Skip to main content
Download PDF

The effects of ambient temperature on non-accidental mortality in the elderly hypertensive subjects, a cohort-based study

BMC Geriatrics volume 24, Article number: 746 (2024) Cite this article

Abstract

Background

The association between ambient temperature and mortality has yielded inconclusive results with previous studies relying on in-patient data to assess the health effects of temperature. Therefore, we aimed to estimate the effect of ambient temperature on non-accidental mortality among elderly hypertensive patients through a prospective cohort study conducted in northeastern China.

Methods

A total of 9634 elderly hypertensive patients from the Kailuan research who participated in the baseline survey and follow-up from January 1, 2006 to December 31, 2017, were included in the study. We employed a Poisson generalized linear regression model to estimate the effects of monthly ambient temperature and temperature variations on non-accidental mortality.

Results

After adjusting for meteorological parameters, the monthly mean temperature (RR = 0.989, 95% CI: 0.984–0.993, p < 0.001), minimum temperature (RR = 0.987, 95% CI: 0.983–0.992, p < 0.001) and maximum temperature (RR = 0.989, 95% CI: 0.985–0.994, p < 0.001) exhibited a negative association with an increased risk of non-accidental mortality. The presence of higher monthly temperature variation was significantly associated with an elevated risk of mortality (RR = 1.097, 95% CI:1.051–1.146, p < 0.001). Further stratified analysis revealed that these associations were more pronounced during colder months as well as among male and older individuals.

Conclusions

Decreased temperature and greater variations in ambient temperature were observed to be linked with non-accidental mortality among elderly hypertensive patients, particularly notable within aging populations and males. These understanding regarding the effects of ambient temperature on mortality holds clinical significance for appropriate treatment strategies targeting these individuals while also serving as an indicator for heightened risk of death.

Peer Review reports

Background

Both short-term and long-term exposure to decreased ambient temperature can lead to an elevation in blood pressure (BP). Previous studies have reported a 0.2—0.4 mmHg increase in systolic blood pressure (SBP) and a 0.1—0.3 mmHg increase in diastolic blood pressure (DBP) per 1 °C decrease in the ambient temperature [1]. Experimental evidence has also demonstrated that sudden exposure to cold temperatures can result in a substantial rise of up to 20–30 mmHg in BP [2]. Furthermore, BP tends to be higher during cold seasons, with an average increase of approximately 5/3 (SBP/DBP) mmHg observed. This effect appears more pronounced among hypertensive patients and older individuals [3]. Additionally, emerging evidence suggests that temperature variation may further contribute to increased BP variability [1].

The elevated levels of BP and its variability associated with decreased temperature or temperature fluctuations could potentially play a crucial role in the excess morbidity and mortality observed during cold weather conditions, particularly regarding adverse cerebrovascular and cardiovascular events [4, 5]. Hypertensive patients may exhibit heightened susceptibility to ambient temperature, as exposure to decreased temperature or temperature variation could amplify BP fluctuations, exacerbate symptoms, worsen disease progression, and consequently elevate the risk of cerebro-cardiovascular events along with additional mortality risks [6]. Moreover, aging is known to impair blood pressure regulation while increasing its variability, thus advancing age might further intensify the manifestation of cold-related symptoms and complaints among hypertensive patients [7].

Most of the previous studies have focuses on assessing the effect of temperature on mortality using in-patient data, such as the number of cases or deaths [8, 9]. In this study, we aimed to investigate the relationship between ambient temperature and non-accidental mortality among elderly individuals with hypertension, based on a prospective cohort study conducted in northeast China.

Methods

Study population

A total of 126,847 inhabitants who underwent their initial health examination in Kailuan reach from 2006 to 2009 (ChiCTR-TNRC-11001489) were selected as the study cohort. Inclusion criteria comprised individuals aged over 65 with a history of hypertension who consented to participate in the Kailuan research and provided informed consent. Hypertension was defined as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg or current use of antihypertensive medication [10]. Exclusion criteria included individuals with a history of myocardial infarction, stroke, tumor, or missing information. Ultimately, a total of 9634 elderly subjects with essential hypertension were included for analysis (Fig. 1). This prospective study adhered to the principles outlined in the Helsinki Declaration and received approval from the Ethics Committee of Kailuan General Hospital. Written informed consent was obtained from all participants. The first physical examination conducted between January 1, 2006, and December 31, 2009 marked the commencement of follow-up. Non-accidental mortality served as the endpoint. The final follow-up date was December 31, 2017.

