Time-series analysis of meteorological factors and emergency department visits due to dog/cat bites in Jinshan area, China.

Background: Meteorological factors play an important role in human health. Clarifying the occurrence of dog and cat bites (DCBs) under different meteorological conditions can provide key insights into the prevention of DCBs. Therefore, the objective of the study was to explore the relationship between meteorological factors and DCBs and to provide caution to avoid the incidents that may occur by DCBs. Methods: In this study, data on meteorological factors and cases of DCBs were retrospectively collected at the Shanghai Climate Center and Jinshan Hospital of Fudan University, respectively, in 2016-2020. The distributed lag non-linear and time series model (DLNM) were used to examine the effect of meteorological elements on daily hospital visits due to DCBs. Results: A total of 26,857 DCBs were collected ranging from 1 to 39 cases per day. The relationship between ambient temperature and DCBs was J-shaped. DCBs were positively correlated with daily mean temperature (rs = 0.588, P < 0.01). The relative risk (RR) of DCBs was associated with high temperature (RR = 1.450; 95% CI [1.220-1.722]). Female was more susceptible to high temperature than male. High temperature increased the risk of DCBs. Conclusions: The extremely high temperature increased the risk of injuries caused by DCBs, particularly for females. These data may help to develop public health strategies for potentially avoiding the occurrence of DCBs.

Effects and Interaction of Meteorological Factors on Pulmonary Tuberculosis in Urumqi, China, 2013-2019.

Background: Most existing studies have only investigated the delayed effect of meteorological factors on pulmonary tuberculosis (PTB). However, the effect of extreme climate and the interaction between meteorological factors on PTB has been rarely investigated. Methods: Newly diagonsed PTB cases and meteorological factors in Urumqi in each week between 2013 and 2019 were collected. The lag-exposure-response relationship between meteorological factors and PTB was analyzed using the distributed lag non-linear model (DLNM). The generalized additive model (GAM) was used to visualize the interaction between meteorological factors. Stratified analysis was used to explore the impact of meteorological factors on PTB in different stratification and RERI, AP and SI were used to quantitatively evaluate the interaction between meteorological factors. Results: A total of 16,793 newly diagnosed PTB cases were documented in Urumqi, China from 2013 to 2019. The median (interquartile range) temperature, relative humidity, wind speed, and PTB cases were measured as 11.3°C (-5.0-20.5), 57.7% (50.7-64.2), 4.1m/s (3.4-4.7), and 47 (37-56), respectively. The effects of temperature, relative humidity and wind speed on PTB were non-linear, which were found with the "N"-shaped, "L"-shaped, "N"-shaped distribution, respectively. With the median meteorological factor as a reference, extreme low temperature was found to have a protective effect on PTB. However, extreme high temperature, extreme high relative humidity, and extreme high wind speed were found to increase the risk of PTB and peaked at 31.8°C, 83.2%, and 7.6 m/s respectively. According to the existing monitoring data, no obvious interaction between meteorological factors was found, but low temperature and low humidity (RR = 1.149, 95%CI: 1.003-1.315), low temperature and low wind speed (RR = 1.273, 95%CI: 1.146-1.415) were more likely to cause the high incidence of PTB. Conclusion: Temperature, relative humidity and wind speed were found to play vital roles in PTB incidence with delayed and non-linear effects. Extreme high temperature, extreme high relative humidity, and extreme high wind speed could increase the risk of PTB. Moreover, low temperature and low humidity, low temperature and low wind speed may increase the incidence of PTB.

The Effect of Ambient Temperature on Infectious Diarrhea and Diarrhea-like Illness in Wuxi, China.

