Objectives Cardiovascular mortality has been linked to changes in outdoor temperature. However, the mechanisms behind these effects are not well established. We aimed to study the effect of outdoor temperature on blood pressure, as increased blood pressure is a risk factor for cardiovascular death.
Methods The study population consisted of men aged 53–100 years living in the Boston area. We used a mixed effects model to estimate the effect of three temperature variables: ambient, apparent and dew point temperature (DPT), on repeated measures (every 3–5 years) of diastolic (DBP) and systolic blood pressure (SBP). Random intercepts for subjects and several possible confounders were used in the models, including black carbon and barometric pressure.
Results We found modest associations between DBP and ambient and apparent temperature. In the basic models, DBP in association with a 5°C decrease in 7-day moving averages of temperatures increased by 1.01% (95% CI −0.06% to 2.09%) and 1.55% (95% CI 0.61% to 2.49%) for ambient and apparent temperature, respectively. Excluding extreme temperatures strengthened these associations (2.13%, 95% CI 0.66% to 3.63%, and 1.65%, 95% CI 0.41% to 2.90%, for ambient and apparent temperature, respectively). Effect estimates for DPT were close to null. The effect of apparent temperature on SBP was similar (1.30% increase (95% CI 0.32% to 2.29%) for a 5°C decrease in 7-day moving average).
Conclusions Cumulative exposure to decreasing ambient and apparent temperature may increase blood pressure. These findings suggest that an increase in blood pressure could be a mechanism behind cold-related, but not heat-related, cardiovascular mortality.
- blood pressure
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What this paper adds
The mechanisms behind temperature-related cardiovascular deaths are not well understood.
Because increased blood pressure is a risk factor for cardiovascular events, we studied possible associations between outdoor temperature and blood pressure.
We found that blood pressure increases in association with cumulative exposure to decreasing ambient and apparent temperature among elderly men.
These results suggest that an increase in blood pressure may be a mechanism triggering cold-related, but not heat-related, deaths.
Apparent temperature may be a more sensitive exposure variable for physiological effects than ambient temperature, but both exposures provided consistent findings in this study.
Numerous study results have shown a link between high ambient temperatures and increased mortality, especially for cardiovascular diseases,1–4 and exposure to cold temperature has also been shown to increase mortality.5 6 Recently, associations between ambient temperature and morbidity have also been reported,7 8 although these associations have not always been similar in magnitude to mortality,8 and null findings have also been reported.9 Also, while the association between temperature and cardiovascular mortality has been reported to be U-shaped in many studies,10 the association with cardiovascular hospitalisation was reported to be linear in the USA.7 As climate change has been predicted to increase not only ambient mean temperature by 1.4°C to 5.8°C by the end of this century, but also the variability of temperature, the occurrence of extreme weather conditions such as heat waves and sudden weather pattern changes may also increase.11 Therefore, the effects of ambient temperature on human health have recently become a target of vigorous research.12 13
Increased blood pressure is a risk factor for cardiovascular mortality14 15 and for coronary heart disease and stroke morbidity.16 17 Therefore, changes in blood pressure might also play a part in the development of cardiovascular events associated with changes in temperature. The effects of mild exposure to cold have been tested under controlled conditions, and the results have shown that short-term exposure to cold causes subcutaneous vasoconstriction that increases central blood volume, which further increases blood pressure.18 19 However, the effects of temperature on blood pressure under ambient conditions with changing air pressure and humidity, which may also include intermittent exposures as people enter and exit buildings, may differ substantially from those in chamber studies, and have not been thoroughly studied. Two epidemiological studies from Europe have reported that systolic blood pressure (SBP),20 or both SBP and diastolic blood pressure (DBP)21 decrease in association with increasing outdoor temperature. Another study has found that increases in outdoor and indoor temperatures may have independent, although similar, negative effects on SBP.22 However, more studies also from North America are needed to assess the validity of these conclusions.
