Food Insecurity and Experiences of Discrimination Among Caregivers of Hospitalized Children

BACKGROUND AND OBJECTIVES

Pediatric hospitals are adopting strategies to address food insecurity (FI), a stigmatizing condition, among families with children. We hypothesized that parents and other caregivers ("caregivers") from households with FI or marginal food security (MFS) are more likely to experience discrimination during their child's hospitalization.

METHODS

We analyzed data from 319 caregivers of children admitted to an urban, academic children's hospital and randomly assigned to the control arm of the double-blind randomized controlled CommunityRx-Hunger trial (November 2020 to June 2022, NCT R01MD012630). Household food security in the 30 days before admission and discrimination during hospitalization were measured with the US Household Food Security Survey and the Discrimination in Medical Settings Scale, respectively. We used logistic regression to model the relationship between food security status and discrimination, adjusting for gender, race, ethnicity, income, and partner status.

RESULTS

Most participants were African American or Black (81.5%), female (94.7%), and the parent of the hospitalized child (93.7%). FI and MFS were prevalent (25.1% and 15.1%, respectively). Experiences of discrimination during a child's hospitalization were prevalent (51.9%). Caregivers with FI had higher odds than caregivers with food security of experiencing discrimination (adjusted odds ratio = 2.0, 95% confidence interval 1.1-3.6, P = .03); MFS was not significantly associated with discrimination (P = .25). Compared with food secure caregivers, those with FI had higher odds of 5 of 7 experiences of discrimination assessed.

CONCLUSIONS

Among parents and other caregivers, household FI is associated with experiences of discrimination during a child's hospitalization.

CommunityRx, a social care assistance intervention for family and friend caregivers delivered at the point of care: two concurrent blinded randomized controlled trials

BACKGROUND

CommunityRx is an evidence-based social care intervention delivered to family and friend caregivers ("caregivers") at the point of healthcare to address health-related social risks (HRSRs). Two CommunityRx randomized controlled trials (RCTs) are being fielded concurrently on Chicago's South Side, a predominantly African American/Black community. CommunityRx-Hunger is a double-blind RCT enrolling caregivers of hospitalized children. CommunityRx-Dementia is a single-blind RCT enrolling caregivers of community-residing people with dementia. RCTs with caregivers face recruitment barriers, including caregiver burden and lack of systematic strategies to identify caregivers in clinical settings. COVID-19 pandemic-related visitor restrictions exacerbated these barriers and prompted the need for iteration of the protocols from in-person to remote operations. This study describes these protocols and methods used for successful iteration to overcome barriers.

METHODS AND FINDINGS

CommunityRx uses individual-level data to generate personalized, local community resource referrals for basic, health and caregiving needs. In early 2020, two in-person RCT protocols were pre-tested. In March 2020, when pandemic conditions prohibited face-to-face clinical enrollment, both protocols were iterated to efficient, caregiver-centered remote operations. Iterations were enabled in part by the Automated Randomized Controlled Trial Information-Communication System (ARCTICS), a trial management system innovation engineered to integrate the data collection database (REDCap) with community resource referral (NowPow) and SMS texting (Mosio) platforms. Enabled by engaged Community Advisory Boards and ARCTICS, both RCTs quickly adapted to remote operations. To accommodate these adaptations, launch was delayed until November (CommunityRx-Hunger) and December (CommunityRx-Dementia) 2020. Despite the delay, 65% of all planned participants (CommunityRx-Hunger n = 417/640; CommunityRx-Dementia n = 222/344) were enrolled by December 2021, halfway through our projected enrollment timeline. Both trials enrolled 13% more participants in the first 12 months than originally projected for in-person enrollment.

DISCUSSION

Our asset-based, community-engaged approach combined with widely accessible institutional and commercial information technologies facilitated rapid migration of in-person trials to remote operations. Remote or hybrid RCT designs for social care interventions may be a viable, scalable alternative to in-person recruitment and intervention delivery protocols, particularly for caregivers and other groups that are under-represented in traditional health services research.

TRIAL REGISTRATION

ClinicalTrials.gov: CommunityRx-Hunger (NCT04171999, 11/21/2019); CommunityRx for Caregivers (NCT04146545, 10/31/2019).

Social Risk and Smoking Among Women Smokers Early in the COVID-19 Pandemic: The Role of Mental Health

Background: We examined patterns of smoking in relation to health-related socioeconomic vulnerability (HRSV) among U.S. women early in the pandemic and whether mental health symptoms mediated these relationships. Materials and Methods: Data were obtained from the April 2020 National U.S. Women's Health COVID-19 Study (N = 3200). Among current smokers, adjusted odds of increased smoking since the start of the pandemic (vs. same or less) by incident and worsening HRSVs were modeled. Structural equation modeling was used to assess anxiety, depression, and traumatic stress symptoms as mediators of the relationship between six HRSVs (food insecurity; housing, utilities, and transportation difficulties; interpersonal violence; financial strain) and increased smoking early in the pandemic. Results: Nearly half (48%) of current smokers reported increased smoking since the pandemic started. Odds of increased smoking were higher among women with incident financial strain (aOR = 2.0, 95% CI 1.2-3.3), incident food insecurity (aOR = 2.9, 95% CI 1.7-5.1), any worsening HRSV (aOR = 2.2, 95% CI 1.5-3.0), and worsening food insecurity (aOR = 1.9, 95% CI 1.3-3.0). Anxiety symptoms were a significant, partial mediator of the relationship between increased smoking and any worsening HRSVs (proportion mediated = 0.17, p = 0.001) and worsening food insecurity (0.19, p = 0.023), specifically. Depression symptoms were a significant, partial mediator of the relationship between increased smoking and any worsening HRSVs (0.15, p = 0.004) and incident financial strain (0.19, p = 0.034). Traumatic stress was not a significant mediator of any tested relationship. Conclusions: Anxiety and depression symptoms partially explain the relationship between rising socioeconomic vulnerability and increased smoking among women early in the pandemic. Addressing HRSVs and mental health may help reduce increased smoking during a public health crisis.

Transportation-related Environmental Mixtures and Diabetes Prevalence and Control in Urban/Metropolitan Counties in the United States

Diabetes rates in the United States are staggering and climbing. Importantly, traditional risk factors fail to completely account for the magnitude of the diabetes epidemic. Environmental exposures, including urban and metropolitan transportation quality, are implicated as contributors to disease. Using data from the county-level Environmental Quality Index (EQI) developed for the United States, we analyzed associations between transportation and air quality environmental metrics with overall diabetes prevalence and control within urban/metropolitan counties in the United States from 2006 to 2012. Additionally, we examined effect modification by race/ethnicity through stratification based on the county-level proportion of minority residents. Last, we applied mixture methods to evaluate the effect of simultaneous poor transportation factors and worse air quality on the same outcomes. We found that increased county-level particulate matter air pollution and nitrogen dioxide along with reduced public transportation usage and lower walkability were all associated with increased diabetes prevalence. The minority proportion of the population influences some of these relationships as some of the effects of air pollution and the transportation-related environment are worse among counties with more minority residents. Furthermore, the transportation and air quality mixtures were found to be associated with increased diabetes prevalence and reduced diabetes control. These data further support the burgeoning evidence that poor environments amplify diabetes risk. Future cohort studies should explore the utility of environmental policies and urban planning as tools for improving metabolic health.

Two concurrent randomized controlled trials of CommunityRx, a social care intervention for family and friend caregivers delivered at the point of care

Background

CommunityRx is an evidence-based social care intervention delivered to family and friend caregivers ("caregivers") at the point of healthcare to address health-related social risks (HRSRs). CommunityRx-Hunger is a double-blind randomized controlled trial (RCT) that enrolls caregivers of hospitalized children. CommunityRx-Dementia is a single-blind RCT that enrolls caregivers of community-residing people with dementia. Clinical trials that enroll caregivers face recruitment barriers, including caregiver burden and lack of systematic strategies to identify and track caregivers. COVID-19 pandemic-related visitor restrictions exacerbated these barriers and prompted the need for iteration of the CommunityRx protocols from in-person to remote operations. This study describes the novel methods used to iterate existing RCT protocols and factors contributing to their successful iteration.

