Objective: To investigate associations between visceral adiposity index (VAI) and cardiovascular and cerebrovascular diseases (CCDs) in the American population from 1999 to 2018.Methods: Data from the National Health and Nutrition Examination Survey (1998–2018) were analyzed in this study. Specifically, VAI scores were calculated using sex-specific equations that incorporate body mass index, waist circumference (WC), high-density lipoprotein (HDL), triglycerides (TG), and cholesterol. Weighted logistic regression analysis was conducted to assess the relationship between VAI tertile and increased risk of CCDs. Restricted cubic splines were used to evaluate the non-linear relationship between VAI and CCDs, such as heart failure, angina, heart attack, stroke, hypertension, and coronary heart disease. Sensitivity analysis was conducted, using VAI quartiles as independent variables.Results: A total of 22,622 subjects aged over 20 years were included. In the fully adjusted model after controlling for covariates, the third VAI tertile was more strongly associated with CCDs than the first VAI tertile, with odds ratio (OR) and 95% confidence interval (95% CI) values for angina of 2.86, 1.68–4.85; heart attack, 1.75, 1.14–2.69; stroke, 2.01, 1.23–3.26; hypertension, 2.28, 1.86–2.78; and coronary heart disease, 1.78, 1.32–2.41; but there was no significant association with heart failure (p > 0.05). Restricted cubic splines revealed parabolic relationships between VAI score and angina (p for non-linear = 0.03), coronary heart disease (p for non-linear = 0.01), and hypertension (p for non-linear < 0.001). Sensitivity analysis indicated that the fourth VAI quartile was more strongly associated with an increased risk of angina (OR = 2.92, 95% CI, 1.49–5.69), hypertension (OR = 2.37, 95% CI, 1.90–2.97), heart attack (OR = 1.77, 95% CI, 1.09–2.88), and coronary heart disease (OR = 1.89, 95% CI, 1.24–2.86) than the first VAI quartile. VAI had superior predictive power for prevalent CCDs than other independent indicators (p < 0.05).Conclusion: Visceral adiposity index score is positively correlated with angina, heart attack, stroke, hypertension, and coronary heart disease, but not heart failure, and the relationships between VAI score and angina, hypertension, and coronary heart disease are non-linear.

Background: Hand-foot-and-mouth disease (HFMD) is considered to be self-limited, however, severe HFMD is a deadly threat for children worldwide, therefore, it is essential to define the clinical and epidemiologic characteristics of children with severe HFMD and identify the risk factors of death. Methods: Between 2013 and 2018, children who diagnosed with severe HFMD from Chongqing, China were enrolled in this population-based study. A total of 459 severe HFMD children cases were identified during the study period, including 415 survivors and 44 fatal cases. Demographic, geographical, epidemiological and clinical data of the cases were acquired and analyzed. Results: Risk factors of the death because of severe HFMD children included female, aged 1 ~ 3 years, enterovirus 71 infection, falling ill in winter, more than one children in home, being taken care of by grandparents, the caregivers’ education not more than 9 years, having fever more than 3 days, consciousness disorders, general weakness, vomiting, general weakness, abnormal pupillary light reflex, repeated cough, tachypnea, moist rales, white frothy sputum, pink frothy sputum, and cyanosis on lips or the whole body, tachycardia, arrhythmia, cold limbs, pale complexion, weakened pulse. (all p < 0.05). Spatial-temporal analysis detected high-value clusters, the most likely cluster located at rural countries in the northern parts of Chongqing, from January, 2015 to July, 2017. (p < 0.01). Besides, some urban districts were also found high incidence of severe HFMD cases according to the incidence maps. Conclusions: The detection of clinical risk factors and the temporal, spatial and socio-demographic distribution epidemiological characteristics of severe HFMD contribute to the timely diagnosis and intervention, the results of this study can be the reference of further clinical and public health practice.

Background: According to the World Health Organization, foodborne disease is a significant public health issue. We will choose the best model to predict foodborne disease by comparison, to provide evidence for government policies to prevent foodborne illness. Methods: The foodborne disease monthly incidence data from June 2017 to April 2022 were obtained from the Chongqing Nan’an District Center for Disease Prevention and Control. Data from June 2017 to June 2021 were used to train the model, and the last 10 months of incidence were used for prediction and validation The incidence was fitted using the seasonal autoregressive integrated moving average (SARIMA) model, Holt-Winters model and Exponential Smoothing (ETS) model. Besides, we used MSE, MAE, RMSE to determine which model fits better. Results: During June 2017 to April 2022, the incidence of foodborne disease showed seasonal changes, the months with the highest incidence are June to November. The optimal model of SARIMA is SARIMA (1,0,0) (1,1,0)₁₂. The MSE, MAE, RMSE of the Holt-Winters model are 8.78, 2.33 and 2.96 respectively, which less than those of the SARIMA and ETS model, and its prediction curve is closer to the true value. The optimal model has good predictive performance. Conclusion: Based on the results, Holt-Winters model produces better prediction accuracy of the model.