The mechanisms behind temperature-related cardiovascular mortality and morbidity are not fully established. As elevated blood pressure is a known risk factor for cardiovascular disease and stroke events, blood pressure can also be part of the mechanism leading to temperature-related deaths. We studied the effect of outdoor temperature on DBP and SBP among elderly men using three different temperature variables (ambient, apparent and dew point temperature (DPT)). In this study, we controlled for confounding by black carbon, a marker of combustion particles that has been shown to have an effect on blood pressure in our cohort23 and elsewhere.24 Possible confounding by ozone was also studied as a suggestion of an association between ozone and blood pressure has been reported.25
The study population consisted of the Normative Ageing Study cohort of ageing men established by the Veterans Administration in 1963, when 2280 men from the Greater Boston area (21–80 years of age) confirmed to be free of known chronic medical conditions were enrolled.26 Subjects were asked to return for physical examinations and to complete questionnaires every 3–5 years. Blood pressure was measured during each visit between January 1990 and June 2009 for participants (n=1200) still presenting for examination.
Study visits were conducted in the morning after an over-night fast and abstention from smoking. Details of the physical examination have been previously described.23 Blood pressure measurements were taken by a physician using a standard mercury sphygmomanometer with a 14 cm cuff. SBP and fifth-phase DBP were measured in each arm while the subject was seated. The mean of SBP from the left and right arms, and similarly for DBP, was used in the analyses. Covariate data (age, medication, body mass index (BMI), alcohol consumption, smoking, etc) were updated at each visit. All subjects provided written informed consent prior to examinations. This investigation has been approved by the Institutional Review Boards of Harvard School of Public Health and the Normative Ageing Study, Veterans Affairs Boston Healthcare System.
Meteorological and air pollution measurements
Ambient temperature, DPT, relative humidity and barometric pressure measurements were derived from the Boston Logan airport weather station. We used only one temperature measurement site for our analyses. However, the correlation between ambient temperatures at Boston Logan airport and T.F. Green Airport (Warwick, Rhode Island), which is 100 km away, was 0.96. This suggests that day-to-day variation in temperature at Boston airport is a good surrogate for day-to-day variation at the locations of the participants (mean distance from Logan airport of 18 km). Apparent temperature, defined as a person's perceived air temperature, was calculated with the following formula: –2.653+(0.994×air temperature (°C)+(0.0153×dew point temperature2 (°C)).27 Black carbon was measured using an aethalometer (Magee Scientific, Berkeley, California) at the Harvard School of Public Health monitoring site, 1 km from the examination site. Black carbon measurements were available for January 1995 to December 2008. Ambient ozone was measured continuously at four monitoring sites in the Greater Boston area that were located in the cities of Boston, Chelsea, Lynn and Waltham. All monitors conformed to US Environmental Protection Agency (EPA) standards. In the analyses we used the average of the four measurements.
After excluding all missing data, we had 2343 clinic visits from 928 participants for the analyses. Since measurement of the indoor temperature of the examination room did not start until November 2000, there were a considerable amount of missing room temperature data, and therefore they were not used in the analyses.
Blood pressure measurements were log10-transformed to improve the normality and stabilise variance. In the mixed effects model we examined whether ambient temperature influences blood pressure, adjusting for a priori chosen known or plausible predictors of blood pressure. In this method, a random intercept is fitted for each subject, so differences across subjects are controlled for and the estimates of associations are effectively from within-subject differences. All models examining blood pressure included fixed effects for personal characteristics: BMI, age, cigarette smoking (never/former/current), alcohol consumption (≥2 drinks/day, yes/no), use of any antihypertensive medication and statins (yes/no), diabetes (yes/no), fasting blood glucose, race and years of education. Temporal variables used were: indicator variables for season (warm: May–September, cold: October–April) and weekday, and sine and cosine terms for day of year to capture seasonality more effectively.
In all models we used black carbon as a possible confounder. We previously reported that relevant associations between blood pressure and black carbon are strongest over longer averaging times. We found a 1.46 (95% CI 0.10 to 2.82) and 0.87 (95% CI 0.15 to 1.59) mm Hg increase in SBP and DBP, respectively, for a 0.43 μg/m3 increase in black carbon over a 7-day moving average,23 and therefore we used a 7-day moving average for black carbon in the current models. It was also found in the study by Mordukhovich et al23 that black carbon, but not PM2.5, was associated with blood pressure in this cohort. Additionally, all models controlled for barometric pressure 24 h prior to a study visit, and in the model for ambient temperature, the 24 h mean of relative humidity was considered as a possible confounder. We controlled for relative humidity or used exposure measures incorporating humidity, because high humidity together with high temperature adds to discomfort and heat stress.
