Gender and age differences in the association between sleep characteristics and fasting glucose levels in Chinese adults

Diabetes in China part 1: epidemiology and risk factors

The prevalence of diabetes in China is rapidly increasing. China now has the largest number of people living with diabetes worldwide, accounting for approximately one-quarter of the global diabetes population. Since the late 1970s, China has experienced profound changes and rapid economic growth, leading to shifts in lifestyle. Changing dietary patterns, reduced physical activity, and stress have contributed to the growing prevalence of overweight and obesity, which are important determinants potentiating the link between insulin resistance and diabetes. Social and environmental factors, such as education, air pollution, and exposure to endocrine-disrupting chemicals, have also contributed to the growing diabetes epidemic in China. The country has one of the fastest ageing populations in the world, which forecasts continued increases in the prevalence of diabetes and its complications. This Review provides an overview of the ongoing diabetes epidemic and risk factors, providing evidence to support effective implementation of public health interventions to slow and prevent the diabetes epidemic in China.

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.

Sleep quality in women with diabetes in pregnancy: a single-center retrospective study

PURPOSE

Sleep quality is an important indicator of individual quality of life, which not only affects people's mental health but is also closely related to the occurrence of many diseases. Sleep disorders associated with diabetes in pregnancy can greatly endanger the health of both mothers and babies, and their hazards are strongly associated with blood glucose levels. This study explored the quality of sleep and sleep disorders in pregnant women with diabetes.

METHODS

From June 2020 to July 2021, a total of 693 patients diagnosed with diabetes during pregnancy in Gansu Provincial Maternal and Child Health Hospital were used as the experiment group, including 626 patients with gestational diabetes mellitus (GDM) and 67 patients with pregestational diabetes mellitus (PGDM). At the same time, 709 women not having diabetes were randomly selected as the control group. To obtain the general situation of the participants, the participants were surveyed using the Pittsburgh Sleep Quality Index (PSQI) and the STOP-BANG (S, Snoring; T, Tiredness; O, Observed apnea; P, high blood Pressure; B, Body mass index > 35 kg/ m2; A, Age > 50 years; N, Neck circumference > 40 cm; G, male Gender) questionnaire. The differences in sleep quality and obstructive sleep apnea-hypopnea syndrome (OSAHS) were analyzed between the experiment group and the control group by using chi-square and t-test, and the clinical features and related factors of sleep disorder were analyzed.

RESULTS

Compared with the control group, the age, pre-pregnancy weight, body mass index (BMI), and neck circumference were larger in the experimental group (P < 0.05). The experimental group had higher PSQI scores for sleep quality, time to fall asleep score, sleep duration, sleep efficiency, sleep disorder, and daytime dysfunction than the control group (all P < 0.001). Specific analysis of the clinical features of sleep disorders indicated that the experimental group scored higher than the control group (P < 0.05). The analysis of the types of daytime dysfunction showed that the experiment group scored higher in terms of frequently feeling sleepy and lack of energy to do things than the control group (P < 0.05). Analysis of STOP-BANG scores indicated that the proportion of patients with GDM or PGDM having fatigue, hypertension, BMI > 35 kg/m2, and neck circumference > 40 cm was higher than that in the control group (P < 0.05). According to regression analysis, sleep quality of patients with GDM was significantly impacted by the increases in age (OR: 1.243, CI:1.197-1.290), neck circumference (OR: 1.350, CI: 1.234-1.476), PSQI score (OR: 2.124, CI:1.656-2.724), and sleep efficiency score (OR: 3.083, CI:1.534-6.195), whereas that of patients with PGDM was impacted by age (OR: 1.191, CI:1.086-1.305), neck circumference (OR: 1.981, CI: 1.469-2.673), and PSQI score (OR: 7.835, CI: 2.383-25.761).

CONCLUSIONS

Pregnant women with diabetes had poorer sleep quality and a higher risk of developing OSAHS than those without diabetes. There may be some link between sleep quality and the onset of diabetic.

Obesity mediates the opposite association of education and diabetes in Chinese men and women: Results from the REACTION study

BACKGROUND

Evidence regarding the impact of education on diabetes risk is scarce in developing countries. We aimed to explore the association between education and diabetes within a large population in China and to identify the possible mediators between them.

METHODS

Information on educational level and lifestyle factors was collected through questionnaires. Diabetes was diagnosed from self-report and biochemical measurements. A structural equation model was constructed to quantify the mediation effect of each mediator.

