Acquired immune deficiency syndrome (AIDS) is a serious public health problem. This study aims to establish a combined model of seasonal autoregressive integrated moving average (SARIMA) and Prophet models based on an L1-norm to predict the incidence of AIDS in Henan province, China. The monthly incidences of AIDS in Henan province from 2012 to 2020 were obtained from the Health Commission of Henan Province. A SARIMA model, a Prophet model, and two combined models were adopted to fit the monthly incidence of AIDS using the data from January 2012 to December 2019. The data from January 2020 to December 2020 was used to verify. The mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) were used to compare the prediction effect among the models. The results showed that the monthly incidence fluctuated from 0.05 to 0.50 per 100,000 individuals, and the monthly incidence of AIDS had a certain periodicity in Henan province. In addition, the prediction effect of the Prophet model was better than SARIMA model, the combined model was better than the single models, and the combined model based on the L1-norm had the best effect values (MSE = 0.0056, MAE = 0.0553, MAPE = 43.5337). This indicated that, compared with the L2-norm, the L1-norm improved the prediction accuracy of the combined model. The combined model of SARIMA and Prophet based on the L1-norm is a suitable method to predict the incidence of AIDS in Henan. Our findings can provide theoretical evidence for the government to formulate policies regarding AIDS prevention.

Aims: Previous studies investigated the associations between sleep traits and cardiac diseases, but the evidence for the causal inferences was unclear. This study aimed to explore the causal relationship between sleep and cardiac diseases by virtue of Mendelian randomization (MR). Methods and results: Summary-level data for exposure variables (sleep duration, chronotype, and insomnia) and outcome variables (ischaemic heart disease, atrial fibrillation, myocardial infarction, and heart failure) were derived from UK Biobank. Data from the FinnGen consortium was used as a robustness check. In MR analysis, the inverse variance weighted (IVW) method was applied to infer causality between exposure and outcome. MR-Egger regression was used to identify pleiotropy, and MR-PRESSO outlier test was used to remove the pleiotropy of the genetic instruments. Based on UK Biobank, MR analysis suggested that sleep duration was weakly associated with atrial fibrillation (OR = 0.9999, 95% CI: 0.9998–0.9999) and ischaemic heart disease (OR = 0.9997, 95% CI: 0.9995–0.9998). Insomnia was associated with ischaemic heart disease (OR = 1.0117, 95% CI: 1.0051–1.0183) and myocardial infarction (OR = 1.0049, 95% CI: 1.0019–1.0079). No associations were found between chronotype and cardiac diseases (P > 0.05). We did not find pleiotropy except for insomnia with ischaemic heart disease and myocardial infarction using MR-Egger regression, and MR-PRESSO analysis consistent with IVW. Finally, we obtained the same direction as with UK Biobank using the FinnGen data. Conclusions: Sleep duration and insomnia might be the potential causal risk factors of cardiac diseases. As the OR was small, these associations are probably not clinically relevant. Further validation studies are needed.

Long-term effects of outdoor and indoor air pollution on chronic liver disease (CLD) remain unclear. Thus, the study was conducted to investigate the relationship between prolonged exposure to ambient particulate matter (PM₁, PM_2.5 and PM₁₀) and household fuel usage with CLD. Data from the China Health and Retirement Longitudinal Study (CHARLS) covering the years 2011 to 2020 were employed. In the cross-sectional analysis, 16,680 participants were included, while 12,969 participants were enrolled in the longitudinal study. The associations between various sizes of particulate matter and CLD were elucidated using logistic regression model and generalized linear-mixed models. Additionally, the additive effects of ambient particulate matter (PM) levels and the utilization of solid fuels for cooking were investigated, with a comparison of effect sizes between converted and non-converted fuel types. Over a 10-year follow-up period, 746 (5.75 %) individuals developed CLD. For a 1-year average concentrations, PM₁, PM_2.5 and PM₁₀ were each linked to a 1.549 (95 %CI:1.522-1.576), 1.296 (95 %CI:1.276-1.317) and 1.134 (95 %CI:1.118-1.150) fold risk of incident CLD per 10 μg/m³ increase, respectively. A similar effect of PM concentrations over a 2-year period on CLD was observed. Moreover, simultaneous exposure to ambient PM and solid fuels is associated with an increased risk of CLD. Those who continue using solid fuels may face a higher risk of CLD compared to individuals who switch to cleaner cooking fuels. Female participants, smokers, and individuals with shorter sleep duration and multiple chronic diseases exhibited slightly stronger effects. Long-term exposure to various sizes of PM (PM_1, PM_2.5, PM₁₀) has been linked to an elevated risk of CLD incidence. Co-exposure to ambient PM and solid fuels is associated with higher health risks.