The effects of temperature on mortality and morbidity have been seen over a lag period of up to 7–10 days,7 but more strongly at shorter lags. We therefore chose a priori to analyse lag days 0–7, and the moving averages of 2, 5 and 7 days. The analyses were performed using statistical software R 2.10.1. and its linear and non-linear mixed effects models library (nlme).28
As a sensitivity analysis, we ran a model that included separate dummy variables for each drug likely to influence blood pressure, that is the use of β- and α-blockers, calcium channel blockers, ACE inhibitors, angiotensin receptor antagonists and diuretics. Including these variables into the model instead of a single variable for the use of any antihypertensive medication (yes/no) did not affect the results. Therefore, only the variable for the use of any antihypertensive medication (yes/no) was used in the final models. We also studied the possible confounding effect of ozone, because even though the association between ozone and blood pressure is not evident,29 30 some studies have suggested ozone exposure has an effect on blood pressure.25 The influence of extreme temperatures on our associations was studied by excluding 2.5% of the hottest and coldest temperatures from the analyses, and we carried out visual inspection of the linearity of the association between temperature and blood pressure using plots created by penalised spline models, using the generalised additive mixed model (gamm) function in R.
As secondary analyses, we studied the possible effect modification of three variables. First, interactions between temperature variables and season were studied because blood pressure has been found to vary seasonally,20 and because the association between cardiovascular mortality and temperature has often been described to be J-, U- or V-shaped.10 Second, we studied interactions between temperature and obesity (BMI>30) because people with more body fat may have more insulation against cold and also be less capable of cooling their body than leaner people,31 and therefore thermoregulation between obese and lean persons may differ. Third, because the use of antihypertensive medication was common among study subjects, the interaction between temperature and antihypertensive medication use was also studied.
The total number of clinic visits was 2343 of which 1319 were during the warm season. A detailed description of the health variables at the first and the last visits is summarised in table 1.
The variation in blood pressure between seasons was minimal: mean DBP in mm Hg (SD) was 75.4 (10.5) and 75.7 (11.0) during the warm and cold seasons, respectively, and mean SBP was 130.0 (17.4) and 130.3 (18.4) during the warm and cold seasons, respectively. On average, DBP was slightly higher among obese (76.6 mm Hg, SD 10.7) than non-obese (75.1, SD 10.7) subjects. The difference in SBP was even smaller: SBP among obese participants was 129.8 mm Hg (SD 16.9) and among non-obese participants 130.2 (SD 18.2).
The mean ambient, apparent and DPT (SD) were 12.7°C (8.7°C), 12.0°C (9.8°C) and 6.4°C (9.4°C), respectively, for the whole year (table 2). Variation in the mean room temperature (23.9°C) in the period from November 2000 to December 2008 was small (SD 1.6°C).
We found mainly negative associations between temperature variables and blood pressure and therefore the results are presented as a per cent change in the arithmetic mean of blood pressure (untransformed) for a 5°C decrease in the temperature with 95% CI.
The association between a 5°C decrease in ambient temperature and DBP was strongest at lag day 5 with a 0.68% (95% CI 0.04% to 1.33%) increase in DBP. Significant associations were observed also between apparent temperature and DBP on lag days 0 and 5, and over the 2-, 5- and 7-day moving averages, the 7-day moving average having the strongest association with a 1.55% increase in DBP (95% CI 0.61% to 2.49%) (table 3). The effect estimates for DPT were somewhat different from the other two exposure variables, being closer to null. The only significant association was observed between the previous day's DPT and SBP (table 3). We found significant associations also between apparent temperature and SBP with a similar lag structure to DBP (table 3).
In all models, black carbon was a highly significant confounder. In post hoc analyses excluding black carbon, the association between ambient temperature and DBP became weaker with a non-significant effect estimate for lag day 5 (0.48%, 95% CI −0.17% to 1.14%). Associations between apparent temperature and DBP also became weaker, and only the association at lag day 5 remained significant (lag day 5: 0.60%, 95% CI 0.02% to 1.19%; 7-day moving average: 0.26%, 95% CI −0.65% to 0.18%). Another post hoc analysis was performed for relative humidity. However, no associations were found between relative humidity and blood pressure (see online table).
