Poor sleep quality is negatively associated with low cognitive performance in general population independent of self-reported sleep disordered breathing.

BACKGROUND: Sleep disordered breathing (SDB) plays a significant role in both sleep quality and cognition and whether it has an impact on the relationship between above two factors remains to be clear. The study aimed to explore the association between sleep quality and cognitive performance in general population by considering influence of sleep disordered breathing (SDB). METHODS: In this cross-sectional study, we enrolled subjects aged ≥ 18 years using a multi-stage random sampling method. Cognitive status was assessed using Mini Mental State Examination (MMSE) questionnaire, sleep quality using Pittsburgh Sleep Quality Index (PSQI) and SDB was assessed using No-SAS scale, respectively. Multi-variable logistic regression was applied to examine the association of sleep quality and cognitive performance. Subgroup analyses were performed in different age groups, and in those with and without SDB. RESULTS: Finally, 30,872 participants aged 47.5 ± 13.8 years with 53.5% women were enrolled, of whom 32.4% had poor sleep quality and 18.6% had low cognitive performance. Compared with good sleepers, subjects with poor sleep quality exhibited significantly higher presence of low cognitive performance (23.7% vs 16.2%, P < 0.001). Poor sleepers revealed 1.26 (95%CI: 1.16,1.36), 1.26 (1.08,1.46) and 1.25 (1.14,1.37) fold odds for low cognitive performance in general population and in subjects with and without self-reported SDB respectively. Stratified by age and SDB, the association was observed in young and middle-aged group without SDB (OR = 1.44, 95%CI: 1.30,1.59) and in the elderly group with SDB (OR = 1.30, 95%CI: 1.07,1.58). CONCLUSIONS: Sleep quality is in a negative association with cognitive performance in general population independent of SDB, implying improvement of sleep disturbances is a potential objective of intervention strategies for cognitive protection at population level.

Secondhand smoke is associated with poor sleep quality in self-reported never-smokers of Northwest China: a cross-sectional study.

OBJECTIVE: To investigate the relationship between secondhand smoke (SHS) exposure and sleep quality in never-smokers of Northwest China. METHODS: Never-smoking adults (≥ 15 years) from Xinjiang, Northwest China, were included in this cross-sectional survey between April and October 2019. SHS exposure in never-smokers was estimated using a structured questionnaire. Sleep quality was evaluated by Pittsburgh Sleep Quality Index (PSQI), with PSQI score > 5 classified as poor sleep quality. Association of SHS exposure and frequency and duration of SHS exposure with poor sleep quality were analyzed by using a multivariate logistic regression after adjusting for potential confounding factors, including stratification by sex. RESULTS: The mean age of participants was 48.0 years, and 77% were females. Of 21,198 never-smokers, 13% (n = 2703) reported SHS exposure and 35% (n = 7390) reported poor sleep quality. In multivariate logistic regression analysis, a significant association was observed between SHS exposure and poor sleep quality (adjusted odds ratio (OR), 1.36; 95% confidence interval (CI) 1.24-1.48). Subgroup analysis showed a negative association of SHS exposure with sleep quality in both sexes. However, a significant dose-response relationship of frequency and duration of SHS exposure per week with poor sleep quality was observed only in females. Consistent results were also observed in the aged ≥ 18 years. CONCLUSION: Exposure to SHS is associated with poor sleep quality in never-smoking adults of Northwest China. A dose-response relationship between SHS exposure and poor sleep quality is found in women. Avoiding SHS exposure may have beneficial effects on sleep quality, especially for females.

Poor sleep quality is associated with new-onset hypertension in a diverse young and middle-aged population.

BACKGROUND: Sleep disorders have been proposed as the potential risk factors for hypertension, thus we aimed to investigate the association of sleep quality with new-onset hypertension. METHODS: We evaluated sleep quality using Pittsburgh Sleep Quality Index (PSQI) and it's seven components in normotensive population aged 18 years old and over in Emin Xinjiang, China in 2016 and followed up till 2019 using annual health checkup data. Poor sleep quality was defined as a PSQI score>5, and good sleep quality was defined as a PSQI score⩽5. RESULTS: Among 9344 analytic sample 57.29% were female. A total of 2958 (31.66%) subjects developed hypertension during 22,960 person-years of follow-up. Poor sleep quality (HR 1.131, 95% CI 1.045, 1.224) showed had higher risk of development hypertension in total population in adjusted Cox models. Fairly bad subjective sleep quality (HR 1.148, 95% CI 1.015, 1.298), habitual sleep efficiency of <65%-75% group (HR 1.174, 95% CI 1.026, 1.344), and mild (HR 1.194, 95% CI 1.098, 1.299) and moderate (HR 1.264, 95% CI 1.080, 1.479) sleep disturbance increased the risk of developing hypertension compared to their counterparts. In age stratification, poor sleep quality (HR 1.100, 95% CI 1.007, 1.202) had higher risk of developing hypertension in the young and middle-aged population after adjusted all covariates. CONCLUSIONS: Poor sleep quality is associated with higher risk of new-onset hypertension in young and middle-aged population.

Association of Hypertension with Mild Cognitive Impairment in Population from Less-Developed Areas of Multiethnic Northwest China.

BACKGROUND: Relationship between hypertension and mild cognitive impairment (MCI) remains undetermined in population from less-developed regions. We aimed to explore whether hypertension is associated with MCI in this specific population. METHODS: In this cross-sectional study, we enrolled subjects aged ≥18 years using multistage random sampling from Emin, China, in 2019. Participants underwent questionnaires and data collection including mini-mental state examination (MMSE) and blood pressure measurement. RESULTS: Finally, 31,329 subjects were included, with 11,270 hypertensives. Compared with normotensive subjects, hypertensives were characterized by significantly older age (55.19 ± 12.25 vs. 43.26 ± 12.71), more men (52.5% vs. 42.9%), low education attainment (≤primary education: 42.4% vs. 26.3%), more abdominal obesity (39.7% vs. 19.1%), poor sleep quality (39.1% vs. 28.7%), and chronic kidney disease (6.6% vs. 3.4%, p for all <0.001). Prevalence of MCI in hypertensives was significantly higher than that of normotensive subjects (24.3% vs. 15.6%, p < 0.001). Multivariate logistic regression analysis showed in a fully adjusted model that the odds for MCI were significantly increased in hypertensives than in normotensive population (OR = 1.19, 95% CI: 1.09, 1.30, p < 0.001) and independent of all the parameters studied including age, education level, and stroke. In the age-stratified regression model, presence of hypertension significantly increased the odds of MCI by 1.17-fold (95% CI: 1.03, 1.33, p = 0.020) and by 1.22-fold (95% CI: 1.04, 1.44, p = 0.016) in middle-aged and elderly population. Sensitivity analysis of excluding those with stroke history showed that hypertension was still a risk factor for MCI in total, middle-aged, and elderly population. CONCLUSION: Hypertension is in independent negative association with MCI in middle-aged and elderly population from underdeveloped regions.

Barriers to Access to Treatment for Hypertensive Patients in Primary Health Care of Less Developed Northwest China: A Predictive Nomogram.

BACKGROUND: This study aims to evaluate the risk factors associated with untreated hypertension and develop and internally validate untreated risk nomograms in patients with hypertension among primary health care of less developed Northwest China. METHODS: A total of 895 eligible patients with hypertension in primary health care of less developed Northwest China were divided into a training set (n = 626) and a validation set (n = 269). Untreated hypertension was defined as not taking antihypertensive medication during the past two weeks. Using least absolute shrinkage and selection operator (LASSO) regression model, we identified the optimized risk factors of nontreatment, followed by establishment of a prediction nomogram. The discriminative ability, calibration, and clinical usefulness were determined using the area under the receiver operating characteristic curve (AUC), calibration curve, and decision analysis. The results were assessed by internal validation in the validation set. RESULTS: Five independent risk factors were derived from LASSO regression model and entered into the nomogram: age, herdsman, family income per member, altitude of habitation, and comorbidity. The nomogram displayed a robust discrimination with an AUC of 0.859 (95% confidence interval: 0.812-0.906) and good calibration. The nomogram was clinically useful when the intervention was decided at the untreated possibility threshold of 7% to 91% in the decision curve analysis. Results were confirmed by internal validation. CONCLUSIONS: Our nomogram showed favorable predictive accuracy for untreated hypertension in primary health care of less developed Northwest China and might help primary health care assess the risk of nontreatment in patients with hypertension.

Association of Depression with Uncontrolled Hypertension in Primary Care Setting: A Cross-Sectional Study in Less-Developed Northwest China.