Methods

CommunityRx uses individual-level data to generate personalized community resource referrals for basic, health and caregiving needs. Our research program uses an asset-based, community-engaged approach including study-specific community advisory boards (CABs). In early 2020, both RCT protocols were pre-tested in-person. In March 2020, when pandemic conditions prohibited enrollment during clinical encounters, both protocols were iterated to efficient, caregiver-centered remote operations. Iterations were enabled in part by the Automated Randomized Controlled Trial Information-Communication System (ARCTICS), a trial management system innovation engineered to integrate the data collection database (REDCap) with community resource referral (NowPow) and SMS texting (Mosio) platforms.

Results

Enabled by engaged CABs and ARCTICS, both RCTs quickly adapted to remote operations. Designed before the pandemic, we had planned to launch both trials by March 2020 and complete enrollment by December 2021. The pandemic postponed launch until November (CommunityRx-Hunger) and December (CommunityRx-Dementia) 2020. Despite the delay, 65% of all planned participants (CommunityRx-Hunger n = 417/640; CommunityRx-Dementia n = 222/344) were enrolled by December 2021, halfway through our projected enrollment timeline. Both trials enrolled 13% more participants in 12 months than originally projected in-person.

Conclusions

Our asset-based, community-engaged approach combined with widely accessible institutional and commercial information technologies facilitated rapid migration to remote trial operations. Remote or hybrid RCT designs for social care interventions may be a viable, scalable alternative to in-person recruitment and intervention delivery protocols, particularly for caregivers and other groups that are under-represented in traditional health services research.

Trial Status

Both studies are registered on ClinicalTrials.gov: CommunityRx-Hunger (NCT04171999); CommunityRx for Caregivers (NCT04146545); My Diabetes My Community (NCT04970810).

Unwanted sexual activity among United States women early in the COVID-19 pandemic

BACKGROUND

Female sexual activity and, accordingly, birth rates tend to decline in times of stress, such as a pandemic. In addition, when resources are scarce or exogenous conditions are threatening, some women may engage in sexual activity primarily to maintain socioeconomic security. Having unwanted sex may indicate sexual activity in exchange for economic security.

OBJECTIVE

This study aimed to describe patterns and correlates of unwanted sex, defined as having sex more frequently than desired, among US women early in the COVID-19 pandemic.

STUDY DESIGN

The National US Women's Health COVID-19 Study was conducted in April 2020, using a nested quota sample design to enroll 3200 English-speaking women (88% cooperation rate) aged 18 to 90 years recruited from a research panel. The quota strata ensured sufficient sample sizes in sociodemographic groups of interest, namely, racial and ethnic subgroups. Patterns of sexual activity, including unwanted sex early in the pandemic, were described. To further elucidate the experiences of women reporting unwanted sex, open-ended responses to an item querying "how the coronavirus pandemic is affecting your sex life" were assessed using conventional content analysis. Logistic regression analyses-adjusting for sociodemographic characteristics, self-reported health, and prepandemic health-related socioeconomic risk factors, including food insecurity, housing instability, utilities and transportation difficulties, and interpersonal violence-were used to model the odds of unwanted sex by a pandemic-related change in health-related socioeconomic risk factors.

RESULTS

The proportion of women who were sexually active early in the pandemic (51%) was about the same as in the 12 months before the pandemic (52%), although 7% of women became active, and 7% of women became inactive. Overall, 11% of sexually active women were having unwanted sex in the early pandemic. The rates of anxiety, depression, traumatic stress symptoms, and each of the 5 health-related socioeconomic risk factors assessed were about 2 times higher among women having unwanted sex than other women (P<.001). Women having unwanted sex were also 5 times more likely than other women to report an increased frequency of sex since the pandemic (65% vs 13%; P<.001) and 6 times more likely to be using emergency contraception (18% vs 3%; P<.001). Women reporting unwanted sex commonly described decreased libido or interest in sex related to mood changes since the pandemic, having "more sex," fear or worry about the transmission of the virus because of sex, and having sex to meet the partner's needs. Among sexually active women, the odds of unwanted sex (adjusting for demographic, reproductive, and health factors) were higher among women with 1 prepandemic health-related socioeconomic risk factor (adjusted odds ratio, 2.0; 95% confidence interval, 1.1-3.8) and 2 or more prepandemic health-related socioeconomic risk factors (adjusted odds ratio, 6.0; 95% confidence interval, 3.4-10.6). Among sexually active women with any prepandemic health-related socioeconomic risk factor, those with new or worsening transportation difficulties early in the pandemic were particularly vulnerable to unwanted sex (adjusted odds ratio, 2.7; 95% confidence interval, 1.7-4.3).

CONCLUSION

More than 1 in 10 sexually active US women was having unwanted sex early in the COVID-19 pandemic. Socioeconomically vulnerable women, especially those with new or worsening transportation problems because of the pandemic, were more likely than others to engage in unwanted sex. Pandemic response and recovery efforts should seek to mitigate unwanted sexual activity and related health and social risks among women.

Aggregated cumulative county arsenic in drinking water and associations with bladder, colorectal, and kidney cancers, accounting for population served

BACKGROUND

Many studies neglect to account for variation in population served by community water systems (CWSs) when aggregating CWS-level contaminant concentrations to county level.

OBJECTIVE

In an ecological epidemiologic analysis, we explored two methods-unweighted and weighted (proportion of CWS population served by county population)-to account for population served by CWS in association between arsenic and three cancers to determine the impact of population served on aggregated measures of exposure.

METHODS

CWS arsenic concentration data for 19 states were obtained from Centers for Disease Control and Prevention (CDC) National Environmental Public Health Tracking Network for 2000-10, aggregated to county level, and linked to county-level cancer data for 2011-5 from National Cancer Institute and CDC State Cancer Profiles. Negative binomial regression models estimated adjusted risk ratios (aRR) and 95% confidence intervals (CI) between county-level bladder, colorectal, and kidney cancers and quartiles of aggregated cumulative county-level arsenic concentration (ppb-years).

RESULTS

We observed positive associations between the highest quartile of exposure, compared to the lowest, of aggregated cumulative county-level arsenic concentration (ppb-year) for bladder [weighted aRR: 1.89(1.53, 2.35)], colorectal [1.64(1.33, 2.01)], and kidney [1.69(1.37, 2.09)] cancers. We observed stronger associations utilizing the weighted exposure assessment method. However, inferences from this study are limited due to the ecologic nature of the analyses and different analytic study designs are needed to assess the utility that the weighted by CWS population served metric has for exposure assessment.

SIGNIFICANCE

Weighting by CWS population served accounts for some potential exposure assignment error in epidemiologic analysis.

Diabetes control is associated with environmental quality in the USA

Environmental parameters, including built and sociodemographic environments, can impact diabetes control (DC). Epidemiological studies have associated specific environmental factors with DC; however, the impact of multidimensional environmental status has not been assessed. The Environmental Quality Index (EQI), a comprehensive quantitative metric capturing five environmental domains, was considered as an exposure. Age-adjusted rates of DC prevalence for each county in the United States were used as an outcome. DC was defined as the proportion of adults aged 20+ years with a previous diabetes diagnosis who currently do not have high fasting blood glucose (≥126 mg/dL) or elevated HbA1c (≥6.5). We conducted county-level analyses of DC prevalence rates for the years 2004-2012 in association with EQI for 2006-2010 and domain-specific indices using random intercept multilevel linear regression models clustered by state and controlled for county-level rates of obesity and physical inactivity. Analyses were stratified by rural-urban strata, and results are reported as prevalence rate differences (PRD) with 95% CIs comparing highest quintile/worst environmental quality to lowest quintile/best environmental quality. The association of DC with cumulative environmental quality was negative after control for all counties (PRD -0.32, 95% CI: -0.38, -0.27); suggesting that rates of DC worsen as environmental quality declines. While overall environmental quality exerts effects on DC that vary across the rural-urban spectrum, poor sociodemographic, and built environmental factors are associated with decreased DC nationally. These data suggest improvements in environmental quality mediated by larger-scale policy and practice interventions may improve glycemic control and reduce the morbidity and mortality arising from hyperglycemia.