BACKGROUND: The disease burden of infectious diarrhea cannot be underestimated. Its seasonal patterns indicate that weather patterns may play an important role and have an important effect on it. The objective of this study was to clarify the relationship between temperature and infectious diarrhea, and diarrhea-like illness. METHODS: Distributed lag non-linear model, which was based on the definition of a cross-basis, was used to examine the effect. RESULTS: Viral diarrhea usually had high incidence in autumn-winter and spring with a peak at -6°C; Norovirus circulated throughout the year with an insignificant peak at 8°C, while related bacteria usually tested positive in summer and peaked at 22°C. The lag-response curve of the proportion of diarrhea-like cases in outpatient and emergency cases revealed that at -6°C, with the lag days increasing, the proportion increased. Similar phenomena were observed at the beginning of the curves of virus and bacterial positive rate, showing that the risk increased as the lag days increased, peaking on days 16 and 9, respectively. The shape of lag-response curve of norovirus positive rate was different from others, presenting m-type, with 2 peaks on day 3 and day 18. CONCLUSION: Weather patterns should be taken into account when developing surveillance programs and formulating relevant public health intervention strategies.

Effects of ambient temperature on influenza-like illness: A multicity analysis in Shandong Province, China, 2014-2017.

Background: The associations between ambient temperature and influenza-like illness (ILI) have been investigated in previous studies. However, they have inconsistent results. The purpose of this study was to estimate the effect of ambient temperature on ILI in Shandong Province, China. Methods: Weekly ILI surveillance and meteorological data over 2014-2017 of the Shandong Province were collected from the Shandong Center for Disease Control and Prevention and the China Meteorological Data Service Center, respectively. A distributed lag non-linear model was adopted to estimate the city-specific temperature-ILI relationships, which were used to pool the regional-level and provincial-level estimates through a multivariate meta-analysis. Results: There were 911,743 ILI cases reported in the study area between 2014 and 2017. The risk of ILI increased with decreasing weekly ambient temperature at the provincial level, and the effect was statistically significant when the temperature was <-1.5°C (RR = 1.24, 95% CI: 1.00-1.54). We found that the relationship between temperature and ILI showed an L-shaped curve at the regional level, except for Southern Shandong (S-shaped). The risk of ILI was influenced by cold, with significant lags from 2.5 to 3 weeks, and no significant effect of heat on ILI was found. Conclusion: Our findings confirm that low temperatures significantly increased the risk of ILI in the study area. In addition, the cold effect of ambient temperature may cause more risk of ILI than the hot effect. The findings have significant implications for developing strategies to control ILI and respond to climate change.

Effect of Asbestos Consumption on Malignant Pleural Mesothelioma in Italy: Forecasts of Mortality up to 2040.

Statistical models used to forecast malignant pleural mesothelioma (MPM) trends often do not take into account historical asbestos consumption, possibly resulting in less accurate predictions of the future MPM death toll. We used the distributed lag non-linear model (DLNM) approach to predict future MPM cases in Italy until 2040, based on past asbestos consumption figures. Analyses were conducted using data on male MPM deaths (1970-2014) and annual asbestos consumption using data on domestic production, importation, and exportation. According to our model, the peak of MPM deaths is expected to occur in 2021 (1122 expected cases), with a subsequent decrease in mortality (344 MPM deaths in 2039). The exposure-response curve shows that relative risk (RR) of MPM increased almost linearly for lower levels of exposure but flattened at higher levels. The lag-specific RR grew until 30 years since exposure and decreased thereafter, suggesting that the most relevant contributions to the risk come from exposures which occurred 20-40 years before death. Our results show that the Italian MPM epidemic is approaching its peak and underline that the association between temporal trends of MPM and time since exposure to asbestos is not monotonic, suggesting a lesser role of remote exposures in the development of MPM than previously assumed.

The modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China.