RESULTS

Compared with their least educated counterparts, men with college education had a higher risk of diabetes (odds ratio [OR] 1.19; 95% confidence interval [CI], 1.12-1.27), while college-educated women were less likely to have diabetes (OR 0.77; 95% CI, 0.73-0.82). Obesity was the strongest mediator in both genders (proportion of mediation: 11.6% in men and 23.9% in women), and its association with education was positive in men (β[SE] 0.0387 [0.0037]) and negative in women (β[SE] -0.0824 [0.0030]). Taken together, all behavioral factors explained 12.4% of the excess risk of diabetes in men and 33.3% in women.

CONCLUSIONS

In a general Chinese population, the association between education level and diabetes was positive in men but negative in women. Obesity was the major mediator underlying the education disparities of diabetes risk, with a stronger mediation effect among women.

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.

Associations between night-time sleep duration and fasting glucose and ratio of triglyceride to high-density lipoprotein cholesterol among adults free of type 2 diabetes or without diagnosed type 2 diabetes: a multicentre, cross-sectional study in China

OBJECTIVES

We aimed to assess the associations between night-time sleep duration and fasting glucose (FG), triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio and body mass index (BMI) among adults free of type 2 diabetes (T2D) or without diagnosed T2D.

DESIGN

Cross-sectional study.

SETTING

Medical examination centres at six hospitals in Beijing-Tianjin-Hebei region, China.

PARTICIPANTS

Participants were recruited via multistage, stratified cluster sampling. We included adults free of T2D or without diagnosed T2D who attended for physical examination and completed the validated questionnaire. 32 497 participants were included in the study, of whom 52.50% were men.

PRIMARY AND SECONDARY OUTCOME MEASURES

FG, TG, HDL-C, height and weight were measured.

RESULTS

Overall, 12.80% and 9.67% reported night sleep duration <7 hours and ≥9 hours, respectively; 6.91% had elevated FG and 3.57% had undiagnosed T2D. Sleep duration had an independent, U-shaped associated with FG (β₁ (linear term)=-0.111, p=0.047; β₂ (quadratic term)=0.008, p=0.026) with 6.9 hours of sleep associated with the lowest FG and a negative association with BMI (β=-0.154, p<0.001). BMI mediated a U-shaped association of sleep duration with TG/HDL-C (β₁=-0.040, p=0.017; β₂=0.003, p=0.023).

CONCLUSIONS

Both short and long night-time sleep was associated with elevated FG, and short sleep duration was associated with increased BMI. BMI mediated a U-shaped association between sleep duration and TG/HDL-C.

Sex Differences in Depression and Sleep Disturbance as Inter-Related Risk Factors of Diabetes

Objectives

Previous studies identified depression and sleep disturbance as risk factors for diabetes. Sleep disturbance and depression are known to be inter-related. Further, women relative to men are more prone to depression. Here, we investigated how depression and sleep disturbance may jointly influence the risk of diabetes and the effects of sex on these influences.

Methods

Using the data of 21,229 participants from the 2018 National Health Interview Survey, we performed multivariate logistic regression with diabetes diagnosis as the dependent variable, sex, self-reported frequency of weekly depression and nightly sleep duration, and their interactions with sex as independent variables, and age, race, income, body mass index and physical activity as covariates. We employed Bayesian and Akaike Information criteria to identify the best model, evaluated the accuracy of the model in predicting diabetes using receiver operating characteristic analysis, and computed the odds ratios of these risk factors.

Results

In the two best models, depression frequency and sleep hours interact with sex in determining the diagnosis of diabetes, with higher depression frequency and nightly duration of sleep longer or shorter than 7 to 8 hours associated with higher likelihood of diabetes. The two models both predicted diabetes at an accuracy (area under the receiver operating characteristic curve) of 0.86. Further, these effects were stronger in men than in women at each depression and sleep level.

Conclusions

Depression and sleep inter-relatedly rather than independently contributes to diabetes. Depression and sleep hours associate with diabetes more significantly in men than in women. The current findings indicate a sex-dependent relationship between depression, sleep disturbance and diabetes risk and add to a growing body of evidence linking mental and physical health.

Association Between Nocturnal Sleep Duration and Obesity Indicators Among People with Type 2 Diabetes: A Cross-Sectional Study in Ningbo, China

AIM

The study aimed to investigate the association between the nocturnal sleep duration and five obesity indicators, namely, visceral fat area (VFA), subcutaneous fat area (SFA), bodyweight, body mass index (BMI) and waist circumference (WC), among people with type 2 diabetes mellitus (T2DM) in Ningbo, China.

