTRACT FROM AUTHOR]

Abstract Background Youth with diabetes are at increased risk for obesity and cardiovascular disease complications. However, less is known about the influence of built food environment on health outcomes in this population. The aim of this study was to explore the associations of accessibility and availability of supermarkets and fast food outlets with Body Mass Index (BMI) z-score and waist circumference among youth with diabetes. Methods Information on residential location and adiposity measures (BMI z-score and waist circumference) for 845 youths with diabetes residing in South Carolina was obtained from the South Carolina site of the SEARCH for Diabetes in Youth study. Food outlets data obtained from the South Carolina Department of Health and Environmental Control and InfoUSA were merged based on names and addresses of the outlets. The comprehensive data on franchised supermarket and fast food outlets was then used to construct three accessibility and availability measures around each youth’s residence. Results Increased number and density of chain supermarkets around residence location were associated with lower BMI z-score and waist circumference among youth with diabetes. For instance, for a female child of 10 years of age with height of 54.2 inches and weight of 70.4 pounds, lower supermarket density around residence location was associated with about 2.8–3.2 pounds higher weight, when compared to female child of same age, height and weight with highest supermarket density around residence location. Similarly, lower supermarket density around residence location was associated with a 3.5–3.7 centimeter higher waist circumference, when compared to residence location with the highest supermarket density. The associations of number and density of chain fast food outlets with adiposity measures, however, were not significant. No significant associations were observed between distance to the nearest supermarket and adiposity measures. However, contrary to our expectation, increased distance to the nearest fast food outlet was associated with higher BMI z-score, but not with waist circumference. Conclusions Food environments conducive to healthy eating may significantly influence health behaviors and outcomes. Efforts to increase the availability of supermarkets providing options/selections for health-promoting foods may significantly improve the dietary intake and reduce adiposity among youth with diabetes.

Abstract Background European ecologic studies suggest higher socioeconomic status is associated with higher incidence of type 1 diabetes. Using data from a case-control study of diabetes among racially/ethnically diverse youth in the United States (U.S.), we aimed to evaluate the independent impact of neighborhood characteristics on type 1 diabetes risk. Data were available for 507 youth with type 1 diabetes and 208 healthy controls aged 10-22 years recruited in South Carolina and Colorado in 2003-2006. Home addresses were used to identify Census tracts of residence. Neighborhood-level variables were obtained from 2000 U.S. Census. Multivariate generalized linear mixed models were applied. Results Controlling for individual risk factors (age, gender, race/ethnicity, infant feeding, birth weight, maternal age, number of household residents, parental education, income, state), higher neighborhood household income (p = 0.005), proportion of population in managerial jobs (p = 0.02), with at least high school education (p = 0.005), working outside the county (p = 0.04) and vehicle ownership (p = 0.03) were each independently associated with increased odds of type 1 diabetes. Conversely, higher percent minority population (p = 0.0003), income from social security (p = 0.002), proportion of crowded households (0.0497) and poverty (p = 0.008) were associated with a decreased odds. Conclusions Our study suggests that neighborhood characteristics related to greater affluence, occupation, and education are associated with higher type 1 diabetes risk. Further research is needed to understand mechanisms underlying the influence of neighborhood context.

Abstract Background There is increasing interest in the study of place effects on health, facilitated in part by geographic information systems. Incomplete or missing address information reduces geocoding success. Several geographic imputation methods have been suggested to overcome this limitation. Accuracy evaluation of these methods can be focused at the level of individuals and at higher group-levels (e.g., spatial distribution). Methods We evaluated the accuracy of eight geo-imputation methods for address allocation from ZIP codes to census tracts at the individual and group level. The spatial apportioning approaches underlying the imputation methods included four fixed (deterministic) and four random (stochastic) allocation methods using land area, total population, population under age 20, and race/ethnicity as weighting factors. Data included more than 2,000 geocoded cases of diabetes mellitus among youth aged 0-19 in four U.S. regions. The imputed distribution of cases across tracts was compared to the true distribution using a chi-squared statistic. Results At the individual level, population-weighted (total or under age 20) fixed allocation showed the greatest level of accuracy, with correct census tract assignments averaging 30.01% across all regions, followed by the race/ethnicity-weighted random method (23.83%). The true distribution of cases across census tracts was that 58.2% of tracts exhibited no cases, 26.2% had one case, 9.5% had two cases, and less than 3% had three or more. This distribution was best captured by random allocation methods, with no significant differences (p-value > 0.90). However, significant differences in distributions based on fixed allocation methods were found (p-value < 0.0003). Conclusion Fixed imputation methods seemed to yield greatest accuracy at the individual level, suggesting use for studies on area-level environmental exposures. Fixed methods result in artificial clusters in single census tracts. For studies focusing on spatial distribution of disease, random methods seemed superior, as they most closely replicated the true spatial distribution. When selecting an imputation approach, researchers should consider carefully the study aims.

Abstract Background Interest in the development of statistical methods for disease cluster detection has experienced rapid growth in recent years. Evaluations of statistical power provide important information for the selection of an appropriate statistical method in environmentally-related disease cluster investigations. Published power evaluations have not yet addressed the use of models for focused cluster detection and have not fully investigated the issues of disease cluster scale and shape. As meteorological and other factors can impact the dispersion of environmental toxicants, it follows that environmental exposures and associated diseases can be dispersed in a variety of spatial patterns. This study simulates disease clusters in a variety of shapes and scales around a centrally located single pollution source. We evaluate the power of a range of focused cluster tests and generalized linear models to detect these various cluster shapes and scales for count data. Results In general, the power of hypothesis tests and models to detect focused clusters improved when the test or model included parameters specific to the shape of cluster being examined (i.e. inclusion of a function for direction improved power of models to detect clustering with an angular effect). However, power to detect clusters where the risk peaked and then declined was limited. Conclusion Findings from this investigation show sizeable changes in power according to the scale and shape of the cluster and the test or model applied. These findings demonstrate the importance of selecting a test or model with functions appropriate to detect the spatial pattern of the disease cluster.

