The Association of Meal Timing With Body Composition and Cardiometabolic Health in Obese Older Adults

Objectives To determine the association between eating window and time of last calorie intake with body composition and cardiometabolic health in obese older adults. Methods We performed a cross-sectional analysis on 36 community-dwelling, overweight-to-obese (BMI 28.0-39.9 kg/m2) older adults, recruited to participate in a weight loss and exercise trial. Time of food intake were extracted from three 24-hour food recalls. Eating window was calculated as the time elapsed between the first and last food intake. We recorded the time of last calorie intake either from food or drink. Blood glucose, triglycerides, high-density (HDL) & low-density (LDL) lipoprotein cholesterols were measured as markers of cardiometabolic health. Total fat and lean mass were assessed by DXA. Partial correlation was used to determine the relationships between eating window and last calorie intake with body composition and cardiometabolic markers, while controlling for sex, age, and total calorie intake. Results On average, participants’ eating window was 12.0±1.1 hours. Time of last calorie intake in 86% of participants was between 6:00-8:00 PM. After controlling for potential confounders, longer eating windows were associated with higher triglyceride levels (P=0.032) and lower HDL (P=0.035), while no association was observed with the other cardiometabolic markers. We observed negative trends, though not statistically significant, between longer eating windows and greater weight, BMI, and fat mass. No association was observed between time of last calorie intake, body composition and cardiometabolic markers. Conclusions Our results suggest that timing of food intake may influence cardiometabolic risk and obesity in older adults.

Polymorphism PLIN1 11482 G>A Interacts with Dietary Intake to Modulate Anthropometric Measures and Lipid Profile in Adults with Normal-Weight Obesity Syndrome

Evidence shows that genetic polymorphisms in perilipin 1 gene (PLIN1) are associated with excessive accumulation of body fat and disturbances in cardiometabolic markers. Therefore, the aim of this study was to verify whether the single nucleotide polymorphism (SNP) PLIN1 11482 G>A (rs894160) interacts with nutrient intake, anthropometric, body composition, and cardiometabolic markers in adults with Normal-Weight Obesity (NWO) syndrome. A cross-sectional study was carried out with 116 individuals aged 20 to 59, with normal body mass index (BMI) and high percentage of body fat. Anthropometric and body composition measures, glycaemic control and serum lipid markers, SNP PLIN1 11482 G>A, and nutrient intake were evaluated. Interactions between nutrient intake and the SNP were determined by regression models and adjusted for potential confounders. The SNP frequency was 56.0% GG, 38.8% GA and 5.2% AA. Anthropometric measures and biochemical markers were not different according to genotype, except for total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C) and non-HDL-C concentrations. However, important interactions between the SNP and dietary intake were observed. Carbohydrate intake interacted with the SNP PLIN1 11482 G>A to modulate waist circumference (WC) and the Homeostatic Model Assessment of Insulin Resistance index. Interaction of lipid intake and the SNP modulated TC and LDL-C concentrations, and the interaction between protein intake and the SNP tended to modulate weight, WC and BMI. The SNP PLIN1 11482 G>A seems to modulate responses in anthropometric and lipid profile biomarkers of subjects with NWO depending on the dietary macronutrient composition, which may have long-term impact on cardiometabolic markers.

Interactions of Dietary Insulin Index and Dietary Insulin Load with BDNF Val66Met Polymorphism in Relation to Cardiometabolic Markers in Iranian Diabetic Patients: A Cross-Sectional Study

The progression of cardiometabolic diseases is determined by both genetic and environmental factors. Gene-diet interactions may therefore be important in modulating the risks of developing metabolic diseases. The objectives were to investigate the effect of the interaction between BDNF Val66Met polymorphisms and Dietary Insulin Index and Insulin Load (DII and DIL) on Cardiometabolic Markers among diabetic patients. In this cross-sectional study, blood samples were collected from 667 patients. DIL & DII were defined using a validated food frequency questionnaire (FFQ). Genotyping the BDNF Val66Met polymorphism was conducted by the PCR-RFLP method. Interactions between dietary indices and gene variants were evaluated using a Generalized Linear Model (GLM). PGF2a concentrations were significantly higher among Val homozygotes than Met alleles carrier. This study revealed that, compared with individuals with the Val/Val genotype, those with the Met/Val or Met/Met genotype had lower BMI (P-interaction =0.04), TG (P-interaction=0.04), leptin (P-interaction =0.01), LDL (P-interaction=0.04) and TC (P-interaction =0.01) when they consumed diets higher on the DIL index. Moreover, the highest quartile of the DIL, compared to the lowest, showed increased in WC (P-interaction =0.02) and LDL/HDL (P-interaction =0.04) for Val/Val homozygotes compared to Met-allele carriers. BDNF Val66Met variants may interact with DIL and DII, thus be involved in the development of cardiometabolic risk factors. If diabetic patients with Met alleles regulate dietary intakes, they have a protective opportunity to regulate their cardiometabolic markers.

