Association of Daytime Napping with chronic diseases among Tibetan people in China: a cross-sectional study

Association between sleep patterns and galectin-3 in a Chinese community population

BACKGROUND

Irregular sleep patterns have been associated with inflammation. Galectin-3, a novel biomarker, plays an important role in inflammation. We investigated the relationship between sleep patterns and galectin-3 in a Chinese population.

METHODS

A total of 1,058 participants from the Shenzhen-Hong Kong United Network on Cardiovascular Disease study were included in the analysis. Age and sex-adjusted linear regression models were employed to investigate the relationship between galectin-3 level and traditional metabolic biomarkers. Logistic regression models were used to estimate the association among sleep disturbance, nighttime sleep duration, and daytime napping duration and elevated galectin-3, with elevated galectin-3 defined as galectin-3 level > 65.1 ng/ml.

RESULTS

Of study participants, the mean age was 45.3 years and 54.3% were women. Waist circumference, natural logarithm (ln)-transformed triglyceride, and ln-transformed high sensitivity C-reactive protein were positively associated with galectin-3 level (age and sex-adjusted standardized β [95% confidence interval (CI)], 0.12 [0.04, 0.21], 0.11 [0.05, 0.17], and 0.08 [0.02, 0.14], respectively). Sleep disturbance was associated with elevated galectin-3 (odds ratio [95% CI], 1.68 [1.05, 2.68], compared to those without sleep disturbance) after adjusting for traditional metabolic biomarkers. No interaction was observed between galectin-3 and age, sex, obesity, hypertension, and diabetes on sleep disturbance. No association was found between nighttime sleep duration or daytime napping duration and elevated galectin-3.

CONCLUSIONS

Our study provides evidence of a significant association between sleep disturbance and elevated galectin-3 level, independent of traditional metabolic biomarkers. Screening and interventions on galectin-3 could assist in preventing sleep disturbance-induced inflammatory disease.

Association between napping and type 2 diabetes mellitus

As the incidence of type 2 diabetes mellitus (T2DM) is increasing rapidly and its consequences are severe, effective intervention and prevention, including sleep-related interventions, are urgently needed. As a component of sleep architecture, naps, alone or in combination with nocturnal sleep, may influence the onset and progression of T2DM. Overall, napping is associated with an increased risk of T2DM in women, especially in postmenopausal White women. Our study showed that napping >30 minutes (min) increased the risk of T2DM by 8-21%. In addition, non-optimal nighttime sleep increases T2DM risk, and this effect combines with the effect of napping. For nondiabetic patients, napping >30 min could increase the risks of high HbA1c levels and impaired fasting glucose (IFG), which would increase the risk of developing T2DM later on. For diabetic patients, prolonged napping may further impair glycemic control and increase the risk of developing diabetic complications (e.g., diabetic nephropathy) in the distant future. The following three mechanisms are suggested as interpretations for the association between napping and T2DM. First, napping >30 min increases the levels of important inflammatory factors, including interleukin 6 and C-reactive protein, elevating the risks of inflammation, associated adiposity and T2DM. Second, the interaction between postmenopausal hormonal changes and napping further increases insulin resistance. Third, prolonged napping may also affect melatonin secretion by interfering with nighttime sleep, leading to circadian rhythm disruption and further increasing the risk of T2DM. This review summarizes the existing evidence on the effect of napping on T2DM and provides detailed information for future T2DM intervention and prevention strategies that address napping.

Relationship between daytime napping with the occurrence and development of diabetes: a systematic review and meta-analysis

OBJECTIVE

To determine the relationship of napping with incident diabetes risk and glycaemic control in people with diabetes.

DESIGN

Systematic review and meta-analysis.

DATA SOURCES

MEDLINE (PubMed), EMBASE, Web of Science and the Cochrane Library were searched for studies published from database inception to 9 May 2023.

ELIGIBILITY CRITERIA

Observational studies reporting the relationship of napping with diabetes or glycaemic control in patients with diabetes in adult populations were included.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently screened the literature, extracted data and assessed the quality of the included studies. The results were reported as ORs and 95% CIs, which were pooled by using fixed and random effects models, and subgroup analyses were performed. The Grading of Recommendations Assessment, Development and Evaluation method was used to assess the quality of the evidence.

RESULTS

Forty studies were included in our review. Habitual napping was associated with an increased diabetes risk (OR 1.20, 95% CI 1.14 to 1.27) and poor glycaemic control in patients with diabetes (OR 2.05, 95% CI 1.55 to 2.73). Nap durations less than 30 min were unrelated to diabetes (OR 1.05, 95% CI 0.97 to 1.14). Nap durations of 30-60 min were associated with diabetes risk (OR 1.09, 95% CI 1.02 to 1.17), but there were differences in the subgroup analysis results. Nap durations of more than 60 min significantly increased the risk of diabetes (OR 1.31, 95% CI 1.20 to 1.44).

CONCLUSIONS

Napping is associated with increased diabetes risk and poor glycaemic control, and future research will need to confirm whether there are sex and regional differences. Nap durations of more than 60 min significantly increases the risk of diabetes, and the relationship between nap duration and glycaemic control in patients with diabetes needs to be further explored in the future.

PROSPERO REGISTRATION NUMBER

CRD42021292103.

Association between napping and 24-hour blood pressure variability among university students: A pilot study

Background

Blood pressure variability (BPV) has been reported to be a predictor of cardiovascular and some cognitive diseases. However, the association between napping and BPV remains unknown. This study aimed to explore the association between napping and BPV.

Materials and methods

A cross-sectional study including 105 university students was conducted. Participants' 24 h ambulatory blood pressure monitoring (24 h ABPM) were measured, and napping behaviors were investigated. BPV were measured by the 24 h ABPM, included standard deviation (SD), coefficient of variation (CV), and average real variability (ARV).

Results

Among the participants, 61.9% reported daytime napping. We found that nap duration was significantly associated with daytime CV of diastolic blood pressure (DBP) (r = 0.250, P = 0.010), nighttime CV of systolic blood pressure (SBP) (r = 0.217, P = 0.026), 24 h WCV of DBP (r = 0.238, P = 0.014), 24 h ARV of SBP (r = 0.246, P = 0.011) and 24 h ARV of DBP (r = 0.291, P = 0.003). Compared with the no napping group, 24 h WCV of DBP, daytime CV of DBP, and daytime SD of DBP were significantly higher in participants with napping duration >60 min. With multiple regression analysis we found that nap duration was an independent predictor for 24 h ARV of SBP (β = 0.859, 95% CI, 0.101-1.616, P = 0.027) and 24 h ARV of DBP (β = 0.674, 95% CI, 0.173-1.175, P = 0.009).

Conclusions

Napping durations are associated with BPV among university students. Especially those with napping durations >60 min had a significantly higher BPV than those non-nappers.

The Association of Midday Napping With Hypertension Among Chinese Adults Older Than 45 Years: Cross-sectional Study

BACKGROUND

Hypertension is one of the main public health issues around worldwide, and midday napping is a popular habit. The association between the two remains to be explored.

OBJECTIVE

The goal of the research was to explore the association of midday napping with hypertension.

METHODS

This study separately selected 11,439, 12,689, and 9464 Chinese respondents aged over 45 years from the China Health and Retirement Longitudinal Study 2011, 2015, and 2018 data sets. Binary logistic regression was used to explore the association of midday napping with hypertension, and the 3-step method was used to test the mediation effect of BMI.

RESULTS

Among all respondents, the prevalence rates of hypertension were 24.6% (2818/11439) in 2011, 21.1% (2683/12689) in 2015, and 22.1% (2092/9464) in 2018. Midday napping was positively correlated with hypertension. In 2011 and 2015, napping 60 to 90 minutes had the greatest odds ratios [OR] (OR₂₀₁₁ 1.705, OR₂₀₁₅ 1.494). In 2018, the biggest OR came from the group napping 30 to 60 minutes (OR 1.223), and ORs of different napping durations decreased from 2011 to 2018. In addition, BMI had a partial mediation effect in 2015 and 2018.

CONCLUSIONS

Midday napping is a potential risk factor for hypertension with BMI acting as a mediator. To prevent hypertension, avoiding prolonged duration of midday napping and taking action to maintain a normal BMI level are recommended.

Association of Sleep Duration and Self-Reported Insomnia Symptoms with Metabolic Syndrome Components among Middle-Aged and Older Adults

The study aimed to explore the association between sleep duration, insomnia symptoms and the components of metabolic syndrome (MetS) among middle-aged and older adults. A cross-sectional study was conducted in five community health centers and physical check-up centers of two comprehensive hospitals in Guangdong. We recruited 1252 participants (658 female), aged 40-96 years and with a body mass index (BMI) of 16.26-35.56 kg/m². MetS was assessed based on the guidelines of the International Diabetes Federation. Self-reported sleep duration was evaluated by a simplified questionnaire. Compared with the participants who slept 6-8 h/day, those who slept shorter (<6 h/day) or longer (>8 h/day) periods of time with or without insomnia symptoms had significantly increased odds ratios (ORs) of high blood pressure (except for the SBP in model 2) and high triglycerides (TGs) in all models (p < 0.05), whereas the participants who slept longer (>8 h/day) or shorter (<6 h/day) periods of time with insomnia symptoms had significantly increased ORs of low HDL-C in all models (p < 0.05), but non-significant in those without insomnia symptoms. BMI is significant for insomnia symptoms but not for sleep duration. Our study indicated that the association of sleep duration with MetS components was partially associated with insomnia symptoms. These findings have significant implications to explore the appropriate sleep duration for adults.

Daytime napping and cardiovascular risk factors, cardiovascular disease, and mortality: A systematic review

Associations between night sleep duration and cardiovascular risk factors in adults have been well documented. However, the associations for daytime napping remain unclear. In this review, six databases were searched for eligible publications to April 8, 2022. A total of 11 articles were identified for umbrella review on the association of daytime napping with diabetes, metabolic syndrome (MetS), cardiovascular disease (CVD), and mortality in adults, 97 for systematic review on the association with CVD and several CVD risk factors. Our umbrella review showed that the associations of daytime napping with diabetes, MetS, CVD, and mortality in most meta-analyses were mainly supported by weak or suggestive evidence. Our systematic review showed that long daytime napping (≥1 h/d) was associated with higher odds of several CVD risk factors, CVD, and mortality, but no significant association was found between short daytime napping and most of the abovementioned outcomes. Our dose-response meta-analyses showed that daytime napping <30 min/d was not significantly associated with higher odds of most CVD risk factors and CVD among young and middle-aged adults. However, among older adults aged >60 years, we observed significant dose-response associations of daytime napping with higher odds of diabetes, dyslipidemia, MetS, and mortality starting from 0 min/d.