Objectives: Within the remote region of Ann Township in Myanmar's Rakhine State, malaria prevalence has remained steady at ∼10% of the population from 2016-2019. Previous studies have linked areas of higher malaria prevalence in the region to heavily forested areas, however, little is known about how people live, work, and move through these areas. This work aims to disentangle landscape from land use in regard to malaria exposure., Methods: We investigated the roles of forest cover, forest loss, and land use activities with malaria prevalence through the combined use of land use surveys, malaria surveillance, and satellite earth observations., Results: Our results confirm previous research that linked areas of high forest cover with high malaria prevalence. However, areas experiencing high levels of deforestation were not associated with malaria prevalence. The land use factors that contribute most significantly to increased malaria risk remained those which put people in direct contact with forests, including conducting forest chores, having an outdoor job, and having a primary occupation in the logging and/or plantation industry., Conclusion: Malaria prevention methods in Myanmar should focus on anyone who lives near forests or engages in land use activities that bring them within proximity of forested landscapes, whether through occupation or chores., Competing Interests: The authors have no competing interests to declare., (© 2023 The Author(s).)

Background: Most U.S. studies that report racial/ethnic disparities in increased risk of low birth weight associated with air pollution exposures have been conducted in California or northeastern states and/or urban areas, limiting generalizability of study results. Few of these studies have examined maternal racial/ethnic groups other than Non-Hispanic Black, non-Hispanic White and Hispanic, nor have they included paternal race. We aimed to examine the independent effects of PM 2.5 on birth weight among a nationally representative sample of U.S. singleton infants and how both maternal and paternal race/ethnicity modify relationships between prenatal PM 2.5 exposures and birth outcomes., Methods: We used data from the Early Childhood Longitudinal Study, Birth Cohort (ECLS-B), a longitudinal nationally representative cohort of 10,700 U.S. children born in 2001, which we linked to U.S.EPA's Community Multi-scale Air Quality (CMAQ)-derived predicted daily PM2.5 concentrations at the centroid of each Census Bureau Zip Code Tabulation Area (ZCTA) for maternal residences. We examined relationships between term birthweight (TBW) , term low birthweight rate (TLBW) and gestational PM 2.5 pollutant using multivariate regression models. Effect modification of air pollution exposures on birth outcomes by maternal and paternal race was evaluated using stratified models. All analyses were conducted with sample weights to provide national-scale estimates., Results: The majority of mothers were White (61%). Fourteen percent of mothers identified as Black, 21% as Hispanic, 3% Asian American and Pacific Islander (AAPI) and 1% American Indian and Alaskan Native (AIAN). Fathers were also racially/ethnically diverse with 55% identified as White Non-Hispanic, 10% as Black Non-Hispanic, 19% as Hispanic, 3% as AAPI and 1% as AIAN. Results from the chi-square and ANOVA tests of significance for racial/ethnic differences indicate disparities in prenatal exposures and birth outcomes by both maternal and paternal race/ethnicity. Prenatal PM 2.5 was associated with reduced birthweights during second and third trimester and over the entire gestational period in adjusted regression models, although results did not reach statistical significance. In models stratified by maternal race and paternal race, one unit increase in PM 2.5 was statistically significantly associated with lower birthweights among AAPI mothers, -5.6 g (95% CI:-10.3, -1.0 g) and AAPI fathers, -7.6 g (95% CI: -13.1, -2.1 g) during 3 rd trimester and among births where father's race was not reported, -14.2 g (95% CI: -24.0, -4.4 g)., Conclusions: These data suggest that paternal characteristics should be used, in addition to maternal characteristics, to describe the risks of adverse birth outcomes. Additionally, our study suggests that serious consideration should be given to investigating environmental and social mechanisms, such as air pollution exposures, as potential contributors to disparities in birth outcomes among AAPI populations., (© 2022. The Author(s).)

Background: Increasing number of studies have linked air pollution exposure with renal function decline and disease. However, there is a lack of data on its impact among end-stage kidney disease (ESKD) patients and its potential modifying effect from extreme heat events (EHE)., Methods: Fresenius Kidney Care records from 28 selected northeastern US counties were used to pool daily all-cause mortality (ACM) and all-cause hospital admissions (ACHA) counts. County-level daily ambient PM 2.5 and ozone (O 3 ) were estimated using a high-resolution spatiotemporal coupled climate-air quality model and matched to ESKD patients based on ZIP codes of treatment sites. We used time-stratified case-crossover analyses to characterize acute exposures using individual and cumulative lag exposures for up to 3 days (Lag 0-3) by using a distributed lag nonlinear model framework. We used a nested model comparison hypothesis test to evaluate for interaction effects between air pollutants and EHE and stratification analyses to estimate effect measures modified by EHE days., Results: From 2001 to 2016, the sample population consisted of 43,338 ESKD patients. We recorded 5217 deaths and 78,433 hospital admissions. A 10-unit increase in PM 2.5 concentration was associated with a 5% increase in ACM (rate ratio [RR Lag0 - 3 ]: 1.05, 95% CI: 1.00-1.10) and same-day O 3 (RR Lag0 : 1.02, 95% CI: 1.01-1.03) after adjusting for extreme heat exposures. Mortality models suggest evidence of interaction and effect measure modification, though not always simultaneously. ACM risk increased up to 8% when daily ozone concentrations exceeded National Ambient Air Quality Standards established by the United States, but the increases in risk were considerably higher during EHE days across lag periods., Conclusion: Our findings suggest interdependent effects of EHE and air pollution among ESKD patients for all-cause mortality risks. National level assessments are needed to consider the ESKD population as a sensitive population and inform treatment protocols during extreme heat and degraded pollution episodes., Competing Interests: Declaration of competing interest Dr. Raimann reported being an employee of the Renal Research Institute (a wholly owned subsidiary of Fresenius Medical Care [FMC]) and owning stock in FMC. Dr. Kotanko reported receiving honoraria from UpToDate, being an employee of the Renal Research Institute, and owning stock in FMC. Dr. Maddux reported owning stock in and being employed by FMC. No other disclosures were reported., (Copyright © 2021. Published by Elsevier B.V.)

