|Year : 2018 | Volume
| Issue : 3 | Page : 97-103
Association between extremely cold weather and ischemic heart disease-related death during 2011–2017, Jinan City
Jinyu Man1, Kunkun Yu2, Lin Zhou3, Liangliang Cui4
1 Department of Epidemiology, School of Public Health, Shandong University, Jinan, Shandong, China
2 Department of Environmental Health, Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong, China
3 Department of Chronic Disease, Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong, China
4 Department of Environmental Health, Jinan Municipal Center for Disease Control and Prevention; Department of Biostatistics, School of Public Health, Shandong University, Jinan, Shandong, China
|Date of Web Publication||24-Sep-2018|
Department of Environmental and Public Health, Jinan Municipal Center for Disease Control and Prevention, No. 2 Weiliu Road, Jinan 250021, Shandong
Source of Support: None, Conflict of Interest: None
Objective: The objective of the study is to evaluate the acute effects of extreme cold weather and cold waves on the risk of death from ischemic heart disease (IHD) in Jinan city. Methods: Daily meteorological data, air pollution data, and IHD-related death data in Jinan from January 1, 2011, to December 31, 2017, were collected. The extreme cold weather was defined as temperatures below the 10th percentile (−1.6 C), 5th percentile (−3.3 C), and 1st percentile (−6.4 C) of the daily average temperature during the study period, expressed as P10, P5, and P1 respectively. Cold strokes were defined as P10, P5, or P1 temperatures lasting for 3 days or more, and were expressed as Cold stroke I, Cold stroke II, and Cold stroke III, respectively. A time-stratified case-crossover study was used to assess the acute effects of extreme cold weather and cold strokes on IHD-related deaths. Results: During the 1486 days of the 2011–2017 cold months, 50,845 IHD deaths were detected with an average of 34 daily deaths. The relatively cold years were observed in 2011, 2012, 2013 and 2016 during the study, and the coldest was for 2012. The maximum effects of P10, P5, and P1 on IHD deaths occurred on lag6, lag6, and lag2, respectively, and the results were 1.08 (95% confidence interval [CI]: 1.04, 1.12), 1.10 (95% CI: 1.04, 1.15), and 1.20(95% CI:1.09, 1.32), respectively. The maximum effect of Cold stroke I and Cold stroke II on IHD mortality risk was 1.09 (95% CI: 1.04, 1.14) and 1.11 (95% CI: 1.04, 1.19), respectively, at lag6 and lag2. Conclusions: Extremely cold weather and cold strokes in the cold months of 2011–2017 in Jinan City significantly increased the risk of acute death from IHD. It was also found that the occurrence of cold weather and cold strokes after warm years can further increase the risk of acute death from IHD.
Keywords: Acute death, case-crossover study, cold stroke, extreme weather, ischemic heart disease
|How to cite this article:|
Man J, Yu K, Zhou L, Cui L. Association between extremely cold weather and ischemic heart disease-related death during 2011–2017, Jinan City. Cardiol Plus 2018;3:97-103
|How to cite this URL:|
Man J, Yu K, Zhou L, Cui L. Association between extremely cold weather and ischemic heart disease-related death during 2011–2017, Jinan City. Cardiol Plus [serial online] 2018 [cited 2019 Feb 22];3:97-103. Available from: http://www.cardiologyplus.org/text.asp?2018/3/3/97/242080
| Introduction|| |
With global climate change, extreme weather events have been occurring more frequently. Extreme cold weather, as an extreme weather phenomenon, has occurred in many parts of the world in recent years.,,, Extreme weather events also frequently occur in China.,, In 2008, China experienced a rare cold wave. Compared with the non-cold stroke periods, the risk of death in the population increased by 43.8% during cold stroke periods. The excess death of 148,729 people could be attributed to the big cold wave. The direct economic loss caused by housing loss was more than 22.3 billion US dollars, and the indirect economic losses were enormous and difficult to estimate.
