The prevalence and year lived with disability of atopic dermatitis in China: Findings from the global burden of disease study 2019.

BACKGROUND: Atopic dermatitis (AD) is a chronic disease with growing prevalence and has become a global public health problem. However, little is known about the burden caused by AD in China. OBJECTIVE: To access the prevalence and burden of AD in China. METHODS: We estimated the prevalence and year lived with disability (YLD) of AD in China, by different age and sex groups. We also compared the burden of AD in China with other countries in the Group of Twenty (G20). We analyzed the changes in the number of AD patients and their YLDs by cause decomposition from 1990 to 2019. RESULTS: AD was the twenty-fourth leading cause of the burden of 369 diseases in China in 2019. From 1990 to 2019, the age-standardized prevalence and YLD rate of AD in China increased by 1.04% and 1.43% respectively, which were the second and the largest increase among the G20 and both higher than the global average (-4.29% and -4.14%). The number of patients with AD increased by 25.65%, of which 20.16% was due to population growth, 3.85% due to population aging, and 1.64% due to age-specific prevalence. Both the prevalence and YLD rate of AD were higher in 1 to 4 year-olds and 95+ years age group. Before the age of 10, the prevalence and YLD rate of AD in males were higher than those in females, while there was a marked sex shift at the ages of 10 to 14. CONCLUSION: AD is a serious public health problem in China. Substantial variations exist in burden due to AD between male and female, and in age groups. Considering these findings will be important for developing preventive strategies and treatments to reduce the burden of AD.

Long-term effectiveness of group-based diabetes self-management on glycosylated haemoglobin for people with type 2 diabetes in community: a protocol of systematic review and meta-analysis.

INTRODUCTION: The rapid rise in the prevalence of diabetes has a negative impact on patients' quality of life. Diabetes self-management group education is cost-effective and efficient for patients to control blood glucose. However, there are no consistent standards for self-management group education, and its long-term effects (≥12 months) are unclear. Although a few systematic reviews evaluated the long-term effects, they did not make clear provisions on the content of self-management, and the number and sample size of included studies were small, which may lead to misclassification bias and reporting bias. Therefore, we plan to conduct this systematic review to evaluate the long-term effects of self-management group education and determine the effects of different self-management characteristics on glycosylated haemoglobin (HbA1c). METHODS AND ANALYSIS: We will retrieve Chinese databases (Wanfang, Chinese Hospital Knowledge Warehouse) and English databases (PubMed, ScienceDirect, EMBASE, Web of Science, Bailian Platform, Cochrane Central Register of Controlled Trials, Google Scholar) for randomly controlled trials and cluster randomly controlled trials of which participants are adults with type 2 diabetes mellitus. We will manually search citation lists and trial registries, and consult authors to obtain relevant articles. The retrieval time range will be from the establishment of the database to July 2020 to avoid omitting relevant studies. The primary outcome will be HbA1c. The secondary outcomes will be fasting plasma glucose, postprandial blood glucose, total cholesterol, triglyceride, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, systolic blood pressure, diastolic blood pressure, body mass index, waist circumference and death event. Two reviewers will independently conduct article screening and assessment of risk of bias, with a third reviewer arbitrating if necessary. We will give priority to the use of meta-analysis to evaluate the pooled effects of all outcomes. For the outcomes of unrecognised sources of heterogeneity, missing data and less than three related studies, narrative synthesis approach will be used. ETHICS AND DISSEMINATION: Ethical approval is not required for this systematic review. We plan to present the findings in a peer-reviewed scientific journal, relevant and responsible organisations, and training meetings. PROSPERO REGISTRATION NUMBER: CRD42020209011.

Self-rated health and health-related quality of life among Chinese residents, China, 2010.

