Preparing the next generation of health professionals to tackle climate change: Are China's medical students ready?

BACKGROUND: Climate change is the biggest global health threat of the 21st century. Medical students will lead the health sector responses and adaptation efforts in the near future, yet little is known in China about their knowledge, perceptions and preparedness to meet these challenges. METHODS: A nationwide study was conducted at five medical universities across different regions of China using a two-stage stratified cluster sampling design. A self-administered questionnaire was applied to collect the information including perception, preparedness and educational needs in response to climate change. The data were first analyzed descriptively, then chi-square tests and kruskal wallis tests were applied to determined differences among subgroups, and logistic regression analysis were deployed to detect the socio-demographic factors influencing student's perception. RESULTS: A total of 1436 medical students were approached and 1387 participated in the study (96.6% response rate). Most students were aware of the health impacts because of climate change, with over 90% perceived air quality-related and heat-related illness, while only a small part identified undernutrition and mental health. Approximately 90% embraced their role in tackling climate change, but 50% reported themselves and the health sectors were not adequately prepared. Compared to clinical students, preventive medicine students were more likely to perceive their responsibility to address climate change (OR:1.36, 95% CI: 1.04, 1.78). Also, 80% students admitted insufficient information and knowledge on climate change and health. Most students agreed that climate change and its health impacts should be included into their current curriculum. CONCLUSIONS: Medical students in China were aware of climate change and felt responsible, but were not ready to make responses to its health impacts. Educational efforts should reinforce eco-medical literacy development and capacity building in the era of climate change.

Comprehensive pan-cancer analysis of YBX family reveals YBX2 as a potential biomarker in liver cancer.

Background: The Y-box-binding proteins (YBX) act as a multifunctional role in tumor progression, metastasis, drug resistance by regulating the transcription and translation process. Nevertheless, their functions in a pan-cancer setting remain unclear. Methods: This study examined the clinical features expression, prognostic value, mutations, along with methylation patterns of three genes from the YBX family (YBX1, YBX2, and YBX3) in 28 different types of cancer. Data used for analysis were obtained from Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. A novel YBXs score was created using the ssGSEA algorithm for the single sample gene set enrichment analysis. Additionally, we explored the YBXs score's association with the tumor microenvironment (TME), response to various treatments, and drug resistance. Results: Our analysis revealed that YBX family genes contribute to tumor progression and are indicative of prognosis in diverse cancer types. We determined that the YBXs score correlates significantly with numerous malignant pathways in pan-cancer. Moreover, this score is also linked with multiple immune-related characteristics. The YBXs score proved to be an effective predictor for the efficacy of a range of treatments in various cancers, particularly immunotherapy. To summarize, the involvement of YBX family genes is vital in pan-cancer and exhibits a significant association with TME. An elevated YBXs score indicates an immune-activated TME and responsiveness to diverse therapies, highlighting its potential as a biomarker in individuals with tumors. Finally, experimental validations were conducted to explore that YBX2 might be a potential biomarker in liver cancer. Conclusion: The creation of YBXs score in our study offered new insights into further studies. Besides, YBX2 was found as a potential therapeutic target, significantly contributing to the improvement of HCC diagnosis and treatment strategies.

Fe1-xS/biochar combined with thiobacillus enhancing lead phytoavailability in contaminated soil: Preparation of biochar, enrichment of thiobacillus and their function on soil lead.

Properly increasing mobility of heavy metals could promote phytoremediation of contaminated soil. Fe1-xS/biochar was successfully prepared from sawdust with loading pyrrhotite (Fe1-xS) at a pyrolysis temperature of 550 °C. Thiobacillus were successfully adsorbed and enriched on the surface of Fe1-xS/biochar. Microbial growth for 36 d supported by bio-oxidization of Fe1-xS decreased the system pH from 4.32 to 3.50, increased the ORP from 298 to 487 mV, and the Fe3+ release reached 25.48 mg/g, enhancing the oxidation and leaching of soil Pb. Finally, Fe1-xS/biochar and Thiobacillus were simultaneously applied into Pb-contaminated soil for 60 d, the soil pH decreased from 7.83 to 6.72, and the exchangeable fraction of soil Pb increased from 22.86% to 37.19%. Ryegrass planting for 60 d in Pb-contaminated soil with Fe1-xS/biochar and Thiobacillus showed that the Pb content in shoot and root of ryegrass increased by 55.65% and 73.43%, respectively, confirming an obvious increase of phytoavailability of soil Pb. The relative abundance of Thiobacillus in remediated soil significantly increased from 0.06% to 34.55% due to the addition of Fe1-xS/biochar and Thiobacillus. This study provides a novel approach for regulating the Pb phytoavailability for phytoremediation of Pb-contaminated soil.

Geographical disparities in the impacts of heat on diabetes mortality and the protective role of greenness in Thailand: A nationwide case-crossover analysis.

Diabetes is a major public health problem globally, and heat exposure may be a potential risk factor for death among diabetes. This study examines the association between heat and diabetes mortality in different regions of Thailand and investigates whether heat effects are modified by regional greenness. Daily temperature and daily diabetes deaths data were obtained for 60 provinces of Thailand during 2000-2008. A case-crossover analysis was conducted to quantify the odds of heat-related death among diabetes. Meta-regression was then used to examine potential modification effects of regional greenness (as represented by the Normalized Difference Vegetation Index) on heat-related mortality. A strong association between heat and diabetes mortality was found in Thailand, with important regional variations. Nationally, the pooled odds ratio of diabetes mortality was 1.10 (95% confidence interval (CI): 1.06-1.14) for heat (90th percentile of temperature) and 1.20 (95% CI: 1.10-1.30) for extreme heat (99th percentile of temperature) compared with the minimum mortality temperature, across lag 0-1 days. Central and northeast Thailand were the most vulnerable regions. Regional greenness modified the effects of heat, with lower mortality impacts in areas of higher levels of greenness. In conclusion, heat exposure increases mortality risk in diabetes, with large geographical variations in risk suggesting the need for region-specific public health strategies. Increasing greenness levels may help to reduce the burden of heat on diabetes in Thailand against the backdrop of a warming climate.

Effects of ambient temperature on bacillary dysentery: A multi-city analysis in Anhui Province, China.

BACKGROUND: Rising ambient temperature is expected to increase incidence of bacillary dysentery (BD), but few studies have compared the temperature-BD effects of different age groups and cities in China, especially in a multi-city setting. OBJECTIVES: We used city-specific data including BD cases and meteorological variables to determine the relationship between BD incidence and temperature at provincial level. METHODS: Weekly BD disease surveillance data and meteorological variables were collected in all 16 prefecture-level cities in Anhui Province of China. Firstly, city-specific weekly mean temperature-BD incidence associations were estimated with Distributed Lag Nonlinear Model (DLNM). Secondly, city-specific estimates were pooled at province-level through multivariate meta-analysis. Also, we conducted subgroup analyses for ages (children <5 years old and population of other ages) and urbanization of cities (high and low level), respectively. RESULTS: In Anhui, BD morbidity risk increased with increasing weekly mean temperature. Relative risks (RR) at the 90th percentile (27.5 °C) versus the 50th percentile (17 °C) of weekly mean temperature were 1.42 (95% confidence interval (CI): 1.16, 1.75) and 2.02 (95% CI: 1.76, 2.32) for children <5 and population of other ages, respectively. The relative risk of high temperature on other ages group was higher than that of children under five years old (p = 0.006). Children under 5 in high urbanized cities appeared to be more vulnerable to the effects of ambient high temperature (RR: 1.56, 95% CI: 1.20, 1.92) than in low urbanized cities (RR: 1.01, 95% CI: 0.70, 1.46), the difference between two intervals was statistically significant (p = 0.044). CONCLUSIONS: This study suggests that high temperatures may be an important trigger of BD incidence, and especially lead to a substantial burden of BD for high urbanized cities in Anhui Province of China.

Short-term effects of moderate and severe floods on infectious diarrheal diseases in Anhui Province, China.

BACKGROUND: Previous studies showed that floods can lead to diarrheal diseases outbreaks; however, the short-term effects of different severity floods on diarrheal diseases are not clear. This study aims to examine 0-14 days lagged effects of moderate and severe floods on diarrhea in Anhui Province, one heavily flood-prone area in China. METHODS: Daily diarrheal cases from January 1, 2013 to August 31, 2017 in 16 cities of Anhui were extracted from the National Notifiable Disease Surveillance System. Meteorological data were obtained, and moderate or severe floods were identified according to Comprehensive Study Group of Major Natural Disasters of the State Science and Technology Commission in China. The quasi-Poisson generalized linear models were applied to evaluate effects of floods on daily diarrheal cases in each city with 0-14 days lag, and we divided post-flood periods into week 1 and week 2, further conducted provincial-level meta-analysis. RESULTS: Immediate effects of floods on diarrheal diseases were observed within 7 days, and at provincial level moderate floods had a RR of 1.05 (95% CI: 1.02-1.09) and severe floods RR = 1.04 (95% CI: 1.01-1.08) controlling for population size, temperature and relative humidity etc., but less effects appeared in the second week. Impacts of flooding on diarrheal diseases varied among cities. Moderate floods in week 1 had a RR of 1.51 (95% CI: 1.29-1.78) in Bozhou, and severe floods had a RR = 1.31 (95% CI: 1.05-1.64) in Chuzhou. The severe floods may have higher RR in week 1 compared with moderate floods in Anqing (1.10 vs 1.06), Chuzhou (1.31 vs 1.07) and Luan (1.18 vs 1.00). CONCLUSIONS: Both moderate and severe floods can significantly increase diarrheal risks in one week with regionally varied effects, and severe floods may lead higher risks. The findings have implications for preparing emergent interventions in hazard periods to reduce health risks of floods.

