Batsis, John A.

Background: The Metabolically Obese Normal Weight (MONW) phenotype has been described as a unique subgroup of individuals with metabolic dysregulation similar to obese individuals, but not considered obese per se . In theory, these individuals have an adiposity-independent substrate predisposing them to metabolic dysregulation. We tested whether central obesity explains the metabolic abnormalities in persons with MONW in a prospective population-based cohort in the Czech Republic. Methods: We used data from Kardiovize Brno 2030 study, a prospective community-based cohort in Central Europe. We defined obesity using World Health Organization categories for body mass index (BMI) and central obesity by waist circumference (WC≥ 94 cm in men and ≥ 80 cm in women). Metabolically obese (MO) was defined using AHA criteria by having three or more of the following: Hypertriglyceridemia (≥ 1.7 mmol/l); HDL cholesterol level <1.0 mmol/l in men or <1.3 mmol/l in women; elevated blood pressure (systolic ≥ 130 mmHg and/or diastolic ≥ 85 mmHg) or antihypertensive drug treatment or history of hypertension; elevated fasting plasma glucose ≥ 5.6 mmol/l; or drug treatment and central obesity. Results: Of the 2,056 participants (46% men; mean age= 47.2 years, SD=11.2) included in the current analysis, 975 (47.4%) had normal weight and 696 (33.8%) were overweight. Prevalence of MO in the overall sample was 20.6% (n=424), 3.7% (n=36) among those with normal BMI and 9.9% (n=204) among overweight individuals. From the 36 subjects with MONW, 33 (91.6%) had central obesity by WC, while 201/204 (98.5%) with metabolically obese overweight, had central obesity by WC. Remarkably, in a subgroup of people with no metabolic obesity factors nobody had central obesity, see Figure . Conclusions: Metabolic dysregulation in people labeled as MONW can be explained by excessive visceral adiposity and not by an inherent predisposition, independent of adiposity.These findings underscore the importance of identifying central obesity in clinical practice even if BMI is below the obese criteria.

Background : The significant bidirectional changes in cardiovascular(CV) risk factor prevalence make the net trend in incident CV risk unknown. We assessed the trends in the net 10-year risk for incident CV disease using the Framingham risk model and data from the National Health and Nutrition Examination Surveys(NHANES). Methods : We used data from NHANES II (1976–1980), NHANES III (1988–1994), and NHANES 1999–2004, including major CV risk factors, all collected in a standardized manner. People with a history of CV disease, pregnant women, people with missing data and those outside the Framingham age range were excluded. The Framingham risk function estimated the 10-year risk for CV disease. The slope of change or rate of change per year between NHANES II/III, and between NHANES III/1999–2004 were determined. The slope difference was calculated and compared to zero. Results : The mean age-adjusted 10-year CV risk decreased from 10 to 7.9% between NHANES II and III, with a significant slope (p<0.001). However, the mean age-adjusted risk decreased to a lesser extent between NHANES III and NHANES 1999–2004 from 7.9 to 7.4% (p<0.001). The slopes were different (p<0.001). In women, CV risk did not change between NHANES III and 1999–2004, 7.9 to 7.5%, (p=0.40). Predicted 10-year risk by age group (Figure ) shows that the decrease in CV risk was lower in the second period compared to the first one in all age groups, except in the elderly. Conclusion : The estimated net risk for CV disease in the US population decreased from 1976–1980 to 1988–1994 but minimally changed from 1988–1994 to 1999–2004, particularly in women. The increased prevalence of obesity may have offset the gain in CV risk reduction. Predicted 10-year Framingham Risk by Age Group

Abstract Background Older persons with obesity aged 65+ residing in rural areas have reduced access to weight management programs due to geographic isolation. The ability to integrate technology into health promotion interventions shows a potential to reach this underserved population. Methods A 12-week pilot in 28 older rural adults with obesity (body mass index [BMI] ≥ 30 kg/m2) was conducted at a community aging center. The intervention consisted of individualized, weekly dietitian visits focusing on behavior therapy and caloric restriction with twice weekly physical therapist-led group strengthening training classes in a community-based aging center. All participants were provided a Fitbit Flex 2. An aerobic activity prescription outside the strength training classes was provided. Results Mean age was 72.9 ± 5.3 years (82% female). Baseline BMI was 37.1 kg/m2, and waist circumference was 120.0 ± 33.0 cm. Mean weight loss (pre/post) was 4.6 ± 3.2 kg (4.9 ± 3.4%; p &lt; .001). Of the 40 eligible participants, 33 (75%) enrolled, and the completion rate was high (84.8%). Objective measures of physical function improved at follow-up: 6-minute walk test improved: 35.7 ± 41.2 m (p &lt; .001); gait speed improved: 0.10 ± 0.24 m/s (p = .04); and five-times sit-to-stand improved by 2.1 seconds (p &lt; .001). Subjective measures of late-life function improved (5.2 ± 7.1 points, p = .003), as did Patient-Reported Outcome Measurement Information Systems mental and physical health scores (5.0 ± 5.7 and 4.4 ± 5.0, both p &lt; .001). Participants wore their Fitbit 93.9% of all intervention days, and were overall satisfied with the trial (4.5/5.0, 1–5 low–high) and with Fitbit (4.0/5.0). Conclusions A multicomponent obesity intervention incorporating a wearable device is feasible and acceptable to older adults with obesity, and potentially holds promise in enhancing health.

The term “obesity” is associated with societal stigma and discrimination. Eight individual semi-structured interviews and five focus groups with 29 community-dwelling, rural older adults with obesity, seven primary care clinicians, and four rural community leaders were completed using purposive and snowball sampling. Clinicians perceived that older adults are less affected by obesity stigma than younger adults, yet this was not observed by community leaders; however, older participants with obesity reported that they often felt ashamed and/or stigmatized because of their weight. There was also a disconnect between clinician and older adult understanding of obesity. For older adults with obesity, the word “obesity” was associated with negative connotations. Just as physiological aspects of obesity persist into older adulthood, so do psychological aspects, such as perceptions of stigma. The use of the word “obesity” in medical settings may hinder communication between clinician and older participants. Heightened awareness may change the dialogue around obesity.