Improving the environmental quality component of the County Health Rankings model.

OBJECTIVES: We examined the association between environmental quality measures and health outcomes by using the County Health Rankings data, and tested whether a revised environmental quality measure for 1 state could improve the models. METHODS: We conducted state-by-state, county-level linear regression analyses to determine how often the model's 4 health determinants (social and economic factors, health behaviors, clinical care, and physical environment) were associated with mortality and morbidity outcomes. We then developed a revised measure of environmental quality for West Virginia, and tested whether the revised measure was superior to the original measure. RESULTS: Measures of social and economic conditions, and health behaviors, were related to health outcomes in 58% to 88% of state models; measures of environmental quality were related to outcomes in 0% to 8% of models. In West Virginia, the original measure of environmental quality was unrelated to any of the 8 health outcome measures, but the revised measure was significantly related to all 8. CONCLUSIONS: The County Health Rankings model underestimates the impact of the physical environment on public health outcomes. Suggestions for other data sources that may contribute to improved measurement of the physical environment are provided.

Adult tooth loss for residents of US coal mining and Appalachian counties.

OBJECTIVES: The authors compared rates of tooth loss between adult residents of Appalachian coal-mining areas and other areas of the nation before and after control for covariate risks. METHODS: The authors conducted a cross-sectional secondary data analysis that merged 2006 national Behavioral Risk Factor Surveillance System data (BRFSS) (N = 242 184) with county coal-mining data and other county characteristics. The hypothesis tested was that adult tooth loss would be greater in Appalachian mining areas after control for other risks. Primary independent variables included main effects for coal-mining present (yes/no) residence in Appalachia (yes/no), and their interaction. Data were weighted using the BRFSS final weights and analyzed using SUDAAN Proc Multilog to account for the multilevel complex sampling structure. The odds of two measures of tooth loss were examined controlling for age, race\ethnicity, drinking, smoking, income, education, supply of dentists, receipt of dental care, fluoridation rate, and other variables. RESULTS: After covariate adjustment, the interaction variable for the residents of Appalachian coal-mining counties showed a significantly elevated odds for any tooth loss [odds ratio (OR) = 1.19, 95% CI = 1.02, 1.38], and greater tooth loss measured by a 4-level edentulism scale (OR = 1.20, 95% CI = 1.05, 1.36). The main effect for Appalachia was also significant for both measures, but the main effect for coal mining was not. CONCLUSIONS: Greater risk of tooth loss among adult residents of Appalachian coal-mining areas is present and is not explained by differences in reported receipt of dental care, fluoridation rates, supply of dentists or other behavioral or socioeconomic risks. Possible contributing factors include mining-specific disparities related to access, behavior or environmental exposures.

The association between mountaintop mining and birth defects among live births in central Appalachia, 1996-2003.

Birth defects are examined in mountaintop coal mining areas compared to other coal mining areas and non-mining areas of central Appalachia. The study hypothesis is that higher birth-defect rates are present in mountaintop mining areas. National Center for Health Statistics natality files were used to analyze 1996-2003 live births in four Central Appalachian states (N=1,889,071). Poisson regression models that control for covariates compare birth defect prevalence rates associated with maternal residence in county mining type: mountaintop mining areas, other mining areas, or non-mining areas. The prevalence rate ratio (PRR) for any birth defect was significantly higher in mountaintop mining areas compared to non-mining areas (PRR=1.26, 95% CI=1.21, 1.32), after controlling for covariates. Rates were significantly higher in mountaintop mining areas for six of seven types of defects: circulatory/respiratory, central nervous system, musculoskeletal, gastrointestinal, urogenital, and 'other'. There was evidence that mountaintop mining effects became more pronounced in the latter years (2000-2003) versus earlier years (1996-1999.) Spatial correlation between mountaintop mining and birth defects was also present, suggesting effects of mountaintop mining in a focal county on birth defects in neighboring counties. Elevated birth defect rates are partly a function of socioeconomic disadvantage, but remain elevated after controlling for those risks. Both socioeconomic and environmental influences in mountaintop mining areas may be contributing factors.

Full cost accounting for the life cycle of coal.

Each stage in the life cycle of coal-extraction, transport, processing, and combustion-generates a waste stream and carries multiple hazards for health and the environment. These costs are external to the coal industry and are thus often considered "externalities." We estimate that the life cycle effects of coal and the waste stream generated are costing the U.S. public a third to over one-half of a trillion dollars annually. Many of these so-called externalities are, moreover, cumulative. Accounting for the damages conservatively doubles to triples the price of electricity from coal per kWh generated, making wind, solar, and other forms of nonfossil fuel power generation, along with investments in efficiency and electricity conservation methods, economically competitive. We focus on Appalachia, though coal is mined in other regions of the United States and is burned throughout the world.

Mortality in Appalachian coal mining regions: the value of statistical life lost.

OBJECTIVES: We examined elevated mortality rates in Appalachian coal mining areas for 1979-2005, and estimated the corresponding value of statistical life (VSL) lost relative to the economic benefits of the coal mining industry. METHODS: We compared age-adjusted mortality rates and socioeconomic conditions across four county groups: Appalachia with high levels of coal mining, Appalachia with lower mining levels, Appalachia without coal mining, and other counties in the nation. We converted mortality estimates to VSL estimates and compared the results with the economic contribution of coal mining. We also conducted a discount analysis to estimate current benefits relative to future mortality costs. RESULTS: The heaviest coal mining areas of Appalachia had the poorest socioeconomic conditions. Before adjusting for covariates, the number of excess annual age-adjusted deaths in coal mining areas ranged from 3975 to 10,923, depending on years studied and comparison group. Corresponding VSL estimates ranged from $18.563 billion to $84.544 billion, with a point estimate of $50.010 billion, greater than the $8.088 billion economic contribution of coal mining. After adjusting for covariates, the number of excess annual deaths in mining areas ranged from 1736 to 2889, and VSL costs continued to exceed the benefits of mining. Discounting VSL costs into the future resulted in excess costs relative to benefits in seven of eight conditions, with a point estimate of $41.846 billion. CONCLUSIONS: Research priorities to reduce Appalachian health disparities should focus on reducing disparities in the coalfields. The human cost of the Appalachian coal mining economy outweighs its economic benefits.

Community participation and the emergence of late-life depressive symptoms: differences between women and men.

OBJECTIVE: To understand the role of community participation in prevention of first lifetime depressive episode in older women and men. METHODS: We used data from the Wisconsin Longitudinal Study to identify variables that predicted risk for the emergence of depressive symptoms and tested a hypothesis that community participation would protect women from depression more than it would protect men. The sample was drawn from Wisconsin high school graduates who were approximately 64-66 years of age in the 2003-2005 data collection period (n = 2546 with complete data meeting inclusion criteria.) The sample consisted of persons who had no evidence of current or prior lifetime depression in the 1993 data collection period. The emergence of high depressive symptoms was examined for women and men as a function of community participation and other covariates, including social support. RESULTS: The emergence of depressive symptoms for both sexes was predicted by poorer reported health status and higher levels of subthreshold depressive symptoms during the previous interview. For men, additional risk factors were pain and low income. For women, additional risks were widowhood, lower education, and lower community participation. CONCLUSIONS: Community participation, in the form of volunteering, religious attendance, and engagement in community organizations, is related to reduced risk of first-time depressive symptoms among older women.

Relations between health indicators and residential proximity to coal mining in West Virginia.

We used data from a survey of 16493 West Virginians merged with county-level coal production and other covariates to investigate the relations between health indicators and residential proximity to coal mining. Results of hierarchical analyses indicated that high levels of coal production were associated with worse adjusted health status and with higher rates of cardiopulmonary disease, chronic obstructive pulmonary disease, hypertension, lung disease, and kidney disease. Research is recommended to ascertain the mechanisms, magnitude, and consequences of a community coal-mining exposure effect.

