The Association of Lifestyle Patterns with Prediabetes in Adults from Families at High Risk for Type 2 Diabetes in Europe: The Feel4Diabetes Study.
Niki MouroutiChristina MavrogianniTheodora MouratidouStavros LiatisPäivi ValveImre RurikPéter TorzsaGreet CardonYulia BazdarskaVioleta IotovaLuis Alberto Moreno AznarKonstantinos MakrilakisYannis ManiosPublished in: Nutrients (2023)
The increasing prevalence of prediabetes globally does not bode well for the growing epidemic of type 2 diabetes (T2D) and its complications. Yet there is a lack of studies regarding lifestyle patterns (LPs) and their association with prediabetes. The present study aimed to examine the association of different LPs with the existence of prediabetes in adults from families at high risk for T2D in Europe. In total, 2759 adults (66.3% females) from six European countries were included in this cross-sectional analysis using data from the baseline assessment of the Feel4Diabetes study. Anthropometric, sociodemographic, dietary and behavioral data were assessed, and fasting blood glucose measurements were also obtained. LPs were derived via principal component analysis. Two LPs were derived, explaining 32% of the total variation. LP 1 was characterized by breakfast consumption, high consumption of fruits and berries, vegetables and nuts and seeds, and low consumption of salty snacks and soft drinks with sugar, while LP 2 was characterized by high consumption of salty and sweet snacks, soft drinks with sugar and juice with sugar and sedentary behavior. After adjusting for various confounders, LP 2 was positively associated with the existence of prediabetes (odds ratio = 1.02, 95% CI 1.01-1.04), while LP 1 was not significantly associated with prediabetes. Understanding LPs would provide necessary evidence for planning intervention and education strategies for prediabetes and T2D.
Keyphrases
- type diabetes
- blood glucose
- inflammatory response
- cardiovascular disease
- cross sectional
- anti inflammatory
- metabolic syndrome
- randomized controlled trial
- healthcare
- risk factors
- physical activity
- weight loss
- insulin resistance
- electronic health record
- adipose tissue
- heavy metals
- artificial intelligence
- deep learning
- human health