Observational Study of the Association between Air Cadmium Exposure and Prostate Cancer Aggressiveness at Diagnosis among a Nationwide Retrospective Cohort of 230,540 Patients in the United States

Although studies have investigated cadmium and prostate cancer (PC) incidence and mortality, the role of cadmium in PC progression might be more clinically relevant. In this observational study, we assessed the association between air cadmium exposure and PC aggressiveness, with PC stage defined as metastatic or localized and Gleason grade defined as high (Gleason score ≥ 8) or low (Gleason score ≤ 6) among PC patients from the 2010–2014 US Surveillance, Epidemiology, and End Results database. The 2005 and 2011 National Air Toxics Assessment provided county-level air cadmium concentrations. Results were presented as odds ratios (OR) with 95% confidence intervals (CI) and were calculated using random intercept mixed effects logistic regression, comparing the 80th to 20th percentile of exposure. We adjusted for age, sociodemographic status, smoking prevalence, and overall air quality at the county level, and stratified by race, age, and degree of urbanization. The cohort consisted of 230,540 cases from 493 counties. Strong associations were observed in nonmetropolitan, urban areas: (OR 1.26, CI 1.14–1.39) for metastatic vs. localized and (OR 1.41, CI 1.27–1.57) for high- vs. low-grade PC where 40 million Americans reside. This study may be hypothesis-generating to inform future studies and public health measures.

Association between environmental quality and diabetes in the USA

AIMS/INTRODUCTION

Caloric excess and physical inactivity fail to fully account for the rise of diabetes prevalence. Individual environmental pollutants can disrupt glucose homeostasis and promote metabolic dysfunction. However, the impact of cumulative exposures on diabetes risk is unknown.

MATERIALS AND METHODS

The Environmental Quality Index, a county-level index composed of five domains, was developed to capture the multifactorial ambient environmental exposures. The Environmental Quality Index was linked to county-level annual age-adjusted population-based estimates of diabetes prevalence rates. Prevalence differences (PD, annual difference per 100,000 persons) and 95% confidence intervals (CI) were estimated using random intercept mixed effects linear regression models. Associations were assessed for overall environmental quality and domain-specific indices, and all analyses were stratified by four rural-urban strata.

RESULTS

Comparing counties in the highest quintile/poorest environmental quality to those in the lowest quintile/best environmental quality, counties with poor environmental quality demonstrated lower total diabetes prevalence rates. Associations varied by rural-urban strata; overall better environmental quality was associated with lower total diabetes prevalence rates in the less urbanized and thinly populated strata. When considering all counties, good sociodemographic environments were associated with lower total diabetes prevalence rates (prevalence difference 2.77, 95% confidence interval 2.71-2.83), suggesting that counties with poor sociodemographic environments have an annual prevalence rate 2.77 per 100,000 persons higher than counties with good sociodemographic environments.

CONCLUSIONS

Increasing attention has focused on environmental exposures as contributors to diabetes pathogenesis, and the present findings suggest that comprehensive approaches to diabetes prevention must include interventions to improve environmental quality.

Watershed integrity and associations with gastrointestinal illness in the United States

Gastrointestinal (GI) illnesses are associated with various environmental factors, such as water quality, stormwater runoff, agricultural runoff, sewer overflows, and wastewater treatment plant effluents. However, rather than assessing an individual factor alone, two indices incorporating a combination of ecological and environmental stressors were created to represent (1) overall watershed integrity, Index of Watershed Integrity (IWI) and (2) catchment integrity, Index of Catchment Integrity (ICI). These indices could provide a more comprehensive understanding of how watershed/catchment integrity potentially impact the rates of GI illness, compared to assessing an individual stressor alone. We utilized the IWI and ICI, as well as agricultural and urban land uses, to assess associations at the county level with the rates of GI illness in a population of adults over 65 years of age. Our findings demonstrated that both watershed and catchment integrity are associated with reduced hospitalizations for any GI outcomes, though association varied by urbanicity. We believe that improved versions of the IWI and ICI may potentially be useful indicators for public health analyses in other circumstances, particularly when considering rural areas or to capture the complex stressors impacting the ecological health of a watershed.

Associations between environmental quality and infant mortality in the United States, 2000-2005

Background

The United States (U.S.) suffers from high infant mortality (IM) rates and there are significant racial/ethnic differences in these rates. Prior studies on the environment and infant mortality are generally limited to singular exposures. We utilize the Environmental Quality Index (EQI), a measure of cumulative environmental exposure (across air, water, land, sociodemographic, and land domains) for U.S. counties from 2000 to 2005, to investigate associations between ambient environment and IM across maternal race/ethnicity.

Methods

We linked 2000–2005 infant data from the U.S. Centers for Disease Control and Prevention to the EQI (n = 22,702,529; 144,741 deaths). We utilized multi-level regression to estimate associations between quartiles of county-level EQI and IM. We also considered associations between quartiles of county level domain specific indices with IM. We controlled for rural-urban status (RUCC1: urban, metropolitan; RUCC2: urban, non-metropolitan; RUCC3: less urbanized; RUCC4: thinly populated), maternal age, maternal education, marital status, infant sex, and stratified on race/ethnicity. Additionally, we estimated associations for linear combinations of environmental quality and rural-urban status.

Results

We found a mix of positive, negative, and null associations and our findings varied across domain and race/ethnicity. Poorer overall environmental quality was associated with decreased odds among Non-Hispanic whites (OR and 95% CI: EQIQ4 (ref. EQIQ1): 0.84[0.80,0.89]). For Non-Hispanic blacks and Hispanics, some increased odds were observed. Poorer air quality was monotonically associated with increased odds among Non-Hispanic whites (airQ4 (ref. airQ1): 1.05[0.99,1.11]) and blacks (airQ4 (ref. airQ1): 1.09 [0.9,1.31]). Rural status was associated with increased IM odds among Hispanics (RUCC4-Q4:1.36[1.04,1.78]; RUCC1-Q4: 1.04[0.92,1.16], ref. for both RUCC1-Q1).

Conclusions

This study is the first to report on associations between ambient environmental quality and IM across the United States. It corroborates prior research suggesting an association between air pollution and IM and identifies residence in thinly populated (rural) areas as a potential risk factor towards IM amongst Hispanics. Some of the counterintuitive findings highlight the need for additional research into potentially differential drivers of environmental quality across the rural-urban continuum, especially with regards to the sociodemographic environment.

Electronic supplementary material

The online version of this article (10.1186/s13690-018-0306-0) contains supplementary material, which is available to authorized users.

Associations between environmental quality and adult asthma prevalence in medical claims data

As of 2014, approximately 7.4% of U.S. adults had current asthma. The etiology of asthma is complex, involving genetics, behavior, and environmental factors. To explore the association between cumulative environmental quality and asthma prevalence in U.S. adults, we linked the U.S. Environmental Protection Agency's Environmental Quality Index (EQI) to the MarketScan® Commercial Claims and Encounters Database. The EQI is a summary measure of five environmental domains (air, water, land, built, sociodemographic). We defined asthma as having at least 2 claims during the study period, 2003-2013. We used a Bayesian approach with non-informative priors, implementing mixed-effects regression modeling with a Poisson link function. Fixed effects variables were EQI, sex, race, and age. Random effects were counties. We modeled quintiles of the EQI comparing higher quintiles (worse quality) to lowest quintile (best quality) to estimate prevalence ratios (PR) and credible intervals (CIs). We estimated associations using the cumulative EQI and domain-specific EQIs; we assessed U.S. overall (non-stratified) as well as stratified by rural-urban continuum codes (RUCC) to assess rural/urban heterogeneity. Among the 71,577,118 U.S. adults with medical claims who could be geocoded to county of residence, 1,147,564 (1.6%) met the asthma definition. Worse environmental quality was associated with increased asthma prevalence using the non-RUCC-stratified cumulative EQI, comparing the worst to best EQI quintile (PR:1.27; 95% CI: 1.21, 1.34). Patterns varied among different EQI domains, as well as by rural/urban status. Poor environmental quality may increase asthma prevalence, but domain-specific drivers may operate differently depending on rural/urban status.