The associations we found were strongest between DBP and apparent temperature over 5- and 7-day moving averages, but we also observed an association with current day. We chose lag 0 and a moving average of 7 days for the more detailed analyses. In these analyses, lag day 0 represented more acute effects, and the moving average of 7 preceding days, accumulated effects.
In the sensitivity analyses, we found that controlling for ozone had a minor effect on the observed associations. The association between ambient temperature and DBP at lag 0 remained the same as in the main analysis (0.64%, 95% CI −0.04% to 1.33%). The increase in DBP in association with a decrease in apparent temperature at lag 0 and over the 7-day moving average was 1.00% (95% CI 0.35% to 1.66%) and 1.42% (95% CI 0.44% to 2.42%), respectively. Ozone did not confound the association between apparent temperature and SBP (1.25%, 95% CI 0.21% to 2.29% for the 7-day moving average).
We observed little change in the results when the hottest (n=57) and coldest (n=50) 2.5% of the temperatures were excluded from the data. The increase in DBP was 0.73% (95% CI 0.01% to 1.46%) for a 5°C decrease in ambient temperature on the current day, and 1.54% (95% CI 0.54% to 2.55%) for a 5°C decrease in the 7-day moving average of apparent temperature. DPT had a slightly stronger effect on DBP (0.66%, 95% CI 0.09% to 1.23%, lag 0). The association between the 7-day moving average of apparent temperature and SBP became weaker (1.09%, 95% CI 0.04% to 2.15%).
As another sensitivity analysis, we tested the linearity assumption by fitting penalised splines for apparent temperature using a generalised additive mixed model. The model chose the optimised degrees of freedom for temperature using generalised cross validation, which were 2 and 1 degrees of freedom for the 7-day moving average of apparent temperature in the DBP and SBP models, respectively, supporting a linear effect.
In the secondary analyses, we found a significant interaction between all exposure variables and obesity (p<0.05) in the DBP, but not in the SBP, models. We observed stronger associations among obese than leaner subjects (table 4). Temperature variables had no interactions with season or with the antihypertensive medication use in our models.
In this study, we found that DBP among elderly men increases in association with decreasing ambient and apparent temperature. These increases were not due to particulate pollution, ozone or extreme temperatures. We found weaker associations between temperature and SBP.
We found an increase in DBP in association with cumulative exposure to decreasing outdoor temperature. Our findings are similar in direction to the recently published findings of the effects of temperature on SPB among elderly subjects,20 even though that result was not an effect controlling for air pollution. The authors also found seasonal variation in blood pressure with higher values occurring during the winter, whereas we found little difference in blood pressure measurements between warm and cold seasons. Seasonal variation in blood pressure was also found in a Norwegian study, but it disappeared after adjusting for outdoor temperature.21 Consistent with our findings, Madsen and Nafstad21 reported an increase in DBP and SBP in association with decreasing outdoor temperature. The multi-city Monica study22 also reported findings consistent with those of our study, as have chamber studies on modest cold exposure.18 19 Given that increased blood pressure is a known risk factor for cardiovascular mortality and morbidity, these findings suggest that increases in blood pressure could be related to cold-induced cardiovascular mortality.
In this cohort, the associations between temperature and DBP were also stronger among obese than leaner participants. This may partly be due to higher average DBP among obese compared to non-obese subjects. However, the hypothesis that more body fat provides better insulation, and therefore leads to smaller changes in blood pressure with exposure to low temperatures, could not be supported. In the study of Alperovitch,20 the decrease in SBP in association with increasing temperature was also greater for obese subjects; however, the authors did not report findings for DBP.
Black carbon was a significant confounder for the associations between temperature and blood pressure, and inability to control for black carbon would have resulted in biased effect estimates. This finding is not surprising as an association between black carbon and blood pressure has already been seen in our study cohort.23 In general, traffic-related air pollution and particles from combustion sources may have even greater adverse effects on cardiovascular health than PM10 or PM2.5 (particles with diameter <10 and <2.5 μm, respectively).32–34 Therefore, the possible confounding by particles specifically from these sources should be controlled for, but several studies assessing the health effects of temperature have failed to do this.1 7 20 35 36 Even though confounding by particles has not been observed in all studies of the health effects of temperature,2 4 the evidence that PM10 may act as a confounder in temperature-related cardiovascular mortality37 38 and the current finding for black carbon underline the importance of considering ambient particles as confounders when the effects of temperature on blood pressure and other cardiovascular outcomes are evaluated.
