This study aimed at investigating the sleep status and its associated factors in Shaanxi province, China. We conducted a cross-sectional study among 11,399 subjects in Shaanxi Province, China. Data were collected via spot field questionnaire surveys. The contents included demographic characteristics, sleep status, lifestyles, disease history and other associated factors. Logistic regression analysis was used to estimate the effect of associated factors on sleep quality. A total of 11,036 subjects were included in the final analysis. In total, 12.8% of the participants had bad or very bad sleep. In the last month, 8.4% of the participants had difficulty in initiating sleep, 7.6% of the participants had difficulty in maintaining sleep, 8.8% of the participants suffered from awakening earlier and 10.3% of the participants had the problem of feeling sleepy during the day ≥3 times per week. Poorer sleep quality was associated with being female, being unmarried or without cohabiting with a boyfriend/girlfriend, being divorced or widowed, heart diseases, musculoskeletal diseases, concerns about their own health, drinking alcohol, taking hypnotics, and a longer daily screen time. Better sleep quality was associated with medium education level, high family monthly income, good self-reported health status, and having breakfast regularly. In conclusion, more than one in ten people did not sleep well and suffered from different sleep problems in Shaanxi, China. Sleep quality was associated with sex, marital status, educational level, family monthly income, heart disease, musculoskeletal diseases, degree of concerning about their own health, self-reported health status, drinking alcohol, having breakfast, taking hypnotics and daily screen time.

This study aimed to investigate prolonged screen time and using electronic devices before sleep and their associated factors in elderly people in Shaanxi province of China. We conducted a cross-sectional study among 2647 elderly participants aged 60–88 years. Data were collected through questionnaires. Demographic characteristics, screen time, using electronic devices before sleep, health status, lifestyles, sleep quality, and other associated factors were investigated. Logistic regression analysis was used to analyze the relationship between the associated factors of screen time and using electronic devices before sleep. The crude odds ratio (cOR) and adjusted odds ratio (aOR) and their 95% confidence intervals (CI) were calculated. A total of 1784 subjects completed the questionnaire. There were 6.89% participants with prolonged screen time and 13.45% using electronic devices before sleep frequently. Prolonged screen time was associated with personal monthly income (aOR = 1.205, p = 0.001), number of household residents (aOR = 0.860, p = 0.010), rural residents (aOR = 0.617, p = 0.038), and regular drinkers (aOR = 2.889, p < 0.001). Using electronic devices before sleep was associated with being female (aOR = 0.657, p = 0.007), family monthly income (aOR = 0.866, p = 0.002), being an occasional drinker (aOR = 1.891, p = 0.005), and self-reported sleep quality (aOR = 1.593, p = 0.007). In conclusion, several factors related to screen time or using electronic devices before sleep were identified. Only being a drinker was a common associated factor for both screen time and using electronic devices before sleep.

Hypertension remains a major public health challenge globally, with suboptimal adherence to treatment and lifestyle modifications exacerbating cardiovascular risks. This study evaluates multidimensional adherence (medication, diet, and behavior) and its determinants among hypertensive patients in rural Northeast China. A cross‐sectional study enrolled 6352 adults aged ≥ 40 years with diagnosed and poorly controlled hypertension from rural villages across five cities (Benxi, Chaoyang, Dandong, Donggang, and Fuxin) in Liaoning Province, Northeast China, using multistage cluster sampling. Adherence was assessed via standardized questionnaires, with logistic regression analyzing sociodemographic, clinical, and behavioral predictors. Medication adherence was reported by 73.7% of participants, while dietary and behavioral adherence rates were 10.5% and 29.3%, respectively. Ethnic disparities emerged, with Han Chinese exhibiting lower medication adherence (aOR = 0.485, 95% CI: 0.377–0.624). Cohabiting with children enhanced dietary adherence (aOR = 2.184, 95% CI: 1.854–2.573), whereas widowed status reduced both dietary (aOR = 0.698, 95% CI: 0.528–0.924) and behavioral adherence (aOR = 0.726, 95% CI: 0.595–0.887). Higher hypertension knowledge scores positively influenced all adherence domains ( p < 0.05). Adherence among rural hypertensive patients is multidimensional, shaped by cultural, socioeconomic, and behavioral factors. Targeted interventions addressing dietary sodium reduction, family‐based support, and health literacy improvement are urgently needed. This study underscores the importance of integrating region‐specific strategies into hypertension management programs to mitigate cardiovascular morbidity in high‐risk populations.

Suboptimal medication adherence and unhealthy lifestyle behaviors are well‐recognized contributing factors to poor blood pressure control in hypertension patients. We evaluated the effectiveness of comprehensive health management in improving medication adherence and promoting healthy lifestyle behaviors among hypertension patients in China. A cluster randomized trial was implemented in rural areas of three provinces of China. Participants were individuals aged ≥ 40 years with uncontrolled hypertension. The intervention group received multidimensional health management measures codeveloped by healthcare organizations, village doctors, and patients, while the control group received standard care. The coprimary outcomes included the proportion of patients demonstrating good medication adherence and adherence to ≥ 3 healthy lifestyle components. Secondary outcomes comprised the proportion achieving controlled hypertension (BP < 140/90 mm Hg). From May 8th to November 28th, 2018, 9204 participants were enrolled. At 18‐month follow‐up, significantly higher medication adherence was observed in the intervention group compared with the control group, with an absolute difference of 5.0% (95% confidence interval (CI): 2.8–7.2; p < 0.001). Similarly, adherence to ≥ 3 healthy lifestyles was achieved by 45.8% in the intervention group versus 33.7% in controls, yielding a 12.1% between‐group difference (95% CI: 9.9–14.3; p < 0.001). Hypertension control rates differed significantly between groups (43.2% vs. 23.9%; absolute difference 19.2% and 95% CI: 17.2–21.3; p < 0.001). Hypertension patients receiving comprehensive health management in rural China demonstrated superior medication adherence and healthier lifestyle behaviors compared with those receiving standard care over 18 months. Further investigations are warranted to evaluate the cost‐effectiveness and generalizability of this intervention. Trial Registration: ClinicalTrials.gov identifier: NCT03527719