The association between physical inactivity and obesity is modified by five domains of environmental quality in U.S. adults: A cross-sectional study

Physical inactivity is a primary contributor to the obesity epidemic, but may be promoted or hindered by environmental factors. To examine how cumulative environmental quality may modify the inactivity-obesity relationship, we conducted a cross-sectional study by linking county-level Behavioral Risk Factor Surveillance System data with the Environmental Quality Index (EQI), a composite measure of five environmental domains (air, water, land, built, sociodemographic) across all U.S. counties. We estimated the county-level association (N = 3,137 counties) between 2009 age-adjusted leisure-time physical inactivity (LTPIA) and 2010 age-adjusted obesity from BRFSS across EQI tertiles using multi-level linear regression, with a random intercept for state, adjusted for percent minority and rural-urban status. We modelled overall and sex-specific estimates, reporting prevalence differences (PD) and 95% confidence intervals (CI). In the overall population, the PD increased from best (PD = 0.341 (95% CI: 0.287, 0.396)) to worst (PD = 0.645 (95% CI: 0.599, 0.690)) EQI tertile. We observed similar trends in males from best (PD = 0.244 (95% CI: 0.194, 0.294)) to worst (PD = 0.601 (95% CI: 0.556, 0.647)) quality environments, and in females from best (PD = 0.446 (95% CI: 0.385, 0.507)) to worst (PD = 0.655 (95% CI: 0.607, 0.703)). We found that poor environmental quality exacerbates the LTPIA-obesity relationship. Efforts to improve obesity through LTPIA may benefit from considering this relationship.

Underutilized and Under Threat: Environmental Policy as a Tool to Address Diabetes Risk

PURPOSE OF REVIEW

Diabetes is a burgeoning threat to public health in the USA. Importantly, the burden of diabetes is not equally borne across society with marked disparities based on geography, race/ethnicity, and income. The etiology of global and population-specific diabetes risk remains incompletely understood; however, evidence linking environmental toxicants acting as endocrine-disrupting chemicals (EDCs), such as particulate matter and arsenic, with diabetes suggests that environmental policies could play an important role in diabetes risk reduction.

RECENT FINDINGS

Evidence suggests that disproportionate exposures to EDCs may contribute to subgroup-specific diabetes risk; however, no federal policies regulate EDCs linked to diabetes based upon diabetogenic potential. Nevertheless, analyses of European Union data indicate that such regulation could reduce diabetes-associated costs and disease burden. Federal laws only regulate EDCs indirectly. The accumulating evidence linking these chemicals with diabetes risk should encourage policymakers to adopt stricter environmental standards that consider both health and economic impacts.

Disparities in Environmental Exposures to Endocrine-Disrupting Chemicals and Diabetes Risk in Vulnerable Populations

Burgeoning epidemiological, animal, and cellular data link environmental endocrine-disrupting chemicals (EDCs) to metabolic dysfunction. Disproportionate exposure to diabetes-associated EDCs may be an underappreciated contributor to disparities in metabolic disease risk. The burden of diabetes is not uniformly borne by American society; rather, this disease disproportionately affects certain populations, including African Americans, Latinos, and low-income individuals. The purpose of this study was to review the evidence linking unequal exposures to EDCs with racial, ethnic, and socioeconomic diabetes disparities in the U.S.; discuss social forces promoting these disparities; and explore potential interventions. Articles examining the links between chemical exposures and metabolic disease were extracted from the U.S. National Library of Medicine for the period of 1966 to 3 December 2016. EDCs associated with diabetes in the literature were then searched for evidence of racial, ethnic, and socioeconomic exposure disparities. Among Latinos, African Americans, and low-income individuals, numerous studies have reported significantly higher exposures to diabetogenic EDCs, including polychlorinated biphenyls, organochlorine pesticides, multiple chemical constituents of air pollution, bisphenol A, and phthalates. This review reveals that unequal exposure to EDCs may be a novel contributor to diabetes disparities. Efforts to reduce the individual and societal burden of diabetes should include educating clinicians on environmental exposures that may increase disease risk, strategies to reduce those exposures, and social policies to address environmental inequality as a novel source of diabetes disparities.

Erratum: "Sanitary Sewer Overflows and Emergency Room Visits for Gastrointestinal Illness: Analysis of Massachusetts Data, 2006-2007"

[This corrects the article DOI: 10.1289/EHP2048.].

Sanitary Sewer Overflows and Emergency Room Visits for Gastrointestinal Illness: Analysis of Massachusetts Data, 2006-2007

BACKGROUND

Sanitary sewer overflows (SSOs) occur when untreated sewage is discharged into water sources before reaching the treatment facility, potentially contaminating the water source with gastrointestinal pathogens.

OBJECTIVES

The objective of this paper is to assess associations between SSO events and rates of gastrointestinal (GI) illness in Massachusetts.

METHODS

A case-crossover study design was used to investigate association between SSO events and emergency room (ER) visits with a primary diagnosis of gastrointestinal (GI) illness in Massachusetts for 2006-2007. ER visits for GI were considered exposed if an SSO event occurred in the county of residence within three hazard periods, 0-4 d, 5-9 d, or 10-14 d, before the visit. A time-stratified bidirectional design was used to select control days for each ER visit on the same day of the week during the same month. Fixed effect logistic regression models were used to estimate the risk of ER visits following the SSO event.

RESULTS

During the study period, there were 270 SSO events for northeastern Massachusetts and 66,460 ER admissions with GI illness listed as the primary diagnostic code. The overall odds ratio (OR) for ER visits for GI illness was 1.09 [95% confidence interval (CI): 1.03, 1.16] in the 10-14 d period following an SSO event, with positive ORs for all age groups and for three of the four counties. The 0-4 d and 5-9 d periods following an SSO event were not associated with ER visits for GI illness overall, and associations by county or age were inconsistent.

CONCLUSIONS

We demonstrated an association between SSO events and ER visits for GI illness using a case-crossover study design. In light of the aging water infrastructure in the United States and the expected increase in heavy rainfall events, our findings suggest a potential health impact associated with sewage overflows. https://doi.org/10.1289/EHP2048.

Swine exposure and methicillin-resistant Staphylococcus aureus infection among hospitalized patients with skin and soft tissue infections in Illinois: A ZIP code-level analysis

BACKGROUND

Methicillin-resistant Staphylococcus aureus (MRSA), a bacterial pathogen, is a predominant cause of skin and soft tissue infections (SSTI) in the United States. Swine-production facilities have been recognized as potential environmental reservoirs of MRSA. To better understand how swine production may contribute to MRSA infection, we evaluated the association between MRSA infection among SSTI inpatients and exposure measures derived from national swine inventory data.

METHODS

Based on adjusted odds ratios from logistic regression models, we evaluated the association between swine exposure metrics and MRSA infections among all Illinois inpatient hospitalizations for SSTI from January 2008 through July 2011. We also assessed if swine exposures had greater association with suspected community-onset MRSA (CO-MRSA) compared to suspected hospital-onset MRSA (HO-MRSA). Exposures were estimated using the Farm Location and Agricultural Production Simulator, generating the number of farms with greater than 1000 swine per residential ZIP code and the residential ZIP code-level swine density (swine/km²).

RESULTS

For every increase in 100 swine/km² within a residential ZIP code, the adjusted OR (aOR) for MRSA infection was 1.36 (95% CI: 1.28-1.45). For every additional large farm (i.e., >1000 swine) per ZIP code, the aOR for MRSA infection was 1.06 (95% CI: 1.04-1.07). The aOR for ZIP codes with any large farms compared to those with no large farms was 1.24 (95% CI: 1.19-1.29). We saw no evidence of an increased association for CO-MRSA compared to HO-MRSA with either continuous exposure metric (aORs=0.99), and observed inconsistent results across exposure categories.

CONCLUSIONS

These publicly-available, ecological exposure data demonstrated positive associations between swine exposure measures and individual-level MRSA infections among SSTI inpatients. Though it is difficult to draw definitive conclusions due to limitations of the data, these findings suggest that the risk of MRSA may increase based on indirect environmental exposure to swine production. Future research can address measurement error related to these data by improving exposure assessment precision, increased specification of MRSA strain, and better characterization of specific environmental exposure pathways.