METHODS

A cross-sectional study was conducted using the National Metabolic Management Centre (MMC) - Ningbo First Hospital data from 1st March 2018 to 28th February 2021. Adults with T2DM were included in the study. Simple and multiple (adjusted for sociodemographic and lifestyle factors and health conditions) linear regression analyses were performed to identify the associations.

RESULTS

In terms of VFA, SFA, bodyweight, BMI and WC, the eligibility criteria were satisfied by 2771, 2771, 2863, 2863 and 2862 patients, respectively. In the unadjusted model, the shorter nocturnal sleep duration was associated with higher VFA, SFA, bodyweight, BMI and WC. In other words, an hour increase in the nocturnal sleep duration was associated with a decrease of 2.07 cm2 in VFA (regression coefficient = -2.07; 95% CI = -3.25 to -0.88), 2.67 cm2 in SFA (-2.67; -4.55 to -0.78); 0.82 kg in bodyweight (-0.82; -1.2 to -0.43), 0.2 kg/m2 in BMI (-0.2; -0.31 to -0.09) and 0.46 cm in WC (-0.46; -0.76 to -0.16). In the adjusted models, the shorter nocturnal sleep duration was still found to be associated with higher VFA, SFA, bodyweight, BMI and WC (except SFA and WC in models where we further adjusted for health conditions).

CONCLUSION

The nocturnal sleep duration among people with T2DM in Ningbo, China is negatively associated with visceral and general obesity indicators (VFA, bodyweight and BMI). Thus, there is a need for appropriate interventions to address the issue of sleep deprivation.

Association of Sleep Duration, Midday Napping with Atrial Fibrillation in Patients with Hypertension

Objective

This study aimed to assess the associations of sleep duration, midday napping and the risk of atrial fibrillation (AF) in patients with hypertension.

Methods

We conducted a cross-sectional study enrolling 11,524 hypertensive participates from the Chinese Hypertension Registry Study. Information on sleep duration and midday napping were obtained by a self-administered questionnaire. Multivariate logistic regression analyses were performed to estimate odds ratio (OR) and 95% confidence intervals (CIs) for the risk of AF.

Results

Compared with sleeping 6 to ≤8 hours/night, those reporting shorter sleep duration (≤5 hours/night) had a greater risk of AF (OR 1.95; 95% CI 1.28–2.95) in the fully adjusted model, while longer sleep (≥9 hours/night) was not significantly associated with the risk of AF. Compared with nonhabitual nappers, nappers had a higher risk of AF (OR 1.28; 95% CI 1.03–1.60) in the fully adjusted model. Moreover, we observed significant joint effects of sleeping ≤5 hours/night and nap (OR 2.13; 95% CI 1.09–4.14) on the risk of AF after adjusting for confounding factors.

Conclusion

Short sleep duration and midday napping were independently and jointly associated with higher risks of AF in patients with hypertension.

The Interaction Between Self-Reported Sleep Duration and Physical Activity on Peripheral Artery Disease in Chinese Adults: A Cross-Sectional Analysis in the Tianning Cohort Study

Purpose

Sleep duration was associated with large artery atherosclerosis, but its association with atherosclerosis in lower extremity arteries was not well studied. Together with sleep, physical activity constitutes main component of our daily life and influences sleep. Here, we aimed to examine the independent and joint associations of sleep duration and physical activity with peripheral artery disease (PAD) in Chinese adults.

Patients and Methods

In Tianning cohort, night-time sleep duration and physical activity were assessed by the Pittsburgh Sleep Quality Index and the Global Physical Activity Questionnaire, respectively, for 5130 participants (51.0±15.6 years, 58.7% female). PAD was defined as ankle-brachial index (ABI) <0.9. General linear, and logistic regression models were used to assess the associations of sleep duration and physical activity with PAD. The biological interaction between sleep duration and physical activity on PAD was examined using additive model.

Results

Compared to participants sleeping 6-8.9 h, those sleeping ≥9 h had a 0.02 lower ABI (β=-0.02, P=0.007) and 38% higher odds of PAD (OR=1.38, P=0.035). Compared to physically active participants sleeping 6-8.9 h, among ≥9 h group, physically inactive individuals had significantly increased odds of PAD (OR=2.40, P<0.001), whereas physically active individuals did not (OR=1.15, P=0.472). On additive scale, attributable proportion due to interaction (0.40, 95% CI: 0.07, 0.73) indicated a significant interaction between sleep duration and physical activity on PAD.

Conclusion

Being physically active may attenuate the detrimental association between prolonged sleep duration and PAD. Moreover, we found a significant interaction between prolonged sleep duration and physical inactivity in the prevalence of PAD.