Background: Typical thermoregulatory responses to elevated temperatures among healthy individuals include reduced blood pressure and perspiration. Individuals with end-stage kidney disease (ESKD) are susceptible to systemic fluctuations caused by ambient temperature changes that may increase morbidity and mortality. We investigated whether pre-dialysis systolic blood pressure (preSBP) and interdialytic weight gain (IDWG) can independently mediate the association between ambient temperature, all-cause hospital admissions (ACHA), and all-cause mortality (ACM)., Methods: The study population consisted of ESKD patients receiving hemodialysis treatments at Fresenius Medical Care facilities in Philadelphia County, PA, from 2011 to 2019 (n = 1981). Within a time-to-event framework, we estimated the association between daily maximum dry-bulb temperature (TMAX) and, as separate models, ACHA and ACM during warmer calendar months. Clinically measured preSBP and IDWG responses to temperature increases were estimated using linear mixed effect models. We employed the difference (c-c') method to decompose total effect models for ACHA and ACM using preSBP and IDWG as time-dependent mediators. Covariate adjustments for exposure-mediator and total and direct effect models include age, race, ethnicity, blood pressure medication use, treatment location, preSBP, and IDWG. We considered lags up to two days for exposure and 1-day lag for mediator variables (Lag 2-Lag 1) to assure temporality between exposure-outcome models. Sensitivity analyses for 2-day (Lag 2-only) and 1-day (Lag 1-only) lag structures were also conducted., Results: Based on Lag 2- Lag 1 temporal ordering, 1 °C increase in daily TMAX was associated with increased hazard of ACHA by 1.4% (adjusted hazard ratio (HR), 1.014; 95% confidence interval, 1.007-1.021) and ACM 7.5% (adjusted HR, 1.075, 1.050-1.100). Short-term lag exposures to 1 °C increase in temperature predicted mean reductions in IDWG and preSBP by 0.013-0.015% and 0.168-0.229 mmHg, respectively. Mediation analysis for ACHA identified significant indirect effects for all three studied pathways (preSBP, IDWG, and preSBP + IDWG) and significant indirect effects for IDWG and conjoined preSBP + IDWG pathways for ACM. Of note, only 1.03% of the association between temperature and ACM was mediated through preSBP. The mechanistic path for IDWG, independent of preSBP, demonstrated inconsistent mediation and, consequently, potential suppression effects in ACHA (-15.5%) and ACM (-6.3%) based on combined pathway models. Proportion mediated estimates from preSBP + IDWG pathways achieved 2.2% and 0.3% in combined pathway analysis for ACHA and ACM outcomes, respectively. Lag 2 discrete-time ACM mediation models exhibited consistent mediation for all three pathways suggesting that 2-day lag in IDWG and preSBP responses can explain 2.11% and 4.41% of total effect association between temperature and mortality, respectively., Conclusion: We corroborated the previously reported association between ambient temperature, ACHA and ACM. Our results foster the understanding of potential physiological linkages that may explain or suppress temperature-driven hospital admissions and mortality risks. Of note, concomitant changes in preSBP and IDWG may have little intermediary effect when analyzed in combined pathway models. These findings advance our assessment of candidate interventions to reduce the impact of outdoor temperature change on ESKD patients., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Leukemia is one of the most common forms of hematologic malignancy, which can affect people of all ages. We previously showed an association between exposure to ambient particulate matter 2.5 μg (PM 2.5 ) and risk for leukemia in adults. The aim of this study was to investigate which PM 2.5 constituents were responsible for our previous observation., Methods: This is a nationwide register-based case-control study. We identified 14,983 persons diagnosed with leukemia at age 20 or above, 1989-2014, in the Danish Cancer Registry. We selected up to four sex and age-matched controls per case at random from the entire Danish population (n = 51,613). We modelled concentrations of ambient PM 2.5 and its constituents at the addresses of cases and controls for the 10-year period before index date with a state-of-the-art multiscale air pollution modeling system. We used conditional logistic regression to estimate odds ratios (ORs) adjusted for individual and neighborhood level socio-demographic variables., Result: The results showed higher risk for overall leukemia in association with interquartile range exposure to PM 2.5 (OR = 1.09; 95% CI: 1.02, 1.17), black carbon (BC) (OR = 1.02; 95% CI: 1.00, 1.03), secondary inorganic aerosols (SIA) (OR = 1.15; 95% CI: 1.03, 1.29) and its components ammonium (NH 4 ) (OR = 1.08; 95% CI: 1.00, 1.17) and nitrate (NO 3 ) (OR = 1.08; 95% CI: 1.02, 1.14). In leukemia subtype analysis, statistically significant associations were found for AML with PM 2.5 (OR = 1.14; 95% CI: 1.00, 1.29), BC (OR = 1.03; 95% CI: 1.00, 1.07), SIA (OR = 1.23; 95% CI: 1.01, 1.51), NH 4 (OR = 1.16; 95% CI: 1.01, 1.34) and NO 3 (OR = 1.12; 95% CI: 1.01, 1.24). The association between PM 2.5 and leukemia persisted in two pollutants models including sum of primary emitted black and organic carbon (BC + OC), secondary organic aerosols (SOA), or sea-salt. The association between black carbon (BC) and leukemia persisted in two pollutants models including organic carbon (OC). The three pollutant model with sulfate (SO 4 ), NH 4 and NO 3 showed an association with NO 3 but not with SO 4 or NH 4 ., Conclusion: Ambient concentrations of the PM 2.5 components BC, NH 4 and NO 3 at the residence showed associations with risk of incident leukemia in adults., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Despite progress toward malaria elimination in the Greater Mekong Subregion, challenges remain owing to the emergence of drug resistance and the persistence of focal transmission reservoirs. Malaria transmission foci in Myanmar are heterogeneous and complex, and many remaining infections are clinically silent, rendering them invisible to routine monitoring. The goal of this research is to define criteria for easy-to-implement methodologies, not reliant on routine monitoring, that can increase the efficiency of targeted malaria elimination strategies. Studies have shown relationships between malaria risk and land cover and land use (LCLU), which can be mapped using remote sensing methodologies. Here we aim to explain malaria risk as a function of LCLU for five rural villages in Myanmar's Rakhine State. Malaria prevalence and incidence data were analyzed through logistic regression with a land use survey of ~1,000 participants and a 30-m land cover map. Malaria prevalence per village ranged from 5% to 20% with the overwhelming majority of cases being subclinical. Villages with high forest cover were associated with increased risk of malaria, even for villagers who did not report visits to forests. Villagers living near croplands experienced decreased malaria risk unless they were directly engaged in farm work. Finally, land cover change (specifically, natural forest loss) appeared to be a substantial contributor to malaria risk in the region, although this was not confirmed through sensitivity analyses. Overall, this study demonstrates that remotely sensed data contextualized with field survey data can be used to inform critical targeting strategies in support of malaria elimination., Competing Interests: The authors declare no conflicts of interest relevant to this study., (©2020. The Authors.)

Background: Emerging research suggests mindfulness may reduce stress and asthma symptoms in children, yet there is a gap in understanding parental views towards learning about mindfulness., Objective: This study aimed to compare the perceived acceptance to learn about mindfulness among parents of children with and without asthma, and to understand differences across income levels., Methods: This was a national, cross-sectional, online survey of parents of children 0-18 years. Acceptance was measured with questions on whether parents believe mindfulness could be beneficial while parenting, and if they would be willing to learn about mindfulness. Comparisons of mindfulness acceptance between income level were conducted using chi-square and Fisher's exact test., Results: Parents of children with asthma were more likely to be interested in learning about mindfulness from their health care provider compared to those without asthma (46% vs. 38%, p < 0.0001). At all income levels examined in the study, parents (63-75%) of children with asthma indicated that they agreed or strongly agreed that mindfulness can be beneficial when parenting., Conclusion: Findings suggest an opportunity to incorporate mindfulness teaching into asthma care for pediatric patients of all income levels.

Background: Air pollution is an established carcinogen. Evidence for an association with brain tumors is, however, inconclusive. We investigated if individual particulate matter constituents were associated with brain tumor risk., Methods: From comprehensive national registers, we identified all (n = 12 928) brain tumor cases, diagnosed in Denmark in the period 1989-2014, and selected 22 961 controls, matched on age, sex and year of birth. We established address histories and estimated 10-year mean residential outdoor concentrations of particulate matter < 2.5 µm, primarily emitted black carbon (BC) and organic carbon (OC), and combined carbon (OC/BC), as well as secondary inorganic and organic PM air pollutants from a detailed dispersion model. We used conditional logistic regression to calculate odds ratios (OR) per inter quartile range (IQR) exposure. We adjusted for income, marital and employment status as well as area-level socio-demographic characteristics., Results: Total tumors of the brain were associated with OC/BC (OR: 1.053, 95%CI: 1.005-1.103, per IQR). The data suggested strongest associations for malignant tumors with ORs per IQR for OC/BC, BC and OC of 1.063 (95% CI: 1.007-1.123), 1.036 (95% CI: 1.006-1.067) and 1.030 (95%CI: 0.979-1.085), respectively. The results did not indicate adverse effects of other PM components., Conclusions: This large, population based study showed associations between primary emitted carbonaceous particles and risk for malignant brain tumors. As the first of its kind, this study needs replication., (Copyright © 2020. Published by Elsevier Ltd.)

There is limited evidence regarding a possible association between exposure to ambient air pollutants and the risk of non-Hodgkin lymphoma (NHL). Previous epidemiological studies have relied on crude estimations for air pollution exposure and/or small numbers of NHL cases. The objective of our study was to analyze this association based on air pollution modeled at the address level and NHL cases identified from the nationwide Danish Cancer Registry. We identified 20,874 incident NHL cases diagnosed between 1989 and 2014 and randomly selected 41,749 controls matched on age and gender among the entire Danish population. We used conditional logistic regression to estimate odds ratios (ORs) and adjusted for individual and neighborhood level sociodemographic variables. There was no association between exposure to PM 2.5 , BC, O 3 , SO 2 or NO 2 and overall risk of NHL but several air pollutants were associated with higher risk of follicular lymphoma, but statistically insignificant, for example, PM 2.5 (OR = 1.15 per 5 μg/m 3 ; 95% CI: 0.98-1.34) and lower risk for diffuse large B-cell lymphoma (OR = 0.92 per 5 μg/m 3 ; 95% CI: 0.82-1.03). In this population-based study, we did not observe any convincing evidence of a higher overall risk for NHL with higher exposure to ambient air pollutants., (© 2020 UICC.)

Background: Particulate matter (PM) air pollution is a complex mixture and the various PM constituents likely affect health differently. The literature on the relationships among specific PM constituents and the risk of cancer is sparse. In this study, we aimed to evaluate the association of PM 2.5 and its constituents with the incidence of non-Hodgkin lymphoma (NHL) and the two main NHL subtypes., Methods: We undertook a nationwide register-based case-control study including 20,847 cases registered in the Danish Cancer Registry with NHL between 1989 and 2014. Among the entire Danish population, we selected 41,749 age and sex-matched controls randomly from the Civil Registration System. We assessed modelled outdoor PM concentrations at addresses of cases and controls with a state-of-the-art multi scale air pollution modelling system and used conditional logistic regression to estimate odds ratios (ORs) adjusted for individual and neighborhood level socio-demographic variables., Results: The 10-year time-weighted average concentrations of PM 2.5 , primary carbonaceous particles (BC/OC), secondary inorganic aerosols (SIA), secondary organic aerosols (SOA) and sea salt were 17.4, 2.3, 7.8, 0.3, and 4.1 μg/m 3 , respectively among controls. The results showed higher risk for NHL in association with exposure to BC/OC (OR = 1.03; 95% CI: 1.00, 1.07, per interquartile range (IQR)) and SOA (OR = 1.54; 95% CI: 1.13, 2.09, per IQR). The results indicated a higher risk for follicular lymphoma in association with several PM components. Including PM 2.5 (OR = 1.16; 95% CI: 0.98-1.38), BC/OC (OR = 1.05; 95% CI: 0.97-1.14), SIA (OR = 1.44; 95% CI: 0.80-1.08), SOA (OR = 4.52; 95% CI: 0.86-23.83) per IQR., Conclusion: This is the first study on PM constituents and the risk of NHL. The results indicated an association with primary carbonaceous and secondary organic PM. The results need replication in other settings before any firm conclusion can be reached., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Background: Social media platforms such as Twitter can serve as a potential data source for public health research to characterize the social neighborhood environment. Few studies have linked Twitter-derived characteristics to individual-level health outcomes., Objective: This study aims to assess the association between Twitter-derived social neighborhood characteristics, including happiness, food, and physical activity mentions, with individual cardiometabolic outcomes using a nationally representative sample., Methods: We collected a random 1% of the geotagged tweets from April 2015 to March 2016 using Twitter's Streaming Application Interface (API). Twitter-derived zip code characteristics on happiness, food, and physical activity were merged to individual outcomes from restricted-use National Health and Nutrition Examination Survey (NHANES) with residential zip codes. Separate regression analyses were performed for each of the neighborhood characteristics using NHANES 2011-2016 and 2007-2016., Results: Individuals living in the zip codes with the two highest tertiles of happy tweets reported BMI of 0.65 (95% CI -1.10 to -0.20) and 0.85 kg/m 2 (95% CI -1.48 to -0.21) lower than those living in zip codes with the lowest frequency of happy tweets. Happy tweets were also associated with a 6%-8% lower prevalence of hypertension. A higher prevalence of healthy food tweets was linked with an 11% (95% CI 2% to 21%) lower prevalence of obesity. Those living in areas with the highest and medium tertiles of physical activity tweets were associated with a lower prevalence of hypertension by 10% (95% CI 4% to 15%) and 8% (95% CI 2% to 14%), respectively., Conclusions: Twitter-derived social neighborhood characteristics were associated with individual-level obesity and hypertension in a nationally representative sample of US adults. Twitter data could be used for capturing neighborhood sociocultural influences on chronic conditions and may be used as a platform for chronic outcomes prevention., (©Dina Huang, Yuru Huang, Sahil Khanna, Pallavi Dwivedi, Natalie Slopen, Kerry M Green, Xin He, Robin Puett, Quynh Nguyen. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 18.08.2020.)

