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Existing studies suggested that ambient temperature may affect the attack of acute appendicitis. However, the identification of the quantitative effect and vulnerable populations are still unknown. The purposes of this study were to quantify the impact of daily mean temperature on the hospitalization of acute appendicitis and clarify vulnerable groups, further guide targeted prevention of acute appendicitis in Tongling. Daily data of cases and meteorological factors were collected in Tongling, China, during 2015–2019. Time stratified case-crossover design and conditional logistic regression model were used to evaluate the odds ratio (OR) of ambient temperature on hospitalizations for acute appendicitis. Stratified analyses were performed by sex, age, and marital status. The odds ratio (OR) of hospitalizations for acute appendicitis increased by 1.6% for per 1 ℃ rise in mean temperature at lag3[OR = 1.016, 95% confidence interval (CI): 1.004–1.028]. In addition, our results suggest it is in the women that increased ambient temperature is more likely to contribute to acute appendicitis hospitalizations; we also found that the married are more susceptible to acute appendicitis hospitalizations due to increased ambient temperature than the unmarried; people in the 21–40 years old are more sensitive to ambient temperature than other age groups. The significant results of the differences between the subgroups indicate that the differences between the groups are all statistically significant. The elevated ambient temperatures increased the risk of hospitalizations for acute appendicitis. The females, married people, and patients aged 21–40 years old were more susceptible to ambient temperature. These findings suggest that more attention should be paid to the impact of high ambient temperature on acute appendicitis in the future. [ABSTRACT FROM AUTHOR]

Young children are thought to be particularly sensitive to heat waves, but relatively less research attention has been paid to this field to date. A systematic review was conducted to elucidate the relationship between heat waves and children's health. Literature published up to August 2012 were identified using the following MeSH terms and keywords: 'heatwave', 'heat wave', 'child health', 'morbidity', 'hospital admission', 'emergency department visit', 'family practice', 'primary health care', 'death' and 'mortality'. Of the 628 publications identified, 12 met the selection criteria. The existing literature does not consistently suggest that mortality among children increases significantly during heat waves, even though infants were associated with more heat-related deaths. Exposure to heat waves in the perinatal period may pose a threat to children's health. Pediatric diseases or conditions associated with heat waves include renal disease, respiratory disease, electrolyte imbalance and fever. Future research should focus on how to develop a consistent definition of a heat wave from a children's health perspective, identifying the best measure of children's exposure to heat waves, exploring sensitive outcome measures to quantify the impact of heat waves on children, evaluating the possible impacts of heat waves on children's birth outcomes, and understanding the differences in vulnerability to heat waves among children of different ages and from different income countries. Projection of the children's disease burden caused by heat waves under climate change scenarios, and development of effective heat wave mitigation and adaptation strategies that incorporate other child protective health measures, are also strongly recommended. [ABSTRACT FROM AUTHOR]

Ambient temperature is an important determinant of mortality and morbidity, making it necessary to assess temperature-related burden of disease (BD) for the planning of public health policies and adaptive responses. To systematically review existing epidemiological evidence on temperature-related BD, we searched three databases (PubMed, Web of Science, and Scopus) on 1 September 2018. We identified 97 studies from 56 counties for this review, of which 75 reported the fraction or number of health outcomes (include deaths and diseases) attributable to temperature, and 22 reported disability-adjusted life years (include years of life lost and years lost due to disability) related to temperature. Non-optimum temperatures (i.e., heat and cold) were responsible for > 2.5% of mortality in all included high-income countries/regions, and > 3.0% of mortality in all included middle-income countries. Cold was mostly reported to be the primary source of mortality burden from non-optimum temperatures, but the relative role of three different temperature exposures (i.e., heat, cold, and temperature variability) in affecting morbidity and mortality remains unclear so far. Under the warming climate scenario, almost all projections assuming no population adaptation suggested future increase in heat-related but decrease in cold-related BD. However, some studies emphasized the great uncertainty in future pattern of temperature-related BD, largely depending on the scenarios of climate, population adaptation, and demography. We also identified important discrepancies and limitations in current research methodologies employed to measure temperature exposures and model temperature-health relationship, and calculate the past and project future temperature-related BD. Overall, exposure to non-optimum ambient temperatures has become and will continue to be a considerable contributor to the global and national BD, but future research is still needed to develop a stronger methodological framework for assessing and comparing temperature-related BD across different settings. [ABSTRACT FROM AUTHOR]

Diurnal temperature range (DTR) and temperature change between neighboring days (TCN) are important meteorological indicators closely associated with global climate change. However, up to date, there have been no studies addressing the impacts of both DTR and TCN on emergency hospital admissions for schizophrenia. We conducted a time-series analysis to assess the relationship between temperature variability and daily schizophrenia onset in Hefei, an inland city in southeast China. Daily meteorological data and emergency hospital admissions for schizophrenia from 2005 to 2014 in Hefei were collected. After stratifying by season of birth, Poisson generalized linear regression combined with distributed lag nonlinear model (DLNM) was used to examine the relationship between temperature variability and schizophrenia, adjusting for long-term trend and seasonality, mean temperature, and relative humidity. Our analysis revealed that extreme temperature variability may increase the risk for schizophrenia onset among patients born in spring, while no such association was found in patients born in summer and autumn. In patients born in spring, the relative risks of extremely high DTR comparing the 95th and 99th percentiles with the reference (50th, 10 °C) at 3-day lag were 1.078 (95 % confidence interval (CI) 1.025-1.135) and 1.159 (95 % CI 1.050-1.279), respectively. For TCN effects, only comparing 99th percentile with reference (50th, 0.7 °C) was significantly associated with emergency hospital admissions for schizophrenia (relative risk (RR) 1.111, 95 % CI 1.002-1.231). This study suggested that exposure to extreme temperature variability in short-term may trigger later days of schizophrenia onset for patients born in spring, which may have important implications for developing intervention strategies to prevent large temperature variability exposure. [ABSTRACT FROM AUTHOR]

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (s R increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0) offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention. [ABSTRACT FROM AUTHOR]

Ambulance dispatch is a proxy of acute health outcomes, and growing epidemiological evidence documented its relation to extreme temperature events. Research, however, on short-term temperature change and ambulance dispatches is scarce. We aimed to investigate the effect of short-term temperature change on ambulance dispatches and potential modification by season. Daily data on ambulance dispatch and weather factors were collected in Huainan, a Chinese inland city from December 2011 through December 2013. A Poison generalized linear regression model combined with distributed lag nonlinear model was constructed to examine the association of temperature change between neighboring days (TCN) with ambulance dispatches. The effect modification by season was also examined. There were 48,700 ambulance attendances during the study period. A statistically significant association of TCN with ambulance dispatches was observed. Temperature rise between neighboring days (TCN > 0) was associated with elevated adverse risk of ambulance dispatches, and the effects appeared to be acute (lag0, on the current day) and could last for at least a week, while temperature drop between neighboring days (TCN < 0) had a protective effect. For a 1 °C increase of TCN at lag0 and lag06 (on the 7-day moving average), the risk of ambulance dispatches increased by 2 % (95 % CI 1-3 %) and 7 (95 % CI 1-13 %), respectively. Extreme TCN increase (95th percentile, 3.3 °C vs. 0 °C) at lag0 and lag05 was accompanied by 6 (95 % CI 3-8 %) and 27 % (95 % CI 12-44 %) increase in ambulance dispatches. Ambulance dispatches were more vulnerable to extremely great temperature rise in summer and autumn. TCN was adopted for the first time to quantify the impact of short-term temperature change on ambulance dispatches. Temperature drop between neighboring days (TCN < 0) had a protective effect on ambulance dispatches, while temperature rise between neighboring days (TCN > 0) could acutely trigger the increase in ambulance dispatches, and TCN effect differs by season. [ABSTRACT FROM AUTHOR]

