Background: The relationship of health risk behavior and disease in adulthood to the breadth of exposure to childhood emotional, physical, or sexual abuse, and household dysfunction during childhood has not previously been described. Methods: A questionnaire about adverse childhood experiences was mailed to 13,494 adults who had completed a standardized medical evaluation at a large HMO; 9,508 (70.5%)responded. Seven categories of adverse childhood experiences were studied: psychological, physical, or sexual abuse; violence against mother; or living with household members who were substance abusers, mentally ill or suicidal, or ever imprisoned. The number of categories of these adverse childhood experiences was then compared to measures of adult risk behavior, health status, and disease. Logistic regression was used to adjust for effects of demographic factors on the association between the cumulative number of categories of childhood exposures (range: 0–7)and risk factors for the leading causes of death in adult life. Results: More than half of respondents reported at least one, and one-fourth reported ≥2 categories of childhood exposures. We found a graded relationship between the number of categories of childhood exposure and each of the adult health risk behaviors and diseases that were studied (P <.001). Persons who had experienced four or more categories of childhood exposure, compared to those who had experienced none, had 4- to 12-fold increased health risks for alcoholism, drug abuse, depression, and suicide attempt; a 2- to 4-fold increase in smoking, poor self-rated health, ≥50 sexual intercourse partners, and sexually transmitted disease; and a 1.4- to 1.6-fold increase in physical inactivity and severe obesity. The number of categories of adverse childhood exposures showed a graded relationship to the presence of adult diseases including ischemic heart disease, cancer, chronic lung disease, skeletal fractures, and liver disease. The seven categories of adverse childhood experiences were strongly interrelated and persons with multiple categories of childhood exposure were likely to have multiple health risk factors later in life. Conclusions: We found a strong graded relationship between the breadth of exposure to abuse or household dysfunction during childhood and multiple risk factors for several of the leading causes of death in adults. © 2019 American Journal of Preventive Medicine

BACKGROUND: Although diabetes is one of the most costly and rapidly increasing serious chronic diseases worldwide, the optimal mix of strategies to reduce diabetes prevalence has not been determined. METHODS: Using a dynamic model that incorporates national data on diabetes prevalence and incidence, migration, mortality rates, and intervention effectiveness, we project the effect of five hypothetical prevention policies on future US diabetes rates through 2030: 1) no diabetes prevention strategy; 2) a "high-risk" strategy, wherein adults with both impaired fasting glucose (IFG) (fasting plasma glucose of 100-124 mg/dl) and impaired glucose tolerance (IGT) (2-hour post-load glucose of 141-199 mg/dl) receive structured lifestyle intervention; 3) a "moderate-risk" strategy, wherein only adults with IFG are offered structured lifestyle intervention; 4) a "population-wide" strategy, in which the entire population is exposed to broad risk reduction policies; and 5) a "combined" strategy, involving both the moderate-risk and population-wide strategies. We assumed that the moderate- and high-risk strategies reduce the annual diabetes incidence rate in the targeted subpopulations by 12.5% through 2030 and that the population-wide approach would reduce the projected annual diabetes incidence rate by 2% in the entire US population. RESULTS: We project that by the year 2030, the combined strategy would prevent 4.6 million incident cases and 3.6 million prevalent cases, attenuating the increase in diabetes prevalence by 14%. The moderate-risk approach is projected to prevent 4.0 million incident cases, 3.1 million prevalent cases, attenuating the increase in prevalence by 12%. The high-risk and population approaches attenuate the projected prevalence increases by 5% and 3%, respectively. Even if the most effective strategy is implemented (the combined strategy), our projections indicate that the diabetes prevalence rate would increase by about 65% over the 23 years (i.e., from 12.9% in 2010 to 21.3% in 2030). CONCLUSIONS: While implementation of appropriate diabetes prevention strategies may slow the rate of increase of the prevalence of diabetes among US adults through 2030, the US diabetes prevalence rate is likely to increase dramatically over the next 20 years. Demand for health care services for people with diabetes complications and diabetes-related disability will continue to grow, and these services will need to be strengthened along with primary diabetes prevention efforts.

BACKGROUND: Weight loss is recommended for overweight or obese patients with type 2 diabetes on the basis of short-term studies, but long-term effects on cardiovascular disease remain unknown. We examined whether an intensive lifestyle intervention for weight loss would decrease cardiovascular morbidity and mortality among such patients. METHODS: In 16 study centers in the United States, we randomly assigned 5145 overweight or obese patients with type 2 diabetes to participate in an intensive lifestyle intervention that promoted weight loss through decreased caloric intake and increased physical activity (intervention group) or to receive diabetes support and education (control group). The primary outcome was a composite of death from cardiovascular causes, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for angina during a maximum follow-up of 13.5 years. RESULTS: The trial was stopped early on the basis of a futility analysis when the median follow-up was 9.6 years. Weight loss was greater in the intervention group than in the control group throughout the study (8.6% vs. 0.7% at 1 year; 6.0% vs. 3.5% at study end). The intensive lifestyle intervention also produced greater reductions in glycated hemoglobin and greater initial improvements in fitness and all cardiovascular risk factors, except for low-density-lipoprotein cholesterol levels. The primary outcome occurred in 403 patients in the intervention group and in 418 in the control group (1.83 and 1.92 events per 100 person-years, respectively; hazard ratio in the intervention group, 0.95; 95% confidence interval, 0.83 to 1.09; P=0.51). CONCLUSIONS: An intensive lifestyle intervention focusing on weight loss did not reduce the rate of cardiovascular events in overweight or obese adults with type 2 diabetes. (Funded by the National Institutes of Health and others; Look AHEAD ClinicalTrials.gov number, NCT00017953.).

Although glycated hemoglobin (HbA1c) has been widely recommended for the diagnosis of diabetes, considerable ambiguity remains about how HbA1c should be used to identify people with prediabetes or other high-risk states for preventive interventions. The current paper provides a synthesis of the epidemiologic basis and the health and economic implications of using various HbA1c-based risk-stratification approaches for diabetes prevention. HbA1c predicts diabetes and related outcomes across a wide range of HbA1c values. However, the authors estimate that, among U.S. adults, the top 15% of the nondiabetic HBA1c distribution (HbA1c of 5.7%-6.4%) accounts for 47% of diabetes cases over 5 years, and the top 30% (5.5%-6.4%) accounts for about 70% of cases. Although this clustering of eventual cases at the high end of the HbA1c risk distribution means that intervention resources will be more efficient when applied to the upper end of the distribution, no obvious threshold exists to prioritize people for preventive interventions. Thus, the choice of optimal thresholds is a tradeoff, wherein selecting a lower HbA1c cut-point will lead to a higher rate of eligibility and health benefits for more people, and a higher HbA1c cut-point will lead to fewer cases of diabetes prevented but greater "economic efficiency" in terms of diabetes cases prevented per intervention participant. Selection of optimal HbA1c thresholds also may change with the evolving science, as better evidence on the biologic effectiveness of lower-intensity interventions and effects of lifestyle interventions on additional outcomes could pave the way for a more comprehensive, tiered approach to risk stratification.

In studies of weight and mortality, the construct of reverse causation has come to be used to imply that the exposure-outcome relation is biased by weight loss due to preexisting illness. Observed weight-mortality associations are sometimes thought to result from this bias. Evidence for the occurrence of such bias is weak and inconsistent, suggesting that either the analytical methods used have been inadequate or else illness-related weight loss is not an important source of bias. Deleting participants has been the most frequent approach to control possible bias. As implemented, this can lead to deletion of almost 90% of all deaths in a sample and to deletion of more overweight and obese participants than participants with normal or below normal weight. Because it has not been demonstrated that the procedures used to adjust for reverse causation increase validity or have large or systematic effects on relative risks, it is premature to consider reverse causation as an important cause of bias. Further research would be useful to elucidate the potential effects and importance of reverse causation or illness-related weight loss as a source of bias in the observed associations between weight and mortality in cohort studies.

BACKGROUND: The American Diabetes Association (ADA) recently proposed the use of hemoglobin A1c as a practical and valid strategy to identify high-risk people for whom delivery of an intensive lifestyle intervention to prevent type 2 diabetes is likely to be cost effective. PURPOSE: To estimate composite risks of developing diabetes and cardiovascular disease (CVD) for adults with different hemoglobin A1c test results and to compare those risks with those of adults who met the 2003 ADA definition for prediabetes. METHODS: Cross-sectional data from the 2005-2006 National Health and Nutrition Examination Survey were analyzed in 2009. The method of Stern and colleagues was used to estimate the 7.5-year probability of type 2 diabetes, and the Framingham General CVD Risk Engine was used to estimate the 10-year probability of CVD for adults with different A1c results. Sample weights were used to account for sampling probability and to adjust for noncoverage and nonresponse. RESULTS: Among adults meeting the 2003 ADA definition for prediabetes, the probabilities for incident type 2 diabetes (over 7.5 years) and CVD (over 10 years) were 33.5% and 10.7%, respectively. Use of A1c alone, in the range of 5.5% to <6.5%, would identify a population with comparable risks for diabetes (32.4% [SE=1.2%]) and CVD (11.4% [SE=0.6%]). A slightly higher cutoff (≥5.7%) would identify adults with risks of 41.3% (SE=1.5%) for diabetes and 13.3% (SE=0.8%) for CVD-risks that are comparable to people enrolled in the Diabetes Prevention Program. CONCLUSIONS: A1c-based testing in clinical settings should be considered as a means to identify greater numbers of adults at high risk of developing type 2 diabetes and CVD.

BACKGROUND: People with diabetes can suffer from diverse complications that seriously erode quality of life. Diabetes, costing the United States more than $174 billion per year in 2007, is expected to take an increasingly large financial toll in subsequent years. Accurate projections of diabetes burden are essential to policymakers planning for future health care needs and costs. METHODS: Using data on prediabetes and diabetes prevalence in the United States, forecasted incidence, and current US Census projections of mortality and migration, the authors constructed a series of dynamic models employing systems of difference equations to project the future burden of diabetes among US adults. A three-state model partitions the US population into no diabetes, undiagnosed diabetes, and diagnosed diabetes. A four-state model divides the state of "no diabetes" into high-risk (prediabetes) and low-risk (normal glucose) states. A five-state model incorporates an intervention designed to prevent or delay diabetes in adults at high risk. RESULTS: The authors project that annual diagnosed diabetes incidence (new cases) will increase from about 8 cases per 1,000 in 2008 to about 15 in 2050. Assuming low incidence and relatively high diabetes mortality, total diabetes prevalence (diagnosed and undiagnosed cases) is projected to increase from 14% in 2010 to 21% of the US adult population by 2050. However, if recent increases in diabetes incidence continue and diabetes mortality is relatively low, prevalence will increase to 33% by 2050. A middle-ground scenario projects a prevalence of 25% to 28% by 2050. Intervention can reduce, but not eliminate, increases in diabetes prevalence. CONCLUSIONS: These projected increases are largely attributable to the aging of the US population, increasing numbers of members of higher-risk minority groups in the population, and people with diabetes living longer. Effective strategies will need to be undertaken to moderate the impact of these factors on national diabetes burden. Our analysis suggests that widespread implementation of reasonably effective preventive interventions focused on high-risk subgroups of the population can considerably reduce, but not eliminate, future increases in diabetes prevalence.

We examined ranges of A1C useful for identifying persons at high risk for diabetes prior to preventive intervention by conducting a systematic review. From 16 included studies, we found that annualized diabetes incidence ranged from 0.1% at A1C <5.0% to 54.1% at A1C >or=6.1%. Findings from 7 studies that examined incident diabetes across a broad range of A1C categories showed 1) risk of incident diabetes increased steeply with A1C across the range of 5.0 to 6.5%; 2) the A1C range of 6.0 to 6.5% was associated with a highly increased risk of incident diabetes, 25 to 50% incidence over 5 years; 3) the A1C range of 5.5 to 6.0% was associated with a moderately increased relative risk, 9 to 25% incidence over 5 years; and 4) the A1C range of 5.0 to 5.5% was associated with an increased incidence relative to those with A1C <5%, but the absolute incidence of diabetes was less than 9% over 5 years. Our systematic review demonstrated that A1C values between 5.5 and 6.5% were associated with a substantially increased risk for developing diabetes.

BACKGROUND: Diabetes can be prevented or delayed in high-risk adults through lifestyle modifications, including dietary changes, moderate-intensity exercise, and modest weight loss. However, the extent to which U.S. adults with prediabetes are making lifestyle changes consistent with reducing risk is unknown. PURPOSE: This study aimed to study lifestyle changes consistent with reducing diabetes risk and factors associated with their adoption among adults with prediabetes. METHODS: In 2009, data were analyzed from 1402 adults aged ≥20 years without diabetes who participated in the 2005-2006 National Health and Nutrition Examination Survey and had valid fasting plasma glucose and oral glucose tolerance tests. The extent to which adults with prediabetes report that in the past year they tried to control or lose weight, reduced the amount of fat or calories in their diet, or increased physical activity or exercise was estimated and factors associated with the adoption of these behaviors were examined. RESULTS: Almost 30% of the U.S. adult population had prediabetes in 2005-2006, but only 7.3% (95% CI=5.5%, 9.2%) were aware they had it. About half of adults with prediabetes reported performing diabetes risk reduction behaviors in the past year, but only about one third of adults with prediabetes had received healthcare provider advice about these behaviors in the past year. In multivariate analyses, provider advice, female gender, and being overweight or obese were positively associated with all three risk reduction behaviors. CONCLUSIONS: Adoption of risk reduction behaviors among U.S. adults with prediabetes is suboptimal. Efforts to improve awareness of prediabetes, increase promotion of healthy behaviors, and improve availability of evidence-based lifestyle programs are needed to slow the growth in new cases of diabetes.

BACKGROUND: Estimates of obesity-associated deaths in the United States for 1991 were published by Allison et al and subsequently for 2000 by Mokdad et al. Flegal et al then published lower estimates of obesity-associated deaths for 2000. All 3 studies incorporated data from the first National Health and Nutrition Examination Survey (NHANES I). OBJECTIVE: The objective was to clarify the effects of methodologic differences between the 3 studies in estimates of obesity-associated deaths in the US population by using NHANES I hazard ratios. DESIGN: The earlier reports used imputed smoking data for much of the NHANES I sample rather than the available reported data and applied a method of calculating attributable fractions that did not adjust for the effects of age, sex, and smoking on mortality in the target US population and did not account for effect modification by age. The effects of these and other methodologic factors were examined. RESULTS: The NHANES I hazard ratios in the earlier reports were too low, probably because of the imputed smoking data. The low hazard ratios obscured the magnitude and direction of the bias arising from the incompletely adjusted attributable fraction method. When corrected hazard ratios were used, the incompletely adjusted attributable fraction method overestimated obesity-associated mortality in the target population by >100,000 deaths. CONCLUSION: Methodologic sources of bias in the reports by Allison et al and Mokdad et al include the assessment of smoking status in NHANES I and the method of calculating attributable fractions.