Background: Mumps is classified as a class C infection disease in China, and the Chongqing area has one of the highest incidence rates in the country. We aimed to establish a prediction model for mumps in Chongqing and analyze its seasonality, which is important for risk analysis and allocation of resources in the health sector. Methods: Data on incidence of mumps from January 2004 to December 2018 were obtained from Chongqing Municipal Bureau of Disease Control and Prevention. The incidence of mumps from 2004 to 2017 was fitted using a seasonal autoregressive comprehensive moving average (SARIMA) model. The root mean square error (RMSE) and mean absolute percentage error (MAPE) were used to compare the goodness of fit of the models. The 2018 incidence data were used for validation. Results: From 2004 to 2018, a total of 159,181 cases (93,655 males and 65,526 females) of mumps were reported in Chongqing, with significantly more men than women. The age group of 0–19 years old accounted for 92.41% of all reported cases, and students made up the largest proportion (62.83%), followed by scattered children and children in kindergarten. The SARIMA(2, 1, 1) × (0, 1, 1)₁₂ was the best fit model, RMSE and MAPE were 0.9950 and 39.8396%, respectively. Conclusion: Based on the study findings, the incidence of mumps in Chongqing has an obvious seasonal trend, and SARIMA(2, 1, 1) × (0, 1, 1)₁₂ model can also predict the incidence of mumps well. The SARIMA model of time series analysis is a feasible and simple method for predicting mumps in Chongqing.

While studies on human immunodeficiency virus self-testing (HIVST) continue to accumulate after the World Health Organization’s recommendation of HIVST as an additional approach to HIV testing services in 2016, few studies have focused on men who have sex with men (MSM) in Chinese cities. A cross-sectional study was conducted to describe the HIVST status of MSM in Chongqing, China. MSM participants were recruited by random sampling, and qualified interviewers collected data, using confidential self-administered questionnaires. Blood specimens were collected for HIV antibody detection. The survey evaluated the uptake and accuracy of HIVST kits and identified factors that may be associated with HIVST. The proportion of HIVST uptake was 15.6%. The sensitivity and specificity of HIVST were 74.2% (95% confidence interval [CI] 66.6%–80.7%) and 99.0% (95% CI 96.9%–99.7%), respectively. The consistency between the HIVST kit and antibody detection results was 90.5% (95% CI 87.5%–93.0%), and the Kappa value was 0.777 (p < 0.001). The positive predictive value of self-testing kits is 80.9% and the negative predictive value is 17.7%. Having been tested ≥2 times in the last year, higher educational levels, and higher scores of basic HIV/AIDS knowledge facilitated higher uptake of HIVST. Self-reported existing barriers for HIVST uptake included older age, marital status, and having resided in Chongqing for more than two years.

(1) Background: During the past 3 years, the COVID-19 pandemic has severely affected the normal school schedule of college students, jeopardizing their mental health, sleep quality, and interpersonal relationships. However, previous studies have focused on the dimension of social support received, and few studies have measured in depth the association of support received from family on adolescents’ physical and mental health. Therefore, this study explored the associations between family support received by Chinese college students during COVID-19 pandemic online classes, stress and sleep quality, and the mediating role of stress. (2) Methods: A cross-sectional study conducted at Chongqing Medical University recruited 712 college students through a university-wide incidental random sample using the Questionnaire Star platform. Statistical description and correlation analysis was conducted using SPSS 25.0, and structural equation modeling was constructed using AMOS 22.0 to test for mediating effects; (3) Results: The family support score of college students during the COVID-19 pandemic online course was 19.41 ± 4.62. Correlation analysis showed that sleep quality was negatively correlated with family support (r = −0.224, p < 0.01), positively correlated with stress (r = 0.324, p < 0.01), and family support was negatively correlated with stress (r = −0.159, p < 0.01). The results of structural equation modeling showed that stress partially mediated the relationship between family support and sleep quality among college students (indirect effect = −0.150, p < 0.01, SE = 0.013,95% CI = [−0.208, −0.064]). The model R2 was 36.4%. (4) Conclusions: Schools should consider implementing sleep education, and stress relief curriculum measures to improve the quality of students’ sleep, and should focus on the role that family plays during online classes. This will help students overcome the negative emotional effects of stress in the COVID-19 pandemic and improve their learning efficiency and physical and mental health.