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Studies about the role of urban characteristics in modifying the health effect of temperature extremes are still unclear. This study is aimed at quantifying the morbidity risk of infectious diarrhea attributable to temperature extremes and the modified effect of a range of city-specific indicators. Distributed lag non-linear model and multivariate meta-regression were applied to estimate fractions of infectious diarrhea morbidity attributable to temperature extremes and to explore the effect modification of city-level characteristics. Extreme heat- and extreme cold-related infectious diarrhea amounted to 0.99% (95% CI: 0.57-1.29) and 1.05% (95% CI: 0.64-1.24) of the total cases, respectively. The attributable fraction of temperature extremes on infectious diarrhea varied between southern and northern China. Several city characteristics modified the association of extreme cold with infectious diarrhea, with a higher morbidity impact related to increased water consumption per capita and decreased latitude. Regions with higher levels of latitude or GDP per capita appeared to be more sensitive to extreme hot. In conclusion, exposure to temperature extremes was associated with increased risks of infectious diarrhea and the effect can be modified by urban characteristics. This finding can inform public health interventions to decrease the adverse effects of temperature extremes on infectious diarrhea., (© 2023. The Author(s) under exclusive licence to International Society of Biometeorology.)

Floods may influence different types of diarrheal diseases and epidemiological studies of pathogen-specific diarrhea due to floods in China are still needed. In addition, few studies have been conducted to quantify the lag and cumulative risk of diarrheal disease due to floods in Guangxi, China. Our study aimed to identify different types of diarrheal diseases that were sensitive to floods and to quantify their lag and cumulative impact. A matched analysis based on time series data of floods and infectious disease from 2006 to 2010 was conducted in Guangxi, China. Each flood day was treated as an independent unit in our study. A simplified assumption that each day of the flood confers the same risk was adopted before analysis. Each flood day was matched to a non-flood day by city and time. Log-linear mixed-effects regression models were used to quantify the association between different types of diarrheal diseases and floods. Lag and cumulative effects were also calculated to get delayed and overall effects. A total of 45,131 diarrhea cases were notified in the study area over the study period. After controlling for the long-term trend, seasonality, and meteorological factors, floods caused a significantly increased risk of total diarrheal diseases. The RR was highest at lag 2 days (RR=1.24, 95% CI: 1.11-1.40). Floods caused a significantly increased risk in bacillary dysentery and in other infectious diarrhea, but not in typhoid fever and paratyphoid fever. Floods were significantly associated with total diarrheal diseases and other infectious diarrhea for both cumulative lag 0-7 and 0-14 days. Our study provides strong evidence of a positive association between floods and diarrheal diseases including bacillary dysentery and other infectious diarrhea in study area. Public health interventions should be taken to prevent a potential risk of these flood-sensitive diarrheal diseases according to the different lag period after floods., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Understanding the potential links between floods and infectious diarrhea is important under the context of climate change. However, little is known about the risk of infectious diarrhea after floods and what factors could modify these effects in China., Objectives: This study aims to quantitatively examine the relationship between floods and infectious diarrhea and their effect modifiers., Methods: Weekly number of infectious diarrhea cases from 2004 to 2011 during flood season in Hunan province were supplied by the National Notifiable Disease Surveillance System. Flood and meteorological data over the same period were obtained. A two-stage model was used to estimate a provincial average association and their effect modifiers between floods and infectious diarrhea, accounting for other confounders., Results: A total of 134,571 cases of infectious diarrhea were notified from 2004 to 2011. After controlling for seasonality, long-term trends, and meteorological factors, floods were significantly associated with infectious diarrhea in the provincial level with a cumulative RR of 1.22 (95% CI: 1.05, 1.43) with a lagged effect of 0-1 week. Geographic locations and economic levels were identified as effect modifiers, with a higher impact of floods on infectious diarrhea in the western and regions with a low economic level of Hunan., Conclusions: Our study provides strong evidence of a positive association between floods and infectious diarrhea in the study area. Local control strategies for public health should be taken in time to prevent and reduce the risk of infectious diarrhea after floods, especially for the vulnerable regions identified., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Objective: Guangdong province is one of the most vulnerable provinces to tropical cyclones in China. Most prior studies concentrated on the relationship between tropical cyclones and injuries and mortality. This study aimed to explore the impacts of different grades of tropical cyclones on infectious diarrhea incidence in Guangdong province, from 2005 to 2011., Methods: Mann-Whitney U test was firstly used to examine if infectious diarrhea were sensitive to tropical cyclone. Then unidirectional 1:1 case-crossover design was performed to quantitatively evaluate the relationship between daily number of infectious diarrhea and tropical cyclone from 2005 to 2011 in Guangdong, China. Principal component analysis (PCA) was applied to eliminate multicollinearity. Multivariate logistic regression model was used to estimate the hazard ratios (HRs) and the 95% confidence intervals (CI)., Results: There were no significant relationships between tropical cyclone and bacillary dysentery, amebic dysentery, typhoid, and paratyphoid cases. Infectious diarrhea other than cholera, dysentery, typhoid and paratyphoid significantly increased after tropical cyclones. The strongest effect were shown on lag 1 day (HRs = 1.95, 95%CI = 1.22, 3.12) and no lagged effect was detected for tropical depression, tropical storm, severe tropical storm and typhoon, with the largest HRs (95%CI) of 2.16 (95%CI = 1.69, 2.76), 2.43 (95%CI = 1.65, 3.58) and 2.21 (95%CI = 1.65, 2.69), respectively. Among children below 5 years old, the impacts of all grades of tropical cyclones were strongest at lag 0 day. And HRs were 2.67 (95%CI = 1.10, 6.48), 2.49 (95%CI = 1.80, 3.44), 4.89 (95%CI = 2.37, 7.37) and 3.18 (95%CI = 2.10, 4.81), respectively., Conclusion: All grades of tropical cyclones could increase risk of other infectious diarrhea. Severe tropical storm has the strongest influence on other infectious diarrhea. The impacts of tropical cyclones on children under 5 years old were higher than total population.