Background/Objectives: Whole-blood fatty acid composition provides an objective biomarker of fatty acid status, but its relationships with nutritional characteristics and subsequent quality-of-life (QoL) changes among cancer survivors remain incompletely understood. We aimed to identify whole-blood fatty acid phenotypes and examine their associations with nutritional characteristics, cross-sectional QoL profiles, and subsequent QoL changes in an overlapping longitudinal subcohort. Methods: In this cohort study, the 2023 baseline investigation included 3175 community-dwelling adult cancer survivors with whole-blood fatty acid profiles and paired questionnaires. After excluding participants with substantial missing QoL data, implausible fatty acid measurements, or missing age, sex, or cancer type, 3009 participants comprised the baseline analytical sample. Among these, 423 overlapped with an independent longitudinal cohort contributing QoL data from June 2021 and June 2024, and 398 had complete covariate data for the core adjusted longitudinal analyses. Whole-blood fatty acid phenotypes were identified using principal component analysis and unsupervised clustering. Nutritional characteristics were assessed using habitual dietary intake, Diet Balance Index 2022 scores, and nutrition literacy measures. QoL was assessed using the EORTC QLQ-C30. Multivariable models examined cross-sectional QoL and annualised QoL changes. An open-source phenotype assignment tool was developed to support reproducible classification in future cohorts. Results: Among 3009 baseline participants (mean [SD] age, 64.9 [7.0] years; 2397 women [79.7%]), five whole-blood fatty acid phenotypes were identified. Phenotypes 2 and 3 were rarely observed in the available general-population reference sample and appeared enriched among survivors. Phenotype 2, a high-SFA/low-PUFA phenotype accompanied by higher red meat intake and greater DBI-22 excess scores for red meat and related animal foods, was associated with statistically significant worsening across multiple QoL domains over 12 months despite relatively favourable baseline QoL. Compared with the general-population-mapped reference pool (Phenotypes 1, 4, and 5), Phenotype 2 showed annualised declines in summary score (−4.66 [95% CI, −8.14 to −1.19]) and role functioning (−5.35 [−9.88 to −0.83]), and worsening pain (8.28 [2.58 to 13.98]), dyspnoea (6.83 [0.16 to 13.50]), and constipation (14.10 [7.30 to 20.90]). Prebaseline annualised QoL changes over the preceding 24 months did not differ significantly across phenotypes. Conclusions: Whole-blood fatty acid profiling identified distinct nutritional-metabolic phenotypes among community-dwelling cancer survivors. The high-SFA/low-PUFA phenotype, accompanied by higher red meat intake and greater DBI-22 excess scores for red meat and related animal foods, was associated with worsening across multiple QoL domains over the subsequent 12 months despite relatively favourable baseline QoL. These findings highlight whole-blood fatty acid phenotyping as a potentially informative framework for characterising nutritional-metabolic heterogeneity and subsequent QoL vulnerability among cancer survivors. The open-source phenotype assignment tool may facilitate reproducible phenotype assignment and external validation in future cohorts.

Background This study aimed at investigating the sleep status and its associated factors in Shaanxi province of China. Methods This cross-sectional study was conducted among 11399 subjects in Shaanxi Province, China. Data was collected via spot field questionnaire survey. The contents included demographic characteristics, sleep status, lifestyles, disease history and other associated factors. Logistic regression analysis was used to estimate the effect of associated factors for sleep quality. Crude odds ratio (cOR) and adjusted odds ratio (aOR) and their 95% confident intervals (CI) were calculated. Results A total of 11036 subjects were included in the final analysis. There were 12.8% participants having a bad or very bad sleep. In the last month, 8.4% participants had difficulty in initiating sleep, 7.6% participants had difficulty in maintaining sleep, 8.8% participants suffered from awakening earlier and 10.3% participants had the problem of feeling sleepy during the day ≥ 3 times per week. There were 16.5% participants having one of the above sleep problems (difficulty in initiating sleep, difficulty in maintaining sleep, awakening early) > 3 months. Poorer sleep quality was associated with female (aOR = 1.792, p < 0.001), unmarried or without cohabiting with boyfriend/girlfriend (aOR = 1.319, 95% CI = 1.022–1.704), divorced or widowed (aOR = 1.436, 95% CI = 1.052–1.960), heart diseases (aOR = 1.478, p = 0.002), musculoskeletal diseases (aOR = 1.460, p = 0.018), concerning about their own health (aOR = 1.113, p = 0.016), alcohol drinking (aOR = 1.201, p < 0.001), taking hypnotics (aOR = 1.643, p < 0.001), a longer daily screen time (aOR = 1.055, p < 0.001). Better sleep quality was associated with medium education level (aOR = 0.748, p = 0.003), high family monthly income (aOR = 0.939, p = 0.004), good self-reported health status (aOR = 0.490, p < 0.001), having breakfast regularly (aOR = 0.935, p = 0.016). Conclusions The self-reported sleep quality was generally good in Shaanxi, China. Sleep quality was associated with gender, marital status, educational level, family monthly income, heart disease, musculoskeletal diseases, degree of concerning about their own health, self-reported health status, alcohol drinking, having breakfast, take hypnotics and daily screen time.