Hospitalization patterns associated with Appalachian coal mining.

The goal of this study was to test whether the volume of coal mining was related to population hospitalization risk for diseases postulated to be sensitive or insensitive to coal mining by-products. The study was a retrospective analysis of 2001 adult hospitalization data (n = 93,952) for West Virginia, Kentucky, and Pennsylvania, merged with county-level coal production figures. Hospitalization data were obtained from the Health Care Utilization Project National Inpatient Sample. Diagnoses postulated to be sensitive to coal mining by-product exposure were contrasted with diagnoses postulated to be insensitive to exposure. Data were analyzed using hierarchical nonlinear models, controlling for patient age, gender, insurance, comorbidities, hospital teaching status, county poverty, and county social capital. Controlling for covariates, the volume of coal mining was significantly related to hospitalization risk for two conditions postulated to be sensitive to exposure: hypertension and chronic obstructive pulmonary disease (COPD). The odds for a COPD hospitalization increased 1% for each 1462 tons of coal, and the odds for a hypertension hospitalization increased 1% for each 1873 tons of coal. Other conditions were not related to mining volume. Exposure to particulates or other pollutants generated by coal mining activities may be linked to increased risk of COPD and hypertension hospitalizations. Limitations in the data likely result in an underestimate of associations.

Anesthesia staffing and anesthetic complications during cesarean delivery: a retrospective analysis.

BACKGROUND: Obstetrical anesthesia services may be provided by Certified Registered Nurse Anesthetists (CRNAs), anesthesiologists, or a combination of the two providers. Research is needed to assist hospitals and anesthesia groups in making cost-effective staffing choices. OBJECTIVES: To identify differences in the rates of anesthetic complications in hospitals whose obstetrical anesthesia is provided solely by CRNAs compared to hospitals with only anesthesiologists. METHODS: Washington State hospital discharge data were obtained from 1993 to 2004 for all cesarean sections, and were merged with a survey of hospital obstetrical anesthesia staffing. Anesthetic complications were identified via International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes. Resulting rates were risk-adjusted using regression analysis. RESULTS: Hospitals with CRNA-only staffing had a lower rate of anesthetic complications than those with anesthesiologist staffing (0.58% vs. 0.76%, p=.0006). However, after regression analysis, this difference was not significant (odds ratio for CRNA vs. anesthesiologist complications: 1.046 to 1, 95% confidence interval 0.649-1.658, p=.85). DISCUSSION: There is no difference in rates of complications between the two types of staffing models. As a result, hospitals and anesthesiology groups may safely examine other variables, such as provider availability and costs, when staffing for obstetrical anesthesia. Further study is needed to validate the use of ICD-9-CM codes for anesthesia complications as an indicator of quality.

Avoidable hospitalizations for diabetes: comorbidity risks.

This study examined the risk for avoidable diabetes hospitalizations associated with comorbid conditions and other risk variables. A retrospective analysis was conducted of hospitalizations with a primary diagnosis of diabetes in a 2004 sample of short stay general hospitals in the United States (N = 97,526.) Data were drawn from the Health Care Utilization Project National Inpatient Sample. Avoidable hospitalizations were defined using criteria from the Agency for Healthcare Research and Quality to analyze 2 types of ambulatory care sensitive conditions (ACSCs): short-term complications and uncontrolled diabetes. Maternal cases, patients younger than age 18, and transfers from other hospitals were excluded. Avoidable hospitalization was estimated using maximum likelihood logistic regression analysis, where independent variables included patient age, gender, comorbidities, uninsurance status, patient's rural-urban residence and income estimate, and hospital variables. Models were identified using multiple runs on 3 random quartiles and validated using the fourth quartile. Costs were estimated from charge data using cost-to-charge ratios. Results indicated that these 2 ACSCs accounted for 35,312 or 36% of all diabetes hospitalizations. Multiple types of comorbid conditions were related to risk for avoidable diabetes hospitalizations. Estimated costs and length of stay were lower among these types of avoidable hospitalizations compared to other diabetes hospitalizations; however, total estimated nationwide costs for 2004 short-term complications and uncontrolled diabetes hospitalizations totaled over $1.3 billion. Recommendations are made for how disease management programs for diabetes could incorporate treatment for comorbid conditions to reduce hospitalization risk.