The impact of the 2016 flood event in Anhui Province, China on infectious diarrhea disease: An interrupted time-series study.

Climate change may bring more frequent and severe floods which will heighten public health problems, including an increased risk of infectious diarrhea in susceptible populations. Affected by heavy rainfall and an El Niño event, a destructive flood occurred in Anhui province, China on 18th June 2016. This study investigates the impact of this severe flood on infectious diarrhea at both city-level and provincial level, and further to identify modifying factor. We obtained information on infectious diarrheal cases during 2013-2017 from the National Disease Surveillance System. An interrupted time-series design was used to estimate effects of the flood event on diarrhea in 16 cities. Then we applied a meta-analysis to estimate the area-level pooled effects of the flood in both flooded areas and non-flooded areas. Finally, a meta-regression was applied to determine whether proximity to flood was a predictor of city-level risks. Stratified analyses by gender and age group were also conducted for flooded areas. A significant increase in infectious diarrhea risk (RR = 1.11, 95% CI: 1.01, 1.23) after the flood event was found in flooded area with variation in risks across cities, while there was no increase in non-flooded areas. Diarrheal risks post-flood was progressively higher in cities with greater proximity to the Yangtze River. Children aged 5-14 were at highest risk of diarrhea post-flood in the flooded areas. Our study provides strong evidence that the 2016 severe flood significantly increased infectious diarrheal risk in exposed populations. Local public health agencies are advised to develop intervention programs to prevent and control infectious diarrhea risk when a major flood occurs, especially in areas close to water bodies and among vulnerable populations.

Identifying Infectious Diarrhea Hot spots and Associated Socioeconomic Factors in Anhui Province, China.

Infectious diarrhea cases have increased during the past years in the Anhui Province of China, but little is known about its spatial cluster pattern and associated socioeconomic factors. We obtained county-level total cases of infectious diarrhea in 105 counties of Anhui in 2016 and computed age-adjusted rates. Socioeconomic factors were collected from the Statistical Yearbook. Hot spot analysis was used to identify hot and cold spot counties for infectious diarrhea incidence. We then applied binary logistic regression models to determine the association between socioeconomic factors and hot spot or cold spot clustering risk. Hot spot analysis indicated there were both significant hot spot (29 counties) and cold spot (18 counties) clustering areas for infectious diarrhea in Anhui (P < 0.10). Multivariate binary logistic regression results showed that infectious diarrhea hot spots were positively associated with per capita gross domestic product (GDP), with an adjusted odds ratio (AOR): 3.51, 95% CI: 2.09-5.91, whereas cold spots clustering were positively associated with the number of medical staffs (AOR: 1.18, 95% CI: 1.08-1.29) and negatively associated with the number of public health physicians (AOR: 0.27, 95% CI: 0.09-0.86). We identified locations for hot and cold spot clusters of infectious diarrhea incidence in Anhui, and the clustering risks were significantly associated with health workforce resources and the regional economic development. Targeted interventions should be carried out with considerations of regional socioeconomic conditions.

Associations between Knowledge of the Causes and Perceived Impacts of Climate Change: A Cross-Sectional Survey of Medical, Public Health and Nursing Students in Universities in China.

This study aimed to measure the knowledge and perceptions of medical, public health, and nursing students about climate change and its impacts, and to identify associations between the knowledge and perceptions. Data were from a nationwide cross-sectional survey of 1387 students sampled in five different regional universities in China (April⁻May 2017). The knowledge and perceptions of the participants were collected by self-administered questionnaires. We found that most respondents believed that climate change is generally "bad" (83%) and bad for human health (88%), while 67% believed that climate change is controllable. The vast majority of respondents acknowledged illness conditions resulting from poor air quality (95%), heat stress (93%), and extreme weather events (91%) as potential impacts of climate change. Nevertheless, only 39% recognized malnutrition as a consequence of food deprivation resulting from climate change. Around 58% of respondents could correctly identify the causes of climate change. The knowledge of the causes of climate change was not associated with the ability to recognize the health consequences of climate change. However, the knowledge of causes of climate change was a significant predictor of increased awareness of the negative impacts of climate change between the medical and nursing students, although this was not the case among their public health counterparts. Poor knowledge about the causes of climate change is evident among students in China. They are able to recognize the direct links between weather events and health, but less likely to understand the consequences involving complicated pathways. Research and training into the underlying mechanisms of health impacts of climate change needs to be strengthened.