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Background: Direct estimates of rare disease prevalence from public health surveillance may only be available in a few catchment areas. Understanding variation among observed prevalence can inform estimates of prevalence in other locations. The Muscular Dystrophy Surveillance, Tracking, and Research Network (MD STARnet) conducts population-based surveillance of major muscular dystrophies in selected areas of the United States. We identified sources of variation in prevalence estimates of Duchenne and Becker muscular dystrophy (DBMD) within MD STARnet from published literature and a survey of MD STARnet investigators, then developed a logic model of the relationships between the sources of variation and estimated prevalence. Results: The 17 identified sources of variability fell into four categories: (1) inherent in surveillance systems, (2) particular to rare diseases, (3) particular to medical-records-based surveillance, and (4) resulting from extrapolation. For the sources of uncertainty measured by MD STARnet, we estimated each source's contribution to the total variance in DBMD prevalence. Based on the logic model we fit a multivariable Poisson regression model to 96 age–site–race/ethnicity strata. Age accounted for 74% of the variation between strata, surveillance site for 6%, race/ethnicity for 3%, and 17% remained unexplained. Conclusion: Variation in estimates derived from a non-random sample of states or counties may not be explained by demographic differences alone. Applying these estimates to other populations requires caution. [ABSTRACT FROM AUTHOR]

The article reports on the Responsible Conduct of Research (RCR) program of Boston College and the challenges facing it. Boston College is a Jesuit university and is noted for its active scholarly life and high academic standards. The RCR program of the college was initiated in 2002 under the responsibility of professor Karen Muskavitch and the author.

Presents a historical context for reelection rates and congressional turnover through citizen legislatures and incumbent processes since the founding of American democracy. Indirect elections of senators in the House of Representatives; Mandatory rotation of offices; Transformation into the industrial nation-state; 18th century Republicanism; Dangers of political careerism.

Focuses on former US President James Madison's argument in favor of term limits for elected officials of Congress. French diplomat Louis Guillaume Otto's comments on term limits for American officials; James Harrington's concept of rotation of offices; Madison's proposed use of legislative term limitation as a means to control special interests; Rise of career politicians in the United States.

Conotruncal heart defects (CTDs) are among the most severe birth defects worldwide. Studies of CTDs indicate both lifestyle behaviors and genetic variation contribute to the risk of CTDs. Based on a hybrid design using data from 616 case-parental and 1645 control-parental triads recruited for the National Birth Defects Prevention Study between 1997 and 2008, we investigated whether the occurrence of CTDs is associated with interactions between 921 maternal and/or fetal single nucleotide polymorphisms (SNPs) and maternal obesity and tobacco use. The maternal genotypes of the variants in the glutamate-cysteine ligase, catalytic subunit (GCLC) gene and the fetal genotypes of the variants in the glutathione S-transferase alpha 3 (GSTA3) gene were associated with an elevated risk of CTDs among obese mothers. The risk of delivering infants with CTDs among obese mothers carrying AC genotype for a variant in the GCLC gene (rs6458939) was 2.00 times the risk among those carrying CC genotype (95% confidence interval: 1.41, 2.38). The maternal genotypes of several variants in the glutathione-S-transferase (GST) family of genes and the fetal genotypes of the variants in the GCLC gene interacted with tobacco exposures to increase the risk of CTDs. Our study suggests that the genetic basis underlying susceptibility of the developing heart to the adverse effects of maternal obesity and tobacco use involve both maternal and embryonic genetic variants. These results may provide insights into the underlying pathophysiology of CTDs, and ultimately lead to novel prevention strategies.

Polycystic ovary syndrome (PCOS) affects 5% to 7% of women of reproductive age. Insulin resistance and obesity are components of this important syndrome that may contribute to excess cardiovascular risk. We analyzed data from 69 patients with PCOS who had undergone quantitative assessment of insulin sensitivity, blood pressure, lipid profiles, and androgen levels to determine the impact of insulin resistance and obesity on parameters of cardiovascular risk. Homeostasis model assessment (HOMA) was used to stratify patients in terms of insulin resistance. To obtain a reference population, we used data from the National Health and Nutrition Examination Study (NHANES III, 1988 to 1994). The most insulin-resistant tertile of patients exhibited higher body mass index (BMI), androgen levels, systolic and diastolic blood pressure (DBP), triglyceride (TG) levels, and decreased high-density lipoprotein cholesterol (HDL-C) levels. Insulin resistance, not BMI, was the main determinant of HDL-C and TG levels and systolic blood pressure (SBP) in PCOS. Among normal women, both BMI and insulin resistance influenced cardiovascular risk factors. Insulin resistance was a more significant predictor of TGs in women with PCOS than in normal women (P =.008). In contrast to normal women, insulin resistance in PCOS appears to be the prime determinant of abnormal lipids, blood pressure, and androgens. Thus, early detection of insulin resistance, as well as weight reduction, should be emphasized for all patients with PCOS.