Are residents of mountain-top mining counties more likely to have infants with birth defects? The West Virginia experience.

BACKGROUND: Pooled 1996 to 2003 birth certificate data for four central states in Appalachia indicated higher rates of infants with birth defects born to residents of counties with mountain-top mining (MTM) than born to residents of non-mining-counties (Ahern 2011). However, those analyses did not consider sources of uncertainty such as unbalanced distributions or quality of data. Quality issues have been a continuing problem with birth certificate analyses. We used 1990 to 2009 live birth certificate data for West Virginia to reassess this hypothesis. METHODS: Forty-four hospitals contributed 98% of the MTM-county births and 95% of the non-mining-county births, of which six had more than 1000 births from both MTM and nonmining counties. Adjusted and stratified prevalence rate ratios (PRRs) were computed both by using Poisson regression and Mantel-Haenszel analysis. RESULTS: Unbalanced distribution of hospital births was observed by mining groups. The prevalence rate of infants with reported birth defects, higher in MTM-counties (0.021) than in non-mining-counties (0.015), yielded a significant crude PRR (cPRR = 1.43; 95% confidence interval [CI] = 1.36-1.52) but a nonsignificant hospital-adjusted PRR (adjPRR = 1.08; 95% CI = 0.97-1.20; p = 0.16) for the 44 hospitals. So did the six hospital data analysis ([cPRR = 2.39; 95% CI = 2.15-2.65] and [adjPRR = 1.01; 95% CI, 0.89-1.14; p = 0.87]). CONCLUSION: No increased risk of birth defects was observed for births from MTM-counties after adjustment for, or stratification by, hospital of birth. These results have consistently demonstrated that the reported association between birth defect rates and MTM coal mining was a consequence of data heterogeneity. The data do not demonstrate evidence of a "Mountain-top Mining" effect on the prevalence of infants with reported birth defects in WV.

Discontinuity in the cancer slope factor as it passes from high to low exposure levels--arsenic in the BFD-endemic area.

BACKGROUND: The ingestion of inorganic arsenic causes bladder and lung cancers demonstrably at >400-500ug/L but questionably below 100-200ug/L. Using the standard 42-village cancer mortality dataset from the Blackfoot-disease (BFD) endemic area of southwest Taiwan (Wu et al., 1989), we examined the risk from low exposures by excluding the high exposures. METHOD: Poisson regression analyses with the sequential removal of the highest exposure village have been performed using the median, mean, or maximum village well water arsenic level and demonstrated graphically. RESULTS: Risk estimates are positive when villages with exposures of 200-400ug/L are included and significantly so when villages with >400ug/L are included. Risk estimates for exposures below 100ug/L are negative but rarely significantly so. The inflection point where the slope is no longer positive occurs in the range of 100-200ug/L, depending upon whether the exposure metric used is the median, the mean or the maximum. CONCLUSION: There is a discontinuity in the cancer slope factor or risk from arsenic exposure that occurs in the range of 100-200ug/L. Above these levels, there are significantly positive risks, while below these levels there are not. The analysis reveals within this dataset an intrinsic non-linearity in the cancer risk. The literature speaks to this discontinuity, but this is the first demonstration within a single dataset that shows the discontinuity across the full exposure range and where the low-dose data are not compromised with high-dose data.

The influence of misclassification bias on the reported rates of congenital anomalies on the birth certificates for West Virginia--a consequence of an open-ended query.

BACKGROUND: Passive surveillance for congenital anomalies using birth certificates are generally considered to have biased reporting, though the sources of those biases are not well-known nor controlled for. We have analyzed the congenital anomaly reporting data for 418,385 live births in West Virginia (1990-2009) from the 1989 US standard birth certificate and have newly identified a particular source of bias. METHODS: Congenital anomaly prevalence rates per 100 live births have been determined for both specified birth defects and for other congenital anomalies by county, by hospital, and by year. Extreme outliers were identified by z score. Text strings for "other congenital anomaly" reports recorded for 1998-2009 were assessed for information on congenital anomalies. RESULTS: While rates for specified birth defects reported in checked-box format showed little variation, rates for "other congenital anomaly" collected in open-ended format showed much variation. Nearly half of the "other congenital anomaly" reports were for neonatal conditions rather than for major structural congenital anomalies. This misclassification alone had elevated the state-wide congenital anomaly reporting rate from 1.1 to 1.8% of live births. Geographic clustering and a temporal bulge in congenital anomaly reports disappeared after misclassified data were removed. CONCLUSIONS: Data collected in checked-box format on specified birth defects showed consistent patterns over time and space, while data collected in open-ended format on "other congenital anomalies" showed an epidemiological pattern reflecting neonatal conditions rather than birth defects. The 2003 US standard birth certificate wisely limits data collection to specified birth defects using the checked-box format.

Bladder/lung cancer mortality in Blackfoot-disease (BFD)-endemic area villages with low (<150 µg/L) well water arsenic levels--an exploration of the dose-response Poisson analysis.

OBJECTIVE: To examine the analytic role of arsenic exposure on cancer mortality among the low-dose (well water arsenic level <150 µg/L) villages in the Blackfoot-disease (BFD) endemic area of southwest Taiwan and with respect to the southwest regional data. METHOD: Poisson analyses of the bladder and lung cancer deaths with respect to arsenic exposure (µg/kg/day) for the low-dose (<150 µg/L) villages with exposure defined by the village median, mean, or maximum and with or without regional data. RESULTS: Use of the village median well water arsenic level as the exposure metric introduced misclassification bias by including villages with levels >500 µg/L, but use of the village mean or the maximum did not. Poisson analyses using mean or maximum arsenic levels showed significant negative cancer slope factors for models of bladder cancers and of bladder and lung cancers combined. Inclusion of the southwest Taiwan regional data did not change the findings when the model contained an explanatory variable for non-arsenic differences. A positive slope could only be generated by including the comparison population as a separate data point with the assumption of zero arsenic exposure from drinking water and eliminating the variable for non-arsenic risk factors. CONCLUSION: The cancer rates are higher among the low-dose (<150 µg/L) villages in the BFD area than in the southwest Taiwan region. However, among the low-dose villages in the BFD area, cancer risks suggest a negative association with well water arsenic levels. Positive differences from regional data seem attributable to non-arsenic ecological factors.