Green space exposure and Chinese residents' physical activity participation: empirical evidence from a health geography perspective.

Background: With continuous efforts made to promote the strategic goals of carbon neutrality and carbon peak, it is crucial to meet the growing and diversified needs of the public for fitness by practicing the concept of green development and promote the combination of national fitness and ecological civilization. Methods: To achieve this purpose, an OLS regression model was applied to estimate the role of green space exposure in Chinese residents' participation in physical activity and its underlying mechanisms, using the microdata from the China General Social Survey (CGSS) data and the Provincial Vegetation Cover Index (NDVI) matched macrostatistical data. Results: The empirical results show that green space exposure significantly increases the probability of residents' physical activity participation, and creating a green environment is conducive to creating a favorable physical activity environment for residents. Also, the core conclusions still hold after the year-by-year regression test is passed and the endogeneity problem is addressed. As revealed by mechanistic studies, green space exposure has indirect effects on the physical activity participation of residents through the independent mediating roles of reducing carbon emissions and promoting social interaction. According to heterogeneity results, males, those in marriage, and urban dweller groups are more inclined to perform physical activity in green spaces. Conclusion: The results show that the exposure of green space can help increase the probability of residents' participation in physical exercise, and can that it achieved through two channels: reducing carbon emissions and enhancing social interaction. It is necessary to further strengthen the protection of the ecological lifestyle, give full play to the advantages of greenness and low-carbon, and create favorable conditions for the green development of a new model of national fitness.

Age-Specific Association Between Visit-to-Visit Blood Pressure Variability and Hearing Loss: A Population-Based Cohort Study.

Background and Objectives: Hearing loss is common and undertreated, and the impact of blood pressure variability (BPV) on the development of hearing loss remains unclear. We aimed to examine the age-specific association between visit-to-visit BPV and hearing loss. Research Design and Methods: This nationally representative cohort study included 3,939 adults over 50 years from the Health and Retirement Study in the United States. Variabilities of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were assessed by standard deviation (SD), coefficient of variation, and variability independent of the mean (VIM), using SBP and DBP from 3 visits. Hearing loss was assessed by self-rated questions. Cox proportional risk models were used to evaluate age-specific associations (50-64, 65-79, and ≥80 years) between BPV and hearing loss. The generalized additive Cox models were further used to visualize the combined effect of age and BPV. Results: During the follow-up up to 7.0 years, 700 participants developed hearing loss. Among people aged under 65 years, we observed a 36% increased risk of hearing loss with per-SD increment in VIM of SBP (hazard ratio [HR] per SD 1.36, 95% confidence interval [CI] 1.13-1.63) and a slightly significant association between VIM of DBP (HR per SD 1.21, 95% CI 1.01-1.45) and hearing loss. We did not observe significant associations among groups aged over 65 years (p > .05). The generalized additive Cox models also showed younger participants had stronger associations between BPV and hearing loss. Discussion and Implications: Higher visit-to-visit variabilities of SBP were associated with an increased risk of hearing loss in middle-aged adults (50-65 years). Intervention in early BPV may help decrease hearing loss in adults aged over 50 years.

High-dimensional generalized median adaptive lasso with application to omics data.

Recently, there has been a growing interest in variable selection for causal inference within the context of high-dimensional data. However, when the outcome exhibits a skewed distribution, ensuring the accuracy of variable selection and causal effect estimation might be challenging. Here, we introduce the generalized median adaptive lasso (GMAL) for covariate selection to achieve an accurate estimation of causal effect even when the outcome follows skewed distributions. A distinctive feature of our proposed method is that we utilize a linear median regression model for constructing penalty weights, thereby maintaining the accuracy of variable selection and causal effect estimation even when the outcome presents extremely skewed distributions. Simulation results showed that our proposed method performs comparably to existing methods in variable selection when the outcome follows a symmetric distribution. Besides, the proposed method exhibited obvious superiority over the existing methods when the outcome follows a skewed distribution. Meanwhile, our proposed method consistently outperformed the existing methods in causal estimation, as indicated by smaller root-mean-square error. We also utilized the GMAL method on a deoxyribonucleic acid methylation dataset from the Alzheimer's disease (AD) neuroimaging initiative database to investigate the association between cerebrospinal fluid tau protein levels and the severity of AD.

Interaction between body mass index and family history of cancer on the risk of female breast cancer.