BACKGROUND: Although exposure to air pollution has been linked to many health issues, few studies have quantified the modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo, China. METHODS: The data of daily incidence of influenza and the relevant meteorological data and air pollution data in Ningbo from 2014 to 2017 were retrieved. Low, medium and high temperature layers were stratified by the daily mean temperature with 25th and 75th percentiles. The potential modification effect of temperature on the relationship between air pollutants and daily incidence of influenza in Ningbo was investigated through analyzing the effects of air pollutants stratified by temperature stratum using distributed lag non-linear model (DLNM). Stratified analysis by sex and age were also conducted. RESULTS: Overall, a 10 µg/m3 increment of O3, PM2.5, PM10 and NO2 could increase the incidence risk of influenza with the cumulative relative risk of 1.028 (95% CI 1.007, 1.050), 1.061 (95% CI 1.004, 1.122), 1.043 (95% CI 1.003, 1.085), and 1.118 (95% CI 1.028, 1.216), respectively. Male and aged 7-17 years were more sensitive to air pollutants. Through the temperature stratification analysis, we found that temperature could modify the impacts of air pollution on daily incidence of influenza with high temperature exacerbating the impact of air pollutants. At high temperature layer, male and the groups aged 0-6 years and 18-64 years were more sensitive to air pollution. CONCLUSION: Temperature modified the relationship between air pollution and daily incidence of influenza and high temperature would exacerbate the effects of air pollutants in Ningbo.

Modelling of Temperature-Attributable Mortality among the Elderly in Lisbon Metropolitan Area, Portugal: A Contribution to Local Strategy for Effective Prevention Plans.

Epidemiological studies on the impact of determining environmental factors on human health have proved that temperature extremes and variability constitute mortality risk factors. However, few studies focus specifically on susceptible individuals living in Portuguese urban areas. This study aimed to estimate and assess the health burden of temperature-attributable mortality among age groups (0-64 years; 65-74 years; 75-84 years; and 85+ years) in Lisbon Metropolitan Area, from 1986-2015. Non-linear and delayed exposure-lag-response relationships between temperature and mortality were fitted with a distributed lag non-linear model (DLNM). In general, the adverse effects of cold and hot temperatures on mortality were greater in the older age groups, presenting a higher risk during the winter season. We found that, for all ages, 10.7% (95% CI: 9.3-12.1%) deaths were attributed to cold temperatures in the winter, and mostly due to moderately cold temperatures, 7.0% (95% CI: 6.2-7.8%), against extremely cold temperatures, 1.4% (95% CI: 0.9-1.8%). When stratified by age, people aged 85+ years were more burdened by cold temperatures (13.8%, 95% CI: 11.5-16.0%). However, for all ages, 5.6% of deaths (95% CI: 2.7-8.4%) can be attributed to hot temperatures. It was observed that the proportion of deaths attributed to exposure to extreme heat is higher than moderate heat. As with cold temperatures, people aged 85+ years are the most vulnerable age group to heat, 8.4% (95% CI: 3.9%, 2.7%), and mostly due to extreme heat, 1.3% (95% CI: 0.8-1.8%). These results provide new evidence on the health burdens associated with alert thresholds, and they can be used in early warning systems and adaptation plans.

Daily mean temperature and HFMD: risk assessment and attributable fraction identification in Ningbo China.

BACKGROUND: Hand, foot, and mouth disease (HFMD) remains a significant public health issue, especially in developing countries. Many studies have reported the association between environmental temperature and HFMD. However, the results are highly heterogeneous in different regions. In addition, there are few studies on the attributable risk of HFMD due to temperature. OBJECTIVES: The study aimed to assess the association between temperature and HFMD incidence and to evaluate the attributable burden of HFMD due to temperature in Ningbo China. METHODS: The research used daily incidence of HFMD from 2014 to 2017 and distributed lag non-linear model (DLNM) to investigate the effects of daily mean temperature (Tmean) on HFMD incidence from lag 0 to 30 days, after controlling potential confounders. The lag effects and cumulative relative risk (CRR) were analyzed. Attributable fraction (AF) of HFMD incidence due to temperature was calculated. Stratified analysis by gender and age were also conducted. RESULTS: The significant associations between Tmean and HFMD incidence were observed in Ningbo for lag 0-30. Two peaks were observed at both low (5-11 °C) and high (16-29 °C) temperature scales. For low temperature scale, the highest CRR was 2.22 (95% CI: 1.61-3.07) at 7 °C on lag 0-30. For high temperature scale, the highest CRR was 3.54 (95% CI: 2.58-4.88) at 24 °C on lag 0-30. The AF due to low and high temperature was 5.23% (95% CI: 3.10-7.14%) and 39.55% (95% CI: 30.91-45.51%), respectively. There was no significant difference between gender- and age-specific AFs, even though the school-age and female children had slightly higher AF values. CONCLUSIONS: The result indicates that both high and low temperatures were associated with daily incidence of HFMD, and more burdens were caused by heat in Ningbo.