Use of Different Food Classification Systems to Assess the Association between Ultra-Processed Food Consumption and Cardiometabolic Health in an Elderly Population with Metabolic Syndrome (PREDIMED-Plus Cohort)

The association between ultra-processed food (UPF) and risk of cardiometabolic disorders is an ongoing concern. Different food processing-based classification systems have originated discrepancies in the conclusions among studies. To test whether the association between UPF consumption and cardiometabolic markers changes with the classification system, we used baseline data from 5636 participants (48.5% female and 51.5% male, mean age 65.1 ± 4.9) of the PREDIMED-Plus (“PREvention with MEDiterranean DIet”) trial. Subjects presented with overweight or obesity and met at least three metabolic syndrome (MetS) criteria. Food consumption was classified using a 143-item food frequency questionnaire according to four food processing-based classifications: NOVA, International Agency for Research on Cancer (IARC), International Food Information Council (IFIC) and University of North Carolina (UNC). Mean changes in nutritional and cardiometabolic markers were assessed according to quintiles of UPF consumption for each system. The association between UPF consumption and cardiometabolic markers was assessed using linear regression analysis. The concordance of the different classifications was assessed with intra-class correlation coefficients (ICC3, overall = 0.51). The highest UPF consumption was obtained with the IARC classification (45.9%) and the lowest with NOVA (7.9%). Subjects with high UPF consumption showed a poor dietary profile. We detected a direct association between UPF consumption and BMI (p = 0.001) when using the NOVA system, and with systolic (p = 0.018) and diastolic (p = 0.042) blood pressure when using the UNC system. Food classification methodologies markedly influenced the association between UPF consumption and cardiometabolic risk markers.

Cardiometabolic markers among Argentinean normal weight and overweight children with and without central obesity

Background: The association between central obesity and cardiometabolic complications justifies exploring its association in normal-weight and overweight/obese (OW/OB) schoolchildren. Objective: To describe cardiometabolic markers in four groups according to BMI/WC categories: 1) normal weight with central OB; 2) normal weight without central OB; 3) OW/OB with central OB; and 4) OW/OB without central OB, in a sample of Argentinean schoolchildren. Methods: A cross-sectional study of 1264 Argentinean schoolchildren (624 F), aged 9.5±2.2 years was performed between November 2013 and 2015. Children’s anthropometric measures, blood pressure (BP), glucose, lipids, and insulin were measured. Children were divided into four groups: 1) normal weight with and with central OB; 2) normal weight without central OB; 3) OW/OB with central OB; and 4) OW/OB without central OB. Results: The prevalence of normal weight children without central OB was 64.3% (796), normal weight with central 5% (66), OW/OB without central OB 11% (137), and OW/OB with central OB 21% (265). Normal weight with central OB had significantly higher triglycerides than normal weight children without central OB (86 vs 70 mg/dL, respectively) and OW/OB children without central OB (81vs 77 mg/dL). Multiple linear regression analyses showed that age, systolic BP, HDL-C, triglycerides, and maternal WC were significantly associated with children’s WC; R2=0.50 as well as children’s BMI; R2=0.37. Conclusion: This study found that children with central OB might be at future higher cardiometabolic risk than those without central OB independently of the presence of OW/OB. However, future longitudinal studies should be performed to confirm these findings.

