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Clinical Trial
. 2020 Mar 12;12(3):751.
doi: 10.3390/nu12030751.

Dietary-Lifestyle Patterns Associated with Adiposity and Metabolic Abnormalities in Adult Men under 40 Years Old: A Cross-Sectional Study (MeDiSH Project)

Affiliations
Clinical Trial

Dietary-Lifestyle Patterns Associated with Adiposity and Metabolic Abnormalities in Adult Men under 40 Years Old: A Cross-Sectional Study (MeDiSH Project)

Marta Lonnie et al. Nutrients. .

Abstract

The aim of this study was to examine the associations of dietary-lifestyle patterns (DLPs) with adiposity and metabolic abnormalities in adult Polish men that were under 40. The cross-sectional study included 358 men that were 19-40-year-old. Dietary and lifestyle data were collected with multicomponent food frequency questionnaire (KomPAN®). DPLs were derived with Principal Component Analysis (PCA) using 25 dietary and six lifestyle as the input variables. Adiposity was determined with the use of: overweight (body mass index 25-29.9 kg/m2), central obesity (waist-to-height ratio ≥ 0.5), general obesity (body fat ≥ 25%), excessive visceral fat tissue (≥ median), and increased skeletal muscle mass (≥ median). The metabolic abnormalities were characterised by elevated: fasting blood glucose (FBG ≥ 100 mg/dL), triglycerides (TG ≥ 150 mg/dL), total cholesterol (TC ≥ 200 mg/dL), or systolic or diastolic blood pressure (≥ 130 or ≥ 85 mmHg, respectively). Four PCA-driven DLPs were derived and labelled accordingly to the most characteristic dietary or lifestyle behaviours that were correlated with each pattern. Multivariate logistic regression revealed that higher adherence (upper vs. bottom tertile as referent) to "Protein food, fried-food, and recreational physical activity" pattern was associated with higher odds of overweight and increased skeletal muscle mass, and lower odds of: general obesity, excessive visceral fat tissue, and elevated TC. Higher adherence to "Healthy diet, active, past smokers" pattern was associated with higher odds of overweight and lower odds of: general obesity, excessive visceral fat tissue, and elevated FBG. Higher adherence to "Sandwiches and convenient diet" pattern was associated with higher odds of: central obesity, general obesity, excessive visceral fat tissue, elevated TC, elevated TG, occurrence at least two metabolic abnormalities, and lower odds of increased skeletal muscle mass. A higher adherence to "Fast foods and stimulants" pattern was associated with higher odds of central obesity, general obesity, excessive visceral fat tissue, and lower odds of increased skeletal muscle mass. The interrelations between diet and lifestyle behaviours were reflected in three out of four patterns. Healthy diet attempts combined with active lifestyle was associated with reduced risk of adiposity and metabolic abnormalities despite some unhealthy components, like former smoking or fried-food consumption. In contrary, patterns that were composed of undesirable dietary behaviours solely, as well as poor diet combined with stimulant use, were associated with higher adiposity and worse metabolic health, despite the relatively young age of the study participants. Accurate mapping of dietary-lifestyle behaviours can serve as a tool for formulating evidence-based recommendations.

Keywords: adiposity; adults; dietary patterns; lifestyle; men; metabolic; principle component analysis; young adults.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Study design and data collection.
Figure 2
Figure 2
Diagrams of factor loadings that characterise each dietary-lifestyle pattern identified with principal component analysis. (A)—“Protein food, fried-food and recreational physical activity” pattern; (B)—““Sandwiches and convenient diet” pattern; (C)—““Fast foods and stimulants” pattern; (D)—““Healthy diet, active, past smokers” pattern; Only factor loadings of >|0.30| are shown for simplicity. Total variance explained by four dietary-lifestyle patterns is 32.2%. The factor loadings for “lard” and “screen time” were <|0.30| in all factors, hence the data are not shown.

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