Simulating the impact of optimized prevention and control measures on the transmission of monkeypox in the United States: A model-based study.

This study aimed to develop a modified susceptible-exposed-infected-recovered (SEIR) model to evaluate monkeypox epidemics in the United States and explore more optimized prevention and control measures. To further assess the impact of public health measures on the transmission of monkeypox, different intervention scenarios were developed based on the classic SEIR model, considering reducing contact, enhancing vaccination, diagnosis delay, and environmental transmission risk, respectively. We evaluated the impact of different measures by simulating their spread in different scenarios. During the simulation period, 8709 people were infected with monkeypox. The simulation analysis showed that: (1) the most effective measures to control monkeypox transmission during the early stage of the epidemic were reducing contact and enhancing vaccination, with cumulative infections at 51.20% and 41.90% of baseline levels, respectively; (2) shortening diagnosis time would delay the peak time of the epidemic by 96 days; and (3) the risk of environmental transmission of monkeypox virus was relatively low. This study indirectly proved the effectiveness of the prevention and control measures, such as reducing contact, enhancing vaccination, shortening diagnosis time, and low risk of environmental transmission, which also provided an important reference and containment experience for nonepidemic countries.

Interaction between home and community-based services and PM2.5 on cognition: A prospective cohort study of Chinese elderly.

PM2.5 and home and community-based services (HCBSs) had been shown to affect cognition, but the evidence on their joint effects was limited. Aimed to study the joint effects of HCBSs and PM2.5 on cognition, we utilized the follow-up data of participants in the Chinese Longitudinal Health Longevity Survey (CLHLS) who were 65 years of age or older and had normal cognitive function at baseline for the 2008-2018, 2011-2018, and 2014-2018 waves. 16,954, 9,765, and 7192 participants from each of these three waves were initially recruited, respectively. The PM2.5 concentration data of each province in China from 2008 to 2018 was obtained from the Atmospheric Composition Analysis Group. Participants were asked what kind of HCBSs were available in their community. The cognitive status of the participants was evaluated by the Chinese version of Mini-Mental State Examination (CMMSE). We applied the Cox proportional hazard regression model to investigate the joint effects of HCBSs and PM2.5 on cognition and further stratified the analysis according to HCBSs. Hazard ratio (HR) and 95% confidence interval (95% CI) were calculated based on Cox models. During a median follow-up period of 5.2 years, 911 (8.8%) participants with normal baseline cognitive function developed cognitive impairment. Compared to participants without HCBSs and exposed to the highest level of PM2.5, those with HCBSs and exposed to the lowest level of PM2.5 had a significantly reduced risk of developing cognitive impairment (HR = 0.428, 95% CI: 0.303-0.605). The results from the stratified analysis revealed that the detrimental effect of PM2.5 on cognition was more pronounced in participants without HCBSs (HR = 3.44, 95% CI: 2.18-5.41) compared with those with HCBSs (HR = 1.42, 95% CI: 0.77-2.61). HCBSs may attenuate the harmful impact of PM2.5 on cognitive status in the elderly Chinese and the government should further promote the application of HCBSs.

Traffic-related air pollution, adherence to healthy lifestyles, and risk of cognitive impairment: A nationwide population-based study.

BACKGROUND: Traffic-related air pollution (TRAP) is a risk factor for cognitive function, whereas healthy lifestyles are associated with better cognition. We aimed to examine their joint effects on cognition among the Chinese elderly. METHODS: The data from the Chinese Longitudinal Healthy Longevity Survey was used. Participants' cognitive performance was assessed by the Chinese version of the mini-mental state examination. Residential proximity to major roadways was obtained through self-report and categorized into five categories: > 300 m, 201-300 m, 101-200 m, 50-100 m, and < 50 m, serving as a surrogate for TRAP. Six lifestyle behaviors (smoking, drinking, exercise, body mass index, sleep duration, and dietary diversity) were taken into account to calculate healthy lifestyle scores. The scores ranged from zero to six and were then divided into three groups: healthy (5-6), intermediate (2-4), and unhealthy (0-1). Logistic regression models were applied to investigate the joint effects of TRAP and healthy lifestyle scores on cognition. RESULTS: Compared to participants living < 50 m from major roadways and adopting an unhealthy lifestyle, those living > 300 m from major roadways and adopting a healthy lifestyle had a significantly decreased risk of cognitive impairment. Stratified analysis indicated that the associations between TRAP and cognitive impairment were more pronounced among participants adopting an unhealthy lifestyle compared to the participants adopting a healthy lifestyle. CONCLUSIONS: TRAP may impair cognitive function, and its detrimental impacts may be lessened by healthy lifestyles.

