Background: The low birth rates and rapid population aging has drawn considerable attention from scholars and policymakers in China and around the world. In 2021, China launched the policy and supportive measures that allow up to 3 children per couple. This study aims to explore the influencing factors of the third-child fertility intention among women aged 20–34 years in China. Methods: We draw data from the National Fertility Survey conducted in 2017. The nationally representative survey adopts a stratified, 3-stage, and probabilities proportional to size sampling method. A total of 61,588 valid samples aged 20–34 years old were obtained. Fertility desire and behavior, childbearing and service use, and potential influencing factors of fertility intention such as the history of pregnancy were assessed. Results: In general, 5.01% of Chinese women of prime childbearing age had fertility intention for a third child, and the proportion varies by region across mainland China. Individual characteristics such as being ethnic minorities, being rural residents, and having more siblings are significantly positively correlated with the third-child fertility intention, while the intention was significantly lower among women with a higher income or education level, migrant women, and those engaged in the non-agricultural labor force. Women who already had a son had lower fertility intention for a third child. Moreover, it was the perceived acceptable costs of childcare services rather than the actual costs that mattered more for the fertility intention. Conclusions: Our study concludes a series of socioeconomic factors, and previous childbearing and childrearing experiences are crucial for women’s fertility intention for a third child. These findings highlight the importance of launching supportive measures in addition to the introduction of the 3-child policy in promoting a fertility-friendly society.

Background: Disability is an important problem in aging societies globally. However, the research findings of the prevalence of disability have been inconsistent. This study aims to estimate the prevalence of disability and its influencing factors among the Chinese older population from 1979 to 31 July 2021. Methods: A systematic review and meta-analysis were conducted using both international (PubMed, Web of Science, CBMdisc, PsycINFO, the Cochrane Library, and EMBASE) and Chinese (CNKI, CQVIP, and WanFang) databases. Meta-analysis was performed using a random-effects model to account for heterogeneity. Subgroup analyses were also done. Results: The pooled prevalence of disability across all 97 studies was 26.2% (95% CI: 23.7–28.6%). The estimates varied according to the types of activities of daily living (ADL), gender, age, and region. Studies based on the identification of cases by using the complete ADL scale showed a higher prevalence than those using the basic ADL scale. The prevalence was slightly higher among female older individuals than among male older individuals. The highest rates were seen in older individuals aged 80 years or older. Elders in central China, southwest China, and northwest China were more likely to be BADL-disabled. Conclusion: Prevalence of disability among the Chinese older population is high, around 26%. Using standardized diagnostic systems to correctly estimate the prevalence of disability would be helpful for public health professionals in China.

Background: The coronavirus disease 2019 (COVID-19) pandemic has caused health concerns worldwide since December 2019. From the beginning of infection, patients will progress through different symptom stages, such as fever, dyspnea or even death. Identifying disease progression and predicting patient outcome at an early stage helps target treatment and resource allocation. However, there is no clear COVID-19 stage definition, and few studies have addressed characterizing COVID-19 progression, making the need for this study evident. Methods: We proposed a temporal deep learning method, based on a time-aware long short-term memory (T-LSTM) neural network and used an online open dataset, including blood samples of 485 patients from Wuhan, China, to train the model. Our method can grasp the dynamic relations in irregularly sampled time series, which is ignored by existing works. Specifically, our method predicted the outcome of COVID-19 patients by considering both the biomarkers and the irregular time intervals. Then, we used the patient representations, extracted from T-LSTM units, to subtype the patient stages and describe the disease progression of COVID-19. Results: Using our method, the accuracy of the outcome of prediction results was more than 90% at 12 days and 98, 95 and 93% at 3, 6, and 9 days, respectively. Most importantly, we found 4 stages of COVID-19 progression with different patient statuses and mortality risks. We ranked 40 biomarkers related to disease and gave the reference values of them for each stage. Top 5 is Lymph, LDH, hs-CRP, Indirect Bilirubin, Creatinine. Besides, we have found 3 complications - myocardial injury, liver function injury and renal function injury. Predicting which of the 4 stages the patient is currently in can help doctors better assess and cure the patient. Conclusions: To combat the COVID-19 epidemic, this paper aims to help clinicians better assess and treat infected patients, provide relevant researchers with potential disease progression patterns, and enable more effective use of medical resources. Our method predicted patient outcomes with high accuracy and identified a four-stage disease progression. We hope that the obtained results and patterns will aid in fighting the disease.