Hospitalizations due to selected infections caused by opportunistic premise plumbing pathogens (OPPP) and reported drug resistance in the United States older adult population in 1991-2006

The Flint Water Crisis-due to changes of water source and treatment procedures-has revealed many unsolved social, environmental, and public health problems for US drinking water, including opportunistic premise plumbing pathogens (OPPP). The true health impact of OPPP, especially in vulnerable populations such as the elderly, is largely unknown. We explored 10⁸ claims in the largest US national uniformly collected data repository to determine rates and costs of OPPP-related hospitalizations. In 1991-2006, 617,291 cases of three selected OPPP infections resulted in the elderly alone of $0.6 billion USD per year of payments. Antibiotic resistance significantly increased OPPP illness costs that are likely to be underreported. More precise estimates for OPPP burdens could be obtained if better clinical, microbiological, administrative, and environmental monitoring data were cross-linked. An urgent dialog across governmental and disciplinary divides, and studies on preventing OPPP through drinking water exposure, are warranted.

County-level cumulative environmental quality associated with cancer incidence

BACKGROUND

Individual environmental exposures are associated with cancer development; however, environmental exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains.

METHODS

The EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results (SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Incident rate differences (IRDs; annual rate difference per 100,000 persons) and 95% confidence intervals (CIs) were estimated using fixed-slope, random intercept multilevel linear regression models. Associations were assessed with domain-specific indices and analyses were stratified by rural/urban status.

RESULTS

Comparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (IRD, 38.55; 95% CI, 29.57-47.53) and for male (IRD, 32.60; 95% CI, 16.28-48.91) and female (IRD, 30.34; 95% CI, 20.47-40.21) subjects, indicating a potential increase in cancer incidence with decreasing environmental quality. Rural/urban stratified models demonstrated positive associations comparing the highest with the lowest quintiles for all strata, except the thinly populated/rural stratum and in the metropolitan/urbanized stratum. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality.

CONCLUSION

We observed strong positive associations between the EQI and all-site cancer incidence rates, and associations differed by rural/urban status and environmental domain. Research focusing on single environmental exposures in cancer development may not address the broader environmental context in which cancers develop, and future research should address cumulative environmental exposures. Cancer 2017;123:2901-8. © 2017 American Cancer Society.

County-level cumulative environmental quality associated with cancer incidence

BACKGROUND

Individual environmental exposures are associated with cancer development; however, environmental exposures occur simultaneously. The Environmental Quality Index (EQI) is a county-level measure of cumulative environmental exposures that occur in 5 domains.

METHODS

The EQI was linked to county-level annual age-adjusted cancer incidence rates from the Surveillance, Epidemiology, and End Results (SEER) Program state cancer profiles. All-site cancer and the top 3 site-specific cancers for male and female subjects were considered. Incident rate differences (IRDs; annual rate difference per 100,000 persons) and 95% confidence intervals (CIs) were estimated using fixed-slope, random intercept multilevel linear regression models. Associations were assessed with domain-specific indices and analyses were stratified by rural/urban status.

RESULTS

Comparing the highest quintile/poorest environmental quality with the lowest quintile/best environmental quality for overall EQI, all-site county-level cancer incidence rate was positively associated with poor environmental quality overall (IRD, 38.55; 95% CI, 29.57-47.53) and for male (IRD, 32.60; 95% CI, 16.28-48.91) and female (IRD, 30.34; 95% CI, 20.47-40.21) subjects, indicating a potential increase in cancer incidence with decreasing environmental quality. Rural/urban stratified models demonstrated positive associations comparing the highest with the lowest quintiles for all strata, except the thinly populated/rural stratum and in the metropolitan/urbanized stratum. Prostate and breast cancer demonstrated the strongest positive associations with poor environmental quality.

CONCLUSION

We observed strong positive associations between the EQI and all-site cancer incidence rates, and associations differed by rural/urban status and environmental domain. Research focusing on single environmental exposures in cancer development may not address the broader environmental context in which cancers develop, and future research should address cumulative environmental exposures. Cancer 2017;123:2901-8. © 2017 American Cancer Society.

Hospitalizations for heat-stress illness varies between rural and urban areas: an analysis of Illinois data, 1987-2014

BACKGROUND

The disease burden due to heat-stress illness (HSI), which can result in significant morbidity and mortality, is expected to increase as the climate continues to warm. In the United States (U.S.) much of what is known about HSI epidemiology is from analyses of urban heat waves. There is limited research addressing whether HSI hospitalization risk varies between urban and rural areas, nor is much known about additional diagnoses of patients hospitalized for HSI.

METHODS

Hospitalizations in Illinois for HSI (ICD-9-CM codes 992.x or E900) in the months of May through September from 1987 to 2014 (n = 8667) were examined. Age-adjusted mean monthly hospitalization rates were calculated for each county using U.S. Census population data. Counties were categorized into five urban-rural strata using Rural Urban Continuum Codes (RUCC) (RUCC1, most urbanized to RUCC5, thinly populated). Average maximum monthly temperature (°C) was calculated for each county using daily data. Multi-level linear regression models were used, with county as the fixed effect and temperature as random effect, to model monthly hospitalization rates, adjusting for the percent of county population below the poverty line, percent of population that is Non-Hispanic Black, and percent of the population that is Hispanic. All analyses were stratified by county RUCC. Additional diagnoses of patients hospitalized for HSI and charges for hospitalization were summarized.

RESULTS

Highest rates of HSI hospitalizations were seen in the most rural, thinly populated stratum (mean annual summer hospitalization rate of 1.16 hospitalizations per 100,000 population in the thinly populated strata vs. 0.45 per 100,000 in the metropolitan urban strata). A one-degree Celsius increase in maximum monthly average temperature was associated with a 0.34 increase in HSI hospitalization rate per 100,000 population in the thinly populated counties compared with 0.02 per 100,000 in highly urbanized counties. The most common additional diagnoses of patients hospitalized with HSI were dehydration, electrolyte abnormalities, and acute renal disorders. Total and mean hospital charges for HSI cases were $167.7 million and $20,500 (in 2014 US dollars).

CONCLUSION

Elevated temperatures appear to have different impacts on HSI hospitalization rates as function of urbanization. The most rural and the most urbanized counties of Illinois had the largest increases in monthly hospitalization rates for HSI per unit increase in the average monthly maximum temperature. This suggests that vulnerability of communities to heat is complex and strategies to reduce HSI may need to be tailored to the degree of urbanization of a county.

Associations between Environmental Quality and Mortality in the Contiguous United States, 2000-2005

BACKGROUND

Assessing cumulative effects of the multiple environmental factors influencing mortality remains a challenging task.

OBJECTIVES

This study aimed to examine the associations between cumulative environmental quality and all-cause and leading cause-specific (heart disease, cancer, and stroke) mortality rates.

METHODS

We used the overall Environmental Quality Index (EQI) and its five domain indices (air, water, land, built, and sociodemographic) to represent environmental exposure. Associations between the EQI and mortality rates (CDC WONDER) for counties in the contiguous United States (n = 3,109) were investigated using multiple linear regression models and random intercept and random slope hierarchical models. Urbanicity, climate, and a combination of the two were used to explore the spatial patterns in the associations.

RESULTS

We found 1 standard deviation increase in the overall EQI (worse environment) was associated with a mean 3.22% (95% CI: 2.80%, 3.64%) increase in all-cause mortality, a 0.54% (95% CI: -0.17%, 1.25%) increase in heart disease mortality, a 2.71% (95% CI: 2.21%, 3.22%) increase in cancer mortality, and a 2.25% (95% CI: 1.11%, 3.39%) increase in stroke mortality. Among the environmental domains, the associations ranged from -1.27% (95% CI: -1.70%, -0.84%) to 3.37% (95% CI: 2.90%, 3.84%) for all-cause mortality, -2.62% (95% CI: -3.52%, -1.73%) to 4.50% (95% CI: 3.73%, 5.27%) for heart disease mortality, -0.88% (95% CI: -2.12%, 0.36%) to 3.72% (95% CI: 2.38%, 5.06%) for stroke mortality, and -0.68% (95% CI: -1.19%, -0.18%) to 3.01% (95% CI: 2.46%, 3.56%) for cancer mortality. Air had the largest associations with all-cause, heart disease, and cancer mortality, whereas the sociodemographic index had the largest association with stroke mortality. Across the urbanicity gradient, no consistent trend was found. Across climate regions, the associations ranged from 2.29% (95% CI: 1.87%, 2.72%) to 5.30% (95% CI: 4.30%, 6.30%) for overall EQI, and larger associations were generally found in dry areas for both overall EQI and domain indices.

