Objective-To investigate a reported association between dental disease and risk of coronary heart disease.

Abbreviations: CHD, coronary heart disease; NHANES III, Third National Health and Nutrition Examination Survey; OR, odds ratio.A table elsewhere in this issue shows conventional and Système International (SI) units and conversion factors for many substances. Diabetes and Physical Disability Among Older U.S. Adults O R I G I N A L A R T I C L EOBJECTIVE -To estimate the prevalence of physical disability associated with diabetes among U.S. adults Ն60 years of age.RESEARCH DESIGN AND METHODS -We analyzed data from a nationally representative sample of 6,588 community-dwelling men and women Ն60 years of age who participated in the Third National Health and Nutrition Examination Survey. Diabetes and comorbidities (coronary heart disease, intermittent claudication, stroke, arthritis, and visual impairment) were assessed by questionnaire. Physical disability was assessed by self-reported ability to walk one-fourth of a mile, climb 10 steps, and do housework. Walking speed, lowerextremity function, and balance were assessed using physical performance tests.RESULTS -Among subjects Ն60 years of age with diabetes, 32% of women and 15% of men reported an inability to walk one-fourth of a mile, climb stairs, or do housework compared with 14% of women and 8% of men without diabetes. Diabetes was associated with a 2-to 3-fold increased odds of not being able to do each task among both men and women and up to a 3.6-fold increased risk of not being able to do all 3 tasks. Among women, diabetes was also associated with slower walking speed, inferior lower-extremity function, decreased balance, and an increased risk of falling. Of the Ͼ5 million U.S. adults Ն60 years of age with diabetes, 1.2 million are unable to do major physical tasks.CONCLUSIONS -Diabetes is associated with a major burden of physical disability in older U.S. adults, and these disabilities are likely to substantially impair their quality of life.

IntductonCross-sectional surveys among United States adults have demonstrated that Black women have a higher prevalence ofoverweight than White women. 1,2 Overweight in US women is directly associated with low socioeconomic status.?-6 Despite the association between Black race and low income or low education, controlling for socioeconomic status has not eliminated the overweight prevalence differences between Black women and White women.1Prevalence alone does not explain the reasons for these observed associations.To understand the origin of overweight, we wondered whether race or socioeconomic factors during adulthood were independently associated with a woman's likelihood of gaining weight and whether marital status was involved (since this factor appears to be associated both with weight status5 and with race). Race, socioeconomic status, or marital status might contribute to overweight prevalence either by promoting weight gain or by inhibitingweight loss. To clarify the circumstances that led to the current weight distribution, we analyzed the mean weight changes, the major weight gains, and the majorweight losses of a nationally representative prospective cohort of adult US women that was followed up over approximately a 10-year interval. Methods Study PopulationThis report analyzes public-use computer tapes containing the data from the First National Health and Nutrition Examination Definitions of Weight ChangeBaseline measurements ofheight and weight were obtained under controlled conditions, with the subject wearing only disposable paper uniforms and foam rubber slippers. The follow-up weightwas obtained in the subject's home after she removed her shoes and articles of heavy clothing. These follow-up values were corrected for the weight of the subject's indoor clothing by subtracting 1.6 kg from the measured weight.10For each subject, weight change was categorized as either major weight gain (an increase of 13.0 kgs or more), major weightloss (a decrease of7.0 kgs or more), or mid-range weight change (weight changes > -7 kgs but < +13 kgs). StatisficalAnalysisConsidering weight change as a continuous variable, we used multiple linear regression models to estimate the effects associated with race, family income, education, and marital change. Our simple model adjusted each of these variables only for age, height, and duration of follow-up. Our fully adjusted model included adjustments for race, family income, education, marital change, age, height, duration of follow-up, body mass index (BMI, kg/m2) at baseline, smoking, physical activity, parity, and rural/urban background (see Appendix for variable definitions).Considering weight change as a categoricalvariable, we used multiple logistic regression analysis (employing the SAS procedure PROC LOGIST12) to estimate the odds ratio of either major weight gain or major weight loss for the various categories of race, family income, education, and marital change. Simple and fully adjusted models were developed as descnrbed above. For these analyses, the mid...

OBJECTIVE: To examine how the relationship between parity increase and weight gain is modi®ed by sociodemographic and behavioral factors. DESIGN: Prospective longitudinal data from the ®rst National Health and Nutrition Examination Survey (NHANES I, 1971±75) and its follow-up of those aged 25 y and older, the NHANES I Epidemiologic Follow-up Survey (NHEFS, 1982± 84). SUBJECTS: The analytical sample was nationally representative of the United States and included 2952 white or African-American non-pregnant women aged 25±45 y at baseline, who were re-measured approximately 10 y later. MEASUREMENTS: Statistical interactions in multiple linear and logistic regression models were examined to identify how eight sociodemographic and three behavioral factors modi®ed the effect of parity increase on body weight change and risk of substantial weight gain. RESULTS: Factors that increased parity-associated weight gain included being African-American, living in a rural area, not working outside the home, having fewer children, lower income and lower education, and being unmarried. Among white women, being younger and having higher body weight at baseline increased parity-associated weight gain, while among African-American women, being older and having lower body weight increased parity-associated weight gain. African-American smokers gained less weight with an increase in parity, while the interactions between smoking and physical activity with parity-associated weight gain in whites were complex. CONCLUSION: The effects of sociodemographic and behavioral factors on parity-associated weight gain varied by race and parity change, with the most consistent ®ndings being that unmarried and unemployed white women had greater parity-associated weight gain, while both white and African-American women who smoked, had higher education, or higher parity had lower parity-associated weight gain. This information may contribute to better targeting and more effective interventions to prevent postpartum weight retention.

Although the prevalence of obesity in US women is well-described, data are limited on the incidence of major weight gain and obesity. We used data from the First National Health and Nutrition Examination Survey Epidemiologic Follow-up Study to estimate the 10-y incidence of major weight gain (greater than or equal to 10 kg) and obesity [body mass index (BMI, in kg/m2) greater than or equal to 29] in a cohort of US women aged 30-55 y (n = 535 blacks and 2976 whites). In women not obese at baseline, blacks were 60% more likely to become obese than whites [incidence in blacks = 15.5%, 95% confidence interval (CI) = 11.2-19.7; incidence in whites = 9.7%, 95% CI = 8.6-10.8]. This higher incidence of obesity in blacks was largely due to their higher average BMI at baseline. The incidence of major weight gain was 50% higher in blacks than in whites (in blacks, 17.3%; 95% CI = 13.6-21.0; in whites, 11.7%; 95% CI = 10.3-13.1). We estimate that in black and white women, respectively, 16% and 12% of coronary heart disease is attributed to major weight gain whereas 35% and 21% is attributed to being obese.