Background: Inconclusive evidence has suggested a possible link between air pollution and central nervous system (CNS) tumors. We investigated a range of air pollutants in relation to types of CNS tumors., Methods: We identified all (n = 21,057) intracranial tumors in brain, meninges and cranial nerves diagnosed in Denmark between 1989 and 2014 and matched controls on age, sex and year of birth. We established personal 10-year mean residential outdoor exposure to particulate matter < 2.5 μm (PM 2.5 ), nitrous oxides (NO X ), primary emitted black carbon (BC) and ozone. We used conditional logistic regression to calculate odds ratios (OR) linearly (per interquartile range (IQR)) and categorically. We accounted for personal income, employment, marital status, use of medication as well as socio-demographic conditions at area level., Results: Malignant tumors of the intracranial CNS was associated with BC (OR: 1.034, 95%CI: 1.005-1.065 per IQR. For NO x the OR per IQR was 1.026 (95%CI: 0.998-1.056). For malignant non-glioma tumors of the brain we found associations with PM 2.5 (OR: 1.267, 95%CI: 1.053-1.524 per IQR), BC (OR: 1.049, 95%CI: 0.996-1.106) and NO x (OR: 1.051, 95% CI: 0.996-1.110)., Conclusion: Our results suggest that air pollution is associated with malignant intracranial CNS tumors and malignant non-glioma of the brain. However, additional studies are needed.

While structural factors may drive health inequities, certain health-promoting attributes of one's "place" known as salutogens may further moderate the cumulative impacts of exposures to socio-environmental stressors that behave as pathogens. Understanding the synergistic relationship between socio-environmental stressors and resilience factors is a critical component in reducing health inequities; however, the catalyst for this concept relies on community-engaged research approaches to ultimately strengthen resiliency and promote health. Furthermore, this concept has not been fully integrated into environmental justice and cumulative risk assessment screening tools designed to identify geospatial variability in environmental factors that may be associated with health inequities. As a result, we propose a hybrid resiliency-stressor conceptual framework to inform the development of environmental justice and cumulative risk assessment screening tools that can detect environmental inequities and opportunities for resilience in vulnerable populations. We explore the relationship between actual exposures to socio-environmental stressors, perceptions of stressors, and one's physiological and psychological stress response to environmental stimuli, which collectively may perpetuate health inequities by increasing allostatic load and initiating disease onset. This comprehensive framework expands the scope of existing screening tools to inform action-based solutions that rely on community-engaged research efforts to increase resiliency and promote positive health outcomes.

Background: The built environment predicts walking in older adults, but the degree to which associations between the objective built environment and walking for different purposes are mediated by environmental perceptions is unknown., Purpose: We examined associations between the neighborhood built environment and leisure and utilitarian walking and mediation by the perceived environment among older women., Methods: Women (N = 2732, M age  = 72.8 ± 6.8 years) from Massachusetts, Pennsylvania, and California completed a neighborhood built environment and walking survey. Objective population and intersection density and density of stores and services variables were created within residential buffers. Perceived built environment variables included measures of land use mix, street connectivity, infrastructure for walking, esthetics, traffic safety, and personal safety. Regression and bootstrapping were used to test associations and indirect effects., Results: Objective population, stores/services, and intersection density indirectly predicted leisure and utilitarian walking via perceived land use mix (odds ratios (ORs) = 1.01-1.08, 95 % bias corrected and accelerated confidence intervals do not include 1). Objective density of stores/services directly predicted ≥150 min utilitarian walking (OR = 1.11; 95% CI = 1.02, 1.22). Perceived land use mix (ORs = 1.16-1.44) and esthetics (ORs = 1.24-1.61) significantly predicted leisure and utilitarian walking, CONCLUSIONS: Perceived built environment mediated associations between objective built environment variables and walking for leisure and utilitarian purposes. Interventions for older adults should take into account how objective built environment characteristics may influence environmental perceptions and walking.

Growing evidence supports that air pollution has become an important risk factor for developing diabetes mellitus. Understanding the contributing effect of air pollution in population studies, elucidating the potential mechanisms involved, and identifying the most responsible pollutants are all required in order to promulgate successful changes in policy and to help formulate preventive measures in an effort to reduce the risk for diabetes. This review summarizes recent findings from epidemiologic studies and mechanistic insights that provide links between exposure to air pollution and a heightened risk for diabetes.

