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Woolcott, Orison O., Till Seuring, and Oscar A. Castillo. Lower prevalence of body fat-defined obesity at higher altitudes in Peruvian adults. High Alt Med Biol . 24:214-222, 2023. Background: Previous studies have reported a lower prevalence of obesity (defined as a body mass index [BMI] ≥30 kg/m 2 ) in populations from higher altitudes. Since BMI does not distinguish fat mass and fat-free mass, it is unclear whether there is an inverse association between altitude and body fat-defined obesity. Methods: We performed an analysis of cross-sectional data to examine the association between altitude and body fat-defined obesity (as opposed to BMI-defined obesity) using individual-level data from a nationally representative sample of the Peruvian adult population living between 0 and 5,400 m altitude. Body fat-defined obesity was diagnosed using the relative fat mass (RFM), an anthropometric index validated to estimate whole-body fat percentage. RFM cutoffs for obesity diagnosis were ≥40% for women and ≥30% for men. We utilized Poisson regression to estimate the prevalence ratio and confidence intervals (CIs) as the measure of the association, adjusting for age, cigarette use, and diabetes. Results: Analysis comprised 36,727 individuals (median age, 39 years; 50.1% women). In rural areas, for a one-km increase in altitude, the prevalence of body fat-defined obesity decreased by 12% among women (adjusted prevalence ratio: 0.88; 95% CI, 0.86 - 0.90; p  < 0.001) and 19% among men (adjusted prevalence ratio: 0.81; 95% CI, 0.77 - 0.86; p  < 0.001), on average, when all the other variables were held constant. The inverse association between altitude and obesity was less strong in urban areas than in rural areas but remained significant among women ( p  = 0.001) and men ( p  < 0.001). However, the relationship between altitude and obesity in women who live in urban areas appears to be nonlinear. Conclusions: In Peruvian adults, the prevalence of body fat-defined obesity was inversely associated with altitude. Whether this inverse association is explained by altitude per se or confounded by socioeconomic or other environmental factors, or differences in race/ethnicity or lifestyle, warrants further investigation.

Background/objectives: We have recently proposed and validated a simple and accurate method to estimate whole-body fat percentage in adults, the relative fat mass (RFM), derived from the ratio of height to waist circumference. We aimed to identify RFM cutoffs to diagnose obesity based on the association between RFM and all-cause mortality., Subjects/methods: We used data from adult participants (≥20 years of age, n = 43,793) of the National Health and Nutrition Examination Survey (NHANES) 1999-2014 linked with death certificate records from the National Death Index. Optimal RFM cutoffs were determined using receiver-operating characteristic analysis (the Youden's index and the Euclidean minimum distance to the coordinate (0,1))., Results: Final dataset for analyses comprised 31,008 adults. During a median follow-up of 8.3 years (IQR, 7.6-13.7), 2,517 deaths occurred. Youden and Euclidean optimal cutoffs of baseline RFM for all-cause mortality were 40.8% and 41.6% for women, and 30.9% and 28.9% for men, respectively. Similar cutoffs were obtained using measured whole-body fat percentage by dual energy X-ray absorptiometry. Adjusting for age, BMI category, ethnicity, education level, and smoking status, the hazard ratio for mortality using Cox proportional hazard regression was 1.41 (95% CI, 1.02-1.95) among women who had an RFM of 40.0-44.9% compared with women who had an RFM <35% (P = 0.035). Among men, the hazard ratio was 1.57 (95% CI, 1.07-2.30) among those with an RFM of 30.0-34.9% compared with men who had an RFM <25% (P = 0.020). Similar adjusted hazard ratios for same RFM categories were obtained in our validation population (NHANES III, n = 12,650, median follow-up: 23.3 years): 1.42 (95% CI, 1.01-2.00) among women (P = 0.043) and 1.50 (95% CI, 1.07-2.10) among men (P = 0.021)., Conclusions: We suggest rounded RFM cutoffs of 40% for women and 30% for men to diagnose obesity and identify individuals at higher risk of death.

