Association of sleep quality components and wake time with metabolic syndrome: The Qazvin Metabolic Diseases Study (QMDS), Iran

Role of gender in explaining metabolic syndrome risk factors in an Iranian rural population using structural equation modelling

Many factors can lead to an increase in the prevalence of metabolic syndrome (MetS) in different populations. Using an advanced structural equation model (SEM), this study is aimed to determine the most important risk factors of MetS, as a continuous latent variable, using a large number of males and females. We also aimed to evaluate the interrelations among the associated factors involved in the development of MetS. This study used data derived from the Fasa PERSIAN cohort study, a branch of the PERSIAN cohort study, for participants aged 35 to 70 years with 10,138 males and females. SEM was used to evaluate the direct and indirect effects, as well as gender effects of influencing factors. Results from the SEM showed that in females most changes in MetS are described by waist circumference (WC), followed by hypertension (HP) and triglyceride (TG), while in males most changes in MetS are described by WC, followed by TG then fasting blood glucose (FBG). Results from the SEM confirmed the gender effects of social status on MetS, mediated by sleep and controlled by age, BMI, ethnicity and physical activity. This study also shows that the integration of TG and WC within genders could be useful as a screening criterion for MetS in our study population.

Investigation of the relationship between sleep-related parameters and metabolic syndrome (MetS) among youths in the Southeast of Iran

BACKGROUND AND AIM

There are few studies and inconsistent findings on the role of sleep-related parameters in the development of metabolic syndrome (MetS) among youths. In this study, we aim to investigate the relationship between sleep-related parameters and MetS among youths in a large sample size in Rafsanjan, a region in the southeast of Iran.

METHODS

The current cross-sectional study was performed on 3,006 young adults aged 15-35, who registered for Rafsanjan Youth Cohort Study (RYCS), as part of Rafsanjan Cohort Study (RCS)). In fact, RCS is a branch of the prospective epidemiological research studies in Iran (PERSIAN). In the present study, we included 2,867 youths after excluding some subjects with missing information on MetS components. MetS was diagnosed based on Adult Treatment Panel III (ATP III) criteria. Besides, data on sleep-related parameters were collected by self-report questionnaires.

RESULTS

The overall prevalence of MetS was 7.74% among the participants. In addition, bedtime, wake time, napping, night shift work, and sleep duration per night and day had no association with the higher odds of having MetS. In contrast, long sleep duration at night was associated with the lower odds of high waist circumference (WC) (OR: 0.82,95% CI :0.67-0.99).

CONCLUSION

In the present study, long sleep duration at night was associated with lower odds of central obesity. However, more longitudinal studies with the objective measurement of sleep-related parameters are needed to verify the associations reported in the current study.

Association between Poor Quality of Sleep and Metabolic Syndrome in Ghanaian University Students: A Cross-Sectional Study

Aim. This study aimed to determine the association between quality of sleep and metabolic syndrome (MetS) and physical activity level in young adults at the University of Ghana. Method. In a cross-sectional design, 340 university students, aged between 20-30 years were recruited. Quality of sleep was assessed using the Pittsburgh Sleep Quality index (PSQI) and physical activity with the short form of the International Physical Activity Questionnaire (IPAQ-SF). Poor quality of sleep was defined as a global PSQI score>5 and low physical activity level as those not meeting the criteria for vigorous-moderate physical activity. Anthropometric features and blood pressures were measured, and fasting blood samples were collected from the participants to measure plasma levels of glucose, lipid profile, urea, and creatinine. MetS was defined using the Joint Scientific Statement criteria. Results. In our study population of young adults from Ghana, the prevalence of poor quality of sleep as measured by PSQI was 54.1%, and MetS was 12.4%. MetS was associated with poor quality of sleep in females [ $\text{OR}\left(95\%\text{CI}\right)=2.11$ (1.04–4.25), $p=0.038$ ] and entire study participants [2.18 (1.09–4.37) $p=0.029$ ] in both crude and adjusted models; no association was found in male participants. Low physical activity status was not associated with poor sleep status. Obesity [1.32 (1.02–3.56), $p=0.043$ ], but not overweight [0.99 (0.58–2.34), $p=0.862$ ], was associated with poor quality of sleep. Conclusion. Young adults in a Ghanaian university have a high prevalence of poor quality of sleep and is associated with MetS and obesity. Physical activity status was not associated with poor quality of sleep.