Association between cold spells and childhood asthma in Hefei, an analysis based on different definitions and characteristics.

BACKGROUND: As the global climate continues to warm, there is an increased focus on heat, but the role of low temperatures on health has been overlooked, especially for developing countries. Methods We collected the admission data of childhood asthma in 2013-2016 from Anhui Provincial Children's Hospital, as well as meteorological data from the Meteorological Bureau for the study period and collected data of pollutants from 10 monitoring stations around Hefei city. Poisson's generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM) was used to estimate the short-term effects of cold spell on childhood asthma in cold seasons (November to March). 16 definitions of cold spells were clearly compared, which combining 4 temperature indexes (daily minimum and mean temperature; daily minimum and mean apparent temperature), 2 temperature thresholds (2.5th and 5th) and 3 durations of at least 2-4 days. We then have an analysis of the modifying effect of characteristics of cold spells and individuals(gender and age), with a view to discovering the susceptible population to cold spell. Results There was significant association between cold spells and admission risk for childhood asthma. And the definition, in which daily minimum apparent temperature falls below 5th percentile for at least 3 consecutive days, produced the optimum model fit performance. Based on this optimal fit we found that, for the total population, the effect of cold spell lasted approximately five days (lag1-lag5), with the largest effect occurring in lag 3 (RR = 1.110; 95% CI: 1.052-1.170). In subgroup analysis, the cumulative effect of lag0-7 was higher in males and school-age children than in females and other age groups, respectively. In addition, we found that the effect of is higher as the duration increases. Conclusion This study suggests an association between cold spell and childhood asthma, and minimum AT may be a better indicator to define the cold spells. Boys and school-age children are more vulnerable to cold spell. And one of our very interesting findings is that if a cold spell lasts for several days, the impact of the cold spell on those later days is likely to be greater than that of the previous days. In conclusion, we should pay more attention to the protection of boys and school-aged children in our future public health protection and give more attention to those cold spells that last longer. Therefore, we recommend that schools and health authorities need to take targeted measures to reduce the risk of asthma in children during the cold spell.

Modelling climate change impacts on attributable-related deaths and demographic changes in the largest metropolitan area in Portugal: A time-series analysis.

Previous studies have consistently analyzed the impact that extreme temperatures will have on human health. However, there are very few data on temperature-related mortality burden considering future demographic changes in a context of climate change in Portugal. This study aims to quantify the impact of climate change on heat-, cold-, and net change mortality burdens, taking into account the future demographic changes in Lisbon Metropolitan Area, Portugal. We applied a time-series generalized linear model with a quasi-Poisson model via a distributed lag nonlinear model to project temperature-related mortality burden for two climatological scenarios: a present (or reference, 1986-2005) scenario and a future scenario (2046-2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that the total attributable fraction due to temperature, extreme and moderate cold, is statistically significant in the historical period and the future projected scenarios, while extreme and moderate heat were only significant in the projected future summer period. Net differences were attributed to moderate cold in the future winter months. Projections show a consistent and significant increase in future heat-related mortality burden. The attributable fraction due to heat in the future period, compared to the historical period, ranges from 0 to 1.5% for moderate heat and from 0 to 0.5% for extreme heat. Adaptation should be implemented at the local level, so as to prevent and diminish the effects on citizens and healthcare services, in a context of climate change.

Bootstrap approach to validate the performance of models for predicting mortality risk temperature in Portuguese Metropolitan Areas.