Background: Zhejiang Province, located in southeastern China, is frequently hit by tropical cyclones. This study quantified the associations between infectious diarrhea and the seven tropical cyclones that landed in Zhejiang from 2005-2011 to assess the impacts of the accompanying precipitation on the studied diseases., Method: A unidirectional case-crossover study design was used to evaluate the impacts of tropical storms and typhoons on infectious diarrhea. Principal component analysis (PCA) was applied to eliminate multicollinearity. A multivariate logistic regression model was used to estimate the odds ratios (ORs) and the 95% confidence intervals (CIs)., Results: For all typhoons studied, the greatest impacts on bacillary dysentery and other infectious diarrhea were identified on lag 6 days (OR = 2.30, 95% CI: 1.81-2.93) and lag 5 days (OR = 3.56, 95% CI: 2.98-4.25), respectively. For all tropical storms, impacts on these diseases were highest on lag 2 days (OR = 2.47, 95% CI: 1.41-4.33) and lag 6 days (OR = 2.46, 95% CI: 1.69-3.56), respectively. The tropical cyclone precipitation was a risk factor for both bacillary dysentery and other infectious diarrhea when daily precipitation reached 25 mm and 50 mm with the largest OR = 3.25 (95% CI: 1.45-7.27) and OR = 3.05 (95% CI: 2.20-4.23), respectively., Conclusions: Both typhoons and tropical storms could contribute to an increase in risk of bacillary dysentery and other infectious diarrhea in Zhejiang. Tropical cyclone precipitation may also be a risk factor for these diseases when it reaches or is above 25 mm and 50 mm, respectively. Public health preventive and intervention measures should consider the adverse health impacts from tropical cyclones.

Background: Persistent and heavy rainfall in the upper and middle Huaihe River of China brought about severe floods during the end of June and July 2007. However, there has been no assessment on the association between the floods and infectious diarrhea. This study aimed to quantify the impact of the floods in 2007 on the burden of disease due to infectious diarrhea in northwest of Anhui Province., Methods: A time-stratified case-crossover analysis was firstly conducted to examine the relationship between daily cases of infectious diarrhea and the 2007 floods in Fuyang and Bozhou of Anhui Province. Odds ratios (ORs) of the flood risk were quantified by conditional logistic regression. The years lived with disability (YLDs) of infectious diarrhea attributable to floods were then estimated based on the WHO framework of the calculating potential impact fraction in the Burden of Disease study., Results: A total of 197 infectious diarrheas were notified during the exposure and control periods in the two study areas. The strongest effect was shown with a 2-day lag in Fuyang and a 5-day lag in Bozhou. Multivariable analysis showed that floods were significantly associated with an increased risk of the number cases of infectious diarrhea (OR = 3.175, 95%CI: 1.126-8.954 in Fuyang; OR = 6.754, 95%CI: 1.954-23.344 in Bozhou). Attributable YLD per 1000 of infectious diarrhea resulting from the floods was 0.0081 in Fuyang and 0.0209 in Bozhou., Conclusions: Our findings confirm that floods have significantly increased the risks of infectious diarrhea in the study areas. In addition, prolonged moderate flood may cause more burdens of infectious diarrheas than severe flood with a shorter duration. More attention should be paid to particular vulnerable groups, including younger children and elderly, in developing public health preparation and intervention programs. Findings have significant implications for developing strategies to prevent and reduce health impact of floods.

Previous studies have explored the effect between ambient temperature and infectious diarrhea (ID) mostly using relative risk, which provides limited information in practical applications. Few studies have focused on the disease burden of ID caused by temperature, especially for different subgroups and cities in a multi-city setting. This study aims to estimate the effects and attributable risks of temperature on category C ID and explore potential modifiers among various cities in Guangdong. First, distributed lag non-linear models (DLNMs) were used to explore city-specific associations between daily mean temperature and category C ID from 2014 to 2016 in Guangdong and pooled by applying multivariate meta-analysis. Then, multivariate meta-regression was implemented to analyze the potential heterogeneity among various cities. Finally, we assessed the attributable burden of category C ID due to temperature, low (below the 5th percentile of temperature) and high temperature (above the 95th percentile of temperature) for each city and subgroup population. Compared with the 50th percentile of daily mean temperature, adverse effects on category C ID were found when the temperature was lower than 12.27 ℃ in Guangdong Province. Some city-specific factors (longitude, urbanization rate, population density, disposable income per capita, and the number of medical technicians and beds per thousand persons) could modify the relationship of temperature-category C ID. During the study period, there were 60,505 category C ID cases (17.14% of total cases) attributable to the exposure of temperature, with the attributable fraction (AF) of low temperature (4.23%, 95% empirical confidence interval (eCI): 1.79–5.71%) higher than high temperature (1.34%, 95% eCI: 0.86–1.64%). Males, people under 5 years, and workers appeared to be more vulnerable to temperature, with AFs of 29.40%, 19.25%, and 21.49%, respectively. The AF varied substantially at the city level, with the largest AF of low temperature occurring in Shaoguan (9.58%, 95% eCI: 8.36–10.09%), and that of high temperature occurring in Shenzhen (3.16%, 95% eCI: 2.70–3.51%). Low temperature was an important risk factor for category C ID in Guangdong Province, China. The exposure–response relationship could be modified by city-specific characteristics. Considering the whole population, the attributable risk of low temperature was much higher than that of high temperature, and males, people under 5 years, and workers were vulnerable populations. [ABSTRACT FROM AUTHOR]