Both body mass index (BMI) and family history of cancer are established risk factors for female breast cancer. However, few studies explored the potential interaction between both factors. We assessed the association of BMI and its interaction with family cancer history on the risk of female breast cancer in Shanghai, China. Based on a population-based prospective cohort study started from 2008 to 2012 with 15,055 Chinese female participants in Minhang district, Shanghai. Cox regression models were used to estimate the association of BMI and its interaction with a family history of cancer on breast cancer risk. The additive interaction was evaluated by the relative excess risk due to interaction (RERI) and the attributable proportion due to interaction (AP), and the multiplicative interaction was assessed by the product term (BMI* family history of cancer) in the Cox regression model. Compared with BMI of < 24 kg/m2 and no family history of cancer, women with BMI of ≥ 24 kg/m2 and a family history of cancer had a higher risk for breast cancer with HR 2.06 (95% CI 1.39, 3.06). There was an additive interaction between BMI and family history of cancer on breast cancer incidence, with the RERI being 0.29 (95% CI 0.08, 0.51) and the AP being 0.37 (95% CI 0.08, 0.66). The coexistence of obesity and cancer family history may exacerbate breast cancer incidence risk, highlighting the importance of weight management in women with a family history of cancer.

Development of preoperative and postoperative models to predict recurrence in postoperative glioma patients: a longitudinal cohort study.

BACKGROUND: Glioma recurrence, subsequent to maximal safe resection, remains a pivotal challenge. This study aimed to identify key clinical predictors influencing recurrence and develop predictive models to enhance neurological diagnostics and therapeutic strategies. METHODS: This longitudinal cohort study with a substantial sample size (n = 2825) included patients with non-recurrent glioma who were pathologically diagnosed and had undergone initial surgical resection between 2010 and 2018. Logistic regression models and stratified Cox proportional hazards models were established with the top 15 clinical variables significantly influencing outcomes screened by the least absolute shrinkage and selection operator (LASSO) method. Preoperative and postoperative models predicting short-term (within 6 months) postoperative recurrence in glioma patients were developed to explore the risk factors associated with short- and long-term recurrence in glioma patients. RESULTS: Preoperative and postoperative logistic models predicting short-term recurrence had accuracies of 0.78 and 0.87, respectively. A range of biological and early symptomatic characteristics linked to short- and long-term recurrence have been pinpointed. Age, headache, muscle weakness, tumor location and Karnofsky score represented significant odd ratios (t > 2.65, p < 0.01) in the preoperative model, while age, WHO grade 4 and chemotherapy or radiotherapy treatments (t > 4.12, p < 0.0001) were most significant in the postoperative period. Postoperative predictive models specifically targeting the glioblastoma and IDH wildtype subgroups were also performed, with an AUC of 0.76 and 0.80, respectively. The 50 combinations of distinct risk factors accommodate diverse recurrence risks among glioma patients, and the nomograms visualizes the results for clinical practice. A stratified Cox model identified many prognostic factors for long-term recurrence, thereby facilitating the enhanced formulation of perioperative care plans for patients, and glioblastoma patients displayed a median progression-free survival (PFS) of only 11 months. CONCLUSION: The constructed preoperative and postoperative models reliably predicted short-term postoperative glioma recurrence in a substantial patient cohort. The combinations risk factors and nomograms enhance the operability of personalized therapeutic strategies and care regimens. Particular emphasis should be placed on patients with recurrence within six months post-surgery, and the corresponding treatment strategies require comprehensive clinical investigation.

Sibling Death in Childhood and Early Adulthood and Risk of Early-Onset Cardiovascular Disease.