BACKGROUND: Hypertensive patients commonly experience comorbid depression, which is closely associated with adverse health outcomes. This study aimed to examine the association between depression and uncontrolled hypertension in primary care setting of Northwest China. METHODS: We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years among primary care setting in Xinjiang, Northwest China, between April and October 2019. Depression was evaluated by Hospital Anxiety and Depression Scale (HADS), with a cut-off score ≥8. We related depression to uncontrolled hypertension, using multiple logistic regression, adjusting for minimally sufficient adjustment set of variables retrieved from a literature-based directed acyclic graphs (DAGs) and optimal adjustment set of variables derived from the least absolute shrinkage and selection operator (LASSO) regression. RESULTS: A total of 1,653 (89.1%) patients had uncontrolled hypertension. The prevalence of depression was 14.5% and 7.4% among patients with uncontrolled and controlled hypertension. Depression was associated with 1.12-fold increased odds of uncontrolled hypertension [odds ratio (OR) 2.12, 95% confidence interval (CI): 1.23-3.65]. The association remained significant even after adjusting for the minimal sufficient adjustment sets and the optimal adjustment set of variables. CONCLUSION: Depression is significantly associated with uncontrolled hypertension in primary care setting of northwest China. The integrated management of depression and hypertension in the setting might be warranted.

Prevalence and predictive nomogram of depression among hypertensive patients in primary care: A cross-sectional study in less developed Northwest China.

ABSTRACT: Hypertensive patients commonly co-exist persistent depressive symptoms. However, these issues are not always identified, especially in primary health care, which may worsen the prognosis of hypertension. Therefore, the aim of this study was to determine the prevalence and risk factor of depression, and to develop risk nomogram of depression in hypertensive patients from primary health care Northwest China.We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years in Xinjiang between April and October 2019. The subjects were randomly divided into a training set (n = 1299) and a validation set (n = 557). Depression was evaluated by Hospital Anxiety and Depression Scale (HADS), with a cut-off score ≥8. Using the least absolute shrinkage and selection operator (LASSO) regression model, we identified optimized risk factors of depression in the training set, followed by the establishment of prediction nomogram. The discriminative ability, calibration, and clinical usefulness of nomogram were assessed. The results were verified by internal validation in validation set.13.7% hypertensive subjects displayed depression. Seven independent risk factors of depression were identified and entered into the nomogram including age, region, ethnicity, marital status, physical activity, sleep quality, and control of hypertension. The nomogram displayed robust discrimination with an AUC of 0.760 [95% confidence interval (CI): 0.724-0.797)] and 0.761 (95%CI: 0.702-0.819), and good calibration in training set and validation set, respectively. The decision curve analysis and clinical impact curve demonstrated clinical usefulness of predictive nomogram.There is a considerable prevalence of depression in patients with hypertension from primary care of Xinjiang, Northwest China. Our nomogram may help primary care providers assess the risk of depression in patients with hypertension.

Prevalence of mild cognitive impairment is higher in hypertensive population: a cross-sectional study in less developed northwest China.

Uncertainty remains about the association of hypertension with mild cognitive impairment (MCI) in less-developed areas.This is a cross-sectional survey conducted in Xinjiang, a less-developed region in China between April and October 2019. We used multi-stage stratified sampling method to obtain study population aged ≥45 years, and we analyzed complete data for 3282 subjects. The Mini-Mental State Examination (MMSE) was used to assess cognitive function. MCI is defined as an MMSE score < 17 for illiterate subjects, <20 for subjects with 1 to 6 years of education, and <24 for subjects with ≥7 years of education.The prevalence of MCI was significantly higher in hypertensive subjects than in non-hypertensive subjects (22.1% vs 16.1%, P < .001) and higher in hypertensives with uncontrolled blood pressure (BP) than in those with controlled BP (27.5% vs 20.7%, P = .01). Hypertensive subjects had significantly lower each item score and total score of MMSE, compared to non-hypertensive subjects. Significant negative correlations were observed between systolic and diastolic BP with MMSE scores (P for all <.001). Multivariate logistic regression analysis showed that hypertension was the significant risk factor for the presence of MCI (OR = 1.62, 95%CI: 1.34, 2.35, P < .001), independent of such factors as gender, age, education attainment, and dyslipidemia.The prevalence of MCI is higher in hypertensive population, and hypertension is an independent risk factor for MCI in less-developed region, suggesting that hypertensives should be screened for MCI to provide improved diagnoses and optimal therapeutics for cognitive decline prevention, specially in settings with approximate conditions.