ObjectivesMost of the studies on the effect of heat stress on preterm birth (PTB) are conducted in temperate climates. Evidence on this effect in hot and arid countries with low and middle income is limited. This paper describes the short-term effect of exposure to the hot and cold environment on a daily number of PTB in Iran.MethodsThe daily number of PTB was obtained from all hospitals of the city. Meteorological and air pollution data from 2011 to 2017 were obtained from a metrological station in the city. A semi-parametric generalized additive model following a quasi-Poisson distribution with the distributed lag non-linear model was selected as a modeling framework for time-series analysis to simultaneously model the short-term and lagged effect of heat stress on PTB in the Sabzevar city.ResultsThe minimum and maximum daily temperature were − 11.2 and 45.4 °C respectively. The highest risk estimate at extreme cold temperature was found for apparent temperature (relative risk (RR) 1.83; 95% CI 1.61: 2.09). This pattern was seen for both models. For extreme hot temperatures, the model with mean temperature showed the highest risk increase for both the main model and air pollution adjusted model (RR 1.36; 95% CI 1.25: 1.49). The lowest risk estimate in extremely cold conditions was found in the model with mean temperature. However, for extremely hot temperature conditions, the lowest risk estimate was found for both maximum and apparent temperature.ConclusionObstetricians working in semi-arid areas should be aware of the influence of environmental extreme temperature on the incidence of PTB.Electronic supplementary materialThe online version of this article (10.1186/s12199-018-0760-x) contains supplementary material, which is available to authorized users.

Extreme temperature could affect traffic crashes by influencing road safety, vehicle performance, and drivers’ behavior and abilities. Studies evaluating the impacts of extreme temperatures on the risk of traffic crashes have mainly overlooked the potential role of vehicle air conditioners. The aim of this study, therefore, was to evaluate the effect of exposure to extreme cold and hot temperatures on seeking medical attention due to motorcycle crashes. The study was conducted in Iran by using medical attendance for motorcycle crashes from March 2011 to June 2017. Data on daily minimum, mean and maximum temperature (°C), relative humidity (%), wind velocity (km/h), and precipitation (mm/day) were collected. We developed semi-parametric generalized additive models following a quasi-Poisson distribution with the distributed nonlinear lag model to estimate the immediate and lagged associations (reported as relative risk [RR], and 95% confidence interval [CI]). Between March 2011 and June 2017, 36,079 medical attendances due to motorcycle road traffic crashes were recorded (15.8 ± 5.92 victims per day). In this time period, the recorded temperature ranged from −11.2 to 45.4 °C (average: 25.5 ± 11.0 °C). We found an increased risk of medical attendance for motorcycle crashes (based on maximum daily temperature) at both extremely cold (1st percentile) and hot (99th percentile) temperatures and also hot (75th percentile) temperatures, mainly during lags 0 to 3 days (e.g., RR: 1.12 [95% CI: 1.05: 1.20]; RR: 1.08 [95% CI: 1.01: 1.16]; RR: 1.20 [95% CI: 1.09: 1.32] at lag0 for extremely cold, hot, and extremely hot conditions, respectively). The risk estimates for extremely hot temperatures were larger than hot and extremely cold temperatures. We estimated that 11.01% (95% CI: 7.77:14.06) of the medical attendance for motorcycle crashes is estimated to be attributable to non-optimal temperature (using mean temperature as exposure variable). Our findings have important public health messaging, given the considerable burden associated with road traffic injury, particularly in low- and middle-income countries.

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Background: Climate change and global warming present a significant threat to outdoor workers. Climatic parameters change has increased the risk of outdoor workers' safety and health. The objective of this paper was to examine the hypothesis of an association between six years data of climatic parameters and outdoor workers' safety and health. Methods: A variety of approaches have been produced to assess and measure workers' occupational heat exposure and the risk of heat-related disorders. In this study, maximum, mean, and minimum daily temperatures were used in the heat wave models to compare the sensitivity of predictions according to different climatic parameters in the case study of Sabzevar, settled in the north east of Iran, Khorasan Razavi Province. In this perusal, we used a 6-year data (from March 2011 to June 2017) on medical attendance because of outdoor workers disorders and also daily values of different climatically parameters to investigate the hypothesis of an association between heat indices and outdoor workers disorders. Results: Mean temperature in the case study period was 18.95(0.21) °C. The minimum and maximum recorded temperature in the perusal period was -11.2 °C and 45.4 °C, respectively. The highest and lowest number of outdoor workers disorders was observed for the 11th (max daily air temperature > 35°C for ≥ 1 day) and 4th (mean daily air temperature > 99th percentile for ≥ 2 sequential days) definition of the heat wave in 16 definitions (17.75(4.80) and 0, respectively). Conclusion: This study found that extreme temperature was associated with outdoor worker disorders in Sabzevar. Research into the future likelihood, existence and magnitude of safety and health consequences of global warming and climate change represent an important input to national policy debates.

Background: One way to achieve a standard heating, ventilating, and air conditioning system with maximum satisfaction is to use a thermal index to identify and determine the thermal comfort of people. In this study we intend to evaluate thermal comfort based on PMV-PPD (Predicted Mean Vote/Predicted Percentage Dissatisfied) model in workers of screening center for COVID-19. Methods: The study period was from March 1 to October 31, 2020. In this study, we used the ISO 7730 model to determinate PMV-PPD index. PMV index was used to determine thermal comfort at different scales in Birjand city with arid and hot climate. All data were analyzed using R software (version 3.3.0) and IBM SPSS statistics softwares. Results: The maximum and minimum recorded physical PMV values in the study period were observed in June as (2.09 ± 0.03) and March as (-1.27 ± 0.14), respectively. The amplitude of the thermal sense in the study period was varied between slightly cool (-1.5) and warm (+2.5). The PPD in spring was 40% which indicated slightly warm to hot condition. Conclusions: The October was the only month during the study in which thermal stress was in comfort or neutral thermal condition.  Our results suggest that thermal comfort has dimensions and indices which are helpful in managing energy consumption.