BACKGROUND: Self-rated health (SRH) and health-related quality of life (HRQOL) are two outcome measures used to assess health status. However, little is known about population-based SRH and HRQOL in China. METHODS: Data from the 2010 China Chronic Disease and Risk Factor Surveillance, a nationally representative sample of 98,658 adults (≥18-year-old) residing in China, were analyzed. SRH was assessed by asking "Would you say that, in general, your health is very good, good, general, poor, or very poor?" HRQOL was assessed by asking "For about how many days during the past 30 days was your health not good due to physical illnesses, injuries, or mental unhealthy?". RESULTS: Overall, 6.3 % of participants rated their health as poor or very poor. The prevalence of poor/very poor health increased with advancing age ranging from 2.0 % in the 18-24 year-olds to 14.9 % in those ≥75 years-old, while it decreased with education levels from 13.0 % in illiterates/those with some primary school education to 2.2 % in college graduates or above. Additionally, women were more likely than men to rate their health as poor or very poor (7.2 % vs. 5.4 %). The reported rate of poor/very poor health was higher in western region residents compared to those in the east (7.4 % vs. 5.3 %). The mean numbers of self-reported physically unhealthy days, injury-caused unhealthy days, or mentally unhealthy days during the past 30 days were 1.48, 0.20, and 0.54, respectively. Older adults had more physically unhealthy days than the younger ones ranging from 2.92 days in those ≥ 75 year-old to 0.95 days in 18-24 year-olds. Women had more physically unhealthy days and mentally unhealthy days than men (1.72 vs. 1.23; 0.62 vs. 0.46, respectively). The highest mean number of physically unhealthy days (2.32) was reported by illiterates or those with some primary school education. The highest mean number of mentally unhealthy days (0.86) reported by college graduates or above. CONCLUSIONS: Substantial variations existed in SRH and HRQOL among age groups, gender groups, education groups, and across regions in China. Considering these disparities will be important when developing health policies and allocating resources.

[Self-rated health status among Chinese residents, China, 2010].

OBJECTIVE: To investigate the self-rated health status among Chinese residents in 2010. METHODS: Data was from the Non-communicable Disease & Risk Factor Surveillance in China, 2010. A total of 98 638 adults aged ≥ 18 years were included in the study. Self-rated health was assessed by four questions: (1) Would you assess your health status as very good or good, general (not good/not poor), poor or very poor? (2) How many days was your health not good for physical illness during the past 30 days? (3) How many days was your health not good for injury during the past 30 days? (4) How many days was your health not good for mental illness, which include stress and problem with emotions depression during the past 30 days? After being weighed according to complex sampling scheme and post-stratification, the sample was used to estimate the prevalence of self-rated health. The Rao-scott χ(2) test with different samples was adopted for comparison among groups. RESULTS: In total, 57.5% (95%CI:55.5%-59.5%) of the participants rated their health as being either very good or good, 36.2% (95%CI:34.5%-37.8%) as general, and only 6.3% (95%CI:5.7%-6.9%) as poor or very poor; In different age groups and gender, the differences were statistically significant (χ(2) values were 1179.88, 85.36, both P values were < 0.05) . The reported rate of poor or very poor health increased significantly with advancing age ranging from 2.0% (95%CI:1.5%-2.4%)in 18-24 year-old group to 14.9% (95%CI:12.6%-17.2%) in ≥ 75 year-old group; Females were more likely than males to rate their health as poor or very poor , respectively (7.2%; 95%CI 6.5%-7.9% and 5.4%; 95%CI:4.9%-5.9%). During the past 30 days 18.5% (95%CI:17.1%-19.8%) of the participants was not in good health for physical illness. The reported rate of physical illness increased significantly with advancing age (χ(2) = 211.99, P < 0.01), and it was the lowest in 25-34 year-old group (15.4%; 95%CI:13.7%-17.0%), and the highest in ≥ 75 year-old group (28.3%; 95%CI:24.9%-31.6%) . It was statistically higher among females (21.1%; 95%CI:19.5%-22.6%) compared to males (15.9%; 95%CI:14.6%-17.3%) (χ(2) = 231.81, P < 0.01); the reported rates of physical illness were 17.4% (95%CI:15.3%-19.5%) among residents in the east region, 17.2% (95%CI:14.7%-19.6%) in the middle region, and 21.5% (95%CI:18.7%-24.4%) in the western region(χ(2) = 6.75, P < 0.01). During the past 30 days 2.7% (95%CI:2.3%-3.2%) of the participants was not in good health for injure. The reported rate of injure decreased significantly with advancing age (χ(2) = 25.54, P < 0.01), and it was the highest in 18-24 year-old group (3.8%; 95%CI:2.6%-5.0%), and the lowest in 35-44 year-old group (2.3%; 95%CI:1.8%-2.7%) . It was statistically higher among males (3.0%; 95%CI:2.4%-3.5%) compared to females (2.5%; 95%CI:2.1%-2.9%) (χ(2) = 8.89 P < 0.01) ; the reported rates of injure were 2.3% (95%CI:1.9%-2.7%) among residents in the east region , 2.1% (1.7%-2.4%) in the middle region, and 4.1% (95%CI:2.6%-5.6%) in the west region (χ(2) = 16.26, P < 0.01). During the past 30 days 10.0% (95%CI:8.8%-11.3%) of the participants was not in good health for mental illness. The reported rate of mental illness decreased significantly with advancing age (χ(2) = 92.14 P < 0.01), and it was the highest in 18-24 year-old group (12.9%; 95%CI: 10.6%-15.2%), and the lowest in ≥ 75 year-old group (5.7%; 95%CI: 4.4%-7.0%) .It was statistically higher among females (10.8%; 95%CI:9.5%-12.1%) than males (9.2%; 95%CI:7.9%-10.5%) (χ(2) = 21.59, P < 0.01). CONCLUSION: The self-rated health status among Chinese residents was good in 2010. Substantial variation exists in self-rated health status across age groups, between genders, and across regions. Considering these disparities will be important for developing health policy and allocating resources.

[Association of pre-pregnancy body weight, gestational weight gain and postpartum weight retention among women in Beijing].

OBJECTIVE: To investigate the relationship of pre-pregnancy body weight, gestational weight gain and postpartum weight retention among women in Beijing. METHODS: Using a cohort design, 600 pregnant women who went to district obstetrics and gynecology hospital in Beijing to establish preconception health care card from 5(th) February to 15(th) March 2009 were recruited. A total of 112 subjects (109 with valid data), 20% of that in baseline, were followed up at 6 months after delivery.70 subjects (66 with valid data) were followed up at one year after delivery. Weight, weight changes and postpartum weight retention were measured for low weight (BMI < 18.5 kg/m(2)), normal weight (18.5 kg/m(2) ≤ BMI ≤ 24.0 kg/m(2)) and overweight or obesity (BMI > 24.0 kg/m(2)) group. RESULTS: The pre-pregnancy weight and antenatal weight were (54.8 ± 8.0) and (70.8 ± 9.3) kg respectively. Gestational weight gain was (16.0 ± 7.0) kg. The postpartum weight of 6 and 12 months were (60.5 ± 9.4) and (57.6 ± 8.6) kg respectively. Comparing to pre-pregnancy, postpartum weight retention in 6 months and 12 months were (5.7 ± 4.5) and (2.7 ± 4.5) kg, weight retention rates were (10.6 ± 8.6)% and (5.2 ± 9.3)%. Antenatal weight among low pre-pregnancy weight group, normal weight and overweight and obese women were (62.6 ± 5.7), (69.9 ± 6.6) and (84.2 ± 9.9) kg, and weight at postpartum 12 months among 3 groups were (49.3 ± 3.2), (56.5 ± 6.9) and (70.5 ± 6.0) kg respectively (F = 25.3, P < 0.01); At postpartum 12 months, low pre-pregnancy weight group ((5.6 ± 5.9) kg), overweight and obese women group ((4.7 ± 1.9) kg) postpartum weight retention was significantly higher than that of the normal weight group ((1.8 ± 4.3) kg) (F = 3.82, P < 0.05). CONCLUSION: The pre-pregnancy body weight is a key risk factor in weight gain during pregnancy and postpartum weight retention.