Association between dietary patterns and body composition in normal-weight subjects with metabolic syndrome

Comparative Analysis of Dietary Habits and Obesity Prediction: Body Mass Index versus Body Fat Percentage Classification Using Bioelectrical Impedance Analysis

Background: Obesity remains a widely debated issue, often criticized for the limitations in its identification and classification. This study aims to compare two distinct systems for classifying obesity: body mass index (BMI) and body fat percentage (BFP) as assessed by bioelectrical impedance analysis (BIA). By examining these measures, the study seeks to clarify how different metrics of body composition influence the identification of obesity-related risk factors. Methods: The study enrolled 1255 adults, comprising 471 males and 784 females, with a mean age of 36 ± 12 years. Participants exhibited varying degrees of weight status, including optimal weight, overweight, and obesity. Body composition analysis was conducted using the TANITA Body Composition Analyzer BC-418 MA III device (T5896, Tokyo, Japan), evaluating the following parameters: current weight, basal metabolic rate (BMR), adipose tissue (%), muscle mass (%), and hydration status (%). Results: Age and psychological factors like cravings, fatigue, stress, and compulsive eating were significant predictors of obesity in the BMI model but not in the BFP model. Additionally, having a family history of diabetes was protective in the BMI model (OR: 0.33, 0.11-0.87) but increased risk in the BFP model (OR: 1.66, 1.01-2.76). The BMI model demonstrates exceptional predictive ability (AUC = 0.998). In contrast, the BFP model, while still performing well, exhibits a lower AUC (0.975), indicating slightly reduced discriminative power compared to the BMI model. Conclusions: BMI classification demonstrates superior predictive accuracy, specificity, and sensitivity. This suggests that BMI remains a more reliable measure for identifying obesity-related risk factors compared to the BFP model.

Dietary inflammatory index and type 2 diabetes in US women: a cross-sectional analysis of the National Health and Nutrition Examination Survey, 2007-2018

Objective

Type 2 diabetes (T2D) is a major public health concern in the United States and worldwide. The dietary inflammatory index (DII) is a useful tool for assessing dietary inflammation. Although much research links the DII to diabetes, little is known about the relationship in adult women with a reproductive history in the United States. We aimed to investigate how the relationship between the DII and T2D varies among different subgroups of American women.

Methods

Secondary data from the National Health and Nutrition Examination Survey from 2007 to 2018 were analyzed. Cross-sectional analysis of 8,394 American women aged 20 years or older who had at least one live birth. The main outcome was the diagnosis of T2D. Multivariate survey-weighted regression was used to determine the odds ratio (OR) and 95% confidence interval (95%CI) for the association between DII and T2D. A weighted restricted cubic spline (RCS) model was constructed to establish OR curves at three knots to examine the dose-response association between DII and T2D. Additionally, a weighted subgroup analysis was performed in a fully adjusted model to verify that the association was robust.

Results

The study main found a significant association between the DII and T2D (OR = 1.19, 95%CI: 1.12, 1.26, p < 0.001). Participants in the highest third of DII scores had a 56% increased risk of T2D (OR = 1.56, 95%CI: 1.16, 2.10; p for trend = 0.003) compared with those in the lowest third of DII scores, after adjusting for all covariates. The multivariable RCS demonstrated a linear association between DII and T2D (p = 0.892). The subsidiary found that subgroup analyses revealed a significant variation in the association between DII and T2D according to obesity, oral health, and poverty-income ratio (PIR) status. Among non-obese women, the OR was 1.22 (95%CI: 1.08, 1.37); among women with good oral health, the OR was 1.17 (95%CI: 1.07, 1.28); among women with low PIR, the OR was 1.17 (95%CI: 1.05, 1.30); and among women with high PIR, the OR was 1.26 (95% CI: 1.07, 1.48).

Conclusion

Our findings suggest that there is a significant association between DII and T2D and that oral health, obesity, and PIR status may influence the relationship between DII and T2D risk. Further studies are warranted to validate our results and evaluate whether the results are similar in other populations.

The Role of Nutrition and Body Composition on Metabolism

Metabolism encompasses the entire array of chemical reactions continuously occurring within the body that sustain life and maintain normal physiological functions [...].

Predictive Roles of Basal Metabolic Rate and Body Water Distribution in Sarcopenia and Sarcopenic Obesity: The link to Carbohydrates

Sarcopenic obesity is a new category of obesity and is a specific condition of sarcopenia. This study aimed to find the relationship of the basal metabolic rate (BMR) and body water distribution with muscle health and their prospective roles in screening for sarcopenic obesity and sarcopenia. The role of nutrients such as carbohydrates in the relationship was further detected. A total of 402 elderly subjects were recruited. Body composition was estimated by bioelectrical impedance analysis. Sarcopenia was defined by the Asian Working Group for Sarcopenia 2019. The cutoff values were determined by the receiver operating characteristic curve. Mediation analyses were performed using SPSS PROCESS. Higher BMR and BMR/body surface area (BSA) were protective factors against sarcopenic obesity (OR = 0.047, p = 0.004; OR = 0.035, p = 0.002) and sarcopenia (OR = 0.085, p = 0.001; OR = 0.100, p = 0.003) in elderly people. Low extracellular water (ECW)/intracellular water (ICW) and ECW/total body water (TBW) were negatively correlated with the skeletal muscle index (SMI). The intake of dietary carbohydrates in people with sarcopenic obesity was the lowest, but in subjects with obesity, it was the highest (p = 0.023). The results of the moderated mediation model showed that BMR fully mediated the positive relationship between carbohydrates and SMI, which was more obvious in the population with an abnormal body water distribution. BMR or BMR/BSA had the potential role of predicting a higher risk of sarcopenic obesity and sarcopenia. Higher BMR and lower ECW/ICW and ECW/TBW may benefit muscle health. The overconsumption of carbohydrates (especially > AMDR) might be a risk factor for obesity. Moderate dietary carbohydrate intake might promote SMI by regulating BMR and body water distribution in the elderly.

Dietary Inflammation Index and Its Association with Long-Term All-Cause and Cardiovascular Mortality in the General US Population by Baseline Glycemic Status

Dietary inflammatory potential has been proven to be correlated with the incidence of diabetes and cardiovascular diseases. However, the evidence regarding the impact of dietary inflammatory patterns on long-term mortality is scarce. This cohort study aims to investigate the dietary inflammatory pattern of the general US individuals by baseline glycemic status and to estimate its association with long-term mortality. A total of 20,762 general American adults with different glycemic statuses from the National Health and Nutrition Examination Survey were included. We extracted 24-h dietary information, and the dietary inflammatory index (DII) was calculated. The outcomes were defined as 5-year all-cause and cardiovascular mortality. Compared with the normoglycemia group, individuals with prediabetes and type 2 diabetes had higher DII scores (overall weighted p < 0.001). Compared with low DII scores, participants with high DII scores were at a higher risk of long-term all-cause mortality (HR: 1.597, 95% CI: 1.370, 1.861; p < 0.001) and cardiovascular mortality (HR: 2.036, 95% CI: 1.458, 2.844; p < 0.001). The results were stable after adjusting for potential confounders. Moreover, the prognostic value of DII for long-term all-cause mortality existed only in diabetic individuals but not in the normoglycemia or prediabetes group (p for interaction = 0.006). In conclusion, compared to the normoglycemia or prediabetes groups, participants with diabetes had a higher DII score, which indicates a greater pro-inflammatory potential. Diabetic individuals with higher DII scores were at a higher risk of long-term all-cause and cardiovascular mortality.