High whole-body fat percentage is independently associated with increased mortality. We aimed to identify a simple anthropometric linear equation that is more accurate than the body mass index (BMI) to estimate whole-body fat percentage among adult individuals. National Health and Nutrition Examination Survey (NHANES) 1999-2004 data (n = 12,581) were used for model development and NHANES 2005-2006 data (n = 3,456) were used for model validation. From the 365 anthropometric indices generated, the final selected equation was as follows: 64 - (20 × height/waist circumference) + (12 × sex), named as the relative fat mass (RFM); sex = 0 for men and 1 for women. In the validation dataset, compared with BMI, RFM better predicted whole-body fat percentage, measured by dual energy X-ray absorptiometry (DXA), among women and men. RFM showed better accuracy than the BMI and had fewer false negative cases of body fat-defined obesity among women and men. RFM reduced total obesity misclassification among all women and all men and, overall, among Mexican-Americans, European-Americans and African-Americans. In the population studied, the suggested RFM was more accurate than BMI to estimate whole-body fat percentage among women and men and improved body fat-defined obesity misclassification among American adult individuals of Mexican, European or African ethnicity.

Objective: To determine the association between altitude and obesity in a nationally representative sample of the Peruvian adult population., Methods: This is a cross-sectional analysis of publicly available data from the Food and Nutrition National Center (CENAN, Peru), period 2009-2010. The Prevalence ratio of obesity and abdominal obesity was determined as a measure of association. Obesity and abdominal obesity were diagnosed based on direct anthropometric measurements., Results: The final data set consisted of 31,549 individuals ≥20 years old. The prevalence ratio of obesity was as follows: 1.00 between 0 and 499 m (reference category), 1.00 (95% confidence interval 0.87-1.16) between 500-1,499 m, 0.74 (0.63-0.86) between 1,500-2,999 m, and 0.54 (0.45-0.64) at ≥3,000 m, adjusting for age, sex, self-reported physical activity, out-migration rate, urbanization, poverty, education, and geographical latitude and longitude. In the same order, the adjusted prevalence ratio of abdominal obesity was 1.00, 1.01 (0.94-1.07), 0.93 (0.87-0.99), and 0.89 (0.82-0.95), respectively. We found an interaction between altitude and sex and between altitude and age (P < 0.001, for both interactions) on the association with obesity and abdominal obesity., Conclusions: Among Peruvian adult individuals, we found an inverse association between altitude and obesity, adjusting for multiple covariates. This adjusted association varied by sex and age., (© 2016 The Obesity Society.)

Background: Obesity has been associated with elevated plasma anandamide levels. In addition, anandamide has been shown to stimulate insulin secretion in vitro, suggesting that anandamide might be linked to hyperinsulinemia., Objective: To determine whether high-fat diet-induced insulin resistance increases anandamide levels and potentiates the insulinotropic effect of anandamide in isolated pancreatic islets., Design and Methods: Dogs were fed a high-fat diet (n = 9) for 22 weeks. Abdominal fat depot was quantified by MRI. Insulin sensitivity was assessed by the euglycemic-hyperinsulinemic clamp. Fasting plasma endocannabinoid levels were analyzed by liquid chromatography-mass spectrometry. All metabolic assessments were performed before and after fat diet regimen. At the end of the study, pancreatic islets were isolated prior to euthanasia to test the in vitro effect of anandamide on islet hormones. mRNA expression of cannabinoid receptors was determined in intact islets. The findings in vitro were compared with those from animals fed a control diet (n = 7)., Results: Prolonged fat feeding increased abdominal fat content by 81.3±21.6% (mean±S.E.M, P<0.01). In vivo insulin sensitivity decreased by 31.3±12.1% (P<0.05), concomitant with a decrease in plasma 2-arachidonoyl glycerol (from 39.1±5.2 to 15.7±2.0 nmol/L) but not anandamide, oleoyl ethanolamide, linoleoyl ethanolamide, or palmitoyl ethanolamide. In control-diet animals (body weight: 28.8±1.0 kg), islets incubated with anandamide had a higher basal and glucose-stimulated insulin secretion as compared with no treatment. Islets from fat-fed animals (34.5±1.3 kg; P<0.05 versus control) did not exhibit further potentiation of anandamide-induced insulin secretion as compared with control-diet animals. Glucagon but not somatostatin secretion in vitro was also increased in response to anandamide, but there was no difference between groups (P = 0.705). No differences in gene expression of CB1R or CB2R between groups were found., Conclusions: In canines, high-fat diet-induced insulin resistance does not alter plasma anandamide levels or further potentiate the insulinotropic effect of anandamide in vitro.

