Objectives: This study aims to understand the disability status of the elderly residents of a County (Guangxi Province, China) and explore its influencing factors. Methods: Respondents consisted of 2300 elderly people aged 60 and above from three townships in the county we studied. The Activities of Daily Living (ADL) Scale was used to assess the disability of the elderly sample. Chi-square test was applied to compare the disability rate among the elderly with different demographic characteristics. The graph showed the disability rates of ADL, six items of Physical Activities of Daily Living (PADL) and eight items of Instrumental Activities of Daily Living (IADL) at different ages. Binary logistic regression was used to analyze the influencing factors of disability rate among the elderly. Results: The disability rates of ADL, PADL, and IADL in the elderly were 43.4%, 11.6%, and 42.4%, respectively. As with the increase in age, the disability rates of ADL, IADL, PADL, and their 14 items gradually increased (p < 0.05), with walking, using the telephone, and using public vehicles having higher disability rates than other items. The influencing factors of ADL disability were gender (OR = 0.579, 95%CI = 0.441–0.759), age (OR = 2.270, 95%CI = 1.867–2.759; OR = 4.719, 95%CI = 2.998–7.429; OR = 6.249, 95%CI = 3.667–10.648), educational level (OR = 2.844, 95%CI = 2.076–3.897; OR = 1.677, 95%CI = 1.246–2.230), and having metabolic syndrome (MetS) (OR = 1.298, 95%CI = 1.044–1.613). Compared with ADL, the influencing factor of PADL disability was gender, whereas that of IADL disability was whether someone had MetS. Conclusions: With age, the possibility of ADL, PADL, and IADL damage in the elderly is higher. Gender, age, educational level, the number of chronic diseases, and whether someone has MetS might be the influencing factors of disability. Interventions should be taken from a variety of sources specific to the content of each entry.

This meta-analysis aimed to estimate the prevalence of burnout among medical students in China. A systematic search from the following electronic databases: China National Knowledge Infrastructure, Wangfang database, VIP database, Chinese biomedical literature database, PubMed, Embase, Web of Science, and Google Scholar was independently conducted by 2 reviewers from inception to September 2019. The data were analyzed using stata software Version 11. Heterogeneity was assessed using I ² tests, and publication bias was evaluated using funnel plots and Egger's test. The source of heterogeneity among subgroups was determined by subgroup analysis of different parameters. A total of 48 articles with a sample size of 29,020 met the inclusion criteria. The aggregate prevalence of learning burnout was 45.9% (95% confidence interval [CI] = 38.1%–53.8%). The prevalence rate of high emotional exhaustion was 37.5% (95% CI: 21.4%–53.7%). The percentage was 44.0% (95% CI: 29.2%–58.8%) for low personal accomplishment. The prevalence rate was 36.0% (95% CI: 23.0%–48.9%) in depersonalization dimension. In the subgroup analysis by specialty, the prevalence of burnout was 30.3% (95% CI: 28.6%–32.0%) for clinical medicine and 43.8% (95% CI: 41.8%–45.8%) for other medical specialties. The total prevalence of burnout between men and women was 46.4% (95% CI: 44.8%–47.9%) and 46.6% (95% CI: 45.5%–47.6%), respectively. The prevalence of burnout with Rong Lian's scale was 43.7% (42.1%–45.2%), and that with the other scales was 51.4% (50.4%–52.4%). The prevalence rates were 62.9% (61.3%–64.6%), 58.7% (56.3%–61.1%), 46.5% (42.9%–50.2%), and 56.0% (51.6%–60.4%) from Grades 1 to 4, respectively. There was a statistically significant difference among the different grades (P = .000). Our findings suggest a high prevalence of burnout among medical students. Society, universities, and families should take appropriate measures and allot more care to prevent burnout among medical students.

Background: To investigate the risk factors of child lead poisoning in China. Methods: A document retrieval was performed using MeSH (Medical subject heading terms) and key words. The Newcastle-Ottawa Scale (NOS) was used to assess the quality of the studies, and the pooled odd ratios with a 95% confidence interval were used to identify the risk factors. We employed Review Manager 5.2 and Stata 10.0 to analyze the data. Heterogeneity was assessed by both the Chi-square and I² tests, and publication bias was evaluated using a funnel plot and Egger’s test. Results: Thirty-four articles reporting 13,587 lead-poisoned children met the inclusion criteria. Unhealthy lifestyle and behaviors, environmental pollution around the home and potential for parents’ occupational exposure to lead were risk factors of child lead poisoning in the pooled analyses. Our assessments yielded no severe publication biases. Conclusions: Seventeen risk factors are associated with child lead poisoning, which can be used to identify high-risk children. Health education and promotion campaigns should be designed in order to minimize or prevent child lead poisoning in China.