Recent studies in both humans and animals suggest that air pollution is an important risk factor for type 2 diabetes mellitus (T2DM). However, the mechanism by which air pollution mediates propensity to diabetes is not fully understood. While a number of epidemiologic studies have shown a positive association between ambient air pollution exposure and risk for T2DM, some studies have not found such a relationship. Experimental studies in susceptible disease models do support this association and suggest the involvement of tissues involved in the pathogenesis of T2DM such as the immune system, adipose, liver, and central nervous system. This review summarizes the epidemiologic and experimental evidence between ambient outdoor air pollution and T2DM., (© The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

The Gullah/Geechee (G/G) heritage is rooted in a culture largely dependent on fish and seafood as a primary food source. Research suggests that African-American (AA) fishers in the Southeastern US consume larger amounts of fish, potentially exposing them to higher environmental contaminant levels. This in-depth study was conducted to explore G/G and AA Sea Island attitudes, perceptions, and cultural beliefs about fishing in one urban and two rural South Carolina coastal counties. Results indicated that study participants in rural counties had slightly different perspectives of fishing (e.g. fishing as an essential dietary supplement) than in urban counties where fishing was viewed more as relaxation. Major misperceptions existed in all counties between fish consumption advisories related to pollution versus harvesting restrictions associated with fishing regulations. Providing clear, culturally tailored health messages regarding fish advisories will promote more informed choices about fish consumption that will minimize potential exposures to environmental pollutants.

Background: The importance of physical activity for health is well-established. Questions remain whether outdoor exercise additionally benefits overall mental and physical well-being., Methods: Using cross-sectional data from the Aerobics Center Longitudinal Study, we examined relationships of physical activity environment (PAE) with reported tension, stress, emotional outlook, and health., Results: 11,649 participants were included. 18% exercised indoors, 54% outdoors, and 28% in both. Participants who exercised partially or entirely outdoors exercised more. In fully adjusted models, for women combined PAE was protective for worse emotional outlook (OR: 0.72; 95% CI: 0.52-0.98). Combined PAE was also protective for reported poor health (OR for women: 0.63; 95% CI: 0.44-0.91; OR for men: 0.75; 95% CI: 0.61-0.92). Amount of physical activity modified PAE relationships with outcomes. Combined and outdoor PAE were more consistently protective for worse outcomes among high activity participants. Regardless of PAE, better outcomes were observed in active versus inactive participants., Conclusion: The current study suggests addition of outdoor PAE may be linked with better stress management, outlook and health perceptions for more active populations, whereas indoor PAE may be more important for low active populations. Further research should examine the order of causation and whether type of outdoor PAE (eg, urban, natural) is important.

Adverse birth outcomes including preterm birth (PTB: <37 weeks gestation) and low birth weight (LBW: <2500 g) can result in severe infant morbidity and mortality. In the United States, there are racial and ethnic differences in the prevalence of PTB and LBW. We investigated the association between PTB and LBW with prenatal mercury (Hg) exposure and season of conception in an urban immigrant community in Brooklyn, New York. We recruited 191 pregnant women aged 18-45 in a Brooklyn Prenatal Clinic and followed them until delivery. Urine specimens were collected from the participants during the 6th to 9th month of pregnancy. Cord blood specimens and neonate anthropometric data were collected at birth. We used multivariate logistic regression models to investigate the odds of LBW or PTB with either maternal urinary mercury or neonate cord blood mercury. We used linear regression models to investigate the association between continuous anthropometric outcomes and maternal urinary mercury or neonate cord blood mercury. We also examined the association between LBW and PTB and the season that pregnancy began. Results showed higher rates of PTB and LBW in this cohort of women compared to other studies. Pregnancies beginning in winter (December, January, February) were at increased odds of LBW births compared with births from pregnancies that began in all other months (OR7.52 [95% CI 1.65, 34.29]). We observed no association between maternal exposure to Hg, and either LBW or PTB. The apparent lack of association is consistent with other studies. Further examination of seasonal association with LBW is warranted.

Background: Mercury is a metal with widespread distribution in aquatic ecosystems and significant neurodevelopmental toxicity in humans. Fish biomonitoring for total mercury has been conducted in South Carolina (SC) since 1976, and consumption advisories have been posted for many SC waterways. However, there is limited information on the potential reproductive impacts of mercury due to recreational or subsistence fish consumption., Methods: To address this issue, geocoded residential locations for live births from the Vital Statistics Registry (1995-2005, N = 362,625) were linked with spatially interpolated total mercury concentrations in fish to estimate potential mercury exposure from consumption of locally caught fish. Generalized estimating equations were used to test the hypothesis that risk of low birth weight (LBW, <2,500 grams) or preterm birth (PTB, < 37 weeks clinical gestation) was greater among women living in areas with elevated total mercury in fish, after adjustment for confounding. Separate analyses estimated term LBW and PTB risks using residential proximity to rivers with fish consumption advisories to characterize exposure., Results: Term LBW was more likely among women residing in areas in the upper quartile of predicted total mercury in fish (odds ratio [OR] = 1.04; 95% confidence interval [CI]: 1.00-1.09) or within 8 kilometers of a river with a 'do not eat' fish advisory (1.05; 1.00-1.11) compared to the lowest quartile, or rivers without fish consumption restrictions, respectively. When stratified by race, risks for term LBW or PTB were 10-18% more likely among African-American (AA) mothers living in areas with the highest total fish mercury concentrations., Conclusions: To our knowledge, this is the first study to examine the relationship between fish total mercury concentrations and adverse reproductive outcomes in a large population-based sample that included AA women. The ecologic nature of exposure assessment in this study precludes causal inference. However, the results suggest a need for more detailed investigations to characterize patterns of local fish consumption and potential dose-response relationships between mercury exposure and adverse reproductive outcomes, particularly among AA mothers.

Objectives: We evaluated the combined impact of community-level environmental and socioeconomic factors on the risk of campylobacteriosis., Methods: We obtained Campylobacter case data (2002-2010; n = 3694) from the Maryland Foodborne Diseases Active Surveillance Network. We obtained community-level socioeconomic and environmental data from the 2000 US Census and the 2007 US Census of Agriculture. We linked data by zip code. We derived incidence rate ratios by Poisson regressions. We mapped a subset of zip code-level characteristics., Results: In zip codes that were 100% rural, incidence rate ratios (IRRs) of campylobacteriosis were 6 times (IRR = 6.18; 95% confidence interval [CI] = 3.19, 11.97) greater than those in urban zip codes. In zip codes with broiler chicken operations, incidence rates were 1.45 times greater than those in zip codes without broilers (IRR = 1.45; 95% CI = 1.34, 1.58). We also observed higher rates in zip codes whose populations were predominantly White and had high median incomes., Conclusions: The community and environment in which one lives may significantly influence the risk of campylobacteriosis.

