Showing papers by "David F. Williamson published in 2007"

Cause-Specific Excess Deaths Associated With Underweight, Overweight, and Obesity

Abstract: ContextThe association of body mass index (BMI) with cause-specific mortality has not been reported for the US populationObjectiveTo estimate cause-specific excess deaths associated with underweight (BMI <185), overweight (BMI 25-<30), and obesity (BMI ≥30)Design, Setting, and ParticipantsCause-specific relative risks of mortality from the National Health and Nutrition Examination Survey (NHANES) I, 1971-1975; II, 1976-1980; and III, 1988-1994, with mortality follow-up through 2000 (571 042 person-years of follow-up) were combined with data on BMI and other covariates from NHANES 1999-2002 with underlying cause of death information for 23 million adults 25 years and older from 2004 vital statistics data for the United StatesMain Outcome MeasuresCause-specific excess deaths in 2004 by BMI levels for categories of cardiovascular disease (CVD), cancer, and all other causes (noncancer, non-CVD causes)ResultsBased on total follow-up, underweight was associated with significantly increased mortality from noncancer, non-CVD causes (23 455 excess deaths; 95% confidence interval [CI], 11 848 to 35 061) but not associated with cancer or CVD mortality Overweight was associated with significantly decreased mortality from noncancer, non-CVD causes (−69 299 excess deaths; 95% CI, −100 702 to −37 897) but not associated with cancer or CVD mortality Obesity was associated with significantly increased CVD mortality (112 159 excess deaths; 95% CI, 87 842 to 136 476) but not associated with cancer mortality or with noncancer, non-CVD mortality In further analyses, overweight and obesity combined were associated with increased mortality from diabetes and kidney disease (61 248 excess deaths; 95% CI, 49 685 to 72 811) and decreased mortality from other noncancer, non-CVD causes (−105 572 excess deaths; 95% CI, −161 816 to −49 328) Obesity was associated with increased mortality from cancers considered obesity-related (13 839 excess deaths; 95% CI, 1920 to 25 758) but not associated with mortality from other cancers Comparisons across surveys suggested a decrease in the association of obesity with CVD mortality over timeConclusionsThe BMI-mortality association varies by cause of death These results help to clarify the associations of BMI with all-cause mortality

Effect of BMI on Lifetime Risk for Diabetes in the U.S.

Abstract: OBJECTIVE. At birth, the lifetime risk of developing diabetes is 1 in 3, but lifetime risks across body mass index (BMI) categories are unknown. We estimated BMI-specific lifetime diabetes risk for the U.S. and age-, sex-, ethnicity-specific subgroups. RESEARCH DESIGN & METHODS. National Health Interview Survey data (n=780,694, 1997-2004) were used to estimate age-, race-, sex-,and BMI-specific prevalence and incidence of diabetes in 2004. U.S. Census Bureau age-, race-, and sex-specific population and mortality rate estimates for 2004 were combined with two previous studies of mortality to estimate Diabetes-BMI-specific mortality rates. These estimates were used in a Markov model to project lifetime risk of diagnosed diabetes by baseline age, race, sex, and BMI. RESULTS. Lifetime diabetes risks (percent) at age 18 increased from 7.6, to 70.3 between underweight and very obese men, and from 12.2, to 74.4 for women. The lifetime risk difference was lower at older ages. At age 65, compared with normal-weight males, lifetime risk differences (percent) increased from +3.7 to +23.9 percentage points, between overweight and very obese men, and from +8.7 to 26.7 percentage points for women. BMI9s impact on diabetes duration also decreased with age. CONCLUSIONS. Overweight, and especially obesity, particularly at younger ages, substantially increases lifetime risk of diagnosed diabetes, while their impact on diabetes risk, life expectancy, and diabetes duration diminishes with age.

Impact of Smoking and Preexisting Illness on Estimates of the Fractions of Deaths Associated with Underweight, Overweight, and Obesity in the US Population

Abstract: Studies of body weight and mortality sometimes exclude participants who have ever smoked or who may have had preexisting illness at baseline. This exclusionary approach was applied to data from the National Health and Nutrition Examination Surveys to investigate the potential effects of smoking and preexisting illness on estimates of the attributable fractions of US deaths in 2000 that were associated with different levels of body mass index (BMI; weight (kg)/height (m2). Synthetic estimates were calculated by using postexclusion relative risks for BMI categories in place of BMI relative risks from the full sample, holding the relative risks for all other covariates constant. When the postexclusion relative risks were used, the attributable fractions of deaths associated with underweight and with higher levels of obesity increased slightly and the attributable fractions of deaths associated with overweight and with grade 1 obesity decreased slightly. The relative risks for BMI categories did not show large or systematic changes after simultaneous exclusion of ever smokers, persons with a history of cancer or cardiovascular disease, and persons who died early in the follow-up period or had their heights and weights measured at older ages. These analyses suggest that residual confounding by smoking or preexisting illness had little effect on previous estimates of attributable fractions from nationally representative data with measured heights and weights.

Agreement between self-reports and medical records was only fair in a cross-sectional study of performance of annual eye examinations among adults with diabetes in managed care.

Abstract: Background:Despite consensus about the importance of measuring quality of diabetes care and the widespread use of self-reports and medical records to assess quality, little is known about the degree of agreement between these data sources.Objectives:To evaluate agreement between self-reported and me

Estimation of attributable number of deaths and standard errors from simple and complex sampled cohorts

Abstract: Estimates of the attributable number of deaths (AD) from all causes can be obtained by first estimating population attributable risk (AR) adjusted for confounding covariates, and then multiplying the AR by the number of deaths determined from vital mortality statistics that occurred in the population for a specific time period. Proportional hazard regression estimates of adjusted relative hazards obtained from mortality follow-up data from a cohort is combined with a joint distribution of risk factor and confounders to compute an adjusted AR. Two estimators of adjusted AR are examined. These estimators differ according to which reference population is used to obtain the joint distribution of risk factor and confounders. Two types of reference populations were considered: (i) the population represented by the baseline cohort and (ii) a population that is external to the cohort. Methods used in survey sampling are applied to obtain estimates of the variance of the AD estimator. These variances can be applied to data that range from simple random samples to multistage stratified cluster samples, which are used in national household surveys. The variance estimation of AD is illustrated in an analysis of excess deaths due to having a non-ideal body mass index using the second National Health and Examination Survey (NHANES) Mortality Study and the 1999-2002 NHANES. These methods can also be used to estimate the attributable number of cause-specific deaths and their standard errors when the time period for the accrual of deaths is short.