Circulatory system diseases are the leading cause of death among cold-related deaths,,, with ischemic heart disease (IHD) being the main cause of death.,, In 2010, IHD was at the forefront of the global deaths, resulting in a disease burden of 29 million disability-adjusted life years greater than in 1990. Some studies have found that extreme cold weather increases the risk of IHD deaths., In China, there are few studies on extreme cold and IHD deaths. Furthermore, the reported results have a short coverage period.,,, Therefore, it is necessary to update the results in recent years to assess the relationship between extreme cold and IHD. Jinan City, located at the north latitude 36°40', 117°00' east longitude, south of Taishan, north across the Yellow River, belongs to the typical inland city in eastern China. It has a mild, temperate monsoon climate and four distinct seasons. In 2016, the average annual temperature was 15.4° C, and the annual precipitation was 1008.2 mm. For these reasons, Jinan City is an appropriate site for studying the impact of extreme weather on the health of the population.
In this study, daily meteorological data, atmospheric pollutants and IHD death data in Jinan were collected from 2011 to 2017. A time-stratified case cross-over study was used to explore the effects of different degrees of extreme cold weather on acute IHD-related death. This study hoped to provide a basis for future extreme cold weather responses, health risk assessment, and early warning practices.
| Methods|| |
A total of 78,309 IHD-related deaths were reported at Jinan Municipal Center for Disease Control and Prevention from January 1, 2011, to December 31, 2017. All the cases of IHD-related deaths in Jinan during the study were extracted from this system. Data extracted included the time of death, the cause of death (diagnosis code), and the residential address of the deceased individual. Non-Jinan residents were excluded based on the residential address. Deaths related to IHD were categorized as I20–I25 according to the International Classification of Diseases, 10th Revision.
Air pollution and meteorological data
Daily weather information for the same period were collected from the China Meteorological Science Data Sharing Service Network (http://cdc.cma.gov.cn/home.do). The following weather data were collected: Daily average temperature (Taverage,°C), daily maximum temperature (Tmax,°C), daily minimum temperature (Tmin,°C), daily average relative humidity (RH, %), daily average air pressure (Pressure, kPa), and daily average wind speeds (Wind, m/s).
Daily mean hourly air pollutant concentration data (inhalable SO2, NO2, and PM2.5) were obtained from the Environmental Monitoring Center of Jinan from January 1, 2011, to December 31, 2017. The data were obtained from 14 fixed monitoring stations, covering the entire region of Jinan. Daily average values of air pollution were used in this study and calculated from the above 14 fixed monitoring stations.
Definitions of extreme cold weather and cold stroke
Because the cold wave in Jinan area occurs mostly from November to April, the limited time in this study was limited to the short months from 2011 to 2017 from October to April of the following year. In this study, the daily mean temperature was used as an indicator of exposure to measure the impact of extreme cold weather on IHD-related deaths. According to previous literature,,,,, extreme cold weather was defined as temperatures below the 10th percentile (−1.6°C), the 5th percentile (−3.3°C), and the first percentile (−6.4°C) of daily average temperature during the study (represented by P10, P5, P1, respectively). Cold stroke was defined as the period in which the daily average temperature was lower than the P10, P5, and P1 of the study for 3 consecutive days or more, and was expressed as Cold stroke I, Cold stroke II, and Cold stroke III, respectively.
Time-stratified case-crossover study
In this study, according to the principle of strict control selection, considering the long-term trend, seasonal fluctuations, and the effects of the day of the week, the dates of the same year, the same month, and the same week as the death case were selected as controls. The number of comparisons was variable, usually about three. The generalized linear model was used to fit the effects of extreme cold weather and cold stroke on the number of IHD deaths. The model controlled for daily average humidity (RH), daily mean pressure (Pressure) and daily mean wind speed (Wind). The specific model was as follows:
Log (E [Yt]) = α + βX + RH + Pressure + Wind + stratum
t was the observation day/observation period; Yt was the number of IHD deaths on the observation day; α was the intercept term; X was the classified variable of “1” and “0” in extremely cold weather (P10, P5, P1, Cold stroke I, Cold stroke II, and Cold stroke III); stratum was the categorical variable, which was the matching variable of year, month, and week.
