BACKGROUND A high body-mass index (BMI, the weight in kilograms divided by the square of the height in meters) is associated with increased mortality from cardiovascular disease and certain cancers, but the precise relationship between BMI and all-cause mortality remains uncertain. METHODS We used Cox regression to estimate hazard ratios and 95% confidence intervals for an association between BMI and all-cause mortality, adjusting for age, study, physical activity, alcohol consumption, education, and marital status in pooled data from 19 prospective studies encompassing 1.46 million white adults, 19 to 84 years of age (median, 58). RESULTS The median baseline BMI was 26.2. During a median follow-up period of 10 years (range, 5 to 28), 160,087 deaths were identified. Among healthy participants who never smoked, there was a J-shaped relationship between BMI and all-cause mortality. With a BMI of 22.5 to 24.9 as the reference category, hazard ratios among women were 1.47 (95 percent confidence interval [CI], 1.33 to 1.62) for a BMI of 15.0 to 18.4; 1.14 (95% CI, 1.07 to 1.22) for a BMI of 18.5 to 19.9; 1.00 (95% CI, 0.96 to 1.04) for a BMI of 20.0 to 22.4; 1.13 (95% CI, 1.09 to 1.17) for a BMI of 25.0 to 29.9; 1.44 (95% CI, 1.38 to 1.50) for a BMI of 30.0 to 34.9; 1.88 (95% CI, 1.77 to 2.00) for a BMI of 35.0 to 39.9; and 2.51 (95% CI, 2.30 to 2.73) for a BMI of 40.0 to 49.9. In general, the hazard ratios for the men were similar. Hazard ratios for a BMI below 20.0 were attenuated with longer-term follow-up. CONCLUSIONS In white adults, overweight and obesity (and possibly underweight) are associated with increased all-cause mortality. All-cause mortality is generally lowest with a BMI of 20.0 to 24.9.

Objective We review uses of electronic healthcare data algorithms, measures of their accuracy, and reasons for prioritizing one measure of accuracy over another. Study design and setting We use real studies to illustrate the variety of uses of automated healthcare data in epidemiologic and health services research. Hypothetical examples show the impact of different types of misclassification when algorithms are used to ascertain exposure and outcome. Results High algorithm sensitivity is important for reducing the costs and burdens associated with the use of a more accurate measurement tool, for enhancing study inclusiveness, and for ascertaining common exposures. High specificity is important for classifying outcomes. High positive predictive value is important for identifying a cohort of persons with a condition of interest but that need not be representative of or include everyone with that condition. Finally, a high negative predictive value is important for reducing the likelihood that study subjects have an exclusionary condition. Conclusion Epidemiologists must often prioritize one measure of accuracy over another when generating an algorithm for use in their study. We recommend researchers publish all tested algorithms—including those without acceptable accuracy levels—to help future studies refine and apply algorithms that are well-suited to their objectives.

Algorithms based on administrative data can identify second breast cancer events with high sensitivity, specificity, and PPV. The algorithms presented here promote efficient outcomes research, allowing researchers to prioritize sensitivity, specificity, or PPV in identifying second breast cancer events.

IMPORTANCE Skin cancer, primarily melanoma, is a leading cause of morbidity and mortality in the United States. OBJECTIVE To provide an updated systematic review for the US Preventive Services Task Force regarding clinical skin cancer screening among adults.

Use of CAM by IBD patients is very common. Most of these patients attribute significant benefits to their CAM use. Few report significant adverse events.

In this cohort study, the authors evaluated how supplemental use of multivitamins, vitamin C, and vitamin E over a 10-year period was related to 5-year total mortality, cancer mortality, and cardiovascular disease (CVD) mortality. Participants (n = 77,719) were Washington State residents aged 50-76 years who completed a mailed self-administered questionnaire in 2000-2002. Adjusted hazard ratios and 95% confidence intervals were computed using Cox regression. Multivitamin use was not related to total mortality. However, vitamin C and vitamin E use were associated with small decreases in risk. In cause-specific analyses, use of multivitamins and use of vitamin E were associated with decreased risks of CVD mortality. The hazard ratio comparing persons who had a 10-year average frequency of multivitamin use of 6-7 days per week with nonusers was 0.84 (95% confidence interval: 0.70, 0.99); and the hazard ratio comparing persons who had a 10-year average daily dose of vitamin E greater than 215 mg with nonusers was 0.72 (95% confidence interval: 0.59, 0.88). In contrast, vitamin C use was not associated with CVD mortality. Multivitamin and vitamin E use were not associated with cancer mortality. Some of the associations we observed were small and may have been due to unmeasured healthy behaviors that were more common in supplement users.

For most of the supplements we examined, there was no association with total mortality. Use of glucosamine and use of chondroitin were each associated with decreased total mortality.

Our results suggest that HCC incidence rates will continue to increase in Canada during the next decade as persons born in more recent birth cohorts, who face a relatively greater risk for HCC, age.