Importance: Sibling death is a highly traumatic event, but empirical evidence on the association of sibling death in childhood and early adulthood with subsequent risk of incident cardiovascular disease (CVD) remains limited. Objective: To evaluate the association between sibling death in the early decades of life and subsequent risk of incident early-onset CVD. Design, Setting, and Participants: This population-based cohort study included 2 098 659 individuals born in Denmark from 1978 to 2018. Follow-up started at age 1 year or the date of the first sibling's birth, whichever occurred later, and it ended at the first diagnosis of CVD, the date of death, emigration, or December 31, 2018, whichever came first. Data analyses were conducted from November 1, 2021, through January 10, 2022. Exposures: The death of a sibling. Main Outcomes and Measures: The outcome was early-onset CVD. Cox models were used to estimate hazard ratios (HRs) with 95% CIs. Results: This study included 2 098 659 individuals (1 076 669 [51.30%] male; median [IQR] age at death of sibling, 11.48 [4.68-21.32] years). During the median (IQR) follow-up of 17.52 (8.85-26.05) years, 1286 and 76 862 individuals in the bereaved and nonbereaved groups, respectively, were diagnosed with CVD. Sibling death in childhood and early adulthood was associated with a 17% increased risk of overall CVD (HR, 1.17; 95% CI, 1.10-1.23; cumulative incidence in bereaved individuals, 1.96% [1.61%-2.34%]; cumulative incidence in nonbereaved individuals at age 41 years, 1.35% [1.34%-1.37%]; cumulative incidence difference: 0.61% [95% CI, 0.24%-0.98%]). Increased risks were also observed for most type-specific CVDs, in particular for myocardial infarction (HR, 1.66; 95% CI, 1.12-2.46), ischemic heart disease (HR, 1.52; 95% CI, 1.22-1.90), and heart failure (HR, 1.50; 95% CI, 1.00-2.26). The association was observed whether the sibling died due to CVD (HR, 2.54; 95% CI, 2.04-3.17) or non-CVD (HR, 1.13; 95% CI, 1.06-1.19) causes. The increased risk of CVD was more pronounced for individuals who lost a twin or younger sibling (HR, 1.25; 95% CI, 1.15-1.36) than an elder sibling (HR, 1.11; 95% CI, 1.03-1.20). Conclusions and Relevance: In this cohort study of the Danish population, sibling death in childhood and early adulthood was associated with increased risks of overall and most type-specific early-onset CVDs, with the strength of associations varying by cause of death and age difference between sibling pairs. The findings highlight the need for extra attention and support to the bereaved siblings to reduce CVD risk later in life.

Age-Dependent Association Between Body Mass Index and All-Cause Mortality Among Patients with Hypertension: A Longitudinal Population-Based Cohort Study in China.

Purpose: The association between body mass index (BMI) and all-cause mortality may vary among hypertensive patients of different ages. This study aimed to investigate the age-dependent association between BMI and all-cause mortality among patients with hypertension. Patients and Methods: A total of 212,394 participants with hypertension aged 20-85 years from Minhang Hypertension Standardization Management System in Shanghai of China were included. Follow-up began at the time when individuals were first recorded and ended at death, loss to follow-up, or December 31, 2018, whichever came first. Additive Cox proportional hazards models with thin plate smoothing functions and conventional Cox proportional hazards models were adopted to examine the relationship between BMI, age, and mortality. The joint effect of BMI and age on mortality was assessed using a bivariate response model. Results: We found that the BMI-mortality relationship followed a U-shaped pattern, with a trough at 26-27 kg/m2. Compared with normal weight, underweight was associated with a 50% increased risk of premature mortality (hazard ratio 1.50, 95% confidence interval 1.43 to 1.57). Whereas among those aged 45-59 and 60-85 years, overweight was associated with 13% (0.87, 0.80 to 0.94) and 18% (0.82, 0.80 to 0.84) reduction in risk of death, respectively. Bivariate response model indicated a significant interaction between BMI and age (P < 0.05). Among younger and older patients, we found a descending trend for mortality risk, with BMI increasing at different age levels, whereas a reverse J-shaped relation pattern was observed among middle-aged patients. Conclusion: The impact of BMI on all-cause mortality in hypertensive patients varies with age, and moderate weight gain may benefit longevity in middle-aged and older patients.

Multiply robust estimator for the difference in survival functions using pseudo-observations.

BACKGROUND: When estimating the causal effect on survival outcomes in observational studies, it is necessary to adjust confounding factors due to unbalanced covariates between treatment and control groups. There is no study on multiple robust method for estimating the difference in survival functions. In this study, we propose a multiply robust (MR) estimator, allowing multiple propensity score models and outcome regression models, to provide multiple protection. METHOD: Based on the previous MR estimator (Han 2014) and pseudo-observation approach, we proposed a new MR estimator for estimating the difference in survival functions. The proposed MR estimator based on the pseudo-observation approach has several advantages. First, the proposed estimator has a small bias when any PS and OR models were correctly specified. Second, the proposed estimator considers the advantage pf the pseudo-observation approach, which avoids proportional hazards assumption. A Monte Carlo simulation study was performed to evaluate the performance of the proposed estimator. And the proposed estimator was used to estimate the effect of chemotherapy on triple-negative breast cancer (TNBC) in real data. RESULTS: The simulation studies showed that the bias of the proposed estimator was small, and the coverage rate was close to 95% when any model for propensity score or outcome regression is correctly specified regardless of whether the proportional hazard assumption holds, finite sample size and censoring rate. And the simulation results also showed that even though the propensity score models are misspecified, the bias of the proposed estimator was still small when there is a correct model in candidate outcome regression models. And we applied the proposed estimator in real data, finding that chemotherapy could improve the prognosis of TNBC. CONCLUSIONS: The proposed estimator, allowing multiple propensity score and outcome regression models, provides multiple protection for estimating the difference in survival functions. The proposed estimator provided a new choice when researchers have a "difficult time" choosing only one model for their studies.

An improved multiply robust estimator for the average treatment effect.

BACKGROUND: In observational studies, double robust or multiply robust (MR) approaches provide more protection from model misspecification than the inverse probability weighting and g-computation for estimating the average treatment effect (ATE). However, the approaches are based on parametric models, leading to biased estimates when all models are incorrectly specified. Nonparametric methods, such as machine learning or nonparametric double robust approaches, are robust to model misspecification, but the efficiency of nonparametric methods is low. METHOD: In the study, we proposed an improved MR method combining parametric and nonparametric models based on the previous MR method (Han, JASA 109(507):1159-73, 2014) to improve the robustness to model misspecification and the efficiency. We performed comprehensive simulations to evaluate the performance of the proposed method. RESULTS: Our simulation study showed that the MR estimators with only outcome regression (OR) models, where one of the models was a nonparametric model, were the most recommended because of the robustness to model misspecification and the lowest root mean square error (RMSE) when including a correct parametric OR model. And the performance of the recommended estimators was comparative, even if all parametric models were misspecified. As an application, the proposed method was used to estimate the effect of social activity on depression levels in the China Health and Retirement Longitudinal Study dataset. CONCLUSIONS: The proposed estimator with nonparametric and parametric models is more robust to model misspecification.

Covariate balance-related propensity score weighting in estimating overall hazard ratio with distributed survival data.

BACKGROUND: When data is distributed across multiple sites, sharing information at the individual level among sites may be difficult. In these multi-site studies, propensity score model can be fitted with data within each site or data from all sites when using inverse probability-weighted Cox regression to estimate overall hazard ratio. However, when there is unknown heterogeneity of covariates in different sites, either approach may lead to potential bias or reduced efficiency. In this study, we proposed a method to estimate propensity score based on covariate balance-related criterion and estimate the overall hazard ratio while overcoming data sharing constraints across sites. METHODS: The proposed propensity score was generated by choosing between global and local propensity score based on covariate balance-related criterion, combining the global propensity score fitted in the entire population and the local propensity score fitted within each site. We used this proposed propensity score to estimate overall hazard ratio of distributed survival data with multiple sites, while requiring only the summary-level information across sites. We conducted simulation studies to evaluate the performance of the proposed method. Besides, we applied the proposed method to real-world data to examine the effect of radiation therapy on time to death among breast cancer patients. RESULTS: The simulation studies showed that the proposed method improved the performance in estimating overall hazard ratio comparing with global and local propensity score method, regardless of the number of sites and sample size in each site. Similar results were observed under both homogeneous and heterogeneous settings. Besides, the proposed method yielded identical results to the pooled individual-level data analysis. The real-world data analysis indicated that the proposed method was more likely to find a significant effect of radiation therapy on mortality compared to the global propensity score method and local propensity score method. CONCLUSIONS: The proposed covariate balance-related propensity score in multi-site distributed survival data outperformed the global propensity score estimated using data from the entire population or the local propensity score estimated within each site in estimating the overall hazard ratio. The proposed approach can be performed without individual-level data transfer between sites and would yield the same results as the corresponding pooled individual-level data analysis.

Association of nocturnal sleep duration and nocturnal sleep changes with instrumental activities of daily living disability among middle-aged and elderly Chinese.

