Poor sleep quality and influencing factors among rural adults in Deqing, China

Dong, Xiaolian; Wang, Yuzhuo; Chen, Yue; Wang, Xuecai; Zhu, Jianfu; Wang, Na; Jiang, Qingwu; Fu, Chaowei

doi:10.1007/s11325-018-1685-8

Cited by 51 publications

(43 citation statements)

References 26 publications

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“…Among the seven PSQI domains, sleep latency was most highly prevalent (39.7%), followed by sleep duration (31.0%) and habitual sleep efficiency (28.8%). These results were slightly different from those of other rural adults or the elderly in other provinces in China [29,31]. Variations in diagnostic criteria, interview techniques, and age of the study populations may also partly contribute to the inconsistent results across studies.…”

Section: Discussioncontrasting

confidence: 69%

“…The epidemiologic studies have indeed frequently indicated that female gender is an independent risk factor for sleep disorders [35,36]. The reason for poor sleep in women may be due to the fact that compared to men, women had higher proportions of low education, low individual income, and more chronic diseases, and were more susceptible to depression and anxiety [5,31,37].…”

Section: Discussionmentioning

confidence: 99%

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Prevalence and associated factors of poor sleep quality among Chinese older adults living in a rural area: a population-based study

et al. 2019

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Objective To investigate the prevalence and associated factors of poor sleep quality among community-dwelling elderly population in a rural area of Northern China. Methods We conducted a cross-sectional survey in August-December 2014 and recruited 2195 participants who were aged 65 years or older and living in Yanlou Town of Yanggu County in western Shandong Province, China. Data on demographics, health-related behaviors, and clinical conditions were collected through structured interviews. The Pittsburgh Sleep Quality Index (PSQI) was used to assess the sleep quality and patterns. Poor sleep quality was defined as a PSQI score > 7. We employed multiple logistic models to relate poor sleep quality to various factors. Results The overall prevalence rates of poor sleep quality were 33.8% in the total sample, 39.2% in women and 26.3% in men (P < 0.01). The most common abnormal sleep domains were prolonged sleep latency (39.7%), decreased sleep duration (31.0%), and reduced habitual sleep efficiency (28.8%). Multiple logistic regression analyses revealed that poor sleep quality was significantly associated with female sex (OR = 1.76, 95% CI 1.46-2.12) and clinical comorbidities such as hypertension (OR = 1.28, 95% CI 1.06-1.54), coronary heart disease (OR = 1.60, 95% CI 1.27-2.00), and chronic obstructive pulmonary disease (OR = 1.82, 95% CI 1.34-2.49). Conclusions The sleep disorders were highly prevalent among the elderly in rural China. Modifiable risk factors such as cardiometabolic risk factors and disorders were associated with poor sleep quality, which might be potential targets for interventions to improve sleep quality in elderly population.

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Section: Discussioncontrasting

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Prevalence and associated factors of poor sleep quality among Chinese older adults living in a rural area: a population-based study

et al. 2019

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“…Information about demographic characteristics, COVID-19 and lifestyle was collected by the selfstructured questionnaire. Questions on lifestyle factors, including regular alcohol drinking (> 3 times/week for ≥ 6 months) (17), regular cigarette smoking (> 3 times/week for ≥ 6 months) (18), regular tea drinking (> 3 times/week for ≥ 6 months) (19) and regular physical activity (> 10 min/day for ≥ 6 months) (20) were designed according to previous epidemiological researches. COVID-19 related information included quarantine status, awareness of COVID-19, self-protection measures and history of vaccination.…”

Section: Measures Of Quality Of Life and In Uencing Factorsmentioning

confidence: 99%

Quality of life during the epidemic of COVID-19 and its associated factors among enterprise workers in East China

Chen¹,

Lin

et al. 2020

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Background: The impact of COVID-19 related quarantine on quality of life was expected and unclear for enterprise workers. We investigated the quality of life during the epidemic in enterprise workers just returned to work and assessed its potential influencing factors to get a better understanding of the impact of COVID-19 epidemic. Methods: This was a cross-sectional study among enterprise workers in Deqing and Taizhou, Zhejiang Province, China. Chinese version of EQ5D to assess life quality, and information about general characteristics and COVID-19 related information was collected by a structured questionnaire online distributed through the social application “Wechat”. Results: A total of 2435 participants were enrolled, 59.5% of which worked in Deqing. About 50% reported worries about the COVID-2019 epidemic and 40.1% of participants performed centralized or home quarantine during the epidemic. The mean EQ-5D score and VAS were 0.990 and 93.5. Multiple logistic regression suggested that physical activities (ORad=0.46) and keeping home ventilation (ORad=0.04) was related with life quality in Deqing, while for participants in Taizhou, wearing a mask when going out (ORad=0.35), keeping home ventilation (ORad=0.16), unmarried status (ORad=2.38) and experienced centralized or home quarantine (ORad=1.64) was related with quality of life.Conclusions: Enterprise workers in two areas with different risk of COVID-19 experienced different life quality during the epidemic of COVID-19. Physical activity, marital status, worry about epidemic of COVID-19, keeping home ventilation, wearing a mask and quarantine were related with quality of life.

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“…Another cross-sectional survey among Inner Mongolia Medical University students found that exercise less than three times a week and skipping breakfast were associated with poor sleep quality [8]. Some research investigated sleep quality and its associated factors among rural adults [9,10], low-income rural adults [11], rural elderly [12,13]. A cross-sectional survey conducted in Deqing County of China reported that rural people who were unmarried or had low personal income or any chronic diseases were more likely to have poor sleep quality [9].…”

mentioning

confidence: 99%

“…Some research investigated sleep quality and its associated factors among rural adults [9,10], low-income rural adults [11], rural elderly [12,13]. A cross-sectional survey conducted in Deqing County of China reported that rural people who were unmarried or had low personal income or any chronic diseases were more likely to have poor sleep quality [9]. Another study among rural adults in Henan province of China showed that older age, being female, unmarried/divorced/widowed, low education level, low income, drinking, depression and dyslipidemia could increase the odds of poor sleep quality [10].…”

mentioning

confidence: 99%

Sleep status and the associated factors, a large cross-sectional study in Shaanxi province of China

Zhang

Wang

et al. 2020

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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.

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Poor sleep quality and influencing factors among rural adults in Deqing, China

Abstract: Sleep problems were prevalent among the rural Chinese adults aged 45+ years. People who were unmarried or had low personal income or any chronic diseases were more likely to have poor sleep quality.

Cited by 51 publications

References 26 publications

Prevalence and associated factors of poor sleep quality among Chinese older adults living in a rural area: a population-based study

Prevalence and associated factors of poor sleep quality among Chinese older adults living in a rural area: a population-based study

Quality of life during the epidemic of COVID-19 and its associated factors among enterprise workers in East China

Sleep status and the associated factors, a large cross-sectional study in Shaanxi province of China

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