As in previous studies, in addition to assessing the acute effects of extreme weather and cold waves, this study further analyzed the effects of extreme weather and cold wave lag effects. Based on the results of the exploratory analysis, the lag time was finally determined to be 8 days (Lag8).
To assess the stability of the model analysis results, the sensitivity analysis carried out included: (A) Air pollutant model: The inclusion of atmospheric pollutants (PM2.5, NO2, and SO2) in the main model to control the acute impact of air pollution on IHD. After the effect, the degree of change of the extreme weather on the IHD death effect was further observed; (B) Control the lowest daily temperature effect: The daily minimum temperature in the main model was introduced, and the stability of the main model results was observed.
The daily meteorological factors, pollutant levels, and IHD deaths during the study were described as mean ± standard deviation according to different years. The number of days and composition ratios of P10, P5, P1, Cold stroke I, Cold stroke II, and Cold stroke III in each year were calculated. The average number of IHD deaths during P10, P5, P1, Cold stroke I, Cold stroke II, and Cold stroke III in each year and the average number of deaths in nonextreme weather were calculated.
In the regression model, the odds ratio (OR) and 95% confidence interval (CI) were used as the estimated expression of the IHD death effect in extreme weather. The maximum value of the Lag effects was chosen as an estimate of the exposure risk of extreme cold weather and cold stroke on IHD deaths.
The above descriptive analyses and regression model analyses were performed using R 3.3.2 (https://www.r-project.org/). The difference in bilateral P < 0.05 was considered statistically significant.
| Results|| |
Descriptive analysis results
[Table 1] shows the mean and standard deviation of meteorological factors, air pollution factors, and IHD daily average deaths in the cold months of each year in Jinan City during 2011–2017. During the cold months, a total of 50,845 IHD deaths were detected in 1486 days, and 34 daily deaths were reported, showing an increasing trend year by year. The lowest daily average temperature, daily maximum temperature, and daily minimum temperature all appeared in 2012.
|Table 1: Description (Mean±SD) of weather, air pollution and mortality of ischemic heart disease in cold season months during 011 and 2017, Jinan City|
Click here to view
[Table 2] shows the number of days and proportion of extreme cold weather and cold wave days in the cold months of Jinan City during 2011–2017. It can be seen from [Table 2] that the number of extremely cold weather (P10) days in 2011, 2012, 2013, and 2016 exceeded 20 days. The number of cold stroke I days in 2011–2013 also exceeded 20 days. Cold stroke III only appeared once in 2013. In the observed 7-year monitoring period, extreme cold weather and cold wave events showed a gradually decreasing trend. 2016 was an exception to this with more severe cold weather and cold strokes days than the previous and subsequent years.
|Table 2: Number of days and proportion of extremely weather in cold season months during 2011 and 2017, Jinan City|
Click here to view
[Table 3] shows the average number of IHD deaths at the time of the cold weather and cold wave days in different years during the study. The results consistently showed that the average daily death toll of IHD during extreme cold weather and cold wave periods was significantly higher than that during noncold weather and noncold wave periods. Compared with the average number of IHD deaths during noncold and noncold weather conditions, the average daily death toll was highest in all years during extreme cold weather and cold wave periods. In 2016, the average daily death toll due to IHD was increased by 31.4% during extreme cold weather (P10) days, and by 58.3% during P1 days. The 2016 Cold stroke I increased IHD-related deaths by 42.9%, and the 2016 Cold stroke II increased IHD-related deaths by 50.0%. The 2013 Cold stroke III increased IHD-related deaths by 63.6%. In 2017, extreme cold weather (P5) days increased IHD-related deaths by 42.1%.