OBJECTIVE: To investigate the association of baseline nocturnal sleep duration and sleep changes with functional disability in middle-aged and elderly Chinese. METHODS: Data for this study were collected from the China Health and Retirement Longitudinal Study (CHARLS) from baseline (2011) to the Wave 3 follow-up (2018). 8361 participants free of IADL disability in 2011 and aged ≥ 45 years old were recruited and prospectively followed till 2018 to analyze the association between baseline nocturnal sleep duration and IADL disability. Of these 8361 participants, a total of 6948 participants had no IADL disability at the first three follow-up visits and completed the 2018 follow-up to analyze the association between nocturnal sleep changes and IADL disability. Nocturnal sleep duration (hours) was self-reported at baseline. The coefficient of variation (CV) of nocturnal sleep duration at baseline and three follow-up visits was used to calculate sleep changes and classified into mild, moderate, and severe degrees by the quantiles. Cox proportional hazards regression model was used to analyze the association of baseline nocturnal sleep duration with IADL disability, and the binary logistic regression model was used to analyze the association of nocturnal sleep changes with IADL disability. RESULTS: Among the 8361 participants of 50237.5 person-years follow-up with a median follow-up of 7 years, 2158 (25.81%) participants developed IADL disabilities. Higher risks of IADL disability were observed among participants with sleep duration <7 h [HR(95%): 1.23(1.09-1.38)], 8∼<9 h [HR(95%): 1.05(1.00-1.32)] and ≥9 h [HR(95%): 1.21(1.01-1.45)] compared to those with 7∼<8 h. Among the 6948 participants, a total of 745 (10.72%) participants finally developed IADL disabilities. Compared with mild nocturnal sleep changes, moderate [OR(95%): 1.48(1.19-1.84)] and severe [OR(95%): 2.43(1.98-3.00)] sleep changes increased the probability of IADL disability. The restricted cubic spline model showed that a higher degree of nocturnal sleep changes was associated with a greater probability of IADL disability. CONCLUSION: Both insufficient and excessive nocturnal sleep duration were associated with higher risk of IADL disability in middle-aged and elderly adults, independent of the participants' gender, age, and napping habits. Higher nocturnal sleep changes were associated with a higher probability of disability in IADL. These findings highlight the importance of appropriate and stable nocturnal sleep, and the need to pay attention to population differences in the impact of nocturnal sleep duration on health.

Subgroup analysis for longitudinal data based on a partial linear varying coefficient model with a change plane.

Subgroup analysis has become an important tool to characterize the treatment effect heterogeneity, and finally towards precision medicine. On the other hand, longitudinal study is widespread in many fields, but subgroup analysis for this data type is still limited. In this article, we study a partial linear varying coefficient model with a change plane, in which the subgroups are defined based on linear combination of grouping variables, and the time-varying effects in different subgroups are estimated to capture the dynamic association between predictors and response. The varying coefficients are approximated by basis functions and the group indicator function is smoothed by kernel function, which are included in the generalized estimating equation for estimation. Asymptotic properties of the estimators for the varying coefficients, the constant coefficients and the change plane coefficients are established. Simulations are conducted to demonstrate the flexibility, efficiency and robustness of the proposed method. Based on the Standard and New Antiepileptic Drugs study, we successfully identify a subgroup in which patients are sensitive to the newer drug in a specific period of time.

Predictive models and survival analysis of postoperative mental health disturbances in adult glioma patients.

Background and Objectives: Patients with primary malignant brain tumors may experience mental health disturbances that can significantly affect their daily life. This study aims to identify risk factors and generate predictive models for postoperative mental health disturbances (PMHDs) in adult glioma patients in accordance with different clinical periods; additionally, survival analyses will be performed. Methods: This longitudinal cohort study included 2,243 adult patients (age at diagnosis ≥ 18 years) with nonrecurrent glioma who were pathologically diagnosed and had undergone initial surgical resection. Six indicators of distress, sadness, fear, irritability, mood and enjoyment of life, ranging from 0-10, were selected to assess PMHDs in glioma patients in the third month after surgery, mainly referring to the M.D. Anderson Symptom Inventory Brain Tumor Module (MDASI-BT). Factor analysis (FA) was applied on these indicators to divide participants into PMHD and control groups based on composite factor scores. Survival analyses were performed, and separate logistic regression models were formulated for preoperative and postoperative factors predicting PMHDs. Results: A total of 2,243 adult glioma patients were included in this study. Based on factor analysis results, 300 glioma patients had PMHDs in the third postoperative month, and the remaining 1,943 were controls. Candidate predictors for PMHDs in the preoperative model were associated with age, clinical symptoms (intracranial space-occupying lesion, muscle weakness and memory deterioration), and tumor location (corpus callosum, basal ganglia and brainstem), whereas age, clinical symptoms (nausea and memory deterioration), tumor location (basal ganglia and brainstem), hospitalization days, WHO grade 4, postoperative chemotherapy or radiotherapy and postoperative Karnofsky Performance Scale (KPS) served as important factors in the postoperative model. In addition, the median overall survival (OS) time for glioma patients with PMHDs was 19 months, compared to 13 months for glioblastoma, IDH-wild type (GBM) patients with PMHDs. Conclusion: The risk factors for PMHDs were identified. These findings may provide new insights into predicting the probability of PMHD occurrence in glioma patients in addition to aiding effective early intervention and improving prognosis based on different clinical stages.

