As global greenhouse gases continue rising, the urgency of more ambitious action is clearer than ever before. China is the world's biggest emitter of greenhouse gases and one of the countries affected most by climate change. The evidence about the impacts of climate change on the environment and human health may encourage China to take more decisive action to mitigate greenhouse gas emissions and adapt to climate impacts. This article aimed to review the evidence of environmental damages and health risks posed by climate change and to provide a new science-based perspective for the delivery of sustainable development goals. Over recent decades, China has experienced a strong warming pattern with a growing frequency of extreme weather events, and the impacts of climate change on China's environment and human health have been consistently observed, with increasing O ₃ air pollution, decreases in water resources and availability, land degradation, and increased risks for both communicable and non-communicable diseases. Therefore, China's climate policy should target the key factors driving climate change and scale up strategic measures to curb carbon emissions and adapt to inevitable increasing climate impacts. It provides new insights for not only China but also other countries, particularly developing and emerging economies, to ensure climate and environmental sustainability whilst pursuing economic growth.
Climate Change ; China ; Humans ; Greenhouse Gases ; Air Pollution ; Sustainable Development ; Environment

Climate and weather significantly influence the duration, timing, and intensity of disease outbreaks, reshaping the global landscape of infectious diseases. Rising temperatures and shifts in precipitation patterns driven by climate change can directly impact the survival and reproduction of pathogens and vector organisms. Moreover, climate change is expected to exacerbate extreme weather events, including floods and droughts, which can disrupt infrastructure and increase the risk of water- and foodborne diseases. There are potential shifts in the temporal and spatial patterns of infectious disease transmission owing to climate change. Furthermore, climate change may alter the epidemiology of vaccine-preventable diseases. These climatic variations not only affect the ecological characteristics of pathogens and vectors but also indirectly influence human behaviors and socioeconomic conditions, further amplifying disease transmission risks. Addressing this challenge requires an interdisciplinary collaboration and comprehensive public health strategies. This review aims to synthesize the current evidence on the impact of climate change on climate-sensitive infectious diseases and elucidate the underlying mechanisms and transmission pathways. Additionally, we explored adaptive policy strategies to mitigate the public health burden of infectious diseases in the context of climate change, offering insights for global health governance and disease control efforts.
Climate Change ; Communicable Diseases/transmission* ; Humans ; Animals ; Global Health

OBJECTIVE: The role of cold spells of different intensities in the economic burden of death is crucial for health adaptation to climate change, especially in a multi-site setting. The objective of the study was to explore the economic burden of mortality attributable to cold spells. METHODS: We performed a two-stage time-series analysis using the Value of Statistical Life (VSL) approach to evaluate the economic impact of mortality related to cold spells of varying lengths and intensities. This analysis employed a case-crossover design, with a distributed lag nonlinear model (DLNM) used for analysis. Analysis was stratified according to age, sex, and region of origin. The results of the assessment show that cold spells have an enormous impact on the economic losses of mortality due to climate change and aging. RESULTS: Totally, 8.3% (95% CI: 0.0%, 16.0%) to 13.8% (95% CI: 1.0%, 24.8%) of VSL were ascribed to cold spells, accounting for economic losses of 4.71 (95% CI: 0.34, 8.47) to 11.45 (95% CI: 0.00, 21.00) billion CNY, in the cold season. The population aged over 65 y and females are particularly vulnerable. Economic impacts in warmer regions, such as the southern and subtropical zones, are more extensive than those in the northern and temperate zones. CONCLUSION Customizing cold spell prevention measures for vulnerable populations or regions is vital to alleviating the socioeconomic burden.
China/epidemiology* ; Humans ; Female ; Male ; Cold Temperature/adverse effects* ; Aged ; Middle Aged ; Adult ; Mortality ; Infant ; Child ; Adolescent ; Child, Preschool ; Young Adult ; Climate Change ; Aged, 80 and over ; Cost of Illness ; Infant, Newborn

OBJECTIVE: To assess the short-term lag effects of climate and air pollution on hospital admissions for cardiovascular and respiratory diseases, and to develop deep learning-based models for daily hospital admission prediction. METHODS: A multi-city study was conducted in Tokyo's 23 wards, Osaka City, and Nagoya City. Random forest models were employed to assess the synergistic short-term lag effects (lag0, lag3, and lag7) of climate and air pollutants on hospitalization for five cardiovascular diseases (CVDs) and two respiratory diseases (RDs). Furthermore, we developed hybrid deep learning models that integrated an autoencoder (AE) with a Long Short-Term Memory network (AE+LSTM) to predict daily hospital admissions. RESULTS: On the day of exposure (lag0), air pollutants, particularly nitrogen oxides (NO x), exhibited the strongest influence on hospital admissions for CVD and RD, with pronounced effects observed for hypertension (I10-I15), ischemic heart disease (I20), arterial and capillary diseases (I70-I79), and lower respiratory infections (J20-J22 and J40-J47). At longer lags (lag3 and lag7), temperature and precipitation were more influential predictors. The AE+LSTM model outperformed the standard LSTM, improving the prediction accuracy by 32.4% for RD in Osaka and 20.94% for CVD in Nagoya. CONCLUSION Our findings reveal the dynamic, time-varying health risks associated with environmental exposure and demonstrate the utility of deep learnings in predicting short-term hospital admissions. This framework can inform early warning systems, enhance healthcare resource allocation, and support climate-adaptive public health strategies.
Humans ; Hospitalization/statistics & numerical data* ; Cardiovascular Diseases/epidemiology* ; Japan/epidemiology* ; Air Pollutants/analysis* ; Air Pollution/adverse effects* ; Cities/epidemiology* ; Climate ; Respiratory Tract Diseases/epidemiology* ; Deep Learning ; Male

BACKGROUND AND OBJECTIVES

Climate anxiety is an emerging concept defined as increased anxiety about climate change and has been linked to negative mental health outcomes. As a relatively new concept, only a few have characterized it and its relationship with mental health, especially in the Global South populations. This study aimed to investigate the relationship between climate anxiety and depressive symptoms among undergraduate students from a college in a higher education institution in Manila, Philippines. Specifically, it aimed to (1) determine the proportion of undergraduate students who reported high levels of climate anxiety and depressive symptoms; and (2) determine the association between climate anxiety and depressive symptoms.

Using a cross-sectional design and a convenience sampling method, the investigators collected data through an online survey to assess levels of climate anxiety and depressive symptoms using the Climate Change Anxiety Scale (CCAS) and the Patient Health Questionnaire 9 (PHQ-9), respectively. Data was analyzed using multiple logistic regression.

Among the 148 respondents (N=325), 14.86% had high climate anxiety (i.e., CCAS score >= 3) and 62.84% had high depressive symptoms (i.e., PHQ-9 score >= 10). Regression analysis showed that the odds of those having high climate anxiety reporting high depressive symptoms are higher than those with low climate anxiety, though this is not significant (OR = 2.53, p=0.144).

The study verifies the existence of climate anxiety among undergraduate students and reflects an alarming mental health situation in the selected college. It is recommended that wide-scope investigations on the current state of climate anxiety and mental health among the youth be done to verify their impacts, along with inter-sectoral efforts such as increasing awareness through health education interventions to improve the youths’ mental health literacy and resilience to the effects of climate change, and promoting climate change-responsive mental health services to address these as pressing threats to youth health.

BACKGROUND: Globally, Japan has the highest drowning mortality among older adults, largely because of bathing customs. Although this mortality rate peaks in winter, the nationwide impact of outdoor temperature has not been quantified, and whether specific days carry greater risks for bathtub drowning deaths remains unclear. Therefore, we aimed to address these gaps using nationwide data from Japan. METHODS: We collected daily data on outdoor temperatures and bathtub drowning deaths (from death certificates), along with population data, across 47 prefectures from 1995-2020. A time series regression model incorporating a cyclic spline for day-of-year and a cross-basis function for outdoor temperature was used to estimate seasonality and temperature attributable fractions (AFs). Prefecture-specific estimates were pooled using meta-analysis. National holidays were defined by the Act on National Holidays. RESULTS: During the study period, 99,930 home bathtub drowning deaths were recorded. The AF for seasonality modelled with a cyclic spline for day-of-year was 77.8% (empirical confidence interval [eCI]: 76.7-78.8%), which decreased to 15.3% (eCI: 13.1-18.0%) after adjusting for outdoor temperature, indicating that outdoor temperature accounted for 80.3% of the seasonal effect. Elevated risks were observed on Sundays (relative risk = 1.16, 95% CI: 1.12-1.20), holidays (1.12, 95% CI: 1.08-1.16), New Year's Day (1.72, 95% CI: 1.61-1.84), and New Year's Eve (1.63, 95% CI: 1.52-1.74) in the adjusted model, which included a cyclic spline for day-of-year and a cross-basis function for outdoor temperature. CONCLUSION Our findings highlight the importance of mitigating the impact of outdoor temperature on bath-related death risk. Identifying high-risk days can be used to help develop targeted preventive strategies.
Seasons ; Humans ; Drowning/epidemiology* ; Japan/epidemiology* ; Temperature ; Aged ; Male ; Adult ; Female ; Middle Aged ; Child ; Young Adult ; Adolescent ; Aged, 80 and over ; Child, Preschool

OBJECTIVES: To study the epidemiological characteristics of respiratory syncytial virus (RSV) infection in hospitalized children with community-acquired pneumonia (CAP) in Hebei Province. METHODS: Hospitalized children with CAP who tested positive for RSV and were admitted to Hebei Children's Hospital from various cities and counties across Hebei Province between January 2019 and December 2023 were included in the study. Clinical data were collected and analyzed to assess epidemiological characteristics. RESULTS: The clinical data of 43 978 children with CAP were collected, with an overall RSV detection rate of 25.98%. The detection rate was higher during the implementation of non-pharmaceutical interventions (NPIs) (30.60%) than in the non-NPIs period. Winter and spring were the primary epidemic seasons for RSV each year except in 2022. The detection rate in males (26.62%) was higher than in females (25.06%) (P<0.001). The highest detection rate (59.18%) was found in infants aged 29 days to <1 year. Single RSV infection was more common, with rhinovirus being the most frequent co-infection. CONCLUSIONS The overall RSV detection rate in Hebei Province is influenced by NPIs, being higher during their implementation. RSV predominantly circulates in winter and spring. The detection rate of RSV is higher in males and infants. RSV infection is primarily single, most often co-occurring with rhinovirus.
Humans ; Respiratory Syncytial Virus Infections/epidemiology* ; Female ; Male ; Infant ; Child, Preschool ; Seasons ; China/epidemiology* ; Infant, Newborn ; Community-Acquired Infections/epidemiology* ; Child