Changing trends in the disease burden of non-melanoma skin cancer globally from 1990 to 2019 and its predicted level in 25 years.

BACKGROUND: The disease burden of non-melanoma skin cancer (NMSC) has become a significant public health threat. We aimed to conduct a comprehensive analysis to mitigate the health hazards of NMSC. METHODS: This study had three objectives. First, we reported the NMSC-related disease burden globally and for different subgroups (sex, socio-demographic index (SDI), etiology, and countries) in 2019. Second, we examined the temporal trend of the disease burden from 1990 to 2019. Finally, we used the Bayesian age-period-cohort (BAPC) model integrated nested Laplacian approximation to predict the disease burden in the coming 25 years. The Norpred age-period-cohort (APC) model and the Autoregressive Integrated Moving Average (ARIMA) model were used for sensitivity analysis. RESULTS: The disease burden was significantly higher in males than in females in 2019. The results showed significant differences in disease burden in different SDI regions. The better the socio-economic development, the heavier the disease burden of NMSC. The number of new cases and the ASIR of basal cell carcinoma (BCC) were higher than that of squamous cell carcinoma (SCC) in 2019 globally. However, the number of DALYs and the age-standardized DALYs rate were the opposite. There were statistically significant differences among different countries. The age-standardized incidence rate (ASIR) of NMSC increased from 54.08/100,000 (95% uncertainty interval (UI): 46.97, 62.08) in 1990 to 79.10/100,000 (95% UI: 72.29, 86.63) in 2019, with an estimated annual percentage change (EAPC) of 1.78. Other indicators (the number of new cases, the number of deaths, the number of disability-adjusted life years (DALYs), the age-standardized mortality rate (ASMR), and the age-standardized DALYs rate) showed the same trend. Our predictions suggested that the number of new cases, deaths, and DALYs attributable to NMSC would increase by at least 1.5 times from 2020 to 2044. CONCLUSIONS: The disease burden attributable to NMSC will continue to increase or remain stable at high levels. Therefore, relevant policies should be developed to manage NMSC, and measures should be taken to target risk factors and high-risk groups.

Changing trends in the air pollution-related disease burden from 1990 to 2019 and its predicted level in 25 years.

In the twenty-first century, exposure to air pollution has become a threat to human health worldwide due to industrial development. Timely, comprehensive, and reliable assessment and prediction of disease burden can help mitigate the health hazards of air pollution. This study conducted a two-stage analysis. First, we reported the air pollution-related disease burden globally and for different subgroups like socio-demographic index (SDI), sex, and age. We analyzed the trend of the disease burden from 1990 to 2019. In addition, we explored whether and how some national indicators modified the disease burden. Second, we predicted the number and the age-standardized rates of death and disability-adjusted life years (DALYs) attributable to air pollution from 2020 to 2044 by the autoregressive integrated moving average (ARIMA) model and exponential smoothing model. The age-period-cohort (APC) model in the maximum likelihood framework and the Bayesian APC model integrated nested Laplace approximations (INLAs) were further applied to perform sensitivity analysis. In 2019, air pollution accounted for 11.62% of death and 0.84% of DALY worldwide. The corresponding age-standardized rate was 85.62 (95% uncertainty interval (UI): 75.71, 96.07) and 2791.08 (95% UI: 2468.81, 3141.39) per 100,000 population. From 1990 to 2019, the number of death attributable to air pollution remained stable, and the number of DALY exhibited a downward trend. The corresponding age-standardized rates both declined. In some countries with larger population densities, higher proportions of elders, and lower proportions of females, the disease burden attributable to air pollution was lower. The predicted results showed that the number of air pollution-related death and DALY would increase. This study comprehensively assessed and predicted the air pollution-related disease burden worldwide. The results indicated that the disease burden would remain very serious in the future. Hence, some relevant policies should be developed to prevent and manage air pollution.

Interaction between the animal-based dietary pattern and green space on cognitive function among Chinese older adults: A prospective cohort study.

