Dataset Information

A Clustering Study of Dietary Patterns and Physical Activity among Workers of the Uruguayan State Electrical Company.

ABSTRACT: Recent studies have shown that certain nutrients, specific food groups, or general dietary patterns (DPs) can promote health and prevent noncommunicable chronic diseases (NCCDs). Both developed and developing countries experience a high prevalence of NCCDs due to poor lifestyle habits, DPs, and low physical activity levels. This study aims to examine the dietary, physical activity, sociodemographic, and lifestyle patterns of Uruguayan State Electrical Company workers (the IN-UTE study). A total of 2194 workers participated in the study, providing information about their sociodemographics, lifestyles, and dietary habits through different questionnaires. To identify DPs from 16 food groups, principal component analysis (PCA) was performed. A hierarchical cluster algorithm was used to combine food groups and sociodemographic/lifestyle variables. Four DPs were extracted from the data; the first DP was related to the intake of energy-dense foods, the second DP to the characteristics of the job, the third DP to a Mediterranean-style diet, and the fourth DP to age and body mass index. In addition, cluster analysis involving a larger number of lifestyle variables produced similar results to the PCA. Lifestyle and sociodemographic factors, including night work, working outside, and moderate and intense PA, were significantly correlated with the dietary clusters, suggesting that working conditions, socioeconomic status, and PA may play an important role in determining DPs to some extent. Accordingly, these findings should be used to design lifestyle interventions to reverse the appearance of unhealthy DPs in the UTE population.

SUBMITTER: Medina-Vadora MM

PROVIDER: S-EPMC10820101 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Clustering Study of Dietary Patterns and Physical Activity among Workers of the Uruguayan State Electrical Company.

Medina-Vadora Maria Mercedes MM Plaza-Diaz Julio J Llorente-Cantarero Francisco Jesús FJ Severi Cecilia C Lecot Carlos C Ruiz-López María Dolores MD Gil Ángel Á

Nutrients 20240119 2

Recent studies have shown that certain nutrients, specific food groups, or general dietary patterns (DPs) can promote health and prevent noncommunicable chronic diseases (NCCDs). Both developed and developing countries experience a high prevalence of NCCDs due to poor lifestyle habits, DPs, and low physical activity levels. This study aims to examine the dietary, physical activity, sociodemographic, and lifestyle patterns of Uruguayan State Electrical Company workers (the IN-UTE study). A total ...[more]

PMID: 38276542

Similar Datasets

Project description:BackgroundGender differences in dietary patterns and physical activity are known to influence metabolic health, but research exploring these differences using principal component analysis (PCA) is limited. This study aims to identify distinct patterns of eating behaviour, body composition and physical activity between men and women, in order to develop tailored interventions.MethodsA cross-sectional study was conducted on 2,509 adults attending a metabolic health centre. Data on eating habits, physical activity and body composition were collected by means of questionnaires and bioimpedance analysis. PCA was used to identify patterns of eating behaviour and physical activity. Statistical analyses were performed to explore gender-specific differences.ResultsBased on the PCA, five distinct groups of participants were identified: Balanced Eaters, Focused on Home Cooking, Routine Eaters, Restaurant Lovers and Varied Eaters. Significant gender differences in food preferences were observed, with men consuming more meat and women more vegetables. Men also reported greater participation in strength and endurance sports, while women showed a more structured eating routine.ConclusionsThis study, using principal component analysis (PCA), revealed gender-specific patterns in diet, physical activity and body composition. PCA identified five distinct behavioural groups, revealing that men tended to consume more meat and engage in strength training, while women adhered to structured, vegetable-rich diets. The application of PCA provided more insight than traditional analysis, highlighting the complexity of gender-specific behaviour. These results emphasize the need for tailored interventions, focusing on increasing vegetable intake in men and encouraging strength training in women. Future research should exploit PCA to explore behavioural patterns longitudinally for more refined and personalised health strategies.Clinical trials registeredThis study is registered on ClinicalTrials.gov (NCT06654674).

Project description:BackgroundDiet and physical activity (PA) are independent risk factors for obesity and chronic diseases including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS). The temporal sequence of these exposures may be used to create patterns with relations to health status indicators.ObjectivesThe objectives were to create clusters of joint temporal dietary and PA patterns (JTDPAPs) and to determine their association with health status indicators including BMI, waist circumference (WC), fasting plasma glucose, glycated hemoglobin, triglycerides, HDL cholesterol, total cholesterol, blood pressure, and disease status including obesity, T2DM, and MetS in US adults.MethodsA 24-h dietary recall and random day of accelerometer data of 1836 participants from the cross-sectional NHANES 2003-2006 data were used to create JTDPAP clusters by constrained dynamic time warping, coupled with a kernel k-means clustering algorithm. Multivariate regression models determined associations between the 4 JTDPAP clusters and health and disease status indicators, controlling for potential confounders and adjusting for multiple comparisons.ResultsA JTDPAP cluster with proportionally equivalent energy consumed at 2 main eating occasions reaching ≤1600 and ≤2200 kcal from 11:00 to 13:00 and from 17:00 to 20:00, respectively, and the highest PA counts among 4 clusters from 08:00 to 20:00, was associated with significantly lower BMI (P < 0.0001), WC (P = 0.0001), total cholesterol (P = 0.02), and odds of obesity (OR: 0.2; 95% CI: 0.1, 0.5) than a JTDPAP cluster with proportionally equivalent energy consumed reaching ≤1600 and ≤1800 kcal from 11:00 to 14:00 and from 17:00 to 21:00, respectively, and high PA counts from 09:00 to 12:00.ConclusionsThe joint temporally patterned sequence of diet and PA can be used to cluster individuals with meaningful associations to BMI, WC, total cholesterol, and obesity. Temporal patterns hold promise for future development of lifestyle patterns that integrate additional temporal and contextual activities.

Dataset Information

A Clustering Study of Dietary Patterns and Physical Activity among Workers of the Uruguayan State Electrical Company.

Publications

A Clustering Study of Dietary Patterns and Physical Activity among Workers of the Uruguayan State Electrical Company.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets