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. Author manuscript; available in PMC: 2022 Dec 1.
Published in final edited form as: Hypertension. 2021 Oct 25;78(6):1801–1808. doi: 10.1161/HYPERTENSIONAHA.121.17708

Long-Term Exposures to Urban Noise and Blood Pressure Levels and Control Among Older Adults

Jennifer D’Souza 1, Jennifer Weuve 2, Robert D Brook 3, Denis A Evans 4, Joel D Kaufman 5, Sara D Adar 1
PMCID: PMC8585701  NIHMSID: NIHMS1741938  PMID: 34689591

Abstract

Urban noise is a common environmental exposure that may increase the burden of hypertension in communities yet it is largely unstudied in the United States and it has not been studied in relation to blood pressure (BP) control.

We investigated associations of urban noise with blood pressure levels and control in the United States.

We used repeated BP and medication data from Chicago-based participants of the Chicago Health and Aging Project (≥65 years) and Multi-Ethnic Study of Atherosclerosis (≥45 years). Using a spatial prediction model with project-specific measurements, we estimated noise at participant homes. We imputed BP levels for those on medication and used mixed-effects models to evaluate associations with noise. Logistic regression was used for uncontrolled and apparent treatment-resistant hypertension (aTRH). Models were run separately by cohort and altogether, all with adjustment for age, sex, sociodemographic factors, and other plausible sources of confounding.

We evaluated 16,462 BP measurements from 6,764 participants (6,073 CHAP and 691 MESA) over an average of 4 years. For both cohorts we found that greater levels of noise were associated with higher BP levels and greater risk of aTRH. In our pooled models, 10-dBA higher residential noise levels corresponded to 1.2 (95% CI: 0.1, 2.2) and 1.1 mmHg greater (95% CI: 0.6, 1.7) systolic and diastolic blood pressures as well as a 20% increased odds of aTRH (OR per 10dBA:1.2 [95% CI: 1.0, 1.4], p=.04)..

Urban noise may increase blood pressure levels and complicate hypertension treatment in the United States.

Keywords: Noise, Hypertension, Blood Pressure, Medication, Resistant Hypertension

Introduction

A high proportion of individuals who have hypertension, is uncontrolled1,2 or resistant to treatment.3-5 Recent analyses showed a concerning declining trend in blood pressure control, with older adults the least likely to have controlled blood pressure.6,7 Altogether these indicate that hypertension will continue to result in substantial costs to the nation.8

The contribution of common environmental exposures to hypertension and blood pressure control may be important to consider because these exposures can be modified at the population level.9 For example, exposure to urban noise is a highly prevalent risk factor for high blood pressure10. Previously, noise has been associated with major pathways that lead to higher blood pressure and worse control, including eliciting stress responses,11,12 disrupting sleep13 and other mechanisms14,15 as well as increased risks of hypertension16,17 and cardiovascular events.18,19 However, these effects have largely been unstudied in the United States and are not considered in current national regulatory standards for noise even though there are effective ways to reduce exposure. Additionally, despite the associations with risk factors for resistant hypertension, noise has not been directly linked with this important outcome. This paper aims to quantify associations of urban noise with both blood pressure levels and control in older adults in Chicago, Illinois using data from two large, prospective cohort studies.

Methods

Because of the sensitive nature of the data collected for this study, requests to access the dataset from qualified researchers trained in human subject confidentiality protocols may be sent to Rush University School of Medicine at kbrajan@ucdavis.edu (Chicago Health and Aging Project) or Collaborative Health Studies Coordinating Center, University of Washington, at chsccweb@u.washington.edu (Multi Ethnic Study of Athersclerosis).

Study Population

This analysis draws data from two prospective cohort studies of older adults: the Multi-Ethnic Study of Atherosclerosis (MESA) and the Chicago Health and Aging Project (CHAP). MESA was designed to investigate subclinical cardiovascular disease and the risk factors for progression to clinical cardiovascular disease. To this end, MESA enrolled 6,814 participants from six metropolitan areas between 2000-2002, who were between 45-84 years of age and free of clinical cardiovascular disease. Individuals were observed in clinical examinations at baseline and during 4 follow-up visits in 2002-4, 2004-5, 2005-8, and 2010-12.20 Since we have a noise model in only Chicago, Illinois, for this study we restricted our analysis to the 1,164 Chicago-based MESA participants for whom we could estimate noise levels.

CHAP was initiated in 1993 in Chicago to study the risk factors for chronic conditions with an emphasis on cognition.21,22 Investigators enrolled a total of 10,802 residents on a rolling basis who were aged 65 years or older and conducted in-home study visits triennially. To be consistent with the MESA cohort, we focused on participants observed after 2000. Study protocols from both studies were approved by the institutional review boards of each study site (Rush University Medical Center, Northwestern University and the University of Washington), all participants provided written consent for inclusion in CHAP and MESA, and this research was approved by the institutional review board at the University of Michigan.

Blood Pressure Levels and Control

Systolic (SBP) and diastolic (DBP) blood pressures were measured in both cohorts during each participant contact. After participants rested for 5 minutes in a seated position, blood pressure measurements were collected using a sphygmomanometer. To get a stable estimate of blood pressure, we averaged two sequential BP measurements from each participant at each exam. We used the hypertension definition contemporaneous with the assessment which was SBP≥140mmHg or DBP≥90mmHg23 or being on antihypertensive medication (self-reported), though the recent thresholds were also used in secondary analyses.24

Blood pressure control was defined as a 3-level outcome: not hypertensive or controlled (measured SBP<140 and DBP<90 and on antihypertensive medication), uncontrolled hypertension (measured SBP≥140 or DBP ≥90 mmHg, regardless of medication), and apparent treatment resistant hypertension (aTRH). aTRH was defined as being on more than 4 classes of antihypertensive medication or being on 3 or more classes of antihypertensive medication (including a diuretic) and remaining hypertensive.3 Data on medication adherence was not available, thus only aTRH could be ascertained.

Noise Modeling

We estimated each participant’s long-term noise exposure using a prediction model developed for Chicago based upon two intensive sampling campaigns conducted between 2006 and 2007.25,26 Briefly, 5-minute grab samples of A-weighted noise levels in decibels (dBA) were taken at 136 locations across the Chicago area during non-rush hour periods to capture noise near participant residences and locations with different proximities to local noise sources (e.g., highways, airports). A-weighting was used so that our noise estimates would reflect what is actually perceived by the human ear by reducing decibel values for frequencies that are imperceptible to the human ear. We constructed a land-use regression model in which geographic covariates (e.g., land use, proximity to roadways, bus stops, trains) were used to predict noise measurements. We then used this model to estimated individual-level, long-term noise exposure for all participants based on their 5-year residential history prior to each interview.

Our models showed strong predictive power with a leave-one-out cross-validated R2 of nearly 0.7. In addition, an external validation data set collected in 2016 demonstrated strong stability in the spatial variation of noise levels across time. Samples collected from the same locations in 2016 and 2006/2007 had a correlation of 0.8, indicating that the spatial differences remained stable. Data from 2016 similarly showed stability in the key predictors of noise captured by the previous model (Table S1).

Covariates for the Estimation of the Noise-Blood Pressure Association

From participant interviews we had self-reported data on each participant’s age, sex, race/ethnicity, income, education, smoking status, alcohol intake, physical activity, and medications. Height and weight were also measured. A subsample in CHAP and all MESA participants were also administered a food frequency questionnaire. At each participant address, we obtained additional environmental factors: air and light pollution levels. Annual average ambient concentrations of nitrogen oxides (NOx) and fine particulate matter (PM2.5) were estimated based on a spatiotemporal model derived from intensive monitoring data in the MESA Air Pollution Study.27 Both NOx and PM2.5 are important as they act as surrogates of traffic-related air pollution, which may be a key source of confounding in the estimated noise-blood pressure association. Light pollution is also associated with urbanization and cardiovascular outcomes.28,29 Total brightness levels at participant addresses were obtained from publicly available data.30 On the area-level, we generated a neighborhood socioeconomic score (NSES) using a principal components analysis of census block-level data, such as percentage of residents with a bachelor’s degree, median home value, and household income.31

Statistical Methods

First, we used multivariable linear mixed models with random person-specific intercepts to estimate associations of long-term residential noise exposure with SBP and DBP levels. For these regression analyses, and following the methodological literature,32,33 we imputed BP levels separately by cohort to adjust for antihypertensive medication use. Conceptually this approach approximates what a participant’s blood pressure would be if they were not on hypertensive medications, as a function of their age, sex, race, and class(es) of antihypertensive medication(s).

Next, we examined the association of noise levels with blood pressure control by modeling the association with a 3-level categorical outcome: normal blood pressure or controlled hypertension (comparison population), uncontrolled hypertension, and aTRH. We used a multinomial nominal logistic regression with generalized estimating equations to account for repeated measures for each participant. This generates separate estimands for each outcome-level (uncontrolled hypertension or aTRH), which represent the difference in odds of the outcome-level with an increase in noise levels, as compared to the normal/controlled hypertension group (referent-level).

All models were run stratified by cohort and altogether since there was no evidence of effect modification as evidenced by an interaction term between noise and cohort in our pooled model. We adjusted for visit-specific variables (age, calendar time,34 smoking status) and time-invariant variables (sex, race, income, education, NOxNSES). Since we observed statistical differences in blood pressure levels and relationships of blood pressure with key covariates by cohort, we also included a cohort term in our combined models as well as interaction terms of cohort with age, race, and sex. All associations are scaled to a 10dBA increase in noise.

In secondary analyses, we checked for non-linearity of the associations between noise and blood pressure using b-splines and categories of exposure overall and stratified by cohort. We further explored adjustment for additional potential sources of confounding (BMI, current alcohol use, physical activity and dietary sodium; PM2.5and light pollution) as well as adjustment for possible selection bias due to attrition, using an inverse probability weighting (IPW) approach.35 Although our primary hypothesis is that exposure to noise would result in a reversible shift in BP levels, we still tested whether noise was associated with altered aging trajectories by estimating the difference in the BP rate of change per year of age, using a noise by age interaction term. Finally, in order to check for consistency with our main findings, we explored associations with prevalent but not incident hypertension due to the very small number of CHAP participants who were not hypertensive at baseline.

Results

After sub-setting to participants with complete exposure and covariate and medication data after 2000, we had a total study population of 6,764 participants (n=6,073 CHAP participants; n=691 MESA participants) with 16,462 repeated measures of blood pressure. For MESA participants, noise exposures were only available within Chicago city limits thus those in the Chicago suburbs were excluded from the analysis. Additionally, participants who had geocovariate values that required extrapolation beyond the limits of the noise model were excluded. As aformenetioned, CHAP was initiated prior to 2000, and participant data from before 2000 were also excluded in order to match the time period of MESA.

As shown in Table 1, there were more females than males (38% male) in the study population and most participants were Black (60%) or White (38%) with only a few identifying as Chinese (1%). The mean age at baseline was 73 years (SD: 8) and correspondingly, most of the study population (86%) was classified as having hypertension at baseline. SBP and DBP were, on average, lower in MESA participants than in CHAP participants, who tended to be older and were more likely to be Black, with less education and lower incomes (Table 1). Participants also experienced a wide range of long-term exposure to residential noise (51 to 81 dB; Figure S1) and air pollution (NOx range: 18.8 to 69.3 ppb) though in this population noise was weakly correlated with NOx , PM2.5 or light pollution levels (Pearson correlation<0.3).

Table 1.

Baseline Characteristics of the Study Population (N (%) or mean(SD*))

Variable Pooled
(n=6,764)		 MESA
(n=691)		 CHAP
(n=6,073)
Age (years) 72.7 (8.0) 63.2 (10.1) 73.8 (7.0)
Followup (years) 4.3 (3.7) 8.0 (2.6) 3.8 (3.6)
Male 38.0% 46.6% 37.0%
Study Cohort
 CHAP 89.8% -- --
 MESA 10.2% -- --
Race
 White 38.3% 53.8% 36.5%
 Chinese 1.3% 12.7% 0.0%
 African-American 60.5% 33.4% 63.5%
Education
 <HS 23.4% 8.1% 25.1%
 HS/Some College 67.0% 31.3% 71.1%
 College 3.8% 23.0% 1.6%
 More than college 5.8% 37.6% 2.2%
Income
 <$14,999 (CHAP)/ <$15,999 (MESA) 20.7% 8.7% 22.0%
 ≤$29,999 34.3% 13.6% 36.7%
 >$29,999 41.8% 75.8% 38.0%
 Missing 3.2% 1.9% 3.3%
Neighborhood SES (higher is more disadvantage) 0.0 (1.0) −1.8 (1.4) 0.2 (0.7)
BMI (kg/m^2) 28.3 (6.1) 27.2 (5.2) 28.5 (6.2)
Smoking Status
 Never 46.4% 45.7% 46.4%
 Former 41.7% 42.4% 41.6%
 Current 12.0% 11.9% 12.0%
Imputed SBP (mmHg) 141.3 (20.5) 126.6 (19.7) 143.0 (19.9)
Observed SBP (mmHg) 134.0 (18.6) 123.4 (20.1) 135.2 (18.1)
Imputed DBP (mmHg) 80.2 (11.4) 73.0 (9.8) 81.0 (11.2)
Observed DBP (mmHg) 76.5 (11.0) 71.1 (10.0) 77.1 (11.0)
Had hypertension§ 86.1% 57.6% 89.3%
 Uncontrolled and 1-2 medications║ 49.1% 19.5% 52.5%
 aTRH # 12.3% 3.5% 13.3%
Noise (dBA) 56.5 (3.5) 59.4 (5.7) 56.2 (2.9)
NOx (ppb) 41.8 (6.6) 44.4 (6.6) 41.5 (6.5)
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*

SD: standard deviation

†

HS: High School

‡

Neighborhood Socioeconomic Score, higher is more disadvantage

§

Hypertensive (antihypertensive medication or SBP≥130mmHg or DBP≥80mmHg);

║

Uncontrolled hypertension (1-2 classes of antihypertensive medication and, SBP≥130mmHg or DBP≥80mmHg)

#

aTRH: Apparent Treatment-Resistant Hypertension (≥3 antihypertensive medication classes, including a diuretic and hypertensive, or ≥4 antihypertensive medication classes)

Associations with Blood Pressure

Positive associations between noise and blood pressure were present in both CHAP and MESA (Figure 1). Following adjustment for personal and neighborhood characteristics, a 10-dBA greater residential noise level was associated with 0.6 (95% CI: −0.6, 1.8), 2.9 (95%CI: 0.6, 5.3) and 1.2 (95% CI: 0.1, 2.2) mmHg higher SBP in CHAP, MESA and both cohorts, respectively. Likewise, there was a 1.1 (95%CI: 0.6, 1.7), 1.3 (95%CI: 0.1, 2.5) and 1.1 mmHg higher DBP (95% CI: 0.4, 1.7) for a 10dBA increase in noise for CHAP, MESA and both cohorts, respectively. Although associations with SBP (but not DBP) were suggestively stronger in the MESA cohort, these results were not statistically different from one another. These associations were monotonic and largely linear (Figure 2), insensitive to different adjustments for antihypertensive medication use (Figure S2), adjustment for additional putative confounders, including co-exposures (Figure S3), and incorporation of IPW to adjust for possible selection bias from differential attrition (Figure S3). Our secondary analyses also indicated that noise was associated with prevalent hypertension (OR:1.2 [95% CI: 1.0, 1.3]) but was not associated with the pace at which blood pressures changed as participants aged (Table S2).

Figure 1. Overall and Study-Specific Associations Between Noise and Blood Pressure Levels and Control.

Figure 1.

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We observed that noise was associated with greater blood pressure levels and increased odds of apparent treatment resistant hypertension in both our overall models and study-specific models.

Models adjusted for adjusted for calendar time, visit age, sex, race, income, education, neighborhood SES, smoking status, air pollution, study cohort and study cohort by age, sex, race, education interaction terms. Note that 95% Confidence Intervals do not account for imputations. Associations are scaled to a 10dBA increase in noise.

Figure 2. Multivariable-adjusted Dose-Response Associations Between Noise and Blood Pressure Levels.

Figure 2.

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Using splines, we observed a linear dose-response association between noise and blood pressure, where increase in noise levels were associated with increases in both systolic and diastolic blood pressures.

Models adjusted for adjusted for calendar time, visit age, sex, race, income, education, neighborhood SES, smoking status, air pollution, study cohort and study cohort by age, sex, race, education interaction terms. Note that 95% Confidence Intervals do not account for imputations.

Associations with Blood Pressure Control

Noise was associated with aTRH (OR:1.2 [95% CI: 1.0, 1.4], p=0.04) and were consistent across both study cohorts (Figure 1; CHAP: 1.2 [95%CI: 1.0, 1.4]; MESA: 1.4 [95%CI: 0.8, 2.4]). These associations were not sensitive to changes in blood pressure cutoffs and were robust to further adjustment for environmental factors (light pollution, PM2.5), and BMI, physical activity, alcohol intake and sodium intake, though the latter slightly strengthened the association with aTRH in the subsample with data on these parameters (n=3047, Figure S3).

Discussion

In this analysis of two cohorts of older adults in Chicago, Illinois we found evidence that higher long-term urban noise levels were associated with both greater blood pressure levels and greater odds of resistant hypertension. Importantly, the observed associations were robust across both independent cohorts even after adjustment for socoeconomic factors and other traffic-related air pollutants. At increases of 1.2 mm Hg in SBP and 1.1 mm Hg in DBP per 10 dBA, the magnitude of the observed associations are also roughly equivalent to changes in blood pressure between persons differing by 1.5 years of age. On the population level, a shift in the mean SBP by as little as 1mm Hg is expected to result in 10 to 20 additional heart failure related hospitalizations and deaths per 100,000 person-years in the United States.36 Since more than half of US city-dwellers experiencing noise above the World Health Organization’s recommended residential levels,37 this work suggests that urban noise may be an important yet understudied and modifiable risk factor for high blood pressure and poor blood pressure control in US communities.

There are plausible biological mechanisms to support observed associations between noise exposures and high blood pressure and worse control. Current hypotheses include pathways of an endocrine stress response11,12 and alterations in sympathetic tone that are initiatied by noise annoyance, sleep disruption,10 or via other direct mechanisms.14,15 Evidence for these mechanisms can be found in rats where noise induced a range of stress-related responses including increased BP and stress hormones.38 DNA damage has also been found in the adrenal gland (an important player in the stress response) of noise-exposed animals that persisted for 24 hours.39 The same mechanisms appear activated in humans with evidence of changes in heart rate variability,40 impaired endothelial function, increased levels stress hormones41 and other stress responses19,42 where nighttime noise43,44 was found to be especially harmful. Nighttime noise exposure has additional impacts of disrupting circadian rhythms and sleep.13 Many of the aforemention mechanisms also overlap with those that have been associated with uncontrolled and resistant hypertension,45,46 in particular the sleep disruption pathway3, and warrant further investigation. Finally, in addition to direct impacts, noise may indirectly affect blood pressure through responses elicited by changes in mood, appetite and cognitive performance, the last of which has been shown specifically in the CHAP cohort included in this analysis.25

This research contributes to the literature as a comprehensive population-based study of associations between urban noise levels and blood pressures and blood pressure control in older adults in the US. It is consistent with a recent smaller US study investigating noise and stress mechansisms,19 as well as adding to the previous research of noise as a risk factor for blood pressure47-50 and hypertension in Europe.16,17,51 It was previously hypothesized that the strength of the associations might differ due to different urban forms (e.g., street configuration, building construction, layout, and ventilation) in the US since the work of Foraster et al 52,53 suggests that building structures may play a strong role in the associations of noise and blood pressure. Our findings, however, suggest that associations observed in Europe are also likely relevant to the US population. Evidence of this relationship is strengthened by consistent findings across two independent cohorts of older adults. Collectively, these findings are important since the last guidelines for community noise levels in the US were set by the Environmental Protection Agency in the 1970s to protect against hearing loss and these do not consider other endpoints like blood pressure levels. As a result, the current US standard is nearly two times more permissible than standards set by the European Union to also minimize cardiovascular disease at 40 dB for nighttime and 50 dB for daytime noise.

We leveraged two large prospective population-based cohort studies with well-collected and comparable measures of BP, medication, and important covariates. As such, our analyses included detailed adjustment for both socioeconomic factors and traffic-related air pollution, which are both established risk factors for cardiovascular disease9,54-60 and correlates of noise.61-63 Repeated measures of blood pressure and medication use over several years also reduced the likelihood of bias due to between-person confounding.17 In addition, this detailed data allowed us to investigate associations with both continuous biological parameter (blood pressure) as well as blood pressure control and hypertension, two clinically relevant outcomes. Our exposure assessment was unique for the US, which historically has not had community noise exposure assessments. Finally, the consistency of the noise association across two independent cohort studies strengthens the evidence that noise is adversely associated with blood pressure.

Study Limitations

Our study had limitations that warrant mention. Our noise assessment, while an improvement over previous studies,17 was still an aggregate measure and did not allow us to disentangle the different aspects of noise exposure including timing of exposure, factors affecting exposure,64 and originating source. We also used noise levels based on daytime and outdoor levels, which have not been associated with BP as strongly as nighttime48 and indoor noise52, and failed to capture any temporal characteristics of noise that can elicit strong stress reactions such as intermittent noise fluctuations,65 peak nighttime noise and the timing of the nighttime noise exposure,43 which would help us determine whether noise is detrimental by disrupting sleep.43,44 Similarly, we did not have data on factors that affect noise exposures, such as window-opening and room orientation. Collectively, this likely added greater imprecision to our exposure measure and may have reduced our ability to detect the true magnitude of the association between noise and blood pressure. Notably although data on noise sources may be important from a noise mitigation perspective, a recent meta-analysis found no difference in associations between air, roadway, and railway noise with prevalent hypertension.16 Finally, our analysis that conditions on hypertension and hypertension medication use has the potential to bias observed associations if predictors of higher levels of noise, such as SES, also predict treatment-related factors like participants’ adherence and suboptimal dosing. We suspect that this is not too problematic since our models were robust to adjustment for SES.

Supplementary Material

Online Supplement

Perspectives.

In summary, this research showed that not only is noise associated with higher blood pressures, but also newly associates noise with resistant hypertension. These findings and its consistency across two cohorts and with those results reported in Europe, altogether suggest that that body of literature has direct relevance to possible standard setting in the US. Such standarads could have wide impacts as 50% or 100 million of Americans experience noise at high levels66 and thus may be an effective means of improving blood pressure levels. Further research is warranted into the specific characteristics of noise that are harmful, especially nighttime noise.

Novelty and Significance.

What Is New?

  • This analysis leverages two cohort studies in Chicago, Illinois to estimate associations between urban noise exposure and blood pressure and resistant hypertension

What Is Relevant?"

  • Greater urban noise exposure is associated with higher blood pressures and odds of resistant hypertension

Summary

This research suggests that the adoption of strategies for mitigating urban noise may be an effective means of improving blood pressure levels and control among the 50% or 100 million of Americans who experience noise at high levels.

Acknowledgements

The authors also thank the other investigators, the staff, and the participants of the MESA and CHAP studies for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. The authors declare they have no actual or potential competing financial interests. The authors thank Drexel Urban Health Collaborative for data and technical support. The authors take sole responsibility for all data analyses, interpretation, and views expressed in this work.

Source of Funding

This work was supported by American Heart Association Grant # 16GRNT30960046 / Sara D. Adar/ 2016. CHAP was funded with awards from the National Institute on Aging of the NIH (NIA/NIH) under award AG011101. This publication was developed under a STAR research assistance agreement, No. RD831697 (MESA Air), awarded by the U.S Environmental protection Agency. It has not been formally reviewed by the EPA, however, and the views expressed in this document are solely those of the authors. The EPA also does not endorse any products or commercial services mentioned in this publication. This work was also supported by the National Institutes of Health (R01-HL086719, R01 HL071759). MESA was further supported by contracts N01-HC-95159 through N01-HC-95169 from the National Heart, Lung, and Blood Institute (NHLBI) and by grants UL1-TR-000040 and UL1-RR-025005 from the National Center for Research Resources (NCRR). One author (JDK) was supported by P30 ES07033 and K24 ES013195.

Abbreviations:

CHAP

Chicago Health and Aging Project

MESA

Multi Ethnic Study of Atherosclerosis

dBA

decibels (A-weighted)

aTRH

apparent treatment-resistant hypertension

SBP

systolic blood pressure

DBP

diastolic blood pressure

Footnotes

Disclosures

None.

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