Guiqiu Chang

Interaction of sleep quality and sleep duration on impaired fasting glucose: a population-based cross-sectional survey in China

Objectives To explore the interactions of sleep quality and sleep duration and their effects on impaired fasting glucose (IFG) in Chinese adults. Design Cross-sectional survey. Setting Community-based investigation in Xuzhou, China. Participants 15 145 Chinese men and women aged 18–75 years old who fulfilled the inclusion criteria. Primary and secondary outcome measures The Pittsburgh Sleep Quality Index was used to produce sleep quality categories of good, common and poor. Fasting blood glucose levels were assessed for IFG. Sleep duration was measured by average hours of sleep per night, with categories of <6, 6–8 and >8 h. The products of sleep and family history of diabetes, obesity and age were added to the logistic regression model to evaluate the addictive interaction and relative excess risk of interaction (RERI) on IFG. The attributable proportion (AP) of the interaction and the synergy index (S) were applied to evaluate the additive interaction of two factors. Bootstrap measures were used to calculate 95% CI of RERI, AP and S. Results The prevalence of IFG was greatest in those with poor sleep quality and short sleep duration (OR 6.37, 95% CI 4.66 to 8.67; p<0.001) compared with those who had good sleep quality and 6–8 h sleep duration, after adjusting for confounders. After adjusting for potential confounders RERI, AP and S values (and their 95% CI) were 1.69 (0.31 to 3.76), 0.42 (0.15 to 0.61) and 2.85 (2.14 to 3.92), respectively, for the interaction between poor sleep quality and short sleep duration, and 0.78 (0.12 to 1.43), 0.61 (0.26 to 0.87) and −65 (−0.94 to −0.27) for the interaction between good sleep quality and long sleep duration. Conclusions The results suggest that there are additive interactions between poor sleep quality and short sleep duration.

Association of sleep quality and quality of life in type 2 diabetes mellitus: A cross-sectional study in China

OBJECTIVE The aim of this study is to investigate sleep quality and quality of life, and to assess the relationship between sleep quality and quality of life in Chinese patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS 944 patients with T2DM were enrolled in our study. General characteristics and laboratory testing such as glycosylated hemoglobin A1c (HbA1c) were measured. Each patient completed a Chinese version of the Pittsburgh sleep quality index (PSQI) and the diabetes specificity quality of life scale (DSQL) questionnaires. A PSQI global score >7 was defined as poor sleep quality. A global DSQL score <40 was defined as a good quality of life. Multiple logistic regression analysis was used to examine the relationships between PSQI and DSQL. RESULTS Poor quality of life in participants was associated with a longer duration of diabetes, a greater number of diabetes complications, no alcohol drinking, poor glycemic control and having depression and anxiety (all P<0.001). Of the participants, 33.6% of them were poor sleepers according to their PSQI. Poor sleepers had significantly lower DSQL (P<001). After adjustment for confounders, poor sleep quality was positively associated with a lower health-related quality of life (OR: 3.67, 95% CI: 1.30-10.33, P<0.001). CONCLUSIONS Our results suggest that poor sleep is prevalent in T2DM and inversely associated with quality of life. It is necessary for primary health-care workers to include sleep related knowledge in diabetes self-management programs to improve sleep quality in diabetes patients.

Effects of sleep duration and sleep quality on prevalence of type 2 diabetes mellitus: A 5-year follow-up study in China.