Fig. 1
figure 1

Flow-chart of the study

Full size image

Subjects assessments

The demographic characteristics and clinical history of each subject were documented, including age, sex, body mass index (BMI), alcohol consumption, smoking habits, diabetes status, and hyperlipidemia. Additionally, the SBP, DBP, and total cholesterol levels of the subjects were recorded. The 10-year ischemic cardiovascular diseases (ICVD) risk assessment system was utilized to assess the ICVD risk in the study population. This risk assessment tool for ischemic stroke and coronary events was specifically developed for the Chinese population [11]. The evaluation system primarily considered seven cerebro-cardiovascular risk factors, including age, sex, SBP, BMI, total cholesterol level, smoking status, and diabetes. The absolute10-year ICVD risk was categorized based on the total score as follows: extremely high risk (score > 40%), high risk (20% < score ≤ 40%), medium risk (10% < score ≤ 20%), low risk (5% < score ≤ 10%) and very low risk (score ≤ 5%). Subjects who had occupational exposure to pulverized coal prior to retirement were classified as having dust exposure. All health examination data were recorded by trained health workers. Non-accidental mortality was defined as death resulting from any cause other than accidental injury during the follow-up period, and was obtained through Kailuan Social Security Information System.

Meteorological data

Tangshan is situated in the northern region of China (117°31′ − 119°19′ E and 38°55′ − 40°28′ N) and experiences a warm temperate semi-humid monsoon continental climate. The Tianjin Meteorological Bureau provided the meteorological data from the Tangshan Climate Monitoring Station, situated at 117°95′ E and 40°20′ N. The meteorological observations were collected from January 1, 2006, to December 31, 2017, encompassing monthly average temperature, maximum temperature, minimum temperature, relative humidity, precipitation, and wind speed. Monthly temperature variation was calculated using the standard deviation of daily average temperatures [12, 13].

Statistical methods

Continuous variables normally distributed were presented as mean ± standard deviation, while categorical variables were reported as counts and percentages. To analyze the differences in risk factors between groups, a t-test was utilized for continuous variables and the Chi-square test for categorical variables. The non-accidental mortality rate was expressed as the average number of deaths that occurred during the study period per 1,000 people per month. A Poisson generalized linear regression model was applied to analyze the impact of ambient temperature on the monthly mortality risk of the study population. The log of the monthly population base from 2006 to 2017 was used as the log-linkage function offset in the statistical model [14]. The effect of monthly temperature on the non-accidental mortality in the elderly hypertensive population was estimated by relative risk (RR) and 95% confidence interval (CI). The models were fitted for each meteorological variable (monthly mean temperature, monthly minimum temperature, monthly maximum temperature) after adjusting for the relative humidity, wind speed and precipitation. The model fitted for monthly temperature variation further adjusted for the monthly mean temperature. Tangshan experiences hot, wet summers and cold, dry winters, thus, all months were categorized into warm season (May through October) and cold season (November through April) based on meteorological reports and previous findings [15, 16]. Further stratified analysis was conducted to investigate the differential effects of monthly temperature on non-accidental mortality during warm and cold seasons and among subjects with varying risk factors stratified by age, sex 10-years ICVD risk, and dust exposure. A two-tailed P value less than 0.05 was considered statistically significant. All analyses were performed using SPSS 25.0.

