Preventing and Managing Cardiometabolic Risk: The Logic for Intervention

Cardiometabolic risk (CMR), also known as metabolic syndrome or insulin resistance syndrome, comprises obesity (particularly central or abdominal obesity), high triglycerides, low HDL, elevated blood pressure, and elevated plasma glucose. Leading to death from diabetes, heart disease, and stroke, the root cause of CMR is inadequate physical activity, a Western diet identified primarily by low intake of fruits, vegetables, and whole grains, and high in saturated fat, as well as a number of yet-to-be-identified genetic factors. While the pathophysiological pathways related to CMR are complex, the universal need for adequate physical activity and a diet that emphasizes fruits and vegetables and whole grains, while minimizing food high in added sugars and saturated fat suggests that these behaviors are the appropriate focus of intervention

From an Apple to a Pear: Moving Fat around for Reversing Insulin Resistance.

Type 2 diabetes (T2D) is a chronic condition where the body is resistant to insulin, leading to an elevated blood glucose state. Obesity is a main factor leading to T2D. Many clinical studies, however, have described a proportion of obese individuals who express a metabolically healthy profile, whereas some lean individuals could develop metabolic disorders. To study obesity as a risk factor, body fat distribution needs to be considered rather than crude body weight. Different individuals' bodies favor storing fat in different depots; some tend to accumulate more fat in the visceral depot, while others tend to store it in the femoral depot. This tendency relies on different factors, including genetic background and lifestyle. Consuming some types of medications can cause a shift in this tendency, leading to fat redistribution. Fat distribution plays an important role in the progression of risk of insulin resistance (IR). Apple-shaped individuals with enhanced abdominal obesity have a higher risk of IR compared to BMI-matched pear-shaped individuals, who store their fat in the gluteal-femoral depots. This is related to the different adipose tissue physiology between these two depots. In this review, we will summarize the recent evidence highlighting the underlying protective mechanisms in gluteal-femoral subcutaneous adipose tissues compared to those associated with abdominal adipose tissue, and we will revise the recent evidence showing antidiabetic drugs that impact fat distribution as they manage the T2D condition.This research was funded by the Qatar National Research Fund (QNRF), grant number NPRP13S-1230-190008

The validity of two compartment model methods of body composition as compared to magnetic resonance imaging in Asian Indian versus Caucasian males

Background: The two-compartment (2C) model is a relatively accessible, inexpensive and time efficient method for body composition measurement. There is very little validated research on the 2C model in Asian Indians: a high risk population in terms of obesity and related disorders. This highlights the need for valid estimates of body composition from the 2C model. Purpose: The goal was to compare 2C model (predictor) estimates of body composition to those from magnetic resonance imaging (MRI) (criterion), an established gold standard measure of total adiposity in order to determine the validity of the 2C model in the Asian Indian population. From this data it is hoped that a correction equation may be determined for more accurate prediction of Asian Indian body composition using 2C model methods. Methods: 21 males (10 Asian Indian and 11 Caucasian, aged 18-55 yrs) had estimates of percent body fat from 2C methods (sum of four skinfolds and anthropometry, bioelectrical impedance analysis [Bodystat 1500 and Tanita segmental impedance analyser], air displacement plethysmography [Bod Pod] and hydrostatic weighing) compared to MRI measured body composition values. Agreement was assessed using multiple linear regression analysis and Bland-Altman plots. Differences were assessed using repeated measures analysis of variance. Results: Regression analysis showed air displacement plethysmography predicts MRI body composition in Caucasian males (adjusted r2 = 0.74; SEE =3.27 ). In Asian Indians, tricep skinfold thickness and hydrostatic weighing predicted MRI body composition with a low prediction error (adjusted r2 = 0.90; SEE =1.75). Despite strong correlations and no significant difference between mean differences of the 2C methods, used in the prediction model, and MRI, BlandAltman plots revealed no acceptable limits of agreement between the methods. Asian Indian body composition was underestimated by all two compartment devices compared to MRI. Conclusion: There appears to be potential for the use of tricep skinfold thickness and hydrostatic weighing to predict an established reference measure (MRI) in the high risk Asian Indian population. The 2C model underestimated Asian Indian body composition, this suggests that un-validated, the 2C model may misidentify obesity and in turn health risk. However the small sample tested, has implications for the interpretation of the findings. Further investigation is required with a greater sample size to validate the 2C model against an established reference measure such as MRI as there is currently little published validation data in this ethnic group

Effects of Exogenous Female Sex Hormones on Food Intake, Macronutrients and Body Weight in the Ovariectomized Postbreeder Female Rat.

Hormone replacement therapy (HRT) is chosen by a growing segment of the postmenopausal population. Mid-life body weight gain is perceived to increase further with exogenous HRT. To examine hormonal effects on caloric intake (CI), carbohydrate (CHO), FAT, protein (PRO), chocolate and body weight (BW) in a female model, Sprague-Dawley postbreeder (n = 55) rats (10 mos., 10 litters of pups) were ovariectomized (OV) and implanted with 17 $\beta$ estradiol (E) and/or progesterone (P), or placebo in three separate studies (phases) of 10 days each. Uterine weights (p =.0001) and radioimmunoassay confirmed hormonal bioactivity. The sham (S) group with placebo implant was used for comparison. In phase I, 3 food cups containing CHO, FAT, and PRO were presented ad libitum to all treatments. Estrogen decreased the rate of body weight gain (p =.001) compared to OV, P, and S with no significant differences in caloric intake (trend of estrogen p =.052). In phase II, all except S received 4 food cups; 2 CHO choices, (sweet, AIN 76 and nonsweet AIN 93), FAT and PRO. The body weight of the P and S groups compared to OV (p =.009) in phase II did not continue to increase. OV produced a carbohydrate appetite for both SW & NSW (p =.007), E&P chose 3 times more SW than NSW (p =.001). For phase III 4 caloric levels of chocolate were added (except for S). Chocolate was consumed at 40% to 53% of total caloric intake with or without HRT with reduced nutrient dense macronutrient consumption. Thus access to chocolate eliminated both the reduced rate of weight gain caused by E (phase I) and the body weight adaptation by P in phase II. Variations in % fate intake (40% to 60%) did not result in treatment differences in body composition (p =.095). The OV group which consumed the most calories from carbohydrate (p =.001), gained the most overall BW (p =.001). The rats consuming the most fat (S 57%) gained the least amount of body weight (p =.001). Caloric conversion ratios (weight gain/by caloric intake $\times$ 1000) varied among treatments (p =.003). Additional research on the metabolism of the postmenopausal female taking hormone replacement therapy is needed