|Table 3: Mean values of daily deaths related to IHD in extreme cold weather days and during non- cold season months from 2011 to 207, Jinan City|
Click here to view
Extreme cold weather and acute effects of ischemic heart disease
[Table 4] shows the acute effects of extreme cold weather (P10, P5, and P1) on IHD deaths in the cold months of Jinan City in 2011–2017. The results of the day effect and the maximum lag 8-day effect showed that for extremely cold weather (P10), the risk of IHD death began to increase significantly in the 2 days after the extreme cold weather occured (Lag2), and the maximum effect was observed at Lag6, with an OR of 1.08 (95% CI: 1.04–1.12), then gradually decreased. Similar to the effect seen by P10, extreme cold weather (P5) were associated with a significant increase in the risk of IHD deaths at Lag1 and reached a maximum at Lag6, with an OR of 1.10 (95%). CI: 1.04–1.15 For extreme cold weather (P1), a significant increase in risk was observed only at Lag1 and Lag2, and the maximum effective value was seen at Lag2 with an OR of 1.20 (95% CI: 1.09–1.32).
|Table 4: Associations of daily ischemic heart disease mortality and extremely temperature during cold season months from 2011 to 2017, Jinan City|
Click here to view
[Table 5] shows the increase in the risk of IHD deaths at the onset of a cold stroke. In this study, because Cold stroke III only appeared in 2013 for 3 days, so Cold stroke III was not analyzed. For Cold stroke I, the significant increase in the risk of IHD deaths occurred at Lag2, and reaching a maximum at Lag6, with an OR of 1.09 (95% CI: 1.04–1.14), followed by a decrease. For Cold stroke II, a significant increase in the risk of IHD deaths was observed on the same day, with a maximum at Lag1, OR of 1.11 (95% CI: 1.04–1.19), and with no significant risk after Lag4.
|Table 5: Associations of daily ischemic heart disease mortality and cold stroke during cold season months from 2011 to 2017, Jinan City|
Click here to view
Sensitive analysis results
The results of sensitivity analyses are shown in [Figure 1] and [Figure 2]. From the sensitivity analysis results of the pollutant model in [Figure 1], it can be seen that the results of the model changed only minimally after controlling the air pollutants PM2.5, NO2, and SO2 in the main models suggesting that the main model was of good fit and the result was stable. In the main model, stable results were also observed when adding the daily minimum temperature.
|Figure 1: The sensitivity analysis of extremely cold weather (P10, P5, and P1)|
Click here to view
| Discussion|| |
This study was conducted in Jinan City, a typical inland city in eastern China, and aimed to analyze the acute effects of extreme weather and cold stroke on IHD-related death during 7 consecutive years. To the best of our knowledge, this study relating to the risk of death from extreme weather and IHD is relevant to the current literature and is a topic of great interest in China. This study found that 64.9% (50,845/78,309) of IHD deaths occurred during the cold months (from October to April). There were also extreme cold weather days and cold strokes in various years, but the frequency of occurrence was significantly different between years. It is worth mentioning that this study also carried out an evaluation of the effects of extreme cold weather and cold stroke on the risk of death from IHD. A time-stratified case-crossover study design was used and found that both extreme cold weather and cold stroke are associated with a significant increase in the risk of death from IHD, but with a lag effect.
With climate change having a great impact globally, the effect of cold stroke on health is gradually receiving more attention. In this study, it was found that extreme cold weather and cold stoke occurred most frequently between 2011 and 2013, and then gradually decreased, but in 2016, intense cold weather and cold stroke of high intensity suddenly appeared again and reached the lowest in 2017 [Table 2]. Further analysis of average daily death from IHD during extreme cold weather and cold stroke showed [Table 3] that the average number of deaths from IHD in extreme cold weather and cold stroke in 2016 was higher than that of the current year. The increased rate was the highest of all years studied, and it was observed that as the extreme cold weather and cold stroke increased, the daily increase in the number of deaths also increased. Studies have shown that people are resistant to cold after living for a period in low-temperature places. A study conducted in Beijing, Tianjin, Wuhan, Guangzhou, and other places also pointed out that people living in relatively low-temperature areas will adapt to the environment and reduce their sensitivity to extreme cold weather. Similar findings in the current study suggested a similar phenomenon. Even after continuous high-intensity extreme cold weather and cold stroke in 2011–2013, no significant increase in the number of IHD deaths were observed. On the contrary, after the warmer years, after the extremely cold weather and cold stroke that reappeared in 2016, the highest proportion of deaths occurred. The most typical example was a rare cold stroke experienced by cities in southern China in 2008. Compared with the noncold stroke period, the cold stroke increased the risk of death by 43.8%.