Results

Baseline characteristics of the subjects

A total of 9634 elderly hypertensive subjects were included in the analysis, with 3254 deaths during the follow-up. The mean age of the surviving subjects was 70.9 (SD = 5.3, n = 6380). Subjects who died during the follow-up exhibited higher baseline age (73.1 ± 5.6), a higher proportion of males, diabetes, smoking, dust exposure and elevated levels of SBP and DBP (p < 0.05) at baseline. Those who died also had higher mid-, high- and very high-risk 10-year ICVD absolute risk levels compared to survivors (p < 0.001). There was no difference in terms of hyperlipidemia and alcohol consumption between the two groups (p > 0.05), as indicated in Table 1. The differences in baseline characteristics among deceased subjects stratified by warm and cold seasons was presented in Table 2. However, no significant differences were found between the two groups.

Table 1 The baseline characteristics of the study subjects with or without death
Full size table
Table 2 Distribution of risk factors of the subjects with death in different warm and cold seasons
Full size table

The monthly distribution of meteorological factors and non-accidental mortality

The mean monthly temperature reached its minimum in January (-5.26℃), and the maximum monthly temperature was recorded in July (26.27℃). The minimum monthly temperature variation occurred in July (standard deviation 1.85), while the greatest variation was observed in March (standard deviation 3.98). The highest monthly non-accidental mortality rate among elderly individuals with hypertension occurred in December, at 32.80 ‰ (95% CI: 29.24–36.36), whereas the lowest monthly non-accidental mortality rate was reported in April, at 24.39 ‰ (95% CI: 21.31–27.47), as detailed in Table 3.

Table 3 Monthly all-cause mortality and monthly ambient temperature data from January 1, 2014 to December 31, 2017
Full size table

The effect of monthly temperature on non-accidental mortality

We analyzed the relationship between monthly temperature and non-accidental mortality risk among the elderly hypertensive subjects by Poisson generalized linear regression model after adjusting for the monthly mean relative humidity, wind speed and precipitation. Our findings revealed that there was a negative association between the monthly mean temperature, minimum temperature and maximum temperature with the increase in non-accidental mortality among the subjects. Specifically, we observed that a decrease of 1 °C in the monthly mean temperature, minimum temperature and maximum temperature correlated with an increase of 1.1%, 1.3% and 1.1% respectively in non-accidental mortality. Furthermore, we found that higher monthly temperature variation was significantly associated with increased non-accidental mortality risk in elderly hypertensive subjects. For every 1 °C increase in the standard deviation of monthly temperature, there was a corresponding 9.7% increase in non-accidental mortality risk within the study population. Upon conducting stratified analysis, it became evident that the effect of the monthly temperature on non-accidental mortality among elderly subjects with hypertension was more pronounced during the cold season, except for the monthly maximum temperature (RR = 0.993, 95% CI: 0.984–1.001, p = 0.080). However, it is worth noting that there was no significant correlation between monthly mean temperature, maximum temperature, or temperature variation and the risk of non-accidental mortality among the study population during warm seasons. Nevertheless, we found that during warm seasons there was a correlation between monthly minimum temperature and increased mortality risk (RR = 0.987, 95% CI: 0.976–0.998, p = 0.019), as shown in Table 4.

Table 4 The effect of monthly temperature and temperature variation on all-cause mortality of the subjects
Full size table

Further stratified analysis was conducted to investigate the variation in the effects of monthly temperature on non-accidental mortality in the elderly hypertensive subjects with different risk factors stratified by age, sex, 10-year ICVD risk and dust exposure in warm and cold seasons. We observed a more pronounced effect of monthly mean temperature, maximum temperature, minimum temperature and temperature variation on hypertensive individuals over 70 years old and those who were male and had dust exposure. However, there was no significant difference in the effect of monthly temperature on non-accidental mortality among the study population with varying 10-year ICVD risks. Although the effect of monthly temperature on subjects with dust exposure was more evident, all results reached statistical significance (Fig. 2A). Subsequent exploration into the distinct effects of monthly temperature on subjects with different risk factors during warm (Fig. 2B) and cold seasons (Fig. 2C) demonstrated a greater impact during cold seasons, except for females in the warm season. The subgroup analysis indicated that monthly minimum and maximum temperatures were negatively associated with non-accidental mortality in males but positively associated with non-accidental mortality in females.

Fig. 2
figure 2

Changes in mortality risk associated with every 1 °C change in the monthly temperature and temperature variations. A The effects of monthly ambient temperature and temperature variations on non-accidental mortality stratified by age, gender, 10-year ICVD risk and dust exposure. B The effects of monthly ambient temperature and temperature variations on non-accidental mortality stratified by age, gender, 10-year ICVD risk and dust exposure during warm seasons (May through October) and (C) cold seasons (November through April)

Full size image

Discussion

We observed a significant association between monthly temperature and its variation with non-accidental mortality among the elderly hypertensive population in the Kailuan research cohort. Monthly mean temperature, minimum temperature and maximum temperature exhibited a tendency towards negative correlation with non-accidental mortality, while higher monthly temperature variation was correlated with an increased rate of non-accidental mortality, particularly during colder months. Subgroup analysis further suggested a greater impact of the monthly temperature and its variation on non-accidental mortality among the older and male subjects.

The absence of differences in the conventional cerebrovascular risk factors between subjects who died in warm and cold months suggested that other risk factors may contribute to the monthly variations in non-accidental mortality. Given the reported associations between meteorological factors and mortality due to climate changes, it is plausible that meteorological factors may contribute to the differences in monthly mortality risk among elderly hypertensive subjects. Previous studies have shown inconsistent results regarding the effects of ambient temperature on non-accidental mortality due to variations in disease patterns, geographical locations and other contributing factors [8, 17]. While both high and low-temperatures increase mortality rates, the effects of cold generally outweigh those of heat on health [17]. The recent Global Burden of Disease Study estimated cause-specific relative risks of ambient temperature on mortality and found that cold effects were most pronounced in China [18]. In the study, we analyzed the effect of ambient temperature on elderly hypertensive subjects, who have been reported as more vulnerable to temperature changes [6]. The Poisson regression model revealed that lower monthly temperatures were associated with increased non-accidental mortality in elderly hypertensive subjects, particularly during cold months. Increased blood pressure during cold months may be a significant factor of the observed excess cold-related morbidity [4].

In addition to ambient temperature, temperature variability has also been identified as a potential trigger for additional mortality risks [12]. Our results indicated that monthly temperature variation was linked to non-accidental mortality risk in elderly subjects with hypertension, especially during cold months. Several epidemiological studies have demonstrated that changes in ambient temperature affect blood pressure variability [1, 19]. While this type of blood pressure variety has little medical relevance, patients with hypertension exhibit more pronounced blood pressure variability and are more susceptible to disruptions in blood pressure regulation due to temperature changes [1, 20]. Excessive blood pressure variability may increase the risk of diseases related to high blood and its complications. The current study suggests that the association between non-accidental mortality and monthly temperature variation could be influenced by the temperature-induced fluctuations in blood pressure. Furthermore, the stronger correlation between monthly temperature variation and mortality during cold months may attribute to the greater temperature variations during this period [19].

While deviations from the established core temperature can initiate a series of adverse physiological responses, the specific biological mechanism linking decreased temperature and temperature variability with an increased risk of mortality has not been fully elucidated, although several plausible explanations have been postulated. Mechanistically, both the sympathetic nervous system (SNS) and the renin–angiotensin–aldosterone axis (RAAS) play a central role in mediating cold-induced increases in mortality [21]. Additionally, various inflammatory or metabolic factors may also contribute to or result from cold-induced SNS/RAAS activation. These pathophysiologic changes can also be triggered by inefficiencies in the thermoregulatory system response to rapid temperature changes [22]. All these pathophysiological alterations will further lead to vasoconstriction, fluctuations in blood pressure, increased blood viscosity, elevated fibrinogen levels and platelet activation, all of which are associated with higher cardio-cerebrovascular risk and ultimately increase mortality [1, 23]. In our study, the higher mortality associated with decreased temperature and temperature variation may primarily be attributed to the effect of ambient temperature on cardio-cerebrovascular events in elderly hypertensive patients.

Subgroup analysis revealed a stronger negative correlation between temperature and non-accidental mortality in subjects over 70-year old, possibly due to the higher prevalence of hypertensive complications and declining thermoregulatory function in older individuals with hypertension [7, 17]. The association between temperature variation and mortality across different age groups showed little difference, suggesting that temperature variation could have a greater estimated impact on mortality compared to decreased temperatures. The stronger association between monthly temperature and mortality in the elderly subjects during colder months may also be attributed to the detrimental effects of cold on health and greater temperature variation during this period [19]. Regarding gender-specificity, our results suggested that male hypertensive patients were more vulnerable to decreased temperature and temperature changes, especially during colder months. The positive association between monthly minimum and maximum temperatures and non-accidental mortality in female subjects during warm periods indicated that women were more susceptible to the effects of high temperatures compared to men. The observed differences in temperature-attributable mortality risk between men and women may be attributed to variations in the physiological characteristics of thermoregulation [24]. Our findings are consistent with previous studies [25, 26], but conflicting results from other research could stem from differences in social demographic characteristics of among subjects in different geographic regions [27,28,29]. Additionally, the higher likelihood of outdoor activities among men compared to women may also contribute to our results. Elderly hypertensive patients are more susceptible to stroke and coronary heart disease, thus we conducted subgroup analysis stratified by the 10-year ICVD risk. Moreover, a considerable proportion of the subjects in the study were coal miners who had previous exposure to dust in their work environment, therefore we carried out the subgroup analysis stratified by dust exposure. However, the subgroup analyses did not reveal any significant differences in mortality when stratified by 10-year ICVD risk and dust exposure, possibly due to the vulnerability of elderly hypertensive patients to ambient temperature effects [30, 31].

The strengths of our study lie in its prospective cohort design and comprehensive medical data collection within a homogeneous geographic area, allowing for a more robust understanding of the dynamic relationship between ambient temperature and mortality risk. Nevertheless, several limitations still exist. Firstly, the sample size of women was relatively small in the current study, however, the comparatively large overall sample size remains persuasive. Secondly, the detailed cause of death was not accessible, thus we did not analyze the effect of temperature on cause-specific mortality. Further studies are required to explore temperature-attributable cause-specific mortality among elderly hypertensive patients. Thirdly, we used outdoor temperature, thus there could be some biases in our results, which could be minimized after adjusting housing conditions [32].

Conclusions

In conclusion, the study demonstrated that both monthly temperature and monthly temperature variation were associated with the risk of non-accidental mortality among elderly hypertensive subjects. The associations were more pronounced among older males during cold months, indicating that the elderly and males were more susceptible to the mortality risk attributed to decreased temperature. Our findings emphasize the necessity for local governments and relevant agencies to formulate targeted recommendations for reducing mortality risks related to temperature in susceptible populations. This is particularly crucial when countries, such as China, are confronted with both significant cerebro-cardiovascular disease burdens and climate change events, especially those related to cold temperatures in northern China.

Availability of data and materials

The datasets used during the current study are available from the corresponding author on reasonable request.

Abbreviations

BP:

Blood pressure

SBP:

Systolic blood pressure

DBP:

Diastolic blood pressure

BMI:

Body mass index

ICVD:

Ischemic cardiovascular diseases

SNS:

Sympathetic nervous system

RAAS:

Renin-angiotensin-aldosterone axis

References

  1. Stergiou GS, Palatini P, Modesti PA, Asayama K, Asmar R, Bilo G, de la Sierra A, Dolan E, Head G, Kario K, et al. Seasonal variation in blood pressure: Evidence, consensus and recommendations for clinical practice. Consensus statement by the European Society of Hypertension Working Group on Blood Pressure Monitoring and Cardiovascular Variability. J Hypertens. 2020;38(7):1235–43.

    Article  PubMed  CAS  Google Scholar 

  2. Korhonen I. Blood pressure and heart rate responses in men exposed to arm and leg cold pressor tests and whole-body cold exposure. Int J Circumpolar Health. 2006;65(2):178–84.

    Article  PubMed  Google Scholar 

  3. Kollias A, Kyriakoulis KG, Stambolliu E, Ntineri A, Anagnostopoulos I, Stergiou GS. Seasonal blood pressure variation assessed by different measurement methods: systematic review and meta-analysis. J Hypertens. 2020;38(5):791–8.

    Article  PubMed  CAS  Google Scholar 

  4. Park S, Kario K, Chia YC, Turana Y, Chen CH, Buranakitjaroen P, Nailes J, Hoshide S, Siddique S, Sison J, et al. The influence of the ambient temperature on blood pressure and how it will affect the epidemiology of hypertension in Asia. J Clin Hypertens (Greenwich). 2020;22(3):438–44.

    Article  PubMed  Google Scholar 

  5. Zafeiratou S, Samoli E, Dimakopoulou K, Rodopoulou S, Analitis A, Gasparrini A, Stafoggia M, De’ Donato F, Rao S, Monteiro A, et al. A systematic review on the association between total and cardiopulmonary mortality/morbidity or cardiovascular risk factors with long-term exposure to increased or decreased ambient temperature. Sci Total Environ. 2021;772:145383.

    Article  PubMed  CAS  Google Scholar 

  6. Ikäheimo TM, Lehtinen T, Antikainen R, Jokelainen J, Näyhä S, Hassi J, Keinänen-Kiukaanniemi S, Laatikainen T, Jousilahti P, Jaakkola JJ. Cold-related cardiorespiratory symptoms among subjects with and without hypertension: the National FINRISK Study 2002. Eur J Pub Health. 2014;24(2):237–43.

    Article  Google Scholar 

  7. Zheng S, Wang MZ, Cheng ZY, Kang F, Nie YH, Mi XY, Li HY, Jin L, Zhang YW, Bai YN. Effects of outdoor temperature on blood pressure in a prospective cohort of Northwest China. Biomed Environ Sci. 2021;34(2):89–100.

    PubMed  Google Scholar 

  8. Gasparrini A, Guo Y, Hashizume M, Lavigne E, Zanobetti A, Schwartz J, Tobias A, Tong S, Rocklöv J, Forsberg B, et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet. 2015;386(9991):369–75.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Alahmad B, Khraishah H, Royé D, Vicedo-Cabrera AM, Guo Y, Papatheodorou SI, Achilleos S, Acquaotta F, Armstrong B, Bell ML, et al. Associations between extreme temperatures and cardiovascular cause-specific mortality: results from 27 Countries. Circulation. 2023;147(1):35–46.

    Article  PubMed  Google Scholar 

  10. Wang Z, Chen Z, Zhang L, Wang X, Hao G, Zhang Z, Shao L, Tian Y, Dong Y, Zheng C, et al. Status of Hypertension in China: Results From the China Hypertension Survey, 2012–2015. Circulation. 2018;137(22):2344–56.

    Article  PubMed  Google Scholar 

  11. Wu Y, Liu X, Li X, Li Y, Zhao L, Chen Z, Li Y, Rao X, Zhou B, Detrano R, et al. Estimation of 10-year risk of fatal and nonfatal ischemic cardiovascular diseases in Chinese adults. Circulation. 2006;114(21):2217–25.

    Article  PubMed  Google Scholar 

  12. Zhang Y, Xiang Q, Yu C, Bao J, Ho HC, Sun S, Ding Z, Hu K, Zhang L. Mortality risk and burden associated with temperature variability in China, United Kingdom and United States: Comparative analysis of daily and hourly exposure metrics. Environ Res. 2019;179(Pt A):108771.

    Article  PubMed  CAS  Google Scholar 

  13. Shi L, Kloog I, Zanobetti A, Liu P, Schwartz JD. Impacts of temperature and its variability on mortality in New England. Nat Clim Chang. 2015;5:988–91.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Han MH, Yi HJ, Kim YS, Kim YS. Effect of seasonal and monthly variation in weather and air pollution factors on stroke incidence in Seoul. Korea Stroke. 2015;46(4):927–35.

    Article  PubMed  CAS  Google Scholar 

  15. Serratore P, Ostanello F, Passalacqua PL, Zavatta E, Bignami G, Serraino A, Giacometti F. First Multi-Year Retrospective Study on Vibrio Parhaemolyticus and Vibrio Vulnificus Prevalence in Ruditapes Philippinarum Harvested in Sacca Di Goro, Italy. Italian journal of food safety. 2016;5(4):6161.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Pearson D, Basu R, Wu XM, Ebisu K. Temperature and hand, foot and mouth disease in California: An exploratory analysis of emergency department visits by season, 2005–2013. Environ Res. 2020;185:109461.

    Article  PubMed  CAS  Google Scholar 

  17. Guo Y, Gasparrini A, Armstrong B, Li S, Tawatsupa B, Tobias A, Lavigne E, de Sousa ZanottiStagliorio Coelho M, Leone M, Pan X, et al. Global variation in the effects of ambient temperature on mortality: a systematic evaluation. Epidemiology. 2014;25(6):781–9.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Burkart KG, Brauer M, Aravkin AY, Godwin WW, Hay SI, He J, Iannucci VC, Larson SL, Lim SS, Liu J, et al. Estimating the cause-specific relative risks of non-optimal temperature on daily mortality: a two-part modelling approach applied to the Global Burden of Disease Study. Lancet. 2021;398(10301):685–97.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Hintsala HE, Kiviniemi AM, Antikainen R, Mäntysaari M, Jokelainen J, Hassi J, Tulppo MP, Herzig KH, Keinänen-Kiukaanniemi S, Rintamäki H, et al. High Home Blood Pressure Variability Associates With Exaggerated Blood Pressure Response to Cold Stress. Am J Hypertens. 2019;32(6):538–46.

    Article  PubMed  CAS  Google Scholar 

  20. Costello HM, Gumz ML. Circadian rhythm, clock genes, and hypertension: recent advances in hypertension. Hypertension (Dallas, Tex : 1979). 2021;78(5):1185–96.

    Article  PubMed  CAS  Google Scholar 

  21. Goel H, Shah K, Kumar A, Hippen JT, Nadar SK. Temperature, cardiovascular mortality, and the role of hypertension and renin-angiotensin-aldosterone axis in seasonal adversity: a narrative review. J Hum Hypertens. 2022;36:1035–47.

    Article  PubMed  CAS  Google Scholar 

  22. Liu C, Yavar Z, Sun Q. Cardiovascular response to thermoregulatory challenges. Am J Physiol Heart Circ Physiol. 2015;309(11):H1793–1812.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Chen Z, Liu P, Xia X, Wang L, Li X. The underlying mechanisms of cold exposure-induced ischemic stroke. Sci Total Environ. 2022;834:155514.

    Article  PubMed  CAS  Google Scholar 

  24. Charkoudian N, Stachenfeld NS. Reproductive hormone influences on thermoregulation in women. Compr Physiol. 2014;4(2):793–804.

    Article  PubMed  Google Scholar 

  25. Zhao Q, Li S, Coelho M, Saldiva PHN, Hu K, Huxley RR, Abramson MJ, Guo Y. Temperature variability and hospitalization for ischaemic heart disease in Brazil: a nationwide case-crossover study during 2000–2015. Sci Total Environ. 2019;664:707–12.

    Article  PubMed  CAS  Google Scholar 

  26. Yatim ANM, Latif MT, Sofwan NM, Ahamad F, Khan MF, Mahiyuddin WRW, Sahani M. The association between temperature and cause-specific mortality in the Klang Valley, Malaysia. Environ Sci Pollut Res Int. 2021;28(42):60209–20.

    Article  PubMed  Google Scholar 

  27. Zhai G, Zhang K, Chai G. Lag effect of ambient temperature on the cardiovascular disease hospital admission in Jiuquan, China. Air Qual Atmos Health. 2021;14(2):181–9.

    Article  CAS  Google Scholar 

  28. Martínez-Solanas È, Quijal-Zamorano M, Achebak H, Petrova D, Robine JM, Herrmann FR, Rodó X, Ballester J. Projections of temperature-attributable mortality in Europe: a time series analysis of 147 contiguous regions in 16 countries. Lancet Planetary Health. 2021;5(7):e446–54.

    Article  PubMed  Google Scholar 

  29. Achebak H, Devolder D, Ballester J. Trends in temperature-related age-specific and sex-specific mortality from cardiovascular diseases in Spain: a national time-series analysis. Lancet Planetary Health. 2019;3(7):e297–306.

    Article  PubMed  Google Scholar 

  30. Chen R, Lu J, Yu Q, Peng L, Yang D, Wang C, Kan H. The acute effects of outdoor temperature on blood pressure in a panel of elderly hypertensive patients. Int J Biometeorol. 2015;59(12):1791–7.

    Article  PubMed  Google Scholar 

  31. Hanazawa T, Asayama K, Watabe D, Tanabe A, Satoh M, Inoue R, Hara A, Obara T, Kikuya M, Nomura K, et al. Association between amplitude of seasonal variation in self-measured home blood pressure and cardiovascular outcomes: HOMED-BP (Hypertension Objective Treatment Based on Measurement By Electrical Devices of Blood Pressure) Study. J Am Heart Assoc. 2018;7(10):e008509.

    Article  PubMed  PubMed Central  Google Scholar 

  32. Umishio W, Ikaga T, Kario K, Fujino Y, Suzuki M, Ando S, Hoshi T, Yoshimura T, Yoshino H, Murakami S. Impact of indoor temperature instability on diurnal and day-by-day variability of home blood pressure in winter: a nationwide Smart Wellness Housing survey in Japan. Hypertens Res. 2021;44(11):1406–16.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

The work was supported by Tianjin Key Medical Discipline (Specialty) Construction Project (TJYXZDXK-065B), Tianjin Municipal Science and Technology Bureau Project (21JCZDJC01230), Tianjin Center for Health and Meteorology Multidisciplinary Innovation, Tianjin Health Committee Project (TJWJ2022QN018), Youth Fund of the Second Hospital of Tianjin Medical University (2022ydey11). The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, and approval of the manuscript; or the decision to submit the manuscript for publication.

Author information

Author notes

  1. Xuemei Qi and Xiaobin Guo contributed equally to this work.

Authors and Affiliations

  1. Department of Neurology, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China

    Xuemei Qi, Xiaobin Guo, Xiaoshuang Xia & Xin Li

  2. Department of General Medicine, The Second Hospital of Tangshan, No. 21 Jianshe North Road, Tangshan, 063015, China

    Xiaobin Guo

  3. Tianjin Environmental Meteorology Center, No. 100, Qixiang Tai Road, Tianjin, 300074, China

    Suqin Han

  4. Department of Geriatrics, The Second Hospital of Tianjin Medical University, No. 23, Pingjiang Road, Tianjin, 300211, China

    Lin Wang

Authors
  1. Xuemei Qi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiaobin Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suqin Han
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaoshuang Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Lin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Xin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Study concept and Design: Xuemei Qi, Xin Li, Xiaoshuang Xia and Lin Wang; Acquisition of data: Xuemei Qi, Xiaobin Guo and Suqin Han; Analysis and interpretation of data: Xuemei Qi, Xiaobin Guo and Xin Li; Preparation of manuscript: Xuemei Qi, Xiaobin Guo Suqin Han Xiaoshuang Xia, Lin Wang and Xin Li. The authors report no conflicts of interest.

Corresponding author

Correspondence to Xin Li.

Ethics declarations

Ethics approval and consent to participate

The study followed the Helsinki Declaration and was approved by the Ethics Committee of Kailuan General Hospital (ChiCTR-TNRC-11001489).

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Qi, X., Guo, X., Han, S. et al. The effects of ambient temperature on non-accidental mortality in the elderly hypertensive subjects, a cohort-based study. BMC Geriatr 24, 746 (2024). https://doi.org/10.1186/s12877-024-05333-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12877-024-05333-2

Keywords

BMC Geriatrics

ISSN: 1471-2318

Contact us