OBJECTIVES: To investigate the epidemiological characteristics of human metapneumovirus (hMPV) and the risk factors for severe pneumonia in hospitalized children. METHODS: The epidemiological characteristics of hMPV in hospitalized children at Hebei Children's Hospital from January 2019 to December 2023 were retrospectively analyzed. The clinical data of hospitalized children with hMPV infection from April to December 2023 were included, and independent risk factors for severe pneumonia were identified through logistic regression. RESULTS: A total of 44 092 children were tested, with an hMPV positive rate of 7.30% (3 220/44 092). Children aged 3-6 years constituted the largest proportion (40.93%, 1 318/3 220) among hMPV-positive cases. The detection rate varied significantly by year (P<0.001), peaking in 2022 (12.35%, 978/7 919). The peak season of the epidemic was winter and spring from 2019 to 2021, but shifted to spring and summer from 2022 to 2023. The proportion of co-infection was 38.70% (1 246/3 220), primarily with rhinovirus (600/1 246, 48.15%), Mycoplasma pneumoniae (217/1 246, 17.42%), and respiratory syncytial virus (182/1 246, 14.61%). The main manifestations of hMPV pneumonia were cough, expectoration, and fever. Children with severe pneumonia were significantly younger (P<0.05). Wheezing, underlying diseases, co-infection, and younger age were identified as independent risk factors for severe pneumonia (P<0.05). CONCLUSIONS There are significant annual and seasonal differences in the epidemiological characteristics of hMPV in hospitalized children. Young age, underlying diseases, wheezing, and co-infection are independent risk factors for severe pneumonia.
Humans ; Risk Factors ; Metapneumovirus ; Child, Preschool ; Child ; Male ; Female ; Paramyxoviridae Infections/complications* ; Pneumonia/epidemiology* ; Retrospective Studies ; Child, Hospitalized ; Infant ; Logistic Models ; Seasons ; Hospitalization

Under the background of climate change, the escalating air pollution and extreme weather events have been identified as risk factors for chronic respiratory diseases (CRD), causing serious public health burden worldwide. This review aims to summarize the effects of changed atmospheric environment caused by climate change on CRD. Results indicated an increased risk of CRD (mainly COPD, asthma) associated with environmental factors, such as air pollutants, adverse meteorological conditions, extreme temperatures, sandstorms, wildfire, and atmospheric allergens. Furthermore, this association can be modified by factors such as socioeconomic status, adaptability, individual behavior, medical services. Potential pathophysiological mechanisms linking climate change and increased risk of CRD involved pulmonary inflammation, immune disorders, oxidative stress. Notably, the elderly, children, impoverished groups and people in regions with limited adaptability are more sensitive to respiratory health risks caused by climate change. This review provides a reference for understanding risk factors of CRD in the context of climate change, and calls for the necessity of adaptive strategies. Further interdisciplinary research and global collaboration are needed in the future to enhance adaptability and address climate health inequality.
Climate Change ; Humans ; Air Pollution/adverse effects* ; Risk Factors ; Respiratory Tract Diseases/etiology* ; Chronic Disease ; Air Pollutants/adverse effects* ; Environmental Exposure/adverse effects*

BACKGROUND AND OBJECTIVES

Climate anxiety is an emerging concept defined as increased anxiety about climate change and has been linked to negative mental health outcomes. As a relatively new concept, only a few have characterized it and its relationship with mental health, especially in the Global South populations. This study aimed to investigate the relationship between climate anxiety and depressive symptoms among undergraduate students from a college in a higher education institution in Manila, Philippines. Specifically, it aimed to (1) determine the proportion of undergraduate students who reported high levels of climate anxiety and depressive symptoms; and (2) determine the association between climate anxiety and depressive symptoms.

Using a cross-sectional design and a convenience sampling method, the investigators collected data through an online survey to assess levels of climate anxiety and depressive symptoms using the Climate Change Anxiety Scale (CCAS) and the Patient Health Questionnaire 9 (PHQ-9), respectively. Data was analyzed using multiple logistic regression.

Among the 148 respondents (N=325), 14.86% had high climate anxiety (i.e., CCAS score >= 3) and 62.84% had high depressive symptoms (i.e., PHQ-9 score >= 10). Regression analysis showed that the odds of those having high climate anxiety reporting high depressive symptoms are higher than those with low climate anxiety, though this is not significant (OR = 2.53, p=0.144).

The study verifies the existence of climate anxiety among undergraduate students and reflects an alarming mental health situation in the selected college. It is recommended that wide-scope investigations on the current state of climate anxiety and mental health among the youth be done to verify their impacts, along with inter-sectoral efforts such as increasing awareness through health education interventions to improve the youths’ mental health literacy and resilience to the effects of climate change, and promoting climate change-responsive mental health services to address these as pressing threats to youth health.