Objective: This study aimed to assess the relationship between the dietary intake of saturated fatty acids (SFAs) and its subtypes (C4:0, C6:0, C8:0, C10:0, C12:0, C14:0, C16:0, and C18:0) and hypertension.Design, participants, and methods: Adults aged 20 years and older based used the U.S. Health and Nutrition Survey (1999–2018) were used as participants. Two averages of 24 h dietary recall data were obtained for weight-adjusted continuous cross-sectional analysis. Two 24-h recall interview data means were obtained for weight-adjusted continuous cross-sectional analysis. A logistic regression model was used to estimate the weighted odds ratio (OR) and its 95% confidence interval (CI) for hypertension.Results: The study included 7,222 respondents over 20 years of age with a hypertension prevalence of 23.2% and a significant difference in the dietary intake of carbohydrates among patients with hypertension. Dietary intake of nutrients was more in men than in women with hypertension. After adjusting for confounders, adjusting for nutrients, and reducing covariance among nutrients, the OR (95% CI) for women’s dietary intake of SFAs, C14:0, C16:0, C18:0 fourth quartile, and C14:0 third quartile were 0.57 (0.34, 0.95), 0.57 (0.34, 0.95), 0.57 (0.34, 0.95), 0.57 (0.34, 0.95), and 0.57 (0.34, 0.95), respectively, which may be a risk factor for hypertension. In older (≥65, years) respondents, the OR (95% CI) for dietary intake of SFAs, C4:0, C14:0, C16:0 fourth quartile, and C12:0 third quartile were 0.42 (0.21, 0.86), 0.46 (0.22, 0.95), 0.39 (0.18, 0.85), 0.38 (0.17, 0.84), and 0.45 (0.20, 0.99), respectively, which may be a protective factor for hypertension.Conclusion: The study was based on the American Health and Nutrition Examination Survey, and a strong correlation was found between dietary intake of SFAs, C14:0, C16:0, and C18:0 and hypertension in women (dietary intake of SFAs, C4:0, C12:0, C14:0, and C16:0) and middle-aged and older adults (dietary intake of SFAs, C4:0, C12:0, C14:0, and C16:0). In addition, dietary nutrient intake should be carefully selected for the rational prevention of hypertension.

Background: Exposure to heavy metals in the environment is widespread, while the relationship between combined exposure to heavy metals and dyslipidemia is unclear.Methods: A cross-sectional study was performed, and 3544 participants aged 30 years or older were included in the analyses. Heavy metal concentrations in plasma were based on inductively coupled plasma‒mass spectrometry. The relationship between heavy metals and dyslipidemia was estimated by logistic regression. BKMR was used to evaluate metal mixtures and their potential interactions.Results: In logistic regression analysis, participants in the fourth quartile of Fe and Zn (Fe > 1352.38 µg/L; Zn > 4401.42 µg/L) had a relatively higher risk of dyslipidemia (Fe, OR = 1.13, 95% CI: 0.92,1.38; Zn, OR = 1.30, 95% CI: 1.03,1.64). After sex stratification, females in the third quartile of plasma Zn (1062.05-4401.42 µg/L) had a higher relative risk of dyslipidemia (OR = 1.75, 95% CI: 1.28, 2.38). In BKMR analysis, metal mixtures were negatively associated with dyslipidemia in females when all metal concentrations were above the 50th percentile. In the total population (estimated from 0.030 to 0.031), As was positively associated with dyslipidemia when other metals were controlled at the 25th, 50th, or 75th percentile, respectively, and As was below the 75th percentile. In females (estimated from − 0.037 to -0.031), Zn was negatively associated with dyslipidemia when it was above the 50th percentile.Conclusion: This study indicated that As was positively associated with dyslipidemia and that Zn may be negatively associated with dyslipidemia in females. Combined metal exposure was negatively associated with dyslipidemia in females. Females with low plasma Zn levels are more likely to develop dyslipidemia and should receive more clinical attention in this population.

The study aims to determine the spatial and temporal variation of a longevous region and explore the correlation between longevity and socioeconomic development. Population data at the township level were obtained from the last four population censuses (1982–2010). Five main lifespan indicators and the Human Development Index (HDI) were calculated. Getis-Ord G*, Gravity modeling, and Pearson’s r between lifespan indicators and HDI were applied. In this study, a stable longevous gathering area was discovered in Hechi during different periods. Under the influence of social and economic development, more longevous areas appeared. However, the effects of genetic and natural environmental factors on longevity were always dominant in this remote and mountainous city. Furthermore, longevity indicators lacked any significant correlation with life expectancy. No significant positive correlation was detected between lifespan indicators and HDI. Thus, we conclude that lifespan indicators can determine the spatial distribution and variation pattern of longevity from multiple dimensions. The geographical scope of longevity in Hechi City is gradually expanding, and significant spatial clustering was detected in southwestern, southern, and eastern parts of Hechi. This study also found that social economic development is likely to have a certain impact on new longevous areas, but their role on extreme longevity is not significant.