Age-specific association of stage of hypertension at diagnosis with cardiovascular and all-cause mortality among elderly patients with hypertension: a cohort study.

BACKGROUND: Hypertension affects 31.1% of adults worldwide, with higher prevalence of great than 60% in elderly. Advanced hypertension stage was associated with the higher risk of mortality. However, little is known about the age-specific association of stage of hypertension at diagnosis on cardiovascular mortality or all-cause mortality. Therefore, we aim to explore this age-specific association among the hypertensive elderly through stratified and interaction analyses. METHODS: This cohort study included 125,978 elderly hypertensive patients aged 60+ years from Shanghai of China. Cox regression was used to estimate the independent and joint effect of hypertension stage and age at diagnosis on cardiovascular and all-cause mortality. Interactions were evaluated both additively and multiplicatively. Multiplicative interaction was examined by the Wald test of the interaction term. Additive interaction was assessed by relative excess risk due to interaction (RERI). All analyses were performed stratified by sex. RESULTS: 28,250 patients died during the follow-up up to 8.85 years, and 13,164 died of cardiovascular events. Older age and advanced hypertension stage were risk factors of cardiovascular mortality and all-cause mortality. Besides, smoking, rarely exercise, BMI < 18.5 and diabetes were also the risk factors. When we compared stage 3 hypertension with stage 1 hypertension, hazard ratios (95% confidence interval) of cardiovascular mortality and all-cause mortality were 1.56(1.41-1.72) and 1.29(1.21-1.37) for males aged 60-69 years, 1.25(1.14-1.36) and 1.13(1.06-1.20) for males aged 70-85 years, 1.48(1.32-1.67) and 1.29(1.19-1.40) for females aged 60-69 years, and 1.19(1.10-1.29) and 1.08(1.01-1.15) for females aged 70-85 years, respectively. Negative multiplicative interaction and positive additive interaction between age at diagnosis and stage of hypertension at diagnosis on cardiovascular mortality were observed in males (HR: 0.81, 95% CI: 0.71-0.93 RERI: 0.59, 95% CI: 0.09-1.07) and females (HR: 0.81, 95% CI: 0.70-0.93 RERI: 0.66, 95% CI: 0.10-1.23). CONCLUSIONS: Diagnosed with stage 3 hypertension was associated with higher risks of cardiovascular mortality and all-cause mortality, which were stronger among patients with age at diagnosis of 60-69 years compared with those with age at diagnosis of 70-85 years. Therefore, for the younger part of the elderly, the Department of Health should pay more attention to treating patients with stage 3 hypertension.

Association of Self-Reported Nighttime Sleep Duration with Chronic Kidney Disease: China Health and Retirement Longitudinal Study.

INTRODUCTION: The cohort study aimed to assess the association of nighttime sleep duration and the change in nighttime sleep duration with chronic kidney disease (CKD) and whether the association between nighttime sleep duration and CKD differed by daytime napping. METHODS: This study included 11,677 individuals from the China Health and Retirement Longitudinal Study (CHARLS) and used data from the 2011 baseline survey and four follow-up waves. Nighttime sleep duration was divided into three groups: short (<7 h per night), optimal (7-9 h), and long nighttime sleep duration (>9 h). Daytime napping was divided into two groups: no nap and with a nap. We used Cox proportional hazards model to examine the effect of nighttime sleep duration at baseline and change in nighttime sleep duration on incident CKD and a joint effect of nighttime sleep duration and nap time on onset CKD. RESULTS: With a follow-up of 7 years, the incidence of CKD among those with short, optimal, and long nighttime sleep duration was 9.89, 6.75, and 9.05 per 1,000 person-years, respectively. Compared to individuals with optimal nighttime sleep duration, short nighttime sleepers had a 44% higher risk of onset CKD (hazard ratio [HR]: 1.44, 95% confidence interval [CI]: 1.21-1.72). Compared to participants with persistent optimal nighttime sleep duration, those with persistent short or long nighttime sleep duration had an increased risk of incident CKD (HR: 1.44, 95% CI: 1.15-1.80). We found a lower incidence of CKD in participants with short nighttime sleep duration and a nap (HR: 0.74, 95% CI: 0.60-0.93), compared to those with short nighttime sleep duration and no nap. CONCLUSION: Short nighttime sleep duration and persistent long or short nighttime sleep duration were associated with a higher risk of onset CKD. Keeping persistent optimal nighttime sleep duration may help reduce CKD risk later in life. Daytime napping may be protective against CKD incidence.