A large body of literature has reported differences in exposure to environments supporting either healthy (e.g. supermarkets) or unhealthy (e.g. fast food outlets) dietary choices by neighborhood characteristics. We explored the associations of both supermarkets and fast food outlets availability with neighborhood characteristics, and clustering of these two outlet types in a largely rural state. Compared to block groups without a supermarket, those with a supermarket had a significantly higher income, higher housing value, larger population with high school education and above, lower minority population and lower population living below poverty even after controlling for urbanicity and population density of census block groups. Surprisingly, a similar relationship was found for block groups with and without fast food outlets. This was due to spatial co-occurrence and clustering of fast food outlets around supermarket locations. Hence, future studies exploring the associations of food environment with diet or diet-related health outcome should concurrently examine all aspects of food environment (healthy and unhealthy)., (© 2013 Elsevier Ltd. All rights reserved.)

Objective: To evaluate the associations of supermarket and fast-food outlet accessibility and availability with dietary intake among youth with diabetes., Design: Subjects' residential location and dietary intake was obtained from the SEARCH for Diabetes in Youth study. Food outlet data obtained from the South Carolina Department of Health and Environmental Control and InfoUSA were merged based on names and addresses of the outlets. The comprehensive data were then used to construct accessibility and availability measures for each participant., Setting: State of South Carolina., Participants: Three hundred fifty-nine youths with diabetes (10 years old and older) from the SEARCH for Diabetes in Youth study., Phenomena of Interest: Supermarket and fast-food outlet accessibility and availability; dietary intake represented by Dietary Approaches to Stop Hypertension (DASH) score., Analysis: Generalized estimating equations analyses., Results: Increased availability and accessibility of supermarkets were significantly associated with higher DASH score, even after adjusting for individual-level correlates, urbanicity, and fast-food outlet accessibility or availability. Fast-food accessibility, however, was associated only with specific food groups (meat, sweets, and low-fat dairy intake), not with the DASH score., Conclusions and Implications: Efforts to promote environments conducive to healthful eating may significantly improve the overall dietary intake and reduce diet-related health complications among youth with diabetes., (Copyright © 2012 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.)

Objective: This ecologic study tested the hypothesis that census tracts with elevated groundwater uranium and more frequent groundwater use have increased cancer incidence., Methods: Data sources included: incident total, leukemia, prostate, breast, colorectal, lung, kidney, and bladder cancers (1996-2005, SC Central Cancer Registry); demographic and groundwater use (1990 US Census); and groundwater uranium concentrations (n = 4,600, from existing federal and state databases). Kriging was used to predict average uranium concentrations within tracts. The relationship between uranium and standardized cancer incidence ratios was modeled among tracts with substantial groundwater use via linear or semiparametric regression, with and without stratification by the proportion of African Americans in each area., Results: A total of 134,685 cancer cases were evaluated. Tracts with ≥50% groundwater use and uranium concentrations in the upper quartile had increased risks for colorectal, breast, kidney, prostate, and total cancer compared to referent tracts. Some of these relationships were more likely to be observed among tracts populated primarily by African Americans., Conclusion: SC regions with elevated groundwater uranium and more groundwater use may have an increased incidence of certain cancers, although additional research is needed since the design precluded adjustment for race or other predictive factors at the individual level.

Background: Environmental uranium exposure originating as a byproduct of uranium processing can impact human health. The Fernald Feed Materials Production Center functioned as a uranium processing facility from 1951 to 1989, and potential health effects among residents living near this plant were investigated via the Fernald Medical Monitoring Program (FMMP)., Methods: Data from 8216 adult FMMP participants were used to test the hypothesis that elevated uranium exposure was associated with indicators of hypertension or changes in hematologic parameters at entry into the program. A cumulative uranium exposure estimate, developed by FMMP investigators, was used to classify exposure. Systolic and diastolic blood pressure and physician diagnoses were used to assess hypertension; and red blood cells, platelets, and white blood cell differential counts were used to characterize hematology. The relationship between uranium exposure and hypertension or hematologic parameters was evaluated using generalized linear models and quantile regression for continuous outcomes, and logistic regression or ordinal logistic regression for categorical outcomes, after adjustment for potential confounding factors., Results: Of 8216 adult FMMP participants 4187 (51%) had low cumulative uranium exposure, 1273 (15%) had moderate exposure, and 2756 (34%) were in the high (>0.50 Sievert) cumulative lifetime uranium exposure category. Participants with elevated uranium exposure had decreased white blood cell and lymphocyte counts and increased eosinophil counts. Female participants with higher uranium exposures had elevated systolic blood pressure compared to women with lower exposures. However, no exposure-related changes were observed in diastolic blood pressure or hypertension diagnoses among female or male participants., Conclusions: Results from this investigation suggest that residents in the vicinity of the Fernald plant with elevated exposure to uranium primarily via inhalation exhibited decreases in white blood cell counts, and small, though statistically significant, gender-specific alterations in systolic blood pressure at entry into the FMMP., (Published by Elsevier Inc.)

Many statistical tests have been developed to assess the significance of clusters of disease located around known sources of environmental contaminants, also known as focused disease clusters. The majority of focused-cluster tests were designed to detect a particular spatial pattern of clustering, one in which the disease cluster centers around the pollution source and declines in a radial fashion with distance. However, other spatial patterns of environmentally related disease clusters are likely given that the spatial dispersion patterns of environmental contaminants, and thus human exposure, depend on a number of factors (i.e., meteorology and topography). For this study, data were simulated with five different spatial patterns of disease clusters, reflecting potential pollutant dispersion scenarios: 1) a radial effect decreasing with increasing distance, 2) a radial effect with a defined peak and decreasing with distance, 3) a simple angular effect, 4) an angular effect decreasing with increasing distance and 5) an angular effect with a defined peak and decreasing with distance. The power to detect each type of spatially distributed disease cluster was evaluated using Stone's Maximum Likelihood Ratio Test, Tango's Focused Test, Bithell's Linear Risk Score Test, and variations of the Lawson-Waller Score Test. Study findings underscore the importance of considering environmental contaminant dispersion patterns, particularly directional effects, with respect to focused-cluster test selection in cluster investigations. The effect of extra variation in risk also is considered, although its effect is not substantial in terms of the power of tests.