OBJECTIVE To explore the interactions of sleep quality and sleep duration on the development of type 2 diabetes mellitus (DM2) in Chinese adults. RESEARCH DESIGN AND METHODS We randomly selected 11,842 Chinese subjects from the Xuzhou community of China and obtained self-reported quality and duration of sleep by questionnaire. DM2 was assessed by fasting blood glucose. Sleep quality was categorized as good, common, or poor. Sleep duration was measured by average hours of sleep per night. We evaluated interaction, relative excess risk of interaction (RERI), the attributable proportion (AP), and the synergy index (S) using a logistic regression model. RESULTS The relative risk for the development of DM2 was higher in subjects with short sleep duration (1.67 [1.34-2.16]) or poor sleep quality (1.91 [1.31-2.74]) or long sleep duration (1.45 [1.02-1.77]). DM2 occurred more frequently with poor sleep quality combined with short sleep duration (odds ratio: 6.21; 95% confidence interval (CI): 2.78-11.81). RERI, AP, and S values (and their 95% CI) were 3.99 (1.41-7.76), 0.64 (0.45-0.76), and 5.15 (3.74-7.89) for the interaction between poor sleep quality and short sleep duration. In subjects with poor sleep quality combined with long sleep duration, the RERI, AP, and S values (and 95% CI) were 0.13 (-0.19 to 0.66), 0.07 (-0.35 to 0.18), and 1.19 (0.85-2.11). CONCLUSIONS Interactions between poor sleep quality and short sleep duration were additive. Preventive measures should focus on short sleep duration and poor sleep quality.

Prevalence and determinants of depressive and anxiety symptoms in adults with type 2 diabetes in China: a cross-sectional study

Objectives To evaluate the prevalence and determinants of anxiety and depression and to assess their impact on glycaemic control in participants with type 2 diabetes mellitus. Design A cross-sectional study. Setting Community-based investigation in Xuzhou, China. Participants 893 Chinese men and women aged 18–84 years who fulfilled the inclusion criteria. Methods People with type 2 diabetes completed the Pittsburgh Sleep Quality Index and the Zung Self-Rating Anxiety and Depression Scales. Demographic and physiological characteristics were recorded. Multiple logistic regression was used to evaluate the combined effect of factors associated with anxiety and depression and to assess the effects of anxiety and depression on glycaemic control. Results The prevalence of depressive symptoms and anxiety symptoms was 56.1% and 43.6%, respectively. Multivariate logistic regression analysis indicated that anxiety symptoms were associated with being woman, low income, chronic disease, depressive symptoms and poor sleep quality. Depressive symptoms were associated with being woman, older age, low education level, being single, diabetes complications, anxiety symptoms and poor sleep quality. Glycaemic control was not related to anxiety symptoms (OR=1.31, 95% CIs 0.94 to 1.67) or depressive symptoms (OR=1.23, 95% CI 0.85 to 1.63). A combination of depressive symptoms and anxiety symptoms was associated with poor glycaemic control (relative excess risk due to interaction: 4.93, 95% CI 2.09 to 7.87; attributable proportion due to interaction: 0.27, 95% CI 0.12 to 0.45). Conclusions There was a high prevalence of depressive and anxiety symptoms in this Chinese sample of participants, although depression and anxiety were not singly associated with glycaemic control. However, a combination of depressive and anxiety symptoms was negatively correlated with glycaemic control in participants with type 2 diabetes.

Combined effects of sleep quality and depression on quality of life in patients with type 2 diabetes.

BackgroundPoor sleep quality and depression negatively impact the health-related quality of life of patients with type 2 diabetes, but the combined effect of the two factors is unknown. This study aimed to assess the interactive effects of poor sleep quality and depression on the quality of life in patients with type 2 diabetes.MethodsPatients with type 2 diabetes (n = 944) completed the Diabetes Specificity Quality of Life scale (DSQL) and questionnaires on sleep quality and depression. The products of poor sleep quality and depression were added to the logistic regression model to evaluate their multiplicative interactions, which were expressed as the relative excess risk of interaction (RERI), the attributable proportion (AP) of interaction, and the synergy index (S).ResultsPoor sleep quality and depressive symptoms both increased DSQL scores. The co-presence of poor sleep quality and depressive symptoms significantly reduced DSQL scores by a factor of 3.96 on biological interaction measures. The relative excess risk of interaction was 1.08. The combined effect of poor sleep quality and depressive symptoms was observed only in women.ConclusionsPatients with both depressive symptoms and poor sleep quality are at an increased risk of reduction in diabetes-related quality of life, and this risk is particularly high for women due to the interaction effect. Clinicians should screen for and treat sleep difficulties and depressive symptoms in patients with type 2 diabetes.