Impact of free hypertension pharmacy program and social distancing policy on stroke: A longitudinal study.

Background: The estimated lifetime risk of stroke was the highest in East Asia worldwide, especially in China. Antihypertensive therapy can significantly reduce stroke mortality. However, blood pressure control is poor. Medication adherence is a barrier as patients' out-of-pocket costs have risen. We aimed to take advantage of a free hypertension pharmacy intervention and quantified the impact on stroke mortality. Methods: A free pharmaceutical intervention program was implemented in Deqing, Zhejiang province in April 2018. Another non-pharmaceutical intervention, social distancing due to the pandemic of Coronavirus disease 2019 (COVID-19), was also key to affecting stroke mortality. We retrospectively collected the routine surveillance data of stroke deaths from Huzhou Municipal Center for Disease Prevention and Control in 2013-2020 and obtained within-city mobility data from Baidu Migration in 2019-2020, then we quantified the effects of both pharmaceutical intervention and social distancing using Serfling regression model. Results: Compared to the predicted number, the actual number of stroke deaths was significantly lower by 10% (95% CI, 6-15%; p < 0.001) from April 2018 to December 2020 in Deqing. Specifically, there was a reduction of 19% (95% CI, 10-28%; p < 0.001) in 2018. Moreover, we observed a 5% (95% CI, -4 - 14%; p = 0.28) increase in stroke mortality due to the adverse effect of COVID-19 but it wasn't statistically significant. Conclusion: Free hypertension pharmacy program has great potential to prevent considerable stroke deaths. In the future, the free supply of low-cost, essential medications that target patients with hypertension at increased risk of stroke could be taken into account in formulating public health policies and guiding allocations of health care resources.

Association of nocturnal sleep duration and midday napping with subjective poor hearing among middle-aged and older adults in China.

Background: Hearing loss has occurred as a critical concern for aging and health. However, it remains unknown whether nocturnal sleep and midday napping duration are associated with hearing loss in middle-aged and older adults. Methods: The study comprised 9,573 adults from China Health and Retirement Longitudinal Study, who have completed the survey for sleep characteristics and subjective functional hearing. We collected self-reported nocturnal sleep duration (<5, 5 to <6, 6 to <7, 7 to <9, ≥9 h/night) and midday napping duration (≤5, 5 to ≤30, and >30 min). The sleep information was classified into different sleep patterns. The primary outcome was self-reported hearing loss events. Multivariate Cox regression models and restricted cubic splines were used to investigate the longitudinal association of sleep characteristics with hearing loss. We applied Cox generalized additive models and bivariate exposure-response surface diagrams to visualize the effects of different sleep patterns on hearing loss. Results: We confirmed 1,073 cases of hearing loss (55.1% female) during the follow-up. After adjusting for demographic characteristics, lifestyle factors and health condition, nocturnal sleep with < 5 h was positively associated with hearing loss [hazard ratio (HR): 1.45, 95% confidence interval [CI]: 1.20, 1.75]. Individuals with napping for 5 to ≤30 min had a 20% (HR: 0.80, 95%CI: 0.63, 1.00) lower risk of hearing loss compared with those with napping ≤ 5 min. Restrictive cubic splines showed the reverse J-shaped association between nocturnal sleep and hearing loss. Moreover, we found significant joint effects of sleeping < 7 h/night and midday napping ≤ 5 min (HR: 1.27, 95% CI: 1.06, 1.52) on hearing loss. Bivariate exposure-response surface diagrams also reflected the finding that short sleep without napping existed the highest risk of hearing loss. Compared with persistently sleeping moderately (7-9 h/night), those who persistently slept < 7 h/night or shifted from < 7 h/night to moderate or > 9 h/night had higher risks of hearing loss. Conclusion: Inadequate nocturnal sleep was associated with an elevated risk of poor subjective hearing in middle-aged and older adults, while moderate napping decreased the risk of hearing loss. Keeping sleep stable within recommendation duration may be a useful strategy for preventing poor hearing loss.

Association of dietary calcium with mortality from all causes, cardiovascular disease and cancer in people with hypertension.