Both domestic and international research have shown that cold weather can increase the risk of death from IHD.,,,, This study also carried out a risk analysis of death from IHD caused by extreme weather and cold stoke. Consistent results were also found, that was, in the maximum 8-day lag effect analysis performed for extreme cold weather (P10), the risk of ischemic heart disease death was 1.08 at Lag6 and very cold (P5) at Lag6 the OR was 1.10, and the extreme cold weather (P1) had an OR of 1.20 at Lag2. These results suggest that as the severity of extreme cold weather increases, the effect of the risk of death from IHD gradually increases, and the effect time is also advanced. The same pattern was also found in the risk analysis for cold stroke. For Cold stroke I, the OR value was 1.09 at Lag6, and for Cold stroke II, the OR value was 1.11 at Lag1. In previous studies in Beijing and Shanghai, China, it was found that the extreme cold weather (P1) was significantly different from the average cold weather (P10) in the cumulative lag 0–7 days, 0–14 days, and 0–27 days. The risk of death from IHD increases in Beijing, with RR values of 1.12, 1.19, and 1.39, respectively. Different from Beijing, Shanghai only found that the significantly increased RR was 1.16 at 0–27 days. Unlike the results of this study, in a previous study in Astana, Kazakhstan, no significant relationship between extreme cold weather and IHD death was found. This may be related to the tolerance of the population's low-temperature environment as reported in this study., In addition, studies have shown that housing conditions are associated with cold-related adverse health consequences and social consequences.
Extreme cold weather can further affect the risk of death from IHD by affecting the risk factors for IHD. For example, animal experiments have found that blood pressure in healthy rats increases when cold weather occurs, and this effect can be maintained until the end of the cold wave. Epidemiological studies have also found that extreme cold weather can cause elevated blood pressure in humans,, and elevated blood pressure is an important cause of death from IHD.,
This study, for the first time in recent years, explores the risk of death from IHD during extremely cold periods and cold strokes in China. The strengths of this study include:First, the study used continuous data for 7 years in 2011–2017 years. The selected city is characteristic of the typical seasonal cities in inland China. The average daily mortality of IHD was large, and this was representative of current research in the region. It is also a useful supplement to the current Chinese studies. Second, this study adopts a strict time-stratified case-crossover study, and the estimation of the effective value is close to unbiased. Third, to explore the impact of extreme cold weather and cold stroke on death risk in different scenarios, this study adopted a variety of widely used definitions of extreme cold weather and cold stroke. At the same time, the change trend of extreme cold weather and cold stroke effect value was discussed. The definitions adopted can better confirm each other and increase the credibility of the results. Finally, we also carried out different types of sensitivity analyses, including an atmospheric pollutant model and an increasing daily minimum temperature model. The results again showed the stability of the results of this analysis. There are also some deficiencies in this study. For example, we did not further identify the sensitivity of cold weather and cold stroke to the characteristics (sex and age) of IHD. In addition, there are some differences in the results of cities in different regions. These results are may not be representative of extreme cold weather and cold stroke responses in other regions.
| Conclusions|| |
During periods of cold weather and cold stroke in Jinan City during the cold months of 2011–2017, there was a significant increase in the risk of acute death from IHD. At the same time, it was found that extreme cold weather and cold stroke after a warm year can further increase the risk of acute death from IHD. It is suggested that all localities should be aware of this association to implement policies to reduce IHD-related death during cold periods.
We would like to thank the Medicine and Technology Development Plan Project of Shandong Province (2015WS0435) for its financial support and sponsorship.
Financial support and sponsorship
This work was funded by grants from the Medicine and Technology Development Plan Project of Shandong Province (2015WS0435).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Rossati A. Global warming and its health impact. Int J Occup Environ Med 2017;8:7-20.
Hashim JH, Hashim Z. Climate change, extreme weather events, and human health implications in the Asia Pacific region. Asia Pac J Public Health 2016;28:8S-14S.
Cohen J, Pfeiffer K, Francis JA. Warm arctic episodes linked with increased frequency of extreme winter weather in the United States. Nat Commun 2018;9:869.