BACKGROUND: There has been increasing interest in assessing the impacts of extreme temperatures on mortality due to diseases of the circulatory system. This is further relevant for future climate scenarios where marked changes in climate are expected. This paper presents a solid method do identify the relationship between extreme temperatures and mortality risk by using as predictors simulated temperature data for cold and hot conditions in two urban areas in Portugal. METHODS: Based on the mortality and meteorological data from Porto Metropolitan Area (PMA) and Lisbon Metropolitan Area (LMA), a distributed lag nonlinear model (DLNM) was implemented to estimate the temperature effects on mortality due to diseases of the circulatory system. The performance of the models was validated via bootstrapping approaching by creating resamples with replacement from the validating data. Bootstrapping was also used to identify the best candidate model and to evaluate the sensitivity of the spline functions to the exposure-lag-response relationship. RESULTS: It is found that the model is able to reproduce the temperature-related mortality risk for two metropolitan areas. Temperature previously simulated by climate models is useful and even better than observed temperature. Although, the biases in predictions in both metropolitan areas are low, mortality risk predictions in PMA are more accurate than in LMA. Using parametric bootstrapping, we found that the overall cumulative association estimated under different bi-dimensional exposure-lag-response relationship are relatively stable, especially for the model selected by Quasi-Akaike Information Criteria (QAIC). Exposure to summer temperature conditions is best related to mortality risk. The association between winter temperature and mortality risk is somewhat less strong. CONCLUSIONS: The use of QAIC to choose from several candidate models provides valid predictions and reduced the uncertainty in the estimated relative risk for circulatory disease mortality. Our findings can be applied to better understand the characteristics and facilitate the prevention of circulatory disease mortality in Porto and Lisbon Metropolitan Areas, namely if we consider the actual context of climate change.

Effects of extreme temperatures on cerebrovascular mortality in Lisbon: a distributed lag non-linear model.

Cerebrovascular diseases are the leading cause of mortality in Portugal, especially when related with extreme temperatures. This study highlights the impacts of the exposure-response relationship or lagged effect of low and high temperatures on cerebrovascular mortality, which can be important to reduce the health burden from cerebrovascular diseases. The purpose of this study was to assess the effects of weather on cerebrovascular mortality, measured by ambient temperature in the District of Lisbon, Portugal. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model was applied to estimate the delayed effects of temperature on cerebrovascular mortality up to 30 days. With reference to minimum mortality temperature threshold of 22 °C, there was a severe risk (RR = 2.09, 95% CI 1.74, 2.51) of mortality for a 30-day-cumulative exposure to extreme cold temperatures of 7.3 °C (1st percentile). Similarly, the cumulative effect of a 30-day exposure to an extreme hot temperature of 30 °C (99th percentile) was 52% (RR = 1.65, 95% CI 1.37, 1.98) higher than same-day exposure. Over the 13 years of study, non-linear effects of temperature on mortality were identified, and the probability of dying from cerebrovascular disease in Lisbon was 7% higher in the winter than in the summer. The findings of this study provide a baseline for future public health prevention programs on weather-related mortality.

The effect of ambient temperature on the activity of influenza and influenza like illness in Jiangsu Province, China.

OBJECTIVE: We aimed to evaluate and quantify the association between ambient temperature and activity of influenza like illness (ILI) and influenza in Jiangsu Province, China. METHOD: Daily data of meteorology, influenza-like illness and detected influenza virus from 1 April 2013 to 27 March 2016 were collected. Distributed lag non-linear model (DLNM) was used to quantify the exposure-lag-response of ILI and influenza activity to daily average temperature. RESULT: Influenza A virus (Flu-A) circulated throughout the year with two peaks at -4 °C and 28 °C respectively, while influenza B (Flu-B) viruses were usually tested positive in winter or early spring and peaked at 5 °C. The lag-response curves revealed that the RR of ILI increased with time and peaked 1 day later at low temperature (3 °C), however, the maximum RR of ILI caused by high temperature (26 °C) appeared immediately on day 0, the similar phenomena of immediate effect to ILI at high temperature were also observed in the lag-response curve for Flu-A or Flu-B. CONCLUSION: ILI and Flu-A experienced two peaks of circulates at both low and high temperature in Jiangsu. The influenza viruses activity did drive up the rising of ILI%, particularly the activity of Flu-A which circulated throughout the year played a crucial role. Regional homogeneity was the relatively mainstream in aspects of cumulative association between influenza activity and temperature in Jiangsu Province.