Dataset Information

Gender differences in the association between sleep duration and body mass index, percentage of body fat and visceral fat area among chinese adults: a cross-sectional study.

ABSTRACT:

Background

The relationship between sleep duration and anthropometric indices are still unclear. This study aimed to explore the association between sleep duration and body mass index (BMI), percentage of body fat (PBF) and visceral fat area (VFA) among Chinese adults, further to explore gender difference in it.

Methods

We analyzed part of the baseline data of a cohort study among adult attendees at two health-screening centers in China. Sleep duration was self-reported and categorized into short (< 7 h/day), optimal (7-9 h/day) and long sleep (≥ 9 h/day). BMI, PBF and VFA were assessed by bioelectric impedance analysis. Demographic characteristics, chronic diseases and medication history, physical activity, smoking and alcohol drinking behaviors were measured by an investigator-administrated questionnaire.

Results

A total of 9059 adult participants (63.08% were females) were included in the analysis. The participants aged from 19 to 91 years with the mean age of 45.0 ± 14.6 years. Short sleep was independently associated with elevated odds of general obesity (defined using BMI) and visceral obesity (defined using VFA) among the total study population, and gender differences were observed in these associations. Among women, short sleep was associated with 62% increased odds of general obesity (OR = 1.62, 95% CI: 1.24-2.12) and 22% increased odds of visceral obesity (OR = 1.22, 95% CI: 1.02-1.45). Among men, long sleep duration was associated with 21% decreased odds of visceral obesity (OR = 0.79, 95% CI: 0.64-0.99). No association was observed between sleep duration and PBF in both sexes.

Conclusions

Sleep duration was associated with increased odds of general and visceral obesity, and this association differed between men and women. No association was observed between sleep duration and PBF among either males or females.

SUBMITTER: Fan Y

PROVIDER: S-EPMC8709998 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundAccurate obesity classification is important so that appropriate intervention can be instituted to modify metabolic risk factors. Commonly utilized body mass index (BMI) and percentage body fat (PBF) are influenced by lean mass whereas fat mass index (FMI) measures only body fat. This study compares the prevalence of obesity and metabolic risk factors with FMI, BMI and PBF using DXA (dual-energy x-ray absorptiometry).Methods489 women randomly recruited from the electoral roll were stratified into 4 age groups; 40-49, 50-59, 60-69 and 70-79 years from 2000 to 2001. Clinical data and DXA body composition were obtained. Statistical analyses were performed using Medcalc v15 (Ostend, Belgium) with significance level at p = 0.05 (two-tailed).ResultsThere was higher prevalence of obesity using PBF compared to BMI and FMI (p<0.001). This difference was greater from age 50-59 (p<0.05) which may be explained by age-related lean mass loss. PBF over-classified obesity in over 35% of normal and 95% of overweight categories compared to FMI and BMI. BMI has a sensitivity of 78.9% and specificity of 98.3% for obesity using FMI as the standard. BMI under-classified obesity in the overweight category by 14.9% compared to FMI. There was no difference in diabetes, dyslipidemia, hypertension and metabolic syndrome prevalence within the BMI-obesity and FMI-obesity categories (p>0.05).ConclusionPBF classified more obesity than BMI and FMI because of its low pre-determined threshold. The greater difference with PBF compared to BMI and FMI from the 50-59 decade onwards can be attributed to age-related lean mass loss. BMI had the lowest sensitivity for obesity diagnosis. BMI under-classified obesity in the overweight category compared to FMI due to its inability to differentiate lean mass. However, there was no significant difference in the prevalence of metabolic risk factors between BMI and FMI-obesity categories indicating that fat location may influence metabolic dysregulation.

Project description:BackgroundHypertension is a major cause of death and disability worldwide. Enhancing health literacy (HL) may help to alleviate the risk of hypertension and its burden. However, evidence on the association between HL and hypertension and potential mechanisms remain to be explored.ObjectivesThis study examined the association between HL and hypertension; and explored whether body mass index (BMI), body fat percentage (PBF), and visceral fat (VF) were mediators of this association in people who resided in rural and suburban areas in Vietnam.MethodsA cross-sectional survey was conducted from 1st July to 31st December 2019, involving 1655 residents and exploring participants' sociodemographic characteristics, HL, health-related behaviors, comorbidities, body composition, and blood pressure (BP). People with systolic BP ≥ 140 mmHg or diastolic BP ≥ 90 mmHg or using antihypertensive medication were classified as having hypertension. Multiple logistic regression and mediation analyses were used to explore associations.ResultsThe hypertension prevalence was 41.9% (694/1,655). In adjusted models, a higher HL score was associated with a lower hypertension likelihood (OR = 0.96; 95%CI = 0.95-0.97; p < 0.001). Factors associated with a higher odd of hypertension were overweight/obese (OR = 1.69; 95%CI = 1.24-2.29; p = 0.001), high PBF (OR = 2.35; 95%CI = 1.85-2.99; p < 0.001), and high VF (OR = 2.27; 95%CI = 1.63-3.16; p < 0.001). Notably, PBF significantly mediated the association between HL and hypertension (indirect effect, OR = 0.99; 95%CI = 0.98-0.99; p = 0.009; percent mediated = 8.56%). The mediating roles of BMI and VF were not found.ConclusionThe prevalence of hypertension was relatively high. People with better HL were less likely to have hypertension. The association between HL and hypertension was partially explained by PBF. Strategic approaches are required to improve people's HL and body fat which further help to manage hypertension in rural and suburban areas.