Salt Intake and Knowledge of Salt Intake in a Chinese Population: A CrosssectionalStudy

Consuming too much salt greatly increases the risk of heart disease and stroke, and limited studies focused on knowledge of salt intake in relation to salt consumption. Our study aimed to investigate salt intake and knowledge of salt intake in a Chinese population. Altogether 42114 adults aged 18 years and above were selected by multi-stage cluster sampling method. Salt consumption and knowledge of salt intake were assessed by self-reported questionnaire. The average salt intake was 15.5 ± 11.9 g/d, and 85.2% of subjects with excessive salt intake. Almost 80% of dietary salt came from salt, followed by salty vegetable (13.5%) and soy sauce (3.3%). There were 28.3% participants knowing the National recommended salt intake, and 29.7% with knowledge of excess salt intake resulting in hypertension. Overall 57.6% participants had ever been received health education on low-salt diet. After adjustment of confounders, subjects without knowledge of salt intake had a higher risk of excessive salt intake. Salt intake is high in the Chinese population. Awareness of salt intake is low, and it is inappropriate with current health education.

The prevalence of alcohol dependence and its association with hypertension: a population-based cross-sectional study4 in Xuzhou city, China

BackgroundTo describe the prevalence of alcohol dependence and to explore the relationship between alcohol dependence and newly detected hypertension in China.MethodsA multistage stratified cluster sampling method was used to obtain samples from February to June 2013. The Michigan Alcoholism Screening Test was used to estimate alcohol dependence level. A standard questionnaire measured other independent variables. Enumeration data were analyzed using chi-square; quantitative data were analyzed using t-tests. Spearman correlation analysis and multivariate logistic regression analysis were performed to identify the relationship between alcohol dependence and hypertension.ResultsThe alcohol dependence rate was 11.56%; 22.02% of males (3854/17501) and 1.74% of females (324/18656) were classified as alcohol dependent. The newly detected hypertension rate was 9.46% (3422/36157). Significant associations were found between alcohol dependence levels and blood pressure (P < 0.01). Alcohol dependence was positively correlated with systolic blood pressure (r = 0.071, P < 0.01) and diastolic blood pressure (r = 0.077, P < 0.01) and was an independent risk factor for hypertension after adjusting for confounders (low alcohol dependence: odds ratio [OR] = 1.44, 95% confidence intervals [CI] = 1.14–1.81, P < 0.01; light alcohol dependence: OR = 1.35, 95% CI = 1.11–1.64, P < 0.01; medium alcohol dependence: OR = 1.83, 95% CI = 1.40–2.41, P < 0.01).ConclusionAlcohol dependence was high and associated with hypertension. Health education and precautions against alcoholism should be implemented in Xuzhou city.

Prevalence and Risk Factors of Diabetic Retinopathy in Xuzhou, China: A Cross-Sectional Study

Background: The prevalence of diabetic retinopathy is not well studied in the Chinese diabetic population.This study investigated the prevalence and risk factors of diabetic retinopathy (DR) among primary care patients with type 2 diabetes mellitus in Xuzhou, China.Methods: 1578 Chinese patients with type 2 diabetes mellitus who were selected with a multi-stage stratified cluster method, retinal photographs were taken of both eyes. The levels of DR were assessed using fundus photography and the Diabetic Retinopathy Disease Severity Scale. Demographic and physiological characteristics were recorded. Participants completed the Pittsburgh Sleep Quality Index and the Zung Self-Rating Anxiety and Depression Scales. Multiple logistic regression was used to evaluate the factors associated with DR.Results: The rate of DR was 28.6%; 25.1% of patients (396/1578) had non-proliferative DR and 3.5% of patients (55/1578) had proliferative DR. Logistic regression analyses showed that HbA1c levels, diabetes duration, hypertension, smoking, anxiety, depression, poor sleep quality, and exercise were independently associated with DR.Conclusions: DR is common in patients with type 2 diabetes mellitus in China. Screening tests for DR should be incorporated into health care settings in China. Patients who have been registered for a long time, or have poor glycemic control, concomitant hypertension, psychological disorders, or sleep disorders, should be considered for early screening of DR.