About 8% of the Americans contract influenza during an average season according to the Centers for Disease Control and Prevention in the United States. It is necessary to strengthen the early warning for influenza and the prediction of public health. In this study, Spatial autocorrelation analysis and spatial scanning analysis were used to identify the spatiotemporal patterns of influenza-like illness (ILI) prevalence in the United States, during the 2011–2020 transmission seasons. A seasonal autoregressive integrated moving average (SARIMA) model was constructed to predict the influenza incidence of high-risk states. We found the highest incidence of ILI was mainly concentrated in the states of Louisiana, District of Columbia and Virginia. Mississippi was a high-risk state with a higher influenza incidence, and exhibited a high-high cluster with neighboring states. A SARIMA (1, 0, 0) (1, 1, 0)₅₂ model was suitable for forecasting the ILI incidence of Mississippi. The relative errors between actual values and predicted values indicated that the predicted values matched the actual values well. Influenza is still an important health problem in the United States. The spread of ILI varies by season and geographical region. The peak season of influenza was the winter and spring, and the states with higher influenza rates are concentrated in the southeast. Increased surveillance in high-risk states could help control the spread of the influenza.

The intake of antioxidant vitamins can scavenge free radicals and reduce oxidative stress, which may be beneficial for stroke. However, the relationship between total antioxidant capacity (TAC) of antioxidant vitamins and stroke is controversial. This study aims to investigate the association between dietary TAC and the risk of stroke in US adults. This study included participants over 20 years old from the 2001–2018 National Health and Nutrition Examination Survey (NHANES). Data from two 24 h dietary recalls were used to estimate the usual intake of antioxidant vitamins. TAC was calculated by the vitamin C equivalent antioxidant capacity reference values of individual antioxidant vitamins. Survey-weighted generalized linear models were performed to evaluate the relationship between TAC and the risk of stroke. A restricted cubic spline regression model was used to investigate the dose–response association. A total of 37,045 participants was involved, of whom 1391 suffered a stroke. Compared with the first tertile, the participants in the second tertile of TAC showed a lower risk of stroke (OR = 0.788, 95% CI: 0.662, 0.936) after adjusting for potential risk factors. The dose–response analysis showed a gradual increase in the risk of stroke as TAC decreases. Subgroups analyses indicated that this association was primarily in the population of those aged over 60 years old, who were female, consumed alcohol, were a former smoker and inactive. The sensitivity analysis presented consistent results. These results suggest that deficiency of dietary TAC was associated with an increased risk of stroke, particularly in populations with underlying oxidative stress injury.

Purposes: Observational studies indicate that birth weight and childhood obesity are associated with essential hypertension, but their causal effect on essential hypertension remains unclear. The aim of our study is to elucidate the causal relationship between birth weight, childhood obesity, and essential hypertension by Mendelian randomization (MR) with genetic variants as instrumental variables (IVs). Methods: We identified IVs based on single nucleotide polymorphisms (SNPs) associated with birth weight (n = 160 295) and childhood obesity (n = 6889, 1509 cases and 5380 controls) from the meta-analysis of a genome-wide association study. Summary level data from the UK Biobank essential hypertension consortium (n = 463 010, 54 358 cases and 408 652 controls) was used to analyze the relationship between IVs and essential hypertension. Two MR analysis methods, two threshold values of selecting IVs, and leave-one-out analysis were used to ensure the robustness of the results. Results: Genetic predisposition to higher birth weight did not increase the risk of essential hypertension. In contrast, per one standard deviation increase in childhood body mass index was significantly associated with an increased risk of essential hypertension (odds ratio = 1.0075, 95% confidence interval: 1.0035–1.0116) when using seven SNPs that achieved genome-wide significance (P < 5 × 10⁻⁸). Sensitivity analysis and MR-Egger regression indicated that the results were robust and not influenced by pleiotropy. Conclusions: No evidence of an association between birth weight and essential hypertension was found. Childhood obesity, however, showed a causal relationship with the risk of essential hypertension, which was helpful to understand the mechanisms of essential hypertension and develop strategies for its prevention.