Project description:BackgroundThe conventional measurement of obesity utilises the body mass index (BMI) criterion. Although there are benefits to this method, there is concern that not all individuals at risk of obesity-associated medical conditions are being identified. Whole-body fat percentage (%FM), and specifically visceral adipose tissue (VAT) mass, are correlated with and potentially implicated in disease trajectories, but are not fully accounted for through BMI evaluation. The aims of this study were (a) to compare five anthropometric predictors of %FM and VAT mass, and (b) to explore new cut-points for the best of these predictors to improve the characterisation of obesity.MethodsBMI, waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR) and waist/height0.5 (WHT.5R) were measured and calculated for 81 adults (40 women, 41 men; mean (SD) age: 38.4 (17.5) years; 94% Caucasian). Total body dual energy X-ray absorptiometry with Corescan (GE Lunar iDXA, Encore version 15.0) was also performed to quantify %FM and VAT mass. Linear regression analysis, stratified by sex, was applied to predict both %FM and VAT mass for each anthropometric variable. Within each sex, we used information theoretic methods (Akaike Information Criterion; AIC) to compare models. For the best anthropometric predictor, we derived tentative cut-points for classifying individuals as obese (>25% FM for men or >35% FM for women, or > highest tertile for VAT mass).ResultsThe best predictor of both %FM and VAT mass in men and women was WHtR. Derived cut-points for predicting whole body obesity were 0.53 in men and 0.54 in women. The cut-point for predicting visceral obesity was 0.59 in both sexes.ConclusionsIn the absence of more objective measures of central obesity and adiposity, WHtR is a suitable proxy measure in both women and men. The proposed DXA-%FM and VAT mass cut-offs require validation in larger studies, but offer potential for improvement of obesity characterisation and the identification of individuals who would most benefit from therapeutic intervention.

Project description:Bioelectrical impedance analysis (BIA)-derived indexes [e.g., fat (FMI) and fat-free mass indexes (FFMI), visceral fat level (VFL)] are used to characterize obesity as a cardiovascular risk factor (CRF). The BIA-derived index that better predicts arterial variability is still discussed.AimsTo determine: (1) the association of classical [weight, height, body mass index (BMI), basal metabolic rate (BMR)] and BIA-derived indexes, with arterial properties deviations from expected values (arterial z-scores); (2) maximum arterial variations attributable to BIA-derived indexes; (3) whether the composition of total body, trunk and/or limbs is most closely associated with arterial variations.MethodsHemodynamic, structural, and functional parameters of different histological types of arteries were assessed (n = 538, 7-85 years). Classical and BIA-derived indexes [fat mass and percentage, FMI, VFL, muscle mass percentage (PMM), FFMI, and percentage] were measured (mono- and multi-segmental devices). Arterial z-scores were obtained using age-related equations derived from individuals not-exposed to CRFs (n = 1,688).ResultsFirst, regardless of the classical index considered, the associations with the arterial properties showed a specific hierarchy order: diameters and local stiffness > aortic and brachial blood pressure (BP) > regional stiffness. Second, all the associations of FMI and FFMI with z-scores were positive. Third, FFMI exceeded the association obtained with BMI and BMR, considering structural z-scores. In contrast, FMI did not exceed the association with z-scores achieved by BMI and BMR. Fourth, regardless of CRFs and classical indexes, arterial z-scores would be mainly explained by FFMI, VFL, and PMM. Fifth, regardless of the body-segment considered, the levels of association between FMI and z-scores did not exceed those found for classic and FFMI. Total fat mass and trunk indexes showed a greater strength of association with z-scores than the FMI of limbs. Sixth, compared to lower limb FFMI indexes, total and upper limbs FFMI showed higher levels of association with z-scores.ConclusionsFFMI (but not FMI) exceeded the strength of association seen between BMI or BMR and structural z-scores. Regardless of the body segment analyzed, the associations between FMI and z-scores did not exceed those found with classic and FFMI. Arterial z-scores could be independently explained by FFMI, VFL, and PMM.

Project description:BackgroundAdolescents who receive an adequate amount of sleep benefit from a positive health status. Previous studies have documented several health consequences connected with obesity as well as short sleep duration among adolescents. Poor sleep quality with obesity and uncontrolled diet can lead to chronic diseases in the future. This study aimed to examine the link between eating habits, sleep duration, and body mass index (BMI) among King Saud University (KSU) students.MethodsThe study was cross-sectional and conducted from February to May 2021 on 311 recruited students (male and female) of KSU premises. Pittsburgh Sleep Quality Index questionnaire was used to describe sleep duration linked with a dietary pattern that included fruit and vegetable intake. The questionnaire consists of two sections of 15 and 10 questions each. The questionnaire was created using the Google Forms tool and distributed through social media platforms like Twitter and WhatsApp. The obtained data was transferred into excel to perform the statistical analysis.ResultsThe mean total of students who participated in this study was 21.45 ± 23.11. Female students (72.3%) were actively involved in this study. About 30.2% of students were found to be overweight and obese. Around 67.8% of students had insufficient sleep, 32.2% had adequate sleep, and over 70% of students fell asleep within 30 min of going to bed. A total of 71.7% of students showed good sleep quality, whereas 28.3% reported poor sleep quality. BMI was categorized into four groups: 17.7% of individuals were underweight, 52.1% were of normal weight threshold, 20.6% were overweight, and 9.6% were obese. On a regular basis, 12.5% of students consume vegetables and 6.4% fruits daily. The results of this study show that only 8% of students eat breakfast, whereas 62.1% eat lunch, and 29.9% eat dinner.ConclusionThis study concludes that short sleep duration was associated with obesity among KSU students. This association was also found between sleep duration and dietary factors, specifically in the consumption of fruits and vegetables in terms of eating behaviour.