Association between calcium intake and premature mortality in the general population has been well studied, but little is known about the association among specific populations. The authors aim to evaluate the association among people with hypertension and to provide a proper reference range of dietary calcium intake. This prospective cohort study included 8534 US adults with hypertension from National Health and Nutrition Examination Survey cycles 2003-2014. Dietary calcium intakes were self-reported and mortality status was ascertained by National Death Index records. During a median follow-up of 5.9 years, 1357 death occurred. Compared with participants of dietary calcium intake in quintile 1, participants in quintiles 2 and 4 had a 27% (HR: 0.73, 95% CI: 0.60-0.89) and a 29% lower risk (HR: 0.71, 95% CI: 0.57-0.88) of all-cause mortality respectively. The authors also observed a 34% lower risk (HR: 0.66, 95% CI: 0.45-0.97) of CVD death among participants in quintile 3 and a 37% lower risk (HR: 0.63, 95% CI: 0.40-0.99) of cancer-related death in participants in quintile 4 respectively. Restricted cubic spline (RCS) regression revealed a consistent protective effect of dietary calcium in participants with a daily intake of over 1000 mg, but a daily intake over 1200 mg fails to show further protective effect. Our findings suggest that elevated dietary calcium was associated with lower mortality risk from all-causes, cardiovascular disease (CVD) and cancer, and supplying sufficient dietary calcium intake, between 1000 and 1200 mg per day, in people with hypertension may be considered cost-effective to decrease risk of premature death.

Evaluation of Hypertensive Disorder of Pregnancy and High Refractive Error in Offspring During Childhood and Adolescence.

Importance: Growing evidence indicates that adverse prenatal or intrauterine environments might contribute to the development of high refractive error (RE) later in life. However, the association of maternal hypertensive disorder of pregnancy (HDP) with high RE in offspring during childhood and adolescence remains unknown. Objective: To investigate the association between maternal HDP and overall and type-specific high REs in offspring in childhood and adolescence. Design, Setting, and Participants: This nationwide population-based cohort study included live-born individuals born in Denmark from 1978 to 2018 in the Danish national health registers. Follow-up started at the date of birth and ended at the date of RE diagnosis, 18th birthday, death, emigration, or December 31, 2018, whichever came first. Data analyses were conducted from November 12, 2021, through June 30, 2022. Exposures: Maternal HDP (n = 104 952), including preeclampsia or eclampsia (n = 70 465) and hypertension (n = 34 487). Main Outcomes and Measures: The main outcomes were the first occurrence of high RE (hyperopia, myopia, and astigmatism) in offspring. A Cox proportional hazards regression model was used to examine the association between maternal HDP and risk of high RE in offspring from birth until age 18 years, adjusting for multiple potential confounders. Results: This study included 2 537 421 live-born individuals, 51.30% of whom were male. During the follow-up of up to 18 years, 946 offspring of 104 952 mothers with HDP (0.90%) and 15 559 offspring of 2 432 469 mothers without HDP (0.64%) were diagnosed with high RE. The cumulative incidence of high RE was higher in the exposed cohort (1.12%; 95% CI, 1.05%-1.19%) than in the unexposed cohort (0.80%; 95% CI, 0.78%-0.81%) at 18 years of age (difference: 0.32%; 95% CI, 0.25%-0.40%). Offspring born to mothers with HDP had a 39% increased risk of overall high RE (hazard ratio [HR], 1.39; 95% CI, 1.31-1.49). Sibling-matched analysis revealed an increased risk of overall high RE in half siblings (HR, 1.21; 95% CI, 1.05-1.39) and full siblings (HR, 1.15; 95% CI, 0.99-1.34), but the difference was not significant for the latter. The elevated risks were observed for hypermetropia (HR, 1.41; 95% CI, 1.30-1.52), myopia (HR, 1.30; 95% CI, 1.10-1.53), and astigmatism (HR, 1.45; 95% CI, 1.22-1.71). The increased risk of high RE persisted among offspring aged 0 to 6 years (HR, 1.51, 95% CI, 1.38-1.65), 7 to 12 years (HR, 1.28; 95% CI, 1.11-1.47), and 13 to 18 years (HR, 1.16; 95% CI, 0.95-1.41), but the difference was not significant for the oldest group. When considering both timing of diagnosis and severity of maternal preeclampsia, the highest risk was observed in offspring prenatally exposed to early-onset and severe preeclampsia (HR, 2.59; 95% CI, 2.17-3.08). Conclusions and Relevance: In this cohort study of the Danish population, maternal HDP, especially early-onset and severe preeclampsia, was associated with an increased risk of high RE in offspring during childhood and adolescence. These findings suggest that early and regular RE screening should be recommended for children of mothers with HDP.