Previous studies have found that both high temperature and low temperature increase the risk of childhood hand, foot and mouth disease (HFMD). However, little is known about whether temperature variation between neighboring days has any effects on childhood HFMD. A Poisson generalized linear regression model, combined with a distributed lag non-linear model, was applied to examine the relationship between temperature change and childhood HFMD in Hefei, China, from 1st January 2010 to 31st December 2012. Temperature change was defined as the difference of current day's mean temperature and previous day's mean temperature. Late spring and early summer (April-July) were chosen as the main study period due to it having the highest childhood HFMD incidence. There was a statistical association between temperature change between neighboring days and childhood HFMD. The effects of temperature change on childhood HFMD increased below a temperature change of 0 °C (temperature drop). The temperature change has the greatest adverse effect on childhood HFMD at 7 days lag, with 4 % (95 % confidence interval 2-7 %) increase per 3 °C drop of temperature. Male children and urban children appeared to be more vulnerable to the effects of temperature change. Temperature change between adjacent days might be an alternative temperature indictor for exploring the temperature-HFMD relationship. [ABSTRACT FROM AUTHOR]

Previous studies have found that mean, maximum, and minimum temperatures were associated with bacillary dysentery (BD). However, little is known about whether the within-day variation of temperature has any impact on bacillary dysentery. The current study aimed to identify the relationship between diurnal temperature range (DTR) and BD in Hefei, China. Daily data on BD counts among children aged 0-14 years from 1 January 2006 to 31 December 2012 were retrieved from Hefei Center for Disease Control and Prevention. Daily data on ambient temperature and relative humidity covering the same period were collected from the Hefei Bureau of Meteorology. A Poisson generalized linear regression model combined with a distributed lag non-linear model (DLNM) was used in the analysis after controlling the effects of season, long-term trends, mean temperature, and relative humidity. The results showed that there existed a statistically significant relationship between DTR and childhood BD. The DTR effect on childhood bacillary dysentery increased when DTR was over 8 °C. And it was greatest at 1-day lag, with an 8 % (95 % CI = 2.9-13.4 %) increase of BD cases per 5 °C increment of DTR. Male children and children aged 0-5 years appeared to be more vulnerable to the DTR effect. The data indicate that large DTR may increase the incidence of childhood BD. Caregivers and health practitioners should be made aware of the potential threat posed by large DTR. Therefore, DTR should be taken into consideration when making targeted health policies and programs to protect children from being harmed by climate impacts. [ABSTRACT FROM AUTHOR]

Increasing epidemiological studies have shown that a rapid temperature change within 1 day is an independent risk factor for human health. This paper aimed to systematically review the epidemiological evidence on the relationship between diurnal temperature range (DTR) and human health and to propose future research directions. A literature search was conducted in October 2013 using the databases including PubMed, ScienceDirect, and EBSCO. Empirical studies regarding the relationship between DTR and mortality and morbidity were included. Twenty-five relevant studies were identified, among which, 11 investigated the relationship between DTR and mortality and 14 examined the impact of DTR on morbidity. The majority of existing studies reported that DTR was significantly associated with mortality and morbidity, particularly for cardiovascular and respiratory diseases. Notably, compared with adults, the elderly and children were more vulnerable to DTR effects. However, there were some inconsistencies regarding the susceptible groups, lag time, and threshold of DTR. The impact of DTR on human health may be confounded or modified by season, socioeconomic, and educational status. Further research is needed to further confirm the adverse effects of DTR in different geographical locations; examine the effects of DTR on the health of children aged one or under; explore extreme DTR effects on human health; analyze the difference of DTR effects on human health in different locations and the modified effects of potential confounding factors; and develop detailed preventive measures against large DTR, particularly for susceptible groups. [ABSTRACT FROM AUTHOR]