Background: The etiology of rheumatoid arthritis (RA) remains largely unknown, although epidemiologic studies suggest genetic and environmental factors may play a role. Geographic variation in incident RA has been observed at the regional level., Objective: Spatial analyses are a useful tool for confirming existing exposure hypotheses or generating new ones. To further explore the association between location and RA risk, we analyzed individual-level data from U.S. women in the Nurses' Health Study, a nationwide cohort study., Methods: Participants included 461 incident RA cases and 9,220 controls with geocoded addresses; participants were followed from 1988 to 2002. We examined spatial variation using addresses at baseline in 1988 and at the time of case diagnosis or the censoring of controls. Generalized additive models (GAMs) were used to predict a continuous risk surface by smoothing on longitude and latitude while adjusting for known risk factors. Permutation tests were conducted to evaluate the overall importance of location and to identify, within the entire study area, those locations of statistically significant risk., Results: A statistically significant area of increased RA risk was identified in the northeast United States (p-value = 0.034). Risk was generally higher at northern latitudes, and it increased slightly when we used the nurses' 1988 locations compared with those at the time of diagnosis or censoring. Crude and adjusted models produced similar results., Conclusions: Spatial analyses suggest women living in higher latitudes may be at greater risk for RA. Further, RA risk may be greater for locations that occur earlier in residential histories. These results illustrate the usefulness of GAM methods in generating hypotheses for future investigation and supporting existing hypotheses.

Background: The geographic variation in rheumatoid arthritis (RA) incidence in the United States is unknown., Methods: We studied residential region from January 1, 1921, to May 31, 1976, and RA risk in a prospective cohort of women, the Nurses' Health Study. Information on state of residence was collected at baseline in 1976 (when participants were aged 30-55 years) and on state of residence at birth, at age 15 years, and at age 30 years in 1992. Among 83,546 participants reporting residence for all 4 time points, 706 incident RA cases from June 1, 1976, to May 31, 2004, were confirmed by screening questionnaire and record review for American College of Rheumatology criteria. Residential region was classified as West, Midwest, mid-Atlantic, New England, and Southeast. Multivariate Cox proportional hazards regression models were used to assess relationships between region and RA risk, adjusting for age, smoking, body mass index, parity, breastfeeding, postmenopausal status, postmenopausal hormone use, father's occupation, race, and physical activity. Analyses were performed in participants who lived in the same regions, or moved, over time., Results: Compared with those in the West, women in New England had a 37% to 45% elevated risk of RA in multivariate models at each time point (eg, state of residence in 1976: rate ratio [RR], 1.42; 95% confidence interval [CI], 1.10-1.82). In analyses of women who lived in the same region at birth, age 15 years, and age 30 years, living in the Midwest was associated with greater risk (RR, 1.47; 95% CI, 1.05-2.05), as was living in New England (RR, 1.40; 95% CI, 0.98-2.00). Compared with living in the West at birth, age 15 years, and age 30 years, RA risk was higher in the East., Conclusions: In this large cohort of US women, significant geographic variation in incident RA existed after controlling for confounders. Potential explanations include regional variation in behavioral factors, climate, environmental exposures, RA diagnosis, and genetic factors.

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or countywide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM(10) concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM(10) emissions, elevation, wind speed, and precipitation were found to be important determinants of PM(10) concentrations and were included in the final model. Final model performance was strong (cross-validation R(2)=0.62), with little bias (-0.4 mug m(-3)) and high precision (6.4 mug m(-3)). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R(2)=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R(2)=0.51) or inverse distance weighted interpolation (cross-validation R(2)=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM(10) exposures for large populations.

This study examined the role of social support in the partner violence-psychological distress relation in a sample of African American women seeking medical care at a large, urban hospital (n = 138). Results from bivariate correlational analyses revealed that partner violence was related to lower perceived social support and greater psychological distress, and lower social support was related to more distress. Furthermore, findings based on path analysis indicated that low levels of social support helped account for battered women's increased distress. Findings point to the need for service providers to screen for partner violence in nontraditional sites, such as hospital emergency rooms, and to address the role of social support resources in preventive interventions with African American battered women.

The aim of this study was to examine psychological and interpersonal risk factors for suicidal behavior in low income, African American women; 285 African American women who reported being in a relationship with a partner in the past year were studied, 148 presented to the hospital following a suicide attempt, and 137 presented for general medical care. Cases were compared to controls with respect to psychological symptoms, alcohol and drug abuse, family violence (intimate partner abuse, childhood trauma), relationship discord, and social support. Psychological risk factors for suicide attempts at the univariate level included psychological distress [Crude Odds Ratio (COR) = 6.5], post traumatic stress disorder (PTSD) symptoms (COR = 3.8), hopelessness (COR = 7.7), and drug abuse (COR = 4.2). Interpersonal risk factors at the univariate level included relationship discord (COR = 4.0), physical partner abuse (COR = 2.5), nonphysical partner abuse (COR = 2.8), childhood maltreatment (COR = 3.2), and low levels of social support (COR = 2.6). A multivariate logistic regression model identified four variables that were strongly and independently associated with an increased risk for suicide attempts: psychological distress, hopelessness, drug abuse, and relationship discord. The model predicted suicide attempt status correctly 77% of the time. The results reveal that African American women who report high levels of psychological distress, hopelessness, drug use, and relationship discord should be assessed carefully for suicidal ideation and referred for appropriate mental health care.

Child sexual abuse (CSA) is a widespread problem that has been associated with a variety of negative health outcomes. There has been a call for prevention of first occurrences of CSA. Public health provides a unique framework for conceptualizing and implementing these prevention efforts. This article explains a model of the public health approach to prevention and illustrates the applicability of this model to CSA. The Centers for Disease Control and Prevention convened a panel of experts to advise the agency about raising awareness of CSA as a public health problem. A summary of the recommendations developed by this expert panel is presented.