Social capital and risk for chronic illnesses.

OBJECTIVES: This study used an ecological model of social capital to examine the relationship between social capital and chronic illness. The model hypothesizes that personal social support and collective social capital are related to risk for chronic illnesses. METHODS: Data were taken from the American Changing Lives public use database. Seven hundred and sixty-nine persons meeting inclusion criteria were included. Dependent variables were the reported presence of hypertension and diabetes. Logistic regression analysis was used to identify correlates of these chronic illnesses, including demographic variables, and social capital and social support variables measured at both the personal and collective levels. RESULTS: Significant results were usually consistent with model hypotheses; that is, measures of social capital and social support were related to the presence of diabetes and hypertension in expected ways. However, in other cases, the hypothesized relationships were not statistically significant, due to limitations in the model or data. DISCUSSION: Social support and social capital both serve as protective factors against chronic illness. Development of social capital may proceed from the personal family and social environment to collective measures of trust and engagement, and this suggests that family relationships are the foundation on which to base efforts to build social capital.

Social capital and trust in providers.

Trust in providers has been in decline in recent decades. This study attempts to identify sources of trust in characteristics of health care systems and the wider community. The design is cross-sectional. Data are from (1) the 1996 Household Survey of the Community Tracking Study, drawn from 24 Metropolitan Statistical Areas; (2) a 1996 multi-city broadcast media marketing database including key social capital indicators; (3) Interstudy; (4) the American Hospital Association; and (5) the American Medical Association. Independent variables include individual socio-demographic variables, HMO enrollment, community-level health sector variables, and social capital. The dependent variable is self-reported trust in physicians. Data are merged from the various sources and analyzed using SUDAAN. Subjects include adults in the Household Survey who responded to the items on trust in physicians (N=17,653). Trust in physicians is independently predicted by community social capital (p<0.001). Trust is also negatively related to HMO enrollment and to many individual characteristics. The effect of HMOs is not uniform across all communities. Social capital plays a role in how health care is perceived by citizens, and how health care is delivered by providers. Efforts to build trust and collaboration in a community may improve trust in physicians, health care quality, access, and preserve local health care control.

Access to health care and community social capital.

OBJECTIVE: To test the hypothesis that variation in reported access to health care is positively related to the level of social capital present in a community. DATA SOURCES: The 1996 Household Survey of the Community Tracking Study, drawn from 22 metropolitan statistical areas across the United States (n = 19,672). Additional data for the 22 communities are from a 1996 multicity broadcast media marketing database, including key social capital indicators, the 1997 National Profile of Local Health Departments survey, and Interstudy, American Hospital Association, and American Medical Association sources. STUDY DESIGN: The design is cross-sectional. Self-reported access to care problems is the dependent variable. Independent variables include individual sociodemographic variables, community-level health sector variables, and social capital variables. DATA COLLECTION/EXTRACTION METHODS: Data are merged from the various sources and weighted to be population representative and are analyzed using hierarchical categorical modeling. PRINCIPAL FINDINGS: Persons who live in metropolitan statistical areas featuring higher levels of social capital report fewer problems accessing health care. A higher HMO penetration rate in a metropolitan statistical area was also associated with fewer access problems. Other health sector variables were not related to health care access. CONCLUSIONS: The results observed for 22 major U.S. cities are consistent with the hypothesis that community social capital enables better access to care, perhaps through improving community accountability mechanisms.