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1.
J Diabetes ; 16(5): e13550, 2024 May.
Article in English | MEDLINE | ID: mdl-38708436

ABSTRACT

BACKGROUND: We aimed to identify clusters of health behaviors and study their associations with cardiometabolic risk factors in adults at high risk for type 2 diabetes in India. METHODS: Baseline data from the Kerala Diabetes Prevention Program (n = 1000; age 30-60 years) were used for this study. Information on physical activity (PA), sedentary behavior, fruit and vegetable intake, sleep, and alcohol and tobacco use was collected using questionnaires. Blood pressure, waist circumference, 2-h plasma glucose, high-density lipoprotein and low-density lipoprotein cholesterol, and triglycerides were measured using standardized protocols. Latent class analysis was used to identify clusters of health behaviors, and multilevel mixed-effects linear regression was employed to examine their associations with cardiometabolic risk factors. RESULTS: Two classes were identified, with 87.4% of participants in class 1 and 12.6% in class 2. Participants in both classes had a high probability of not engaging in leisure-time PA (0.80 for class 1; 0.73 for class 2) and consuming <5 servings of fruit and vegetables per day (0.70 for class 1; 0.63 for class 2). However, participants in class 1 had a lower probability of sitting for >=3 h per day (0.26 vs 0.42), tobacco use (0.10 vs 0.75), and alcohol use (0.08 vs 1.00) compared to those in class 2. Class 1 had a significantly lower mean systolic blood pressure (ß = -3.70 mm Hg, 95% confidence interval [CI] -7.05, -0.36), diastolic blood pressure (ß = -2.45 mm Hg, 95% CI -4.74, -0.16), and triglycerides (ß = -0.81 mg/dL, 95% CI -0.75, -0.89). CONCLUSION: Implementing intervention strategies, tailored to cluster-specific health behaviors, is required for the effective prevention of cardiometabolic disorders among high-risk adults for type 2 diabetes.


Subject(s)
Cardiometabolic Risk Factors , Diabetes Mellitus, Type 2 , Health Behavior , Latent Class Analysis , Humans , Diabetes Mellitus, Type 2/epidemiology , Diabetes Mellitus, Type 2/prevention & control , Male , Female , India/epidemiology , Middle Aged , Adult , Exercise , Sedentary Behavior , Risk Factors , Cluster Analysis , Blood Pressure , Cardiovascular Diseases/epidemiology , Cardiovascular Diseases/prevention & control , Cardiovascular Diseases/etiology
2.
BMC Public Health ; 24(1): 1080, 2024 Apr 18.
Article in English | MEDLINE | ID: mdl-38637757

ABSTRACT

Movement-related behaviors (physical activity [PA], sedentary behavior [SB], and sleep) and diet interact with each other and play important roles in health indicators in youth. This systematic review aimed to investigate how PA, SB, sleep, and diet cluster in youth by biological sex; and to examine which cluster are associated with health indicators. This study was registered in PROSPERO (number: CRD42018094826). Five electronic databases were assessed. Eligibility criteria allowed studies that included youth (aged 19 years and younger), and only the four behaviors {PA, SB, sleep, and diet (ultra-processed foods [UPF]; fruits and vegetables [FV])} analyzed by applying data-based cluster procedures. From 12,719 articles screened; 23 were included. Of these, four investigated children, and ten identified clusters by biological sex. Sixty-six mixed cluster were identified including, 34 in mixed-sex samples, 10 in boys and 11 in girls. The most frequent clusters in mixed-sex samples were "High SB UPF Low Sleep", "Low PA High SB Satisfactory Sleep", and "High PA". The main difference in profiles according to sex was that girls' clusters were characterized by high sleep duration, whereas boys' clusters by high PA. There were a few associations found between cluster types and health indicators, highlighting that youth assigned to cluster types with low PA exhibited higher adiposity. In conclusion, the youth presented a range of clusters of behaviors, typically exhibiting at least one unhealthy behavior. Similar patterns were observed in both sexes with the biggest difference in time of sleep for girls and PA for boys. These findings underscore the importance of intervention strategies targeting multiple behaviors simultaneously to enhance health risk profiles and indicators in children and adolescents.


Subject(s)
Diet , Exercise , Obesity , Sedentary Behavior , Adolescent , Child , Female , Humans , Male , Health Behavior , Motor Activity , Sleep
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