Background Type 2 diabetes affects approximately 8 percent of adults in the United States. Some risk factors — elevated plasma glucose concentrations in the fasting state and after an oral glucose load, overweight, and a sedentary lifestyle — are potentially reversible. We hypothesized that modifying these factors with a lifestyle-intervention program or the administration of metformin would prevent or delay the development of diabetes. Methods We randomly assigned 3234 nondiabetic persons with elevated fasting and post-load plasma glucose concentrations to placebo, metformin (850 mg twice daily), or a lifestyle modification program with the goals of at least a 7 percent weight loss and at least 150 minutes of physical activity per week. The mean age of the participants was 51 years, and the mean body-mass index (the weight in kilograms divided by the square of the height in meters) was 34.0; 68 percent were women, and 45 percent were members of minority groups. Results The average follow-up was 2.8 years. The incidence of diabetes was 11.0, 7.8, and 4.8 cases per 100 person-years in the placebo, metformin, and lifestyle groups, respectively. The lifestyle intervention reduced the incidence by 58 percent (95 percent confidence interval, 48 to 66 percent) and metformin by 31 percent (95 percent confidence interval, 17 to 43 percent), as compared with placebo; the lifestyle intervention was significantly more effective than metformin. To prevent one case of diabetes during a period of three years, 6.9 persons would have to participate in the lifestyle-intervention program, and 13.9 would have to receive metformin. Conclusions Lifestyle changes and treatment with metformin both reduced the incidence of diabetes in persons at high risk. The lifestyle intervention was more effective than metformin.

Reduction in the incidence of type 2 diabetes with lifestyle intervention or metformin.

Objective. —To identify and quantify the major external (nongenetic) factors that contribute to death in the United States. Data Sources. —Articles published between 1977 and 1993 were identified through MEDLINE searches, reference citations, and expert consultation. Government reports and compilations of vital statistics and surveillance data were also obtained. Study Selection. —Sources selected were those that were often cited and those that indicated a quantitative assessment of the relative contributions of various factors to mortality and morbidity. Data Extraction. —Data used were those for which specific methodological assumptions were stated. A table quantifying the contributions of leading factors was constructed using actual counts, generally accepted estimates, and calculated estimates that were developed by summing various individual estimates and correcting to avoid double counting. For the factors of greatest complexity and uncertainty (diet and activity patterns and toxic agents), a conservative approach was taken by choosing the lower boundaries of the various estimates. Data Synthesis. —The most prominent contributors to mortality in the United States in 1990 were tobacco (an estimated 400000 deaths), diet and activity patterns (300 000), alcohol (100 000), microbial agents (90 000), toxic agents (60 000), firearms (35 000), sexual behavior (30 000), motor vehicles (25 000), and illicit use of drugs (20 000). Socioeconomic status and access to medical care are also important contributors, but difficult to quantify independent of the other factors cited. Because the studies reviewed used different approaches to derive estimates, the stated numbers should be viewed as first approximations. Conclusions. —Approximately half of all deaths that occurred in 1990 could be attributed to the factors identified. Although no attempt was made to further quantify the impact of these factors on morbidity and quality of life, the public health burden they impose is considerable and offers guidance for shaping health policy priorities. (JAMA. 1993;270:2207-2212)

https://jamanetwork.com/journals/JAMA/articlepdf/409171/jama_270_18_038.pdf

Actual causes of death in the United States.

OBJECTIVE To assess predictors of CVD mortality among men with and without diabetes and to assess the independent effect of diabetes on the risk of CVD death. RESEARCH DESIGN AND METHODS Participants in this cohort study were screened from 1973 to 1975; vital status has been ascertained over an average of 12 yr of follow-up (range 11–13 yr). Participants were 347,978 men aged 35–57 yr, screened in 20 centers for MRFIT. The outcome measure was CVD mortality. RESULTS Among 5163 men who reported taking medication for diabetes, 1092 deaths (603 CVD deaths) occurred in an average of 12 yr of follow-up. Among 342,815 men not taking medication for diabetes, 20,867 deaths were identified, 8965 ascribed to CVD. Absolute risk of CVD death was much higher for diabetic than nondiabetic men of every age stratum, ethnic background, and risk factor level—overall three times higher, with adjustment for age, race, income, serum cholesterol level, sBP, and reported number of cigarettes/day ( P CONCLUSIONS These findings emphasize the importance of rigorous sustained intervention in people with diabetes to control blood pressure, lower serum cholesterol, and abolish cigarette smoking, and the importance of considering nutritional-hygienic approaches on a mass scale to prevent diabetes.

https://www.siditalia.it/pdf/Diabete-ed-Arterosclerosi/MRFIT_Diab_care_1993.pdf

Diabetes, other risk factors, and 12-yr cardiovascular mortality for men screened in the Multiple Risk Factor Intervention Trial.

Chronic kidney disease1 (CKD) is a worldwide public health problem. In the United States, there is a rising incidence and prevalence of kidney failure, with poor outcomes and high cost. The number of individuals with kidney failure treated by dialysis and transplantation exceeded 320 000 in 1998 and is expected to surpass 650 000 by 2010.1,2 There is an even higher prevalence of earlier stages of CKD (Table 1).1,3 Kidney failure requiring treatment with dialysis or transplantation is the most visible outcome of CKD. However, cardiovascular disease (CVD) is also frequently associated with CKD, which is important because individuals with CKD are more likely to die of CVD than to develop kidney failure,4 CVD in CKD is treatable and potentially preventable, and CKD appears to be a risk factor for CVD. In 1998, the National Kidney Foundation (NKF) Task Force on Cardiovascular Disease in Chronic Renal Disease issued a report emphasizing the high risk of CVD in CKD.5 This report showed that there was a high prevalence of CVD in CKD and that mortality due to CVD was 10 to 30 times higher in dialysis patients than in the general population (Figure 1 and Table 2).6–18 The task force recommended that patients with CKD be considered in the “highest risk group” for subsequent CVD events and that treatment recommendations based on CVD risk stratification should take into account the highest-risk status of patients with CKD. 

View this table:

TABLE 1. Stages of CKD 





Figure 1. Cardiovascular mortality defined by death due to arrhythmias, cardiomyopathy, cardiac arrest, myocardial infarction, atherosclerotic heart disease, and pulmonary edema in general population (GP; National Center for Health Statistics [NCHS] multiple cause of mortality data files International Classification of Diseases, 9th Revision [ICD 9] codes 402, 404, 410 to 414, and …

Kidney disease as a risk factor for development of cardiovascular disease: a statement from the American Heart Association Councils on Kidney in Cardiovascular Disease, High Blood Pressure Research, Clinical Cardiology, and Epidemiology and Prevention.

Body-mass index and cause-specific mortality in 900 000 adults: collaborative analyses of 57 prospective studies

The NHANES I Epidemiologic Followup Study contains several sources of information that can be used to define case status. Incidence rates and relative risks associated with selected, documented risk factors for heart disease were estimated using nine different case definitions. Despite wide variation in the estimates of incidence, the characteristics of the cases were remarkably similar as were the risks associated with heart disease incidence. The main difference occurred when cases were defined on the basis of death certificate information. Cases defined this way are more severe and models based on this definition result in relative risks of greater magnitude.

Differences in morbidity measures and risk factor identification using multiple data sources: The case of coronary heart disease

The purpose of this study is to investigate differential use of hormone replacement therapy (HRT) by race after controlling for family income and education. Data from the Epidemiologic Followup to the First National Health and Nutrition Examination Survey (NHEFS), a nationally representative cohort followed from the mid-1970s until 1992, were analyzed to address this question. Included in the analysis are women who became menopausal during the year of their baseline examination or during follow-up, had answered questions about their HRT use, and were either black or white. After controlling for education, body mass index, and history of bilateral oophorectomy or hysterectomy, black women were 60% less likely to have ever taken HRT than white women (odds ratio [OR] = 0.41, 95% confidence interval [CI] = 0.30–0.55). Furthermore, even among the women who did take HRT at some point, black women were less than half as likely as white women to have continued use of the therapy for five or more years (OR = 0.44. 95% CI = 0.29–0.68). These data suggest that black women, regardless of educational level, are less likely to use HRT, and those that do are less likely to continue long enough to affect their probability of these diseases.

Differences in Use of Postmenopausal Hormone Replacement Therapy by Black and White Women

The possibility that bias in selection of the hospital controls may have influenced results of 2 recent case-control studies on vasectomy and prostate cancer is examined from other sources of prostate cancer rates. The study by Rosenberg et al. found a relative risk of 5.3 in men aged 40-69 and that of Mettlin et al. arrived at a relative risk of 1.7 in older men vasectomized >20 years ago. The prevalence of vasectomy among controls in the Rosenberg study was 8.5 4.4 and 1.5% for men aged 40-70 by decade compared to prevalence of 25.3 12.3 and 4.6% in the region. Similarly in the Mettlin study reported prevalence of vasectomy was 6.7 2.4 and 2.0% for 5-year age groups between 58-72 years compared to 6.4 5.2 and 3.1% computed from regional data. Other case-control studies have found relative risks of slightly less than 1 and 1.0. Moreover while prostate cancer rates are rising rapidly they are rising just as fast in Blacks and in men >60 who have very low prevalence of vasectomy. It appears that the relative risk reported in the Mettlin study 1.7 is more accurate.

Re: “vasectomy and the risk of prostate cancer”

NHAMCS: does it hold up to scrutiny?

The multidimensionality of the concept of disability makes the development of questions to measure the concept very complicated. In addition, the purposes of data collection can require a variety of different dimensions of the concept of disability to meet the variety of data uses. This paper proposes a data matrix for use in focusing the methodologist on the issues related to the multidimensionality of the concept and the variety of data needs when planning surveys. Discussions of the three components of the matrix, purpose, conceptual domains and question characteristics, provides the reader with an understanding of the elements of this tool. Multiple tables provide examples of the possible uses of the matrix.

Jennifer H. Madans

Papers

Differences in morbidity measures and risk factor identification using multiple data sources: The case of coronary heart disease

Differences in Use of Postmenopausal Hormone Replacement Therapy by Black and White Women

Re: “vasectomy and the risk of prostate cancer”

NHAMCS: does it hold up to scrutiny?

Disability Measurement Matrix: A Tool for the Coordination of Measurement Purpose and Instrument Development