Empirically derived dietary patterns and obesity among Iranian Adults: Yazd Health Study-TAMYZ and Shahedieh cohort study

Bone mineral density and muscle mass associated with healthy eating index in postmenopausal women; results from RaNCD cohort study

BACKGROUND

The Healthy Eating Index 2015 (HEI-2015) is a tool for checking the quality of diet. This index is used to examine how well people's dietary behavior fits certain criteria for achieving a healthy diet in Dietary Guidelines for Americans 2015-2020. We look at the possible association between the HEI-2015 and bone mineral density (BMD) and muscle strength in postmenopausal women.

METHODS

This research included 1012 postmenopausal women from the recruitment phase of the Ravansar Noncommunicable Diseases (RaNCD) cohort study in Kermanshah-Iran. A standardized and repeatable food-frequency questionnaire (FFQ) that contains 118 items was used to quantify dietary consumption. Anthropometric indices measured via Bio-Impedance Analyzer BIA (Inbody 770, Inbody Co, Seoul, Korea).

RESULT

The mean age of postmenopausal women was (56.41 ± 5.31) years. Participants in the highest quartile had a more daily energy intake compared to the lowest quartile (2329.89 ± 837.59), (P < 0.001). Women in the upper quartiles had greater Skeletal Muscle Mass (SMM) than those in the lower quartiles (21.61 ± 2.80 vs 20.52 ± 3.13; p = 0.0002). The linear model didn't show a significant relationship between HEI score and greater BMD (β = 0.0014, P = 0.169).

CONCLUSION

A diet of high quality followed by a high HEL-2015 score was shown to be strongly connected to increased BMD and muscle mass in Kurdish postmenopausal women.

Dietary patterns derived using principal component analysis and associations with sociodemographic characteristics and overweight and obesity: A cross-sectional analysis of Iranian adults

Introduction

This study examined the cross-sectional association between household dietary patterns and sociodemographic characteristics and BMI in a nationally representative sample of Iranian adults.

Methods

Data on 6,833 households (n = 17,824 adults) from the National Comprehensive Study on Household Food Consumption Pattern and Nutritional Status 2001-2003 were used. Principal component analysis (PCA) was used to extract dietary patterns from three household 24-h dietary recalls. Linear regression analyses were used to examine associations between dietary patterns and sociodemographic characteristics and BMI.

Results

Three dietary patterns were identified: the first was characterized by high citrus fruit intake, the second by high hydrogenated fats intake and the third by high non-leafy vegetables intake. The first and third patterns were associated with household heads with higher education and living in urban areas, while the second was associated with household heads with lower education and living in rural areas. All dietary patterns were positively associated with BMI. The strongest association was found with the first dietary pattern (β: 0.49, 95% CI: 0.43, 0.55).

Discussion

While all three dietary patterns were positively associated with BMI, the sociodemographic characteristics of Iranian adults who consumed them differed. These findings inform the design of population-level dietary interventions to address rising obesity rates in Iran.

Determining the effective factors in predicting diet adherence using an intelligent model

Adhering to a healthy diet plays an essential role in preventing many nutrition-related diseases, such as obesity, diabetes, high blood pressure, and other cardiovascular diseases. This study aimed to predict adherence to the prescribed diets using a hybrid model of artificial neural networks (ANNs) and the genetic algorithm (GA). In this study, 26 factors affecting diet adherence were modeled using ANN and GA(ANGA). A dataset of 1528 patients, including 1116 females and 412 males, referred to a private clinic was applied. SPSS Ver.25 and MATLAB toolbox 2017 were employed to make the model and analyze the data. The results showed that the accuracy of the proposed ANN and ANGA models for predicting diet adherence was 93.22% and 93.51%, respectively. Also, the Pearson coefficient showed a significant relationship among the factors. The developed model showed the proper performance for predicting adherence to the diet. Moreover, the most effective factors were selected using GA. Some important factors that affect diet adherence include the duration of the marriage, the reason for referring to the clinic, weight, body mass index (BMI), weight satisfaction, lunch and dinner times, and sleep time. Therefore, applying the proposed model can help dietitians identify people who need more support to adhere to the diet.

Empirically-Derived Dietary Patterns in Relation to Non-Alcoholic Fatty Liver Diseases Among Adult Participants in Amol, Northern Iran: A Structural Equation Modeling Approach

Dietary modifications remain the mainstay in managing nonalcoholic fatty liver disease (NAFLD). Published data on the effect of overall dietary patterns on NAFLD is scarce. The present study aims to extract the dietary patterns and investigate their association to NAFLD by gender, using structural equation modeling, among adult participants in Amol, northern Iran. In this cross-sectional study, data from 3,149 participants in the Amol cohort study (55.3% men, n = 1,741) were analyzed. Usual dietary intake was assessed by a validated 168-items semiquantitative food frequency questionnaire. We classified major dietary patterns by explanatory factor analysis (EFA) and confirmatory factor analysis (CFA). NAFLD diagnosis was based on ultrasound scanning, including increased hepatic echogenicity, abnormal appearance of hepatic arteries, and diaphragm in the absence of excessive alcohol consumption. Multivariable logistic regression and structural equation modeling (SEM) were used to explore the relationship between dietary patterns and NAFLD. Three distinct dietary patterns, including western, healthy, and traditional/mixed dietary patterns, were identified. Adult male who adhere to the western dietary pattern were more affected with NAFLD risk [Q1, Q2, Q3, Q4, odds ratio (OR) = 1, 1.16, 1.34, 1.39; 95% confidence interval (CI) = 0.83–1.61, 0.96–1.85, 0.98–1.96, p_trend = 0.04, respectively]. A full mediating effect of healthy dietary pattern, western dietary pattern, and traditional dietary pattern via dietary acid load (DAL) proxy (of dietary patterns to DAL: βstd = −0.35, p < 0.006, βstd = 0.15, p = 0.009, and βstd = 0.08, p = 0.001, respectively), on NAFLD was found through mediation analysis using SEM. A western dietary pattern comprising frequent intake of salty and sweet snacks, soft drinks, refined grains, processed meats, cooked and fried potatoes, eggs, and coffee was associated with a higher odds of NAFLD in an Iranian male population. Additionally, our findings might provide a mechanistic explanation for the association between dietary patterns and NAFLD via DAL proxy. However, further prospective studies, including assessing acid-base biomarkers, are needed.

Is the Mediterranean Diet Pattern Associated with Weight Related Health Complications in Adults? A Cross-Sectional Study of Australian Health Survey

We hypothesized that unhealthy dietary pattern would be associated with weight related complications among overweight. We analysed data from the Australian Health Survey conducted from 2011 to 2013. A total of 5055 adults with at least overweight (body mass index ≥25 kg/m²) were analysed. We used logistic regression to assess the association between unhealthy dietary pattern, defined by low adherence to Mediterranean Diet Score (MDS), and weight related complications, defined by the Edmonton Obesity Staging System (EOSS). We repeated the logistic regression models by age and socio-economic disadvantage strata in sensitivity analyses. We also repeated the main analysis on a propensity score matched dataset (n = 3364). Complications by EOSS ≥2 was present in 3036 (60.1%) participants. There was no statistically significant association between unhealthy dietary pattern and weight related complication (odds ratio 0.98 (95%confidence interval: 0.85, 1.12)). The null association remained the same after repeating the analysis on three age and five socio-economic indexes for areas strata. The finding persisted after the analysis was repeated on a propensity score matched dataset. We found no evidence to support the hypothesis that unhealthy dietary pattern was associated with weight related complications in this cross-sectional study of the Australian population with overweight or obesity.