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

Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention, Atlanta, Georgia 30322, USA.
Diabetes care (Impact Factor: 8.42). 07/2007; 30(6):1562-6. DOI: 10.2337/dc06-2544
Source: PubMed


At birth, the lifetime risk of developing diabetes is one in three, but lifetime risks across BMI categories are unknown. We estimated BMI-specific lifetime diabetes risk in the U.S. for age-, sex-, and ethnicity-specific subgroups.
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- and 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.
Lifetime diabetes risk at 18 years of age 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 65 years of age, compared with normal-weight male subjects, 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. The impact of BMI on diabetes duration also decreased with age.
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.

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    • "Being overweight is considered as having a BMI between 25 and 29.9, and being classified as obese falls into a BMI of 30.0 or greater [2]. Obesity is associated with an increased risk of cardiovascular disease and type 2 diabetes [3,4]. However, an inverse relationship between obesity and mortality has been described in patients with heart failure, coronary heart disease, and diabetes [5-7]. "
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    ABSTRACT: It is unclear whether an 'obesity survival paradox' exists for pneumonia. Therefore, we conducted a meta-analysis to assess the associations between increased body mass index (BMI), pneumonia risk, and mortality risk. Cohort studies were identified from the PubMed and Embase databases. Summary relative risks (RRs) with their corresponding 95% confidence intervals (CIs) were calculated using a random effects model. Thirteen cohort studies on pneumonia risk (n = 1,536,623), and ten cohort studies on mortality (n = 1,375,482) were included. Overweight and obese individuals were significantly associated with an increased risk of pneumonia (RR = 1.33, 95% CI 1.04 to 1.71, P = 0.02, I2 = 87%). In the dose-response analysis, the estimated summary RR of pneumonia per 5 kg/m2 increase in BMI was 1.04 (95% CI 1.01 to 1.07, P = 0.01, I2 = 84%). Inversely, overweight and obese subjects were significantly associated with reduced risk of pneumonia mortality (RR = 0.83, 95% CI 0.77 to 0.91, P < 0.01, I2 = 34%). The estimated summary RR of mortality per 5 kg/m2 increase in BMI was 0.95 (95% CI 0.93 to 0.98, P < 0.01, I2 = 77%). This meta-analysis suggests that an 'obesity survival paradox' exists for pneumonia. Because this meta-analysis is based on observational studies, more studies are required to confirm the results.
    BMC Medicine 04/2014; 12(1):61. DOI:10.1186/1741-7015-12-61 · 7.25 Impact Factor
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    • "Furthermore, adult survivors of childhood cancer may be particularly prone to weight-related problems as approximately half report low levels of physical activity [9, 10]. In the general population, a high body mass index (BMI) in the overweight or obese range is associated with an increased risk for chronic health conditions including hypertension [11], diabetes [12], cancer [13], and cardiovascular disease [5, 14]. Late effects from treatment and low levels of physical activity may compound the risk of additional weight-related problems among survivors with abnormal BMIs. "
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    ABSTRACT: Background. Population-based studies are needed to estimate the prevalence of underweight or overweight/obese childhood cancer survivors. Procedure. Adult survivors (diagnosed ≤20 years) were identified from the linked Utah Cancer Registry and Utah Population Database. We included survivors currently aged ≥20 years and ≥5 years from diagnosis (N = 1060), and a comparison cohort selected on birth year and sex (N = 5410). BMI was calculated from driver license data available from 2000 to 2010. Multivariable generalized linear regression models were used to calculate prevalence relative risks (RR) and 95% confidence intervals (95% CI) of BMI outcomes for survivors and the comparison cohort. Results. Average time since diagnosis was 18.5 years (SD = 7.8), and mean age at BMI for both groups was 30.5 (survivors SD = 7.7, comparison SD = 8.0). Considering all diagnoses, survivors were not at higher risk for being underweight or overweight/obese than the comparison. Male central nervous system tumor survivors were overweight (RR = 1.12, 95% CI 1.01-1.23) more often than the comparison. Female survivors, who were diagnosed at age 10 and under, had a 10% higher risk of being obese than survivors diagnosed at ages 16-20 (P < 0.05). Conclusion. While certain groups of childhood cancer survivors are at risk for being overweight/obese, in general they do not differ from population estimates.
    Journal of Cancer Epidemiology 01/2014; 2014:531958. DOI:10.1155/2014/531958
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    • "periodontitis after adjustment for age, gender, ethnicity and tobacco abuse. These results replicated by our method are widely reported in the literature (Williams & Mahan 1960, Grossi & Genco 1998, Resnick et al. 1998, Iacopino 2001, Soskolne & Klinger 2001, Campus et al. 2005, Mealey 2006, Mealey & Oates 2006, Narayan et al. 2007, Mealey & Rose 2008, Lalla & Papapanou 2011, Hodge et al. 2012). We found diabetes with ophthalmic manifestations (ICD-9 250.5) to be associated with periodontitis (OR = 1.8, 95% CI 1.34 –2.47, p < 0.001), which replicates the result from a study of Pima Indian diabetic patients with retinopathy who were found to be approximately five times more likely to have periodontitis (L€ oe 1993). "
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    ABSTRACT: Aim: To use linked electronic medical and dental records to discover associations between periodontitis and medical conditions independent of a priori hypotheses. Materials and methods: This case-control study included 2475 patients who underwent dental treatment at the College of Dental Medicine at Columbia University and medical treatment at NewYork-Presbyterian Hospital. Our cases are patients who received periodontal treatment and our controls are patients who received dental maintenance but no periodontal treatment. Chi-square analysis was performed for medical treatment codes and logistic regression was used to adjust for confounders. Results: Our method replicated several important periodontitis associations in a largely Hispanic population, including diabetes mellitus type I (OR = 1.6, 95% CI 1.30-1.99, p < 0.001) and type II (OR = 1.4, 95% CI 1.22-1.67, p < 0.001), hypertension (OR = 1.2, 95% CI 1.10-1.37, p < 0.001), hypercholesterolaemia (OR = 1.2, 95% CI 1.07-1.38, p = 0.004), hyperlipidaemia (OR = 1.2, 95% CI 1.06-1.43, p = 0.008) and conditions pertaining to pregnancy and childbirth (OR = 2.9, 95% CI: 1.32-7.21, p = 0.014). We also found a previously unreported association with benign prostatic hyperplasia (OR = 1.5, 95% CI 1.05-2.10, p = 0.026) after adjusting for age, gender, ethnicity, hypertension, diabetes, obesity, lipid and circulatory system conditions, alcohol and tobacco abuse. Conclusions: This study contributes a high-throughput method for associating periodontitis with systemic diseases using linked electronic records.
    Journal Of Clinical Periodontology 02/2013; 40(5). DOI:10.1111/jcpe.12086 · 4.01 Impact Factor
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