Sleep characteristic profiles and the correlation with spectrum of metabolic syndrome among older adult: a cross-sectional study

Background

Metabolic Syndrome (MetS) is a common health problem among older adults. Previous studies have revealed the relationship between sleep duration as well as global sleep status and MetS.

Objectives

This study aims to examine the association between the specific sleep characteristic and MetS as well as MetS components among community-dwelling old adults.

Methods

This cross-sectional study included 1499 community residents aged ≥ 60 years. Sleep characteristics were assessed using the Pittsburgh Sleep Quality Index (PSQI) and bed/rise time of the residents. Logistic regression analysis and multiple linear regression analysis were used to examine the associations between sleep characteristics and MetS as well as MetS components. A generalized additive model was built to assess the smooth relationship between triglyceride (TG) levels and sleep duration.

Results

Of the 1499 participants, 449 (30.0%) had MetS, and 443 (29.6%) had poor sleep quality. The rise time was found to be associated with MetS (> 6:00 vs. 5:00 ~ 6:00: adjusted OR (95%) = 1.77 (1.17–2.69), P = 0.007). For the MetS components, a U-shaped relationship was first revealed for sleep duration and TG levels (EDF = 1.85, P < 0.001). Furthermore, significant associations also included the associations of subjective sleep quality and daytime dysfunction with hypertension, the associations of sleep efficiency and rise time with hyperglycemia, the associations of rise time with TG levels, and the association of bedtime with waist circumference.

Conclusions

The different sleep characteristics were associated with different MetS components.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-022-03074-8.

Sleep duration and metabolic syndrome: An updated systematic review and meta-analysis

We examined the association between self-reported sleep duration and metabolic syndrome (MetS). Data were collected from 36 cross-sectional and 9 longitudinal studies with a total of 164,799 MetS subjects and 430,895 controls. Odds ratios (ORs) for prevalent MetS and risk ratios (RRs) for incident MetS were calculated through meta-analyses of adjusted data from individual studies. Short sleep duration was significantly associated with increased prevalent MetS (OR = 1.11, 95% CI = 1.05-1.18) and incident MetS (RR = 1.28, 95% CI = 1.07-1.53) in cross-sectional and longitudinal studies, respectively. Furthermore, long sleep duration was significantly associated with increased prevalent MetS in cross-sectional studies (OR = 1.14, 95% CI = 1.05-1.23), but not incident MetS (RR = 1.16, 95% CI = 0.95-1.41) in longitudinal studies. Interestingly, the association between long sleep and prevalent MetS was found in sleep duration defined by 24-h sleep (including naps) rather than nighttime sleep. Our findings suggest 1) a "U-shape" relationship between sleep duration and MetS in cross-sectional studies and 2) association between short sleep duration, but not long sleep duration with incident MetS. Future studies should shed light on the underlying mechanisms related to the association between sleep duration and MetS and examine if normalizing sleep duration reduces MetS risk in the general population.

Occupational Difference in Association of Poor Sleep Quality and Metabolic Syndrome: Differences between Workers and Employees

Background

Regarding insufficient data about interaction of job in association of sleep quality with metabolic syndrome (MS), this study has been designed to evaluate this association in workers and employees.

Methods

This cross-sectional study was conducted on 448 municipal staff (employee group: N = 295; worker group: N = 153) referring for periodic examinations. The relationship between sleep quality and MS and their relevant components was investigated in both groups.

Results

In the worker group, poor sleep quality was independently associated with the risk of MS by 3.04 times (P < 0.01). Among the components of metabolic syndrome, hypertriglyceridemia was associated with a greater number of sleep disorder components. There was no association between metabolic syndrome and sleep quality in the employee group.

Conclusion

Poor sleep quality exerts different effects on metabolic complications in employees and workers.

Smoking cessation, metabolic risk behaviors, and stress management over time in a sample of young adult smokers

Smoking cessation may support changes in metabolic risk behaviors (e.g., high-fat diet, physical inactivity, poor sleep, low fruit and vegetable consumption [FVC]). We examined the association between smoking cessation and metabolic risk behavior profiles, mediated by readiness to change risk behaviors and moderated by stress management. Participants were young adult smokers in a randomized controlled trial of a Facebook smoking cessation intervention. Measures included stage of change for five metabolic risk behaviors: FVC, diet, physical activity, sleep hygiene, and stress management. Moderated mediation was used to examine relationships between smoking cessation at T1 (predictor), readiness to change metabolic risk behaviors at T2 (mediators), stress management at T3 (moderator), and metabolic risk behavior profile at T3 (outcome) over 9 months. T1 smoking abstinence was associated with greater readiness to increase FVC at T2, which predicted lower likelihood of T3 metabolic risk (β = -0.22, 95% confidence interval [CI] [-0.53, -0.03]). This indirect effect was moderated by stress management such that greater readiness to increase FVC at T2 was associated with lower T3 metabolic risk for participants with unmanaged stress (β = -0.90, 95% CI [-1.32, -0.49], p < .001), but not for participants with well-managed stress (β = -.22, 95% CI [-0.48, 0.04], p = .096). Young adults who quit smoking subsequently had lower metabolic risk behaviors. Among participants with unmanaged stress, those who quit smoking had greater readiness to increase FVC and lower likelihood of subsequent metabolic risk. Smoking cessation interventions could aim to teach broadly applicable behavior change skills and build confidence for decreasing metabolic risk.

Protein intake in inhabitants with regular exercise is associated with sleep quality: Results of the Shika study

STUDY OBJECTIVES

Although associations between sleep quality and environmental factors and nutrient intake have been reported, interactions between these factors have not been elucidated in detail. Therefore, this cross-sectional study examined the effects of regular exercise and nutrient intake on sleep quality using the Pittsburgh Sleep Quality Index (PSQI), which is the most frequently used index for sleep evaluation.

METHODS

The participants included 378 individuals aged 40 years or older living in Shika Town, Ishikawa Prefecture. Of these individuals, 185 met the inclusion criteria. The participants completed a self-administered questionnaire assessing lifestyle habits and frequency and duration of exercise, the PSQI, and the brief-type self-administered diet history questionnaire (BDHQ) on nutrient intake.

RESULTS

A two-way analysis of covariance on regular exercise and PSQI scores indicated that protein intake (17.13% of energy) was significantly higher in the regular exercise and PSQI ≤10 groups than in the non-regular exercise or PSQI ≥11 groups (p = 0.002). In a multiple logistic regression analysis with PSQI scores (≤10 and ≥11), protein intake was a significant independent variable in any of the models adjusted for confounding factors such as age, sex, body mass index, current smoker, and current drinker (OR: 1.357, 95% CI: 1.081, 1.704, p = 0.009) in the regular exercise group but not in the non-regular exercise group.Conclusions We identified a positive relationship between sleep quality and protein intake in the regular exercise group. These findings suggest that regular exercise at least twice a week for 30 minutes or longer combined with high protein intake contributes to good sleep quality.

Metabolic syndrome is associated with better quality of sleep in the oldest old: results from the "Mugello Study"

BACKGROUND AND AIMS

Reduced sleep quality is common in advanced age. Poor sleep quality is associated with adverse outcomes, chiefly cardiovascular, in young and middle-aged subjects, possibly because of its association with metabolic syndrome (MetS). However, the correlates of sleep quality in oldest populations are unknown. We evaluated the association of sleep quality with MetS in a cohort of subjects aged 90+.

METHODS AND RESULTS

We analysed data of 343 subjects aged 90+ living in the Mugello area (Tuscany, Italy). Quality of sleep was assessed using the Pittsburgh Sleep Quality Assessment Index (PSQI). Good quality of sleep was defined by a PSQI score < 5. MetS was diagnosed according to the National Cholesterol Education Program's ATP-III criteria; 83 (24%) participants reported good quality of sleep. MetS was diagnosed in 110 (24%) participants. In linear and logistic models, MetS was inversely associated with PSQI score ((B = - 1.04; 95% CI - 2.06 to - .03; P = .044), with increased probability of good sleep quality (OR = 2.52; 95% CI 1.26-5.02; P = .009), and with a PSQI below the median (OR = 2.11; 95% CI 1.11-3.40, P = .022), after adjusting. None of the single components of MetS were associated with PSQI (all P values > .050). However, an increasing number of MetS components was associated with increasing probability of good quality of sleep (P for trend = .002), and of PSQI below the median (P for trend = .007). Generalized Additive Model analysis documented no smoothing function suggestive of nonlinear association between PSQI and MetS.

CONCLUSION

Our results confirm a high prevalence of poor sleep quality in oldest age; however, in these subjects, MetS seems to be associated with better sleep quality. Additional larger, dedicated studies are required to confirm our results, and, if so, to identify the subsystems involved and the potential therapeutic implications of such an association.

Association between sleep quality and metabolic syndrome: A systematic review and meta-analysis

Sleep quality has been suggested to play an important role in development of metabolic syndrome (MetS). However, the results have been inconsistent. A systematic review of observational studies aimed to evaluate the association between sleep quality and MetS. A comprehensive search was conducted in PubMed and EMBASE. The pooled odd ratios (ORs) were calculated using random effects models. The construction of funnel plot was used to explore publication bias, with further application of Egger's test. 22 studies were included. The pooled finding showed that overall sleep quality had a significant positive association with MetS (OR 1.37, 95% CI 1.15-1.64), with substantial heterogeneity (I² = 62.4%, P < 0.1). Similarly, the complaints of sleep, including difficulty in falling sleep (OR 1.18, 95% CI 1.05-1.33), difficulty in maintaining sleep (OR 1.15, 95% CI 1.02-1.30) and sleep inefficiency (OR 1.40, 95% CI 1.04-1.89) were proved to be associated with the risk of MetS. Our results indicated the overall sleep quality as well as sleep complaints have significant positive associations with MetS. Further studies based on a longitudinal design using validated tools that measure both objective and subjective components of sleep quality are needed to explore the causal relationship between sleep quality and MetS.

Multiple poor sleep characteristics and metabolic abnormalities consistent with metabolic syndrome among white, black, and Hispanic/Latina women: modification by menopausal status

BACKGROUND

Poor sleep is a potential risk factor for metabolic syndrome (MetS), and its relationship with MetS may vary by race/ethnicity and menopausal status among women.

METHODS

We used Sister Study enrollment data from 2003 to 2009 to investigate the cross-sectional associations between multiple subjective sleep characteristics and having ≥ 3 prevalent metabolic abnormalities consistent with MetS among white, black, and Hispanic/Latina women. Self-reported sleep characteristics included average sleep duration (short [< 7 h] vs. recommended [7-9 h]), sleep debt (≥ 2-h difference between shortest and longest sleep duration, napping ≥ 3 times/week, and insomnia symptoms (difficulty falling or staying asleep). We used Poisson regression with robust variance to estimate adjusted prevalence ratios (PRs) and 95% confidence intervals (CIs) to compare MetS prevalence between women with poor sleep (e.g., short sleep, sleep debt, frequent napping, or insomnia symptoms [all yes vs. no]) and non-poor sleep within menopausal status categories (premenopausal or postmenopausal). We adjusted for sociodemographic characteristics, mental health, and health behaviors.

RESULTS

Among 38,007 eligible women (13,988 premenopausal, 24,019 postmenopausal), mean age was 55 ± 8.8 years, racial/ethnic composition was 86.63% white, 8.53% black, and 4.84% Hispanic/Latina, and 12% had MetS. Associations between certain poor sleep characteristics [i.e., short sleep (PRpremenopausal = 1.23 [95% CI 1.06-1.42], PRpostmenopausal = 1.09 [1.02-1.16], pshort sleep*menopause = 0.0070) and insomnia symptoms (PRpremenopausal = 1.21 [1.05-1.41], PRpostmenopausal = 1.11 [1.05-1.18], pinsomnia symptoms*menopause = 0.035)] and prevalent MetS were stronger among premenopausal compared to postmenopausal women, but did not vary by race/ethnicity. Associations between concurrent short sleep/insomnia symptoms and MetS were stronger among white and Hispanic/Latina postmenopausal women compared to their black counterparts. Menopausal status and race/ethnicity did not modify positive associations for other poor sleep characteristics.

CONCLUSIONS

Poor sleep was positively associated with MetS prevalence. Associations between individual poor sleep characteristics (i.e., short sleep, insomnia symptoms) were stronger among premenopausal compared to postmenopausal women but did not vary by race/ethnicity.