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Estimating uncertainty in observational studies of associations between continuous variables: example of methylmercury and neuropsychological testing in children.

ABSTRACT: BACKGROUND:We suggest that the need to account for systematic error may explain the apparent lack of agreement among studies of maternal dietary methylmercury exposure and neuropsychological testing outcomes in children, a topic of ongoing debate. METHODS:These sensitivity analyses address the possible role of systematic error on reported associations between low-level prenatal exposure to methylmercury and neuropsychological test results in two well known, but apparently conflicting cohort studies: the Faroe Islands Study (FIS) and the Seychelles Child Development Study (SCDS). We estimated the potential impact of confounding, selection bias, and information bias on reported results in these studies using the Boston Naming Test (BNT) score as the outcome variable. RESULTS:Our findings indicate that, assuming various degrees of bias (in either direction) the corrected regression coefficients largely overlap. Thus, the reported effects in the two studies are not necessarily different from each other. CONCLUSION:Based on our sensitivity analysis results, it is not possible to draw definitive conclusions about the presence or absence of neurodevelopmental effects due to in utero methylmercury exposure at levels reported in the FIS and SCDS.

SUBMITTER: Goodman M

PROVIDER: S-EPMC2137924 | biostudies-literature | 2007 Sep

REPOSITORIES: biostudies-literature

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Estimating uncertainty in observational studies of associations between continuous variables: example of methylmercury and neuropsychological testing in children.

Goodman Michael M Barraj Leila M LM Mink Pamela J PJ Britton Nicole L NL Yager Janice W JW Flanders W Dana WD Kelsh Michael A MA

Epidemiologic perspectives & innovations : EP+I 20070926

<h4>Background</h4>We suggest that the need to account for systematic error may explain the apparent lack of agreement among studies of maternal dietary methylmercury exposure and neuropsychological testing outcomes in children, a topic of ongoing debate.<h4>Methods</h4>These sensitivity analyses address the possible role of systematic error on reported associations between low-level prenatal exposure to methylmercury and neuropsychological test results in two well known, but apparently conflict ...[more]

PMID: 17894895

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Project description:ObjectiveTo estimate health care systems' value in treating major illnesses for each US state and identify system characteristics associated with value.Data sourcesAnnual condition-specific death and incidence estimates for each US state from the Global Burden Disease 2019 Study and annual health care spending per person for each state from the National Health Expenditure Accounts.Study designUsing non-linear meta-stochastic frontier analysis, mortality incidence ratios for 136 major treatable illnesses were regressed separately on per capita health care spending and key covariates such as age, obesity, smoking, and educational attainment. State- and year-specific inefficiency estimates were extracted for each health condition and combined to create a single estimate of health care delivery system value for each US state for each year, 1991-2014. The association between changes in health care value and changes in 23 key health care system characteristics and state policies was measured.Data collection/extraction methodsNot applicable.Principal findingsUS state with relatively high spending per person or relatively poor health-outcomes were shown to have low health care delivery system value. New Jersey, Maryland, Florida, Arizona, and New York attained the highest value scores in 2014 (81 [95% uncertainty interval 72-88], 80 [72-87], 80 [71-86], 77 [69-84], and 77 [66-85], respectively), after controlling for health care spending, age, obesity, smoking, physical activity, race, and educational attainment. Greater market concentration of hospitals and of insurers were associated with worse health care value (p-value ranging from <0.01 to 0.02). Higher hospital geographic density and use were also associated with worse health care value (p-value ranging from 0.03 to 0.05). Enrollment in Medicare Advantage HMOs was associated with better value, as was more generous Medicaid income eligibility (p-value 0.04 and 0.01).ConclusionsSubstantial variation in the value of health care exists across states. Key health system characteristics such as market concentration and provider density were associated with value.

Dataset Information

Estimating uncertainty in observational studies of associations between continuous variables: example of methylmercury and neuropsychological testing in children.

Publications

Estimating uncertainty in observational studies of associations between continuous variables: example of methylmercury and neuropsychological testing in children.

Similar Datasets

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