Green space is associated with better cognition, while the animal-based dietary pattern can be a risk factor. We aimed to verify the associations and explore their interaction among the elderly. The China Longitudinal Healthy Longevity Survey (CLHLS) cohort including 17,827 participants was used. The average green space coverage rate was used to measure green space exposure. The animal-based diet index (ADI) was scored based on the non-quantitative frequency questionnaire of ten types of food intake (three types of animal foods and seven types of plant foods). We used the Mini-Mental State Examination (MMSE) to assess cognitive function. The Cox proportional hazard regression was applied to explore the correlations and interactions. In the models, we gradually adjusted for the potential risk factors. Compared with participants living in the area with the lowest green space, those living with the highest were associated with a 20% decrease in the risk of cognitive impairment (hazard ratio (HR): 0.80, 95% CI: 0.73, 0.89). As for ADI, the highest group was related to a 64% increase in the risk of cognitive impairment (HR: 1.64, 95% CI: 1.38, 1.95). The protective effect of the highest green space group on cognitive impairment was more evident among participants with low ADI (HR = 0.72, 95% CI: 0.62, 0.83), compared to those with high ADI. Green space was positively associated with cognition, while the animal-based dietary pattern was a cognitive disadvantage. The animal-based dietary pattern may mitigate the beneficial effects of green space on cognition.

Associations of family income and healthy lifestyle with all-cause mortality.

Background: There is a lack of evidence on whether combined lifestyle factors mediate the association between family income and all-cause mortality, as well as the joint relations between family income and lifestyle factors with mortality. Methods: Using data on family income and lifestyle factors of participants in the US National Health Interview Survey 2016-2018, we performed multivariable logistic regression models to estimate the odds ratios (ORs) and 95% confidence intervals (CI) for the association of all-cause mortality with said data. Results: We included 73 729 participants with a mean age of 47.1 years (standard deviation (SD) = 18.0), 51% of whom were women and 65% of whom were non-Hispanic Whites. There were 2284 deaths documented. After multivariable adjustment, middle-income participants had an OR of 0.73 (95% CI = 0.61-0.88) for mortality, while high-income participants had an OR of 0.47 (95% CI = 0.37-0.60) compared with low-income participants. We found that lower all-cause mortality was related to higher lifestyle scores. Adults from high-income families with lifestyle scores of 3 and 4 had an OR for mortality of 0.44 (95% CI = 0.30-0.65) compared to those from low-income families and lifestyle scores of 0 or 1. When comparing those in highest vs lowest income groups in the mediation analysis, 9.8% (95% CI = 7.4-13.0) of the relation for all-cause mortality was mediated by lifestyles. Adults from high-income families with lifestyle scores of 3 or 4 had an OR of 0.23 (95% CI = 0.17-0.33) for mortality compared with those from low-income families and lifestyle scores of 0 or 1. Conclusions: A lower risk of all-cause mortality was linked to higher family income and healthier lifestyles. Furthermore, lifestyle factors mediated a small proportion of the association between family income and mortality among US adults. Economic disparity in health may not be eliminated by changing only one's lifestyle. Therefore, besides promoting a healthy lifestyle, we should stress how family income inequality affects health outcomes.

Metabolomic profiles, polygenic risk scores and risk of rheumatoid arthritis: a population-based cohort study in the UK Biobank.

OBJECTIVE: To investigate the relationship between metabolomic profiles, genome-wide polygenic risk scores (PRSs) and risk of rheumatoid arthritis (RA). METHODS: 143 nuclear magnetic resonance-based plasma metabolic biomarkers were measured among 93 800 participants in the UK Biobank. The Cox regression model was used to assess the associations between these metabolic biomarkers and RA risk, and genetic correlation and Mendelian randomisation analyses were performed to reveal their causal relationships. Subsequently, a metabolic risk score (MRS) comprised of the weighted sum of 17 clinically validated metabolic markers was constructed. A PRS was derived by assigning weights to genetic variants that exhibited significant associations with RA at a genome-wide level. RESULTS: A total of 620 incident RA cases were recorded during a median follow-up time of 8.2 years. We determined that 30 metabolic biomarkers were potentially associated with RA, while no further significant causal associations were found. Individuals in the top decile of MRS had an increased risk of RA (HR 3.52, 95% CI: 2.80 to 4.43) compared with those below the median of MRS. Further, significant gradient associations between MRS and RA risk were observed across genetic risk strata. Specifically, compared with the low genetic risk and favourable MRS group, the risk of incident RA in the high genetic risk and unfavourable MRS group has almost elevated by fivefold (HR 6.10, 95% CI: 4.06 to 9.14). CONCLUSION: Our findings suggested the metabolic profiles comprising multiple metabolic biomarkers contribute to capturing an elevated risk of RA, and the integration of genome-wide PRSs further improved risk stratification.