Lhotka O, Kysely J. Characterizing joint effects of spatial extent, temperature magnitude and duration of heat waves and cold spells over central Europe. Int J Climatol 2015;35:1232-44.
Shone KB. A note on the cold spell of December 1981 in central England. Weather 1982;37:143-8.
Tomczyk AM, Bednorz E. Heat and cold waves on the southern coast of the Baltic Sea. Baltica 2014;27:45-54.
Mei M, Jiang Y, Wang Z, Liu L, Ye D, Wang Y. Climatic characteristics and major meteorological events over China in 2016. Mereorological Mon 2017;43:468-76.
Liao Y, Wang L, Wang Z, Ye D, Zhou B, Hou W. Climate characteristics and major meteorological events over China in 2015. Mereorological Mon 2016;42:472-80.
Liao Y, Wang L, Wang Z, Ye D, Zhou B, Hou W. Climatic characteristics and major meteorological events over China in 2017. Mereorological mon 2018;44:548-55.
Zhou MG, Wang LJ, Liu T, Zhang YH, Lin HL, Luo Y, et al.
Health impact of the 2008 cold spell on mortality in subtropical China: The climate and health impact national assessment study (CHINAs). Environ Health 2014;13:60.
Keatinge WR, Donaldson GC, Bucher K, Jendritsky G, Cordioli E, Martinelli M. Cold exposure and winter mortality from ischaemic heart disease, cerebrovascular disease, respiratory disease, and all causes in warm and cold regions of Europe. Lancet 1997;349:1341-6.
Linares C, Diaz J, Tobias A, Carmona R, Miron IJ. Impact of heat and cold waves on circulatory-cause and respiratory-cause mortality in Spain: 1975-2008. Stoch Environ Res Risk Assess 2015;29:2037-46.
Qiu H, Tian L, Ho KF, Yu IT, Thach TQ, Wong CM, et al.
Who is more vulnerable to death from extremely cold temperatures? A case-only approach in Hong Kong with a temperate climate. Int J Biometeorol 2016;60:711-7.
Wang Y, Bi Y, Wu B, Wang Z, Cui Q, Dong H. Influence of cardiovascular and cerebrovascular diseases on life expectancy in Shandong. Chin J Health Stat 2017;34:610-3.
Wang X, Cai L, Cui W, Zhao K, He J, Chu H. Study on burden of ischemic heart disease in Tonghai County of Yunnan Province. Mod Prev Med 2013;40:3608-9, 14.
Luo H, Zhou J, Tao R, Qin Y, Han R, Luo P. Trend and life lost analysis on the mortality of cardiovascular diseases from 2010-2016 in Jiangsu province. Jiangsu J Prev Med 2017;28:488-92.
Moran AE, Forouzanfar MH, Roth GA, Mensah GA, Ezzati M, Murray CJ, et al.
Temporal trends in ischemic heart disease mortality in 21 world regions, 1980 to 2010: The Global Burden of Disease 2010 study. Circulation 2014;129:1483-92.
Moran AE, Forouzanfar MH, Roth GA, Mensah GA, Ezzati M, Flaxman A, et al
. The global burden of ischemic heart disease in 1990 and 2010: The Global Burden of Disease 2010 study. Circulation 2014;129:1493-501.
Chen TH, Li X, Zhao J, Zhang K. Impacts of cold weather on all-cause and cause-specific mortality in Texas, 1990-2011. Environ Pollut 2017;225:244-51.
Davídkovová H, Plavcová E, Kynčl J, Kyselý J. Impacts of hot and cold spells differ for acute and chronic ischaemic heart diseases. BMC Public Health 2014;14:480.
Zhang Y, Li C, Feng R, Zhu Y, Wu K, Tan X, et al.
The short-term effect of ambient temperature on mortality in wuhan, china: A time-series study using a distributed lag non-linear model. Int J Environ Res Public Health 2016;13. pii: E722.
Guo Y, Li S, Zhang Y, Armstrong B, Jaakkola JJ, Tong S, et al.
Extremely cold and hot temperatures increase the risk of ischaemic heart disease mortality: Epidemiological evidence from China. Heart 2013;99:195-203.
Wang X, Li G, Liu L, Westerdahl D, Jin X, Pan X, et al.
Effects of extreme temperatures on cause-specific cardiovascular mortality in China. Int J Environ Res Public Health 2015;12:16136-56.
Li M, Zhou M, Zhang X, Huang J, Bai L, Sang S, et al.
Impact of temperature on non-accidental deaths and cause-specific mortality in four districts of Jinan. Zhonghua Liu Xing Bing Xue Za Zhi 2014;35:684-8.
National Bureau of Statistics of the People's Republic of China. China Statistical Yearbook-2016. Beijing: China Statistics Press; 2017.
Ni Y, Liang H, Xu J, Xiao J. The characteristics of the change of cold tide in North China. Agric Dev Equip 2017;3:66-7.
Song X, Wang S, Li T, Tian J, Ding G, Wang J, et al.
The impact of heat waves and cold spells on respiratory emergency department visits in Beijing, China. Sci Total Environ 2018;615:1499-505.
Wang Y, Shi L, Zanobetti A, Schwartz JD. Estimating and projecting the effect of cold waves on mortality in 209 US cities. Environ Int 2016;94:141-9.
Ma W, Xu X, Peng L, Kan H. Impact of extreme temperature on hospital admission in Shanghai, China. Sci Total Environ 2011;409:3634-7.
Lee W, Choi HM, Lee JY, Kim DH, Honda Y, Kim H, et al.
Temporal changes in mortality impacts of heat wave and cold spell in Korea and Japan. Environ Int 2018;116:136-46.
Barnett AG, Hajat S, Gasparrini A, Rocklöv J. Cold and heat waves in the United States. Environ Res 2012;112:218-24.
Arbuthnott K, Hajat S, Heaviside C, Vardoulakis S. Changes in population susceptibility to heat and cold over time: Assessing adaptation to climate change. Environ Health 2016;15 Suppl 1:33.
Näyhä S, Hassi J. Cold and mortality from ischaemic heart disease in Northern Finland. Arctic Med Res 1995;54 Suppl 2:19-25.
Elwood PC, Beswick A, O'Brien JR, Renaud S, Fifield R, Limb ES, et al.
Temperature and risk factors for ischaemic heart disease in the caerphilly prospective study. Br Heart J 1993;70:520-3.
Grjibovski AM, Nurgaliyeva N, Kosbayeva A, Menne B. No association between temperature and deaths from cardiovascular and cerebrovascular diseases during the cold season in astana, kazakhstan – The second coldest capital in the world. Int J Circumpolar Health 2012;71:19769.
Tanner LM, Moffatt S, Milne EM, Mills SD, White M. Socioeconomic and behavioural risk factors for adverse winter health and social outcomes in economically developed countries: A systematic review of quantitative observational studies. J Epidemiol Community Health 2013;67:1061-7.
Zhang X, Zhou J, Zhang S, Ma S, Wang B. Experimental reseach of the impact of simulated cold wave on hypertension disease. Meteorological Mon 2014;40:754-8.
Saeki K, Obayashi K, Iwamoto J, Tone N, Okamoto N, Tomioka K, et al.
Stronger association of indoor temperature than outdoor temperature with blood pressure in colder months. J Hypertens 2014;32:1582-9.
Su D, Du H, Zhang X, Qian Y, Chen L, Chen Y, et al.
Season and outdoor temperature in relation to detection and control of hypertension in a large rural Chinese population. Int J Epidemiol 2014;43:1835-45.
Kokubo Y, Iwashima Y. Higher blood pressure as a risk factor for diseases other than stroke and ischemic heart disease. Hypertension 2015;66:254-9.
Conlon KC, Rajkovich NB, White-Newsome JL, Larsen L, O'Neill MS. Preventing cold-related morbidity and mortality in a changing climate. Maturitas 2011;69:197-202.
Janes H, Sheppard L, Lumley T. Case-crossover analyses of air pollution exposure data: Referent selection strategies and their implications for bias. Epidemiology 2005;16:717-26.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]