The endocannabinoid system is highly implicated in the development of insulin resistance associated with obesity. It has been shown that antagonism of the CB(1) receptor improves insulin sensitivity (S(I)). However, it is unknown whether this improvement is due to the direct effect of CB(1) blockade on peripheral tissues or secondary to decreased fat mass. Here, we examine in the canine dog model the longitudinal changes in S(I) and fat deposition when obesity was induced with a high-fat diet (HFD) and animals were treated with the CB(1) antagonist rimonabant. S(I) was assessed (n = 20) in animals fed a HFD for 6 wk to establish obesity. Thereafter, while HFD was continued for 16 additional weeks, animals were divided into two groups: rimonabant (1.25 mg·kg(-1)·day(-1) RIM; n = 11) and placebo (n = 9). Euglycemic hyperinsulinemic clamps were performed to evaluate changes in insulin resistance and glucose turnover before HFD (week -6) after HFD but before treatment (week 0) and at weeks 2, 6, 12, and 16 of treatment (or placebo) + HFD. Magnetic resonance imaging was performed to determine adiposity- related changes in S(I). Animals developed significant insulin resistance and increased visceral and subcutaneous adiposity after 6 wk of HFD. Treatment with RIM resulted in a modest decrease in total trunk fat with relatively little change in peripheral glucose uptake. However, there was significant improvement in hepatic insulin resistance after only 2 wk of RIM treatment with a concomitant increase in plasma adiponectin levels; both were maintained for the duration of the RIM treatment. CB(1) receptor antagonism appears to have a direct effect on hepatic insulin sensitivity that may be mediated by adiponectin and independent of pronounced reductions in body fat. However, the relatively modest effect on peripheral insulin sensitivity suggests that significant improvements may be secondary to reduced fat mass.

We investigated whether rimonabant, a type 1 cannabinoid receptor antagonist, reduces visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in dogs maintained on a hypercaloric high-fat diet (HHFD). To determine whether energy expenditure contributed to body weight changes, we also calculated resting metabolic rate. Twenty male dogs received either rimonabant (1.25 mg.kg(-1).day(-1), orally; n = 11) or placebo (n = 9) for 16 wk, concomitant with a HHFD. VAT, SAT, and nonfat tissue were measured by magnetic resonance imaging. Resting metabolic rate was assessed by indirect calorimetry. By week 16 of treatment, rimonabant dogs lost 2.5% of their body weight (P = 0.029), whereas in placebo dogs body weight increased by 6.2% (P < 0.001). Rimonabant reduced food intake (P = 0.027), concomitant with a reduction of SAT by 19.5% (P < 0.001). In contrast with the VAT increase with placebo (P < 0.01), VAT did not change with rimonabant. Nonfat tissue remained unchanged in both groups. Body weight loss was not associated with either resting metabolic rate (r(2) = 0.24; P = 0.154) or food intake (r(2) = 0.24; P = 0.166). In conclusion, rimonabant reduced body weight together with a reduction in abdominal fat, mainly because of SAT loss. Body weight changes were not associated with either resting metabolic rate or food intake. The findings provide evidence of a peripheral effect of rimonabant to reduce adiposity and body weight, possibly through a direct effect on adipose tissue.