Weight-Loss Parameters and Quality of Life in Obese Aged Women Using WATERinMOTION

Background: There are controversial studies on weight loss, cardiometabolic markers, and quality of life (QOL) in obese aged women participating in water sports. Objectives: This study aimed to determine the effects of the WATERinMOTION exercise program accompanied with no diet on the inactive obese aged women’s weight, cardiometabolic markers, and QOL. Methods: Sixty-four inactive obese aged women were recruited to participate in this cross-sectional study at the Ukrainian Sports Center, Kyiv, 2019. They were randomly assigned into two Case (n = 32, with the WATERinMOTION aquatics exercise program) and control (n = 32, held in a sitting position simultaneously) groups using the convenient sampling method. The two programs were run twice a week (55 minutes each time) and lasted for one month. Moreover, anthropometric indices (weight, height, waist circumference), cardiometabolic markers (blood lipid markers and glycaemia), QOL (SF-36 questionnaire), and dietary monitoring were assessed before and after the intervention. Results: The groups did not differ significantly regarding each of the analyzed variables prior to the intervention. Comparing pre-and post-intervention results revealed significant weight loss (-1.3, P = 0.004) and average BMI (-0.4, P = 0.002) in the case group. Moreover, a significant variation was revealed only in terms of weight after the intervention (P = 0.001). Regarding QOL, improvements in health status, vitality, and social aspects were significant in the case group after the intervention. Conclusions: The present study suggests that the WATERinMOTION program accompanied with no diet has a positive effect on weight loss, waist circumference, and metabolic profiles in obese aged women. However, the improvement in the QOL should not be neglected.

The effect of endurance and endurance-strength training on body composition and cardiometabolic markers in abdominally obese women: a randomised trial

Studies comparing the effect of endurance and endurance-strength training on cardiometabolic markers provided inconsistent results. Therefore, the study aimed to compare the effect of endurance and endurance-strength training on body composition and cardiometabolic parameters in abdominally obese women. In this randomised trial, 101 subjects were included and divided into endurance (n = 52) and endurance-strength (n = 49) training. During the 12-week intervention, participants performed supervised one-hour training three times a week. Body composition, blood pressure (BP), markers of glucose and lipid homeostasis, and myoglobin levels were measured before and after the intervention. In total, 85 subjects completed the trial. Both interventions decreased fat mass and visceral adipose tissue and increased free fat mass, appendicular lean mass index and lean mass index. Neither endurance training nor endurance-strength training affected glucose and lipid metabolism. However, only endurance training significantly decreased paraoxonase and myoglobin levels. Both training programmes significantly decreased BP, with a more reduction of diastolic BP noted in the endurance group. In conclusion, both training programmes had a favourable effect on body composition but did not improve glucose and lipid homeostasis. Besides, endurance training decreased paraoxonase activity and myoglobin levels and was more effective in reducing BP.The study was registered with the German Clinical Trials Register (DRKS) within the number: DRKS00019832 (retrospective registration), date of registration: 26/02/2020.

The Association of Meal Timing With Body Composition & Cardiometabolic Health in Obese Older Adults

Objectives To determine the association between eating window and time of last calorie intake with body composition and cardiometabolic health in obese older adults. Methods We performed a cross-sectional analysis on 36 community-dwelling, overweight-to-obese (BMI 28.0–39.9 kg/m2) older adults (aged 70.6 ± 6.1 years, 83% women, 86% white), recruited to participate in a weight loss and exercise trial. Time of food and nutrient intake were extracted from three 24-hour food recalls. Eating window was calculated as the time elapsed between the first and last food intake. We recorded the time of last calorie intake either from food or drink. Blood glucose, triglycerides, high-density (HDL) & low-density (LDL) lipoprotein cholesterols were measured as markers of cardiometabolic health. Body composition metrics, including total fat and lean mass, were assessed by dual-energy X-ray absorptiometry. Body weight and height were measured to calculate BMI. Partial correlation was used to determine the relationships between eating window and last calorie intake with body composition and cardiometabolic markers, while controlling for sex, age, and total calorie intake. Results On average, participants’ eating window was 12.0 ± 1.1 hours. Eating window in 43% of participants was <12 hours, while it was ≥13 hours in 29% of the participants. Time of last calorie intake in the majority of participants (86%) was between 6:00–8:00 PM. After controlling for potential confounders, longer eating windows were associated with higher triglyceride levels (P = 0.032) and lower HDL (P = 0.035), while no association was observed with the other cardiometabolic markers. We also observed negative trends, though not statistically significant, between longer eating windows and greater weight, BMI, and fat mass. No association was observed between time of last calorie intake, body composition and cardiometabolicy markers. Conclusions Our results suggest that timing of food intake may influence cardiometabolic risk and obesity in older adults. However, further research is required to determine the importance of meal timing on obesity in older adults. Funding Sources Center for Disease Control (U48 DP000025) and NIA T32-AG0001810.