Of the three temperature variables, we found the strongest associations for apparent temperature, but the effect of ambient temperature was very similar and the effect lag structures of these variables were consistent. Apparent temperature is an exposure variable that is used to describe how people perceive the combination of temperature and humidity. At warm temperatures, high humidity increases the feeling of discomfort and heat stress, and therefore apparent temperature may be more a sensitive exposure variable for physiological effects than ambient temperature. However, based on our findings, both of these exposure variables are useful when estimating the health effects of outdoor temperature. DPT had slightly different effect estimates from ambient and apparent temperatures, especially with the cumulative exposures, which may be due to the close relationship between DPT and relative humidity. DPT reflects temperature well on days when humidity is high, but if humidity is low it may be a worse proxy of temperature than humidity.
There are several limitations related to our study. One is that the study population consisted of elderly men from one metropolitan area, which is why the results are not representative of the general population, or applicable for regions with different climate conditions. For example, one study has suggested that vulnerability to cold-related mortality is higher among elderly men than women,39 and others have found regional differences in cold-related mortality.5 40 Elderly people may also be more vulnerable to cold and heat exposures than younger populations due to changes in thermoregulation. As an example, older people may have poorer vasoconstrictor response to cold exposure than younger people, which leads to greater heat loss,41 or they can have reduced skin blood flow when under heat stress leading to inadequate heat loss.42 However, controlling for the effects of sedentary lifestyle and chronic conditions may diminish the effect that ageing has on thermal tolerance.31
Another limitation is that we were not able to control for the possible confounding effect of indoor temperature or clothing. It has previously been noticed that air conditioning and behaviour can modify the adverse impacts of temperature extremes.35 We had no data on the subjects' home indoor temperature, and the temperature in the examination room was measured for 5 years less than other variables. However, when indoor temperature was measured, it varied little. Additional limitations are that we had only one measurement of blood pressure for each clinic visit, which may have been affected by many external stimuli, and even though we had data from several clinic visits for most subjects, some attended only one visit during this study period. Mixed effect models are used especially for studies with repeated measures, but do not require repeated measures for all subjects. Even though we note that while the estimated random intercepts for subjects with only one measurement are noisily estimated, the inferences for the fixed effects, such as temperatures, are appropriate in these models. Moreover, these models have been used for the same population in previous studies.23 43
We also had data from only one measurement site for temperature and black carbon, which may cause some exposure misclassification. However, we did find high correlation between temperatures measured at airports 100 km apart, which suggests that variation in temperature in the study area is small. For black carbon, it seems likely that using one measurement station would lead to an underestimation rather than an overestimation of the health (or confounding) effects, because most of the measurement error would be so-called Berkson error, which reduces power to reveal significant effect.44 Furthermore, the goal of this paper was not to estimate the effect of black carbon, but of temperature, and black carbon was examined only as a potential confounder.
In conclusion, we found that a decrease in outdoor temperature can cause an increase in DBP among elderly men. These results suggest that blood pressure may increase with decreasing temperature, therefore possibly playing a part in cold-related, but not heat-related, mortality. However, more research on the effects of outdoor temperature on blood pressure is needed using diverse study cohorts and personal measurements to confirm our findings. Ambient and apparent temperature can be used as exposure variables when investigating the health effects of temperature.
Funding This work was supported by National Institute of Environmental Health Sciences grants ES014663, ES 15172 and ES-00002, and by U.S. EPA grant R83241. The VA Normative Ageing Study is supported by the Cooperative Studies Program/Epidemiology Research and Information Centers of the U.S. Department of Veterans Affairs and is a component of the Massachusetts Veterans Epidemiology Research and Information Center, Boston, Massachusetts. Financial support for Jaana I Halonen from the Finnish Cultural Foundation and Finnish Foundation for Cardiovascular Research is warmly acknowledged.
Competing interests None.
Ethics approval The study was approved by the Human Subject's Committee of the Harvard School of Public Health, and the IRB of the U.S. Veteran's Administration.
Provenance and peer review Not commissioned; externally peer reviewed.
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