|
In a short-term experimental study about one-third of subjects exposed to noise shows both increases and decreases in blood pressure. While the association of noise with hypertension is established it is not yet known whether hypotension is associated with noise in field studies. In a cross-sectional study the association of self-reported hypotension and low blood pressure readings with traffic noise was examined in adults (age 25-65, N = 1989, participation = 62%). Noise exposure was based on both, short and long-term day/night recordings and standard noise mapping. Questionnaire data on socio-demographics, housing, life-style, noise and weather sensitivity, health status, mental and physical symptoms were available to adjust for potential confounding and testing for moderation. Non-linear multiple regression was applied to estimate the association between the two outcomes and overall noise exposure. We did not observe a stable relation between noise and low blood pressure readings since the number of subjects based on the recommended cut-off points (5 th percentile or 110 (100)/60 mmHg) was too small. However, self-reported hypotension was non-linearly associated with noise exposure ( P = 0.044) in the presence of a strong sex × age effect modification ( P < 0.0001). Another significant moderation by noise were observed with reported symptoms of exhaustion ( P = 0.03). Weather sensitivity showed a significant interaction with noise sensitivity ( P = 0.02) and also a non-linear interaction with age ( P = 0.02). The results remained stable after adjustment for variables known to be associated with constitutional hypotension. The exposure-effect curve ascends around sound levels of 55 dBA. The results suggest a novel moