Factors Associated with Obesity and Coronary Heart Disease in People with Intellectual Disabilities

Abstract

Advances in health care for people with intellectual disabilities (ID) that have resulted in increased longevity also force health care providers, researchers, and policymakers to question the adequacy of chronic disease management for the growing number of middle aged and elderly persons in this population. We report on sociodemographic and clinical factors associated with obesity, hypertension, hypercholesterolemia, and diabetes mellitus in an ethnically/racially diverse sample of people with ID in New York City. Administrative and chart review data were collected from a community-based specialty medical practice for people with intellectual disabilities. Adult subjects were included if they had an intellectual disability, lived in the community either independently or with relatives, received all of their planned, outpatient health care services though this practice, and had a primary care visit within the study period. One hundred twenty-six (43.0%) persons were obese, 58 (19.9%) had hypertension, 77 (26.5%) had hypercholesterolemia, and 13 (4.5%) had diabetes mellitus. Age, gender, and BMI (for the latter three conditions) were the most consistent risk factors. Intellectual functioning and behavioral problems were not associated with greater odds of these conditions. This study provides crucial information for improving community-based primary care for people with intellectual disabilities. Specifically, these findings highlight the importance of constructing innovative strategies to mitigate chronic disease risk factors in this population that involve community-based case management service providers who can help adults with ID and their families adopt needed lifestyle and behavior changes.

Body mass index and waist circumference of Latin American adult athletes with intellectual disability

“…Our findings show that women were more likely to be overweight, obese, and have abdominal obesity than men. These sex-based differences are similar to those documented in smaller scale studies conducted in the USA, UK, and South Africa, 1,2,19,22,23 and two larger studies from the USA 28,32 and an earlier international study with Special Olympics participants. 10 The logistic regression analyses also revealed that age was a significant predictor of overweight, obesity, and abdominal obesity.…”

“…Similarly, the proportion of women with WC levels indicative of abdominal obesity was significantly higher among women than men (χ 2 = 5.93, df = 1, p =.015). and United States and Canada; 1,25,26 our data generally show lower levels of overweight/obesity. However, we found similar levels of overweight (BMI ≥ 25) compared to previous studies of Special Olympics participants who were not from the USA 10,27 or Europe.…”

“…1,4 High BMIs are also associated with higher serum triglyceride and fasting glucose levels, 5 unsatisfactory oral health status, 6 and more sleep disturbance. 7 Although the abdominal obesity of adults with intellectual disabilities has been studied less often, abdominal obesity assessed via waist circumference (WC) is associated with higher fasting plasma glucose and triglyceride levels, 5 and hypertension.…”

“…A mong adults with intellectual disabilities, higher body mass index (BMI) levels are associated with elevated rates of hypertension, 1,2 hypercholesterolemia, 1 the metabolic syndrome, 3 and Type 2 diabetes. 1,4 High BMIs are also associated with higher serum triglyceride and fasting glucose levels, 5 unsatisfactory oral health status, 6 and more sleep disturbance.…”

Screening for glucose intolerance and development of a lifestyle education programme for prevention of type 2 diabetes in a population with intellectual disabilities: the STOP Diabetes research project

“…Primarily, the included studies were cross-sectional observational (n = 31 81,82,98,[100][101][102]104,106,[109][110][111]114,116,119,121,124,[126][127][128][129][130][131][132][133][134][135]137,139,142,143,145 ). The remaining studies involved retrospective database or medical records data (n = 22 [83][84][85][86][87][88][89]94,95,99,107,113,115,117,118,120,122,123,136,…”