Study population

This observational, cross‑sectional study was conducted in a rural area near Kraków, Poland, between June 2015 and June 2016. The study included 2 groups of individuals: exposed (people affected by chronic nighttime aircraft noise) and unexposed (those who were not affected). Based on an acoustic map prepared in 2009 by the Małopolska Regional Council—Resolution no XXXII/470/09¹⁷ (Figure 1), we selected exposed participants from an area influenced by high nighttime aircraft noise levels (L_N exceeding 50 dB) in the Morawica village located within the deep blue equal‑loudness contour at L_N of 50 dB and the red one at an A‑weighted long‑term average sound level over 24 hours of 60 dB. That area was also selected for noise‑exposed participants recruited in our previous study.¹⁸ The unexposed group was recruited from another village (Jeziorzany) located 15 km from an airport outside the light blue equal‑loudness contour at L_N of 45 dB in the south, as indicated by the yearly weighted nighttime sound level, L_N.¹⁹ Cutoff levels were consistent with those endorsed by the World Health Organization and European environmental noise guidelines for evaluating the health effects of noise^20,21 and confirmed using field noise measurements. Other environmental conditions did not differ between the selected sites.

Age between 40 and 65 years, which was considered optimal for assessing hypertension‑mediated organ damage (hypertension‑mediated organ damage was the primary research objective in a previously published paper of this team¹⁸), length of residence in a given area (a minimum of 3 years), and willingness to participate in the study constituted additional inclusion criteria. The exclusion criteria were as follows: heart failure, coronary artery disease, myocardial infarction, stroke, liver, kidney, or respiratory disease, deafness or serious hearing loss, and obstructive sleep apnea,²² as classified by the International Classification of Diseases, Tenth Revision codes. Shift workers were also excluded from the study.

The total study population primarily considered for study inclusion consisted of 619 inhabitants from 2 locations affected by low and high noise level exposure, as derived from the population registries. All 300 people living in the area of high nocturnal noise level exposure (>50 dB, the Morawica village) were invited to participate in the study. Among them, 143 individuals responded to the invitation (reportability rate, 47.7%), while 101 met the basic inclusion criteria. Of 101 participants, 53 were further excluded due to arterial hypertension defined as previously diagnosed and treated hypertension or BP values during 24‑hour ambulatory BP monitoring exceeding: systolic BP (SBP) of 130 mm Hg and / or diastolic BP (DBP) of 80 mm Hg and SBP of 140 mm Hg; and / or DBP of 90 mm Hg in the office setting. Ultimately, for the presented analyses, we included 48 normotensive participants (the exposed group [n = 48]).

A comparison group of individuals exposed to a low nighttime aircraft noise level (<⁠45 dB, the Jeziorzany village) in their place of residence was also recruited. We invited 319 inhabitants, 134 of whom volunteered to participate in the study (reportability rate, 42%), and 100 met the inclusion criteria. Among those, 50 had arterial hypertension and 50 constituted the control normotensive group (the unexposed group [n = 50]).

We obtained anthropometric data and information on lifestyle habits, subjective noise annoyance, and sleep quality from all participants using a dedicated, standardized questionnaire. Noise annoyance was evaluated with a 3‑point scale: 0, none; 1, moderate; and 2, high. In addition, on the day of the participant’s visit at the outpatient clinic, we performed a physical examination and took their medical history. Study examinations and surveys were consecutively conducted during a single entire day: a standardized questionnaire, BP measurements, and ambulatory BP monitoring setup.

The study complied with the Declaration of Helsinki. The Jagiellonian University Ethics Committee approved the study protocol. All participants were informed about the purpose and methodology of the study and provided written consent to participate in it.

Blood pressure measurement

We measured office BP twice in the nondominant arm after 10 minutes of rest, using the Omron M5‑I device (Omron, Kyoto, Japan). The mean value of the 2 measurements was used in further analyses. Measured office BP values included SBP and DBP. Pulse pressure (PP) was calculated as SBP minus DBP. Additionally, 24‑hour ambulatory BP monitoring was performed using SpaceLabs 90207, a device equipped with the appropriate software (SpaceLabs Healthcare, Snoqualmie, Washington, United States). Measurements were taken every 15 minutes during daily activity (6:00 am–10:00 pm) and every 20 minutes at night (10:00 pm–6:00 am). We collected data on 24‑hour, daytime, and nighttime BP and heart rate (HR).

The nocturnal dipping of SBP and DBP as well as the night drop of HR were calculated as the difference between the mean daytime BP or HR value and the mean nighttime BP or HR value and expressed as a percentage of the day value.

Sleep quality analysis

Insomnia was evaluated using the Athens Insomnia Scale (AIS).²³ Sleep quality was measured by assessing 8 factors, among which the first 5 were related to nocturnal sleep and the last 3, to daytime dysfunction. These were rated on a scale ranging from 0 to 3, and sleep was ultimately evaluated from the cumulative scores of all factors and reported as an individual’s sleep outcome. A cutoff score higher than or equal to 6 on the AIS was used to diagnose insomnia.²⁴

Statistical analysis

Statistical analyses were performed using the SAS software, version 9.1 (SAS Institute, Cary, North Carolina, United States). Results were expressed as numbers and percentages for categorical variables and as mean (SD) for continuous variables.

The exposed and unexposed groups were compared using the t test for continuous variables and the χ² for qualitative variables. The risk of insomnia in the exposed participants was assessed by calculating the odds ratio (OR) in the univariate LOGISTIC procedure. Differences in the AIS score among participants were grouped according to self‑reported noise annoyance degree (0, 1, or 2) and assessed using the Kruskall–Wallis test. The Dunn post hoc test was used to determine differences between the study groups. In order to detect BP differences in response to aircraft noise exposure, noise‑induced insomnia, and the interaction of the latter, we implemented the analysis of covariance with BP as a dependent variable and the following independent variables: aircraft noise exposure, AIS score, and their interaction. We used a linear regression model to analyze factors influencing the AIS score. In all analyses, a P value less than 0.05 was considered significant.