Background: The aim of the current study is to assess the cross-sectional association of chronic non-communicable diseases (hypertension, diabetes mellitus, arthritis, and cerebrovascular) with depressive symptoms among older adults in China. Methods: Data was obtained from the China Longitudinal Ageing Social Survey (CLASS) conducted in 2014. A total of 7505 participants were included. Depressive symptoms status was assessed by 9-item Center for Epidemiological Studies Depression Scale (CES-D) Associations between depressive symptoms and chronic diseases, adjusting for so, demographics and chronic diseases risk factors were assessed by using logistic regression model. Results: We found negative associations between depressive symptoms and several socioeconomic factors, including education attainment and economic level. Widowed/divorced/ unmarried individuals are more likely to suffer from depressive symptoms. Hypertension (Odds ratio:1.29 [95%CI:1.16, 1.42]), diabetes (1.41 [95%CI:1.19,1.67]), arthritis (1.72 [1.52, 1.96]), and cerebrovascular disease (1.69 [1.41, 2.02]) were found to be associated with depressive symptoms. Conclusions: Most depressive symptoms cases were found to be significantly associated with chronic diseases. Our findings have provided evidence for understanding co-morbid depressive symptoms with chronic diseases, which could help clinicians to evaluate, diagnose and manage depression promptly.

To evaluate the status of feeding practices and analyze the association between feeding practice and health status among Tibetan infants, a cross-sectional survey of 386 women with children aged under 24 months was conducted in rural areas surrounding Lhasa, Tibet. All participants were selected using simple random sampling and were interviewed face-to-face by trained interviewers. Mothers were interviewed to collect information on their feeding practices. A feeding practices index was created using the rank sum ratio method. Most of the infants had been or were being breastfed at the time of the interview. The feeding practices index was significantly and inversely associated with the prevalence of acute upper respiratory infection, and the odds ratio for the qualified feeding practices index vs. the non-qualified feeding practices index was 0.43 (95% confidence interval: 0.20–0.94). There were no measurable associations observed between acute upper respiratory infection, diarrhea, and the feeding practices index after controlling for selected factors. The method of rank sum ratio provides a flexible way to evaluate feeding practices and is easy to understand. Furthermore, appropriate infant feeding practices might play a protective role in Tibetan infants’ health.

Visual impairment has become a global challenge, especially for developing countries. This study aims to estimate the prevalence, causes and social factors of visual impairment among Chinese adults. Data were from a nationally representative population-based cross-sectional study. The study population were 1,909,199 non-institutionalized adults aged 18 years and older in mainland China. In the survey, low vision and blindness were checked by ophthalmologists according to the WHO best-corrected visual acuity (BCVA) criteria. Population weighted numbers and prevalence of low vision and blindness with 95% confidence intervals (CIs) were estimated where appropriate. Multivariable logistic regression analysis was used to identify the social factors of visual impairment. The weighted prevalence of visual impairment was 17.17 (95% CI, 16.84–17.50) per 1000 Chinese adults aged 18 years and older. Cataract (57.35%), disorders of choroid and retina (9.80%), and disorders of cornea (6.49%) contributed more than 70 percent to the visual impairment in Chinese adults. Older age groups, young or middle-aged male adults, female elders, illiterate, rural dwellers, non-eastern residents, singles, unemployment, and from family with lower income were associated with visual impairment. More efforts are warranted to enhance treatment and rehabilitation among people with eye disorders to prevent visual impairment.