CONCLUSIONS

These results suggest that poor environmental quality, particularly poor air quality, was associated with increased mortality and that associations vary by urbanicity and climate region. Citation: Jian Y, Messer LC, Jagai JS, Rappazzo KM, Gray CL, Grabich SC, Lobdell DT. 2017. Associations between environmental quality and mortality in the contiguous United States, 2000-2005. Environ Health Perspect 125:355-362; http://dx.doi.org/10.1289/EHP119.

Additive Interaction between Heterogeneous Environmental Quality Domains (Air, Water, Land, Sociodemographic, and Built Environment) on Preterm Birth

BACKGROUND

Environmental exposures often occur in tandem; however, epidemiological research often focuses on singular exposures. Statistical interactions among broad, well-characterized environmental domains have not yet been evaluated in association with health. We address this gap by conducting a county-level cross-sectional analysis of interactions between Environmental Quality Index (EQI) domain indices on preterm birth in the Unites States from 2000 to 2005.

METHODS

The EQI, a county-level index constructed for the 2000-2005 time period, was constructed from five domain-specific indices (air, water, land, built, and sociodemographic) using principal component analyses. County-level preterm birth rates (n = 3141) were estimated using live births from the National Center for Health Statistics. Linear regression was used to estimate prevalence differences (PDs) and 95% confidence intervals (CIs) comparing worse environmental quality to the better quality for each model for (a) each individual domain main effect, (b) the interaction contrast, and (c) the two main effects plus interaction effect (i.e., the "net effect") to show departure from additivity for the all U.S. counties. Analyses were also performed for subgroupings by four urban/rural strata.

RESULTS

We found the suggestion of antagonistic interactions but no synergism, along with several purely additive (i.e., no interaction) associations. In the non-stratified model, we observed antagonistic interactions, between the sociodemographic/air domains [net effect (i.e., the association, including main effects and interaction effects) PD: -0.004 (95% CI: -0.007, 0.000), interaction contrast: -0.013 (95% CI: -0.020, -0.007)] and built/air domains [net effect PD: 0.008 (95% CI 0.004, 0.011), interaction contrast: -0.008 (95% CI: -0.015, -0.002)]. Most interactions were between the air domain and other respective domains. Interactions differed by urbanicity, with more interactions observed in non-metropolitan regions.

CONCLUSION

Observed antagonistic associations may indicate that those living in areas with multiple detrimental domains may have other interfering factors reducing the burden of environmental exposure. This study is the first to explore interactions across different environmental domains and demonstrates the utility of the EQI to examine the relationship between environmental domain interactions and human health. While we did observe some departures from additivity, many observed effects were additive. This study demonstrated that interactions between environmental domains should be considered in future analyses.

Extreme Precipitation and Emergency Room Visits for Gastrointestinal Illness in Areas with and without Combined Sewer Systems: An Analysis of Massachusetts Data, 2003-2007

BACKGROUND

Combined sewer overflows (CSOs) occur in combined sewer systems when sewage and stormwater runoff are released into water bodies, potentially contaminating water sources. CSOs are often caused by heavy precipitation and are expected to increase with increasing extreme precipitation associated with climate change.

OBJECTIVES

The aim of this study was to assess whether the association between heavy rainfall and rate of emergency room (ER) visits for gastrointestinal (GI) illness differed in the presence of CSOs.

METHODS

For the study period 2003-2007, time series of daily rate of ER visits for GI illness and meteorological data were organized for three exposure regions: a) CSOs impacting drinking water sources, b) CSOs impacting recreational waters, c) no CSOs. A distributed lag Poisson regression assessed cumulative effects for an 8-day lag period following heavy (≥ 90th and ≥ 95th percentile) and extreme (≥ 99th percentile) precipitation events, controlling for temperature and long-term time trends.

RESULTS

The association between extreme rainfall and rate of ER visits for GI illness differed among regions. Only the region with drinking water exposed to CSOs demonstrated a significant increased cumulative risk for rate (CRR) of ER visits for GI for all ages in the 8-day period following extreme rainfall: CRR: 1.13 (95% CI: 1.00, 1.28) compared with no rainfall.

CONCLUSIONS

The rate of ER visits for GI illness was associated with extreme precipitation in the area with CSO discharges to a drinking water source. Our findings suggest an increased risk for GI illness among consumers whose drinking water source may be impacted by CSOs after extreme precipitation.

CITATION

Jagai JS, Li Q, Wang S, Messier KP, Wade TJ, Hilborn ED. 2015. Extreme precipitation and emergency room visits for gastrointestinal illness in areas with and without combined sewer systems: an analysis of Massachusetts data, 2003-2007. Environ Health Perspect 123:873-879; http://dx.doi.org/10.1289/ehp.1408971.

The associations between environmental quality and preterm birth in the United States, 2000-2005: a cross-sectional analysis

BACKGROUND

Many environmental factors have been independently associated with preterm birth (PTB). However, exposure is not isolated to a single environmental factor, but rather to many positive and negative factors that co-occur. The environmental quality index (EQI), a measure of cumulative environmental exposure across all US counties from 2000-2005, was used to investigate associations between ambient environment and PTB.

METHODS

With 2000-2005 birth data from the National Center for Health Statistics for the United States (n = 24,483,348), we estimated the association between increasing quintiles of the EQI and county-level and individual-level PTB; we also considered environmental domain-specific (air, water, land, sociodemographic and built environment) and urban-rural stratifications.

RESULTS

Effect estimates for the relationship between environmental quality and PTB varied by domain and by urban-rural strata but were consistent across county- and individual-level analyses. The county-level prevalence difference (PD (95% confidence interval) for the non-stratified EQI comparing the highest quintile (poorest environmental quality) to the lowest quintile (best environmental quality) was -0.0166 (-0.0198, -0.0134). The air and sociodemographic domains had the strongest associations with PTB; PDs were 0.0196 (0.0162, 0.0229) and -0.0262 (-0.0300, -0.0224) for the air and sociodemographic domain indices, respectively. Within the most urban strata, the PD for the sociodemographic domain index was 0.0256 (0.0205, 0.0307). Odds ratios (OR) for the individual-level analysis were congruent with PDs.

CONCLUSION

We observed both strong positive and negative associations between measures of broad environmental quality and preterm birth. Associations differed by rural-urban stratum and by the five environmental domains. Our study demonstrates the use of a large scale composite environment exposure metric with preterm birth, an important indicator of population health and shows potential for future research.

Trends in gastroenteritis-associated mortality in the United States, 1985-2005: variations by ICD-9 and ICD-10 codes

BACKGROUND

Trends in gastroenteritis-associated mortality are changing over time with development of antibiotic resistant strains of certain pathogens, improved diagnostic methods, and changing healthcare. In 1999, ICD-10 coding was introduced for mortality records which can also affect trends. We assess trends in gastroenteritis-associated mortality and changes associated with coding.

METHODS

Trends in gastroenteritis-associated mortality rates in the United States were examined using the National Center for Health Statistics Multiple Cause-of-Death Mortality databases for 1985-2005. All deaths with the underlying cause or any contributing cause included gastroenteritis were included. Cases were selected based on ICD9 (pre-1999) and ICD10 (1999-2005) codes and all analyses were stratified by ICD usage. Annual trends in age adjusted mortality rates were assessed using linear regression spline analysis. Relative risks and 95% confidence intervals (CIs) were calculated using Poisson regression adjusted for age group, sex, race, and region.

RESULTS

There were a total of 190,674 deaths related to gastroenteritis in the U.S. from 1985-2005 with an average of 9,080 per year. During this time the percent of deaths related to gastroenteritis more than tripled, increasing from 0.25% to 0.80% of all deaths. Though the time periods varied in length, we demonstrate a significant increase in slope from a 0.0054% annual increase during the period 1985-1998, when ICD-9 coding was used, to a 0.0550% annual increase during 1999-2005, when ICD-10 coding was used. For both time periods, the oldest age group (75+ years) demonstrated the highest risk of death due to gastroenteritis. Additionally, males demonstrated higher risk than females and blacks were at higher risk than whites for death due to gastroenteritis.

CONCLUSIONS

This analysis demonstrates the public health burden of gastroenteritis-associated mortality in the United States and changes in trends due to change from ICD-9 to ICD-10 coding. The overall rate of gastroenteritis-associated mortality has more than tripled over the 21-year period from 1985 to 2005 and the primary burden of deaths due to gastroenteritis is in the elderly population.

Flooding and emergency room visits for gastrointestinal illness in Massachusetts: a case-crossover study

Introduction

Floods and other severe weather events are anticipated to increase as a result of global climate change. Floods can lead to outbreaks of gastroenteritis and other infectious diseases due to disruption of sewage and water infrastructure and impacts on sanitation and hygiene. Floods have also been indirectly associated with outbreaks through population displacement and crowding.

Methods

We conducted a case-crossover study to investigate the association between flooding and emergency room visits for gastrointestinal illness (ER-GI) in Massachusetts for the years 2003 through 2007. We obtained ER-GI visits from the State of Massachusetts and records of floods from the National Oceanic and Atmospheric Association’s Storm Events Database. ER-GI visits were considered exposed if a flood occurred in the town of residence within three hazard periods of the visit: 0–4 days; 5–9 days; and 10–14 days. A time-stratified bi-directional design was used for control selection, matching on day of the week with two weeks lead or lag time from the ER-GI visit. Fixed effect logistic regression models were used to estimate the risk of ER-GI visits following the flood.

Results and Conclusions

A total of 270,457 ER-GI visits and 129 floods occurred in Massachusetts over the study period. Across all counties, flooding was associated with an increased risk for ER-GI in the 0–4 day period after flooding (Odds Ratio: 1.08; 95% Confidence Interval: 1.03–1.12); but not the 5–9 days (Odds Ratio: 0.995; 95% Confidence Interval: 0.955–1.04) or the 10–14 days after (Odds Ratio: 0.966, 95% Confidence Interval: 0.927–1.01). Similar results were observed for different definitions of ER-GI. The effect differed across counties, suggesting local differences in the risk and impact of flooding. Statewide, across the study period, an estimated 7% of ER-GI visits in the 0–4 days after a flood event were attributable to flooding.

Construction of an environmental quality index for public health research

BACKGROUND

A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.

METHODS

The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.

RESULTS

Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).

CONCLUSION

The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.

Construction of an environmental quality index for public health research

BACKGROUND

A more comprehensive estimate of environmental quality would improve our understanding of the relationship between environmental conditions and human health. An environmental quality index (EQI) for all counties in the U.S. was developed.

METHODS

The EQI was developed in four parts: domain identification; data source acquisition; variable construction; and data reduction. Five environmental domains (air, water, land, built and sociodemographic) were recognized. Within each domain, data sources were identified; each was temporally (years 2000-2005) and geographically (county) restricted. Variables were constructed for each domain and assessed for missingness, collinearity, and normality. Domain-specific data reduction was accomplished using principal components analysis (PCA), resulting in domain-specific indices. Domain-specific indices were then combined into an overall EQI using PCA. In each PCA procedure, the first principal component was retained. Both domain-specific indices and overall EQI were stratified by four rural-urban continuum codes (RUCC). Higher values for each index were set to correspond to areas with poorer environmental quality.

RESULTS

Concentrations of included variables differed across rural-urban strata, as did within-domain variable loadings, and domain index loadings for the EQI. In general, higher values of the air and sociodemographic indices were found in the more metropolitan areas and the most thinly populated areas have the lowest values of each of the domain indices. The less-urbanized counties (RUCC 3) demonstrated the greatest heterogeneity and range of EQI scores (-4.76, 3.57) while the thinly populated strata (RUCC 4) contained counties with the most positive scores (EQI score ranges from -5.86, 2.52).

CONCLUSION

The EQI holds promise for improving our characterization of the overall environment for public health. The EQI describes the non-residential ambient county-level conditions to which residents are exposed and domain-specific EQI loadings indicate which of the environmental domains account for the largest portion of the variability in the EQI environment. The EQI was constructed for all counties in the United States, incorporating a variety of data to provide a broad picture of environmental conditions. We undertook a reproducible approach that primarily utilized publically-available data sources.

Seasonality of rotavirus in South Asia: a meta-analysis approach assessing associations with temperature, precipitation, and vegetation index

BACKGROUND

Rotavirus infection causes a significant proportion of diarrhea in infants and young children worldwide leading to dehydration, hospitalization, and in some cases death. Rotavirus infection represents a significant burden of disease in developing countries, such as those in South Asia.

METHODS

We conducted a meta-analysis to examine how patterns of rotavirus infection relate to temperature and precipitation in South Asia. Monthly rotavirus data were abstracted from 39 published epidemiological studies and related to monthly aggregated ambient temperature and cumulative precipitation for each study location using linear mixed-effects models. We also considered associations with vegetation index, gathered from remote sensing data. Finally, we assessed whether the relationship varied in tropical climates and humid mid-latitude climates.

RESULTS

Overall, as well as in tropical and humid mid-latitude climates, low temperature and precipitation levels are significant predictors of an increased rate of rotaviral diarrhea. A 1°C decrease in monthly ambient temperature and a decrease of 10 mm in precipitation are associated with 1.3% and 0.3% increase above the annual level in rotavirus infections, respectively. When assessing lagged relationships, temperature and precipitation in the previous month remained significant predictors and the association with temperature was stronger in the tropical climate. The same association was seen for vegetation index; a seasonal decline of 0.1 units results in a 3.8% increase in rate of rotavirus.

CONCLUSIONS

In South Asia the highest rate of rotavirus was seen in the colder, drier months. Meteorological characteristics can be used to better focus and target public health prevention programs.

Seasonal patterns of gastrointestinal illness and streamflow along the Ohio River

Waterborne gastrointestinal (GI) illnesses demonstrate seasonal increases associated with water quality and meteorological characteristics. However, few studies have been conducted on the association of hydrological parameters, such as streamflow, and seasonality of GI illnesses. Streamflow is correlated with biological contamination and can be used as proxy for drinking water contamination. We compare seasonal patterns of GI illnesses in the elderly (65 years and older) along the Ohio River for a 14-year period (1991-2004) to seasonal patterns of streamflow. Focusing on six counties in close proximity to the river, we compiled weekly time series of hospitalizations for GI illnesses and streamflow data. Seasonal patterns were explored using Poisson annual harmonic regression with and without adjustment for streamflow. GI illnesses demonstrated significant seasonal patterns with peak timing preceding peak timing of streamflow for all six counties. Seasonal patterns of illness remain consistent after adjusting for streamflow. This study found that the time of peak GI illness precedes the peak of streamflow, suggesting either an indirect relationship or a more direct path whereby pathogens enter water supplies prior to the peak in streamflow. Such findings call for interdisciplinary research to better understand associations among streamflow, pathogen loading, and rates of gastrointestinal illnesses.

Data sources for an environmental quality index: availability, quality, and utility

OBJECTIVES

An environmental quality index (EQI) for all counties in the United States is under development to explore the relationship between environmental insults and human health. The EQI is potentially useful for investigators researching health disparities to account for other concurrent environmental conditions. This article focused on the identification and assessment of data sources used in developing the EQI. Data source strengths, limitations, and utility were addressed.

METHODS

Five domains were identified that contribute to environmental quality: air, water, land, built, and sociodemographic environments. An inventory of possible data sources was created. Data sources were evaluated for appropriate spatial and temporal coverage and data quality.

RESULTS

The overall data inventory identified multiple data sources for each domain. From the inventory (187 sources, 617 records), the air, water, land, built environment, and sociodemographic domains retained 2, 9, 7, 4, and 2 data sources for inclusion in the EQI, respectively. However, differences in data quality, geographic coverage, and data availability existed between the domains.

CONCLUSIONS

The data sources identified for use in the EQI may be useful to researchers, advocates, and communities to explore specific environmental quality questions.

Hospitalization of the elderly in the United States for nonspecific gastrointestinal diseases: a search for etiological clues

The frequency of hospitalization among the elderly in the United States caused by gastrointestinal diseases between 1991 and 2004 increased dramatically, especially hospitalization of elderly individuals with nonspecific diagnoses. We analyzed 6 640 304 gastrointestinal disease-associated hospitalization records in this 14-year period by comparing the peak times of nonspecific gastrointestinal diseases with those of specific diseases. We found that most nonspecific gastrointestinal diseases peak concurrently with viral enteritis, suggesting a lack of diagnostic testing for viruses, which may adversely affect the efficiency of prevention, surveillance, and treatment efforts.

Patterns of protozoan infections: spatiotemporal associations with cattle density

Waste from cattle production contains protozoa, such as Cryptosporidium spp. and Giardia, which can be transmitted to humans. People residing in areas of high cattle density may be at increased risk for protozoan infections. The objective of this study was to assess spatial and temporal associations between cattle density and hospitalizations for protozoan infections in the U.S. elderly. Data on protozoan infections were abstracted from Centers for Medicare and Medicaid Services datasets for a 14-year period (1991-2004). Cattle inventory data were abstracted from the 2002 U.S. Census of Agriculture. Counties were classified into one of five exposure categories based on both cattle density and human density. Our analyses considered differences in rates, trends, and variations in seasonal patterns based on exposure categories. Cryptosporidiosis demonstrated a trend of increasing annual rates related to increased potential exposure to cattle. Both cryptosporidiosis and giardiasis demonstrated significant seasonal patterns peaking during the fourth week of October in areas of high cattle/low population density and the second week of September in counties with low cattle/low human density, respectively. Counties with low human population density (regardless of cattle density) had the highest rate of all protozoan infections, peaking in the summer. These results demonstrate the elderly population is at increased risk of protozoan infections in areas of high cattle density, particularly cryptosporidiosis. The seasonal patterns and higher annual rates seen in rural areas suggest time-variant environmental exposures, which may be affected with geographical and temporal targeting of agricultural policies and interventions to improve public health.

Seasonality of cryptosporidiosis: A meta-analysis approach

OBJECTIVES

We developed methodology for and conducted a meta-analysis to examine how seasonal patterns of cryptosporidiosis, a primarily waterborne diarrheal illness, relate to precipitation and temperature fluctuations worldwide.

METHODS

Monthly cryptosporidiosis data were abstracted from 61 published epidemiological studies that cover various climate regions based on the Köppen Climate Classification. Outcome data were supplemented with monthly aggregated ambient temperature and precipitation for each study location. We applied a linear mixed-effect model to relate the monthly normalized cryptosporidiosis incidence with normalized location-specific temperature and precipitation data. We also conducted a sub-analysis of associations between the Normalized Difference Vegetation Index (NDVI), a remote sensing measure for the combined effect of temperature and precipitation on vegetation, and cryptosporidiosis in Sub-Saharan Africa.

RESULTS

Overall, and after adjusting for distance from the equator, increases in temperature and precipitation predict an increase in cryptosporidiosis; the strengths of relationship vary by climate subcategory. In moist tropical locations, precipitation is a strong seasonal driver for cryptosporidiosis whereas temperature is in mid-latitude and temperate climates. When assessing lagged relationships, temperature and precipitation remain strong predictors. In Sub-Saharan Africa, after adjusting for distance from the equator, low NDVI values are predictive of an increase in cryptosporidiosis in the following month.

DISCUSSION

In this study we propose novel methodology to assess relationships between disease outcomes and meteorological data on a global scale. Our findings demonstrate that while climatic conditions typically define a pathogen habitat area, meteorological factors affect timing and intensity of seasonal outbreaks. Therefore, meteorological forecasts can be utilized to develop focused prevention programs for waterborne cryptosporidiosis.

The SEEDs of two gastrointestinal diseases: socioeconomic, environmental, and demographic factors related to cryptosporidiosis and giardiasis in Massachusetts

OBJECTIVES

We assessed associations between community-level socioeconomic, demographic, and environmental characteristics, and the presence of two potentially waterborne infectious diseases, cryptosporidiosis and giardiasis, as reported to the Massachusetts Department of Public Health.

METHODS

We created a series of maps showing the spatial distribution of cryptosporidiosis and giardiasis in Massachusetts (1993-2002) overall and by age, using logistic regression to analyze associations between community-level characteristics and the presence of at least one reported case of each disease. This analysis was repeated for communities with predominantly private water supplies.

RESULT

After adjusting for population size, higher population density and larger than average household sizes were associated with increased odds of reported cases of cryptosporidiosis. Giardiasis was also associated with high population density, but was not associated with household size. In the elderly, income was positively associated with the presence of giardiasis.

DISCUSSION

These findings suggest that greater population density and larger household sizes may increase the likelihood of protozoan gastrointestinal infection. The results emphasize the necessity to account for distal factors, such as demographic characteristics, that may ultimately play a role in the transmission or reporting of disease.

Seasonality in six enterically transmitted diseases and ambient temperature

We propose an analytical and conceptual framework for a systematic and comprehensive assessment of disease seasonality to detect changes and to quantify and compare temporal patterns. To demonstrate the proposed technique, we examined seasonal patterns of six enterically transmitted reportable diseases (EDs) in Massachusetts collected over a 10-year period (1992-2001). We quantified the timing and intensity of seasonal peaks of ED incidence and examined the synchronization in timing of these peaks with respect to ambient temperature. All EDs, except hepatitis A, exhibited well-defined seasonal patterns which clustered into two groups. The peak in daily incidence of Campylobacter and Salmonella closely followed the peak in ambient temperature with the lag of 2-14 days. Cryptosporidium, Shigella, and Giardia exhibited significant delays relative to the peak in temperature (approximately 40 days, P<0.02). The proposed approach provides a detailed quantification of seasonality that enabled us to detect significant differences in the seasonal peaks of enteric infections which would have been lost in an analysis using monthly or weekly cumulative information. This highly relevant to disease surveillance approach can be used to generate and test hypotheses related to disease seasonality and potential routes of transmission with respect to environmental factors.

Emergency room visits for respiratory conditions in children increased after Guagua Pichincha volcanic eruptions in April 2000 in Quito, Ecuador observational study: time series analysis

BACKGROUND

This study documented elevated rates of emergency room (ER) visits for acute upper and lower respiratory infections and asthma-related conditions in the children of Quito, Ecuador associated with the eruption of Guagua Pichincha in April of 2000.

METHODS

We abstracted 5169 (43% females) ER records with primary respiratory conditions treated from January 1-December 27, 2000 and examined the change in pediatric ER visits for respiratory conditions before, during, and after exposure events of April, 2000. We applied a Poisson regression model adapted to time series of cases for three non-overlapping disease categories: acute upper respiratory infection (AURI), acute lower respiratory infection (ALRI), and asthma-related conditions in boys and girls for three age groups: 0-4, 5-9, and 10-15 years.

RESULTS

At the main pediatric medical facility, the Baca Ortiz Pediatric Hospital, the rate of emergency room (ER) visits due to respiratory conditions substantially increased in the three weeks after eruption (RR = 2.22, 95%CI = [1.95, 2.52] and RR = 1.72 95%CI = [1.49, 1.97] for lower and upper respiratory tract infections respectively. The largest impact of eruptions on respiratory distress was observed in children younger than 5 years (RR = 2.21, 95%CI = [1.79, 2.73] and RR = 2.16 95%CI = [1.67, 2.76] in boys and girls respectively). The rate of asthma and asthma-related diagnosis doubled during the period of volcano fumarolic activity (RR = 1.97, 95%CI = [1.19, 3.24]). Overall, 28 days of volcanic activity and ash releases resulted in 345 (95%CI = [241, 460]) additional ER visits due to respiratory conditions.

CONCLUSION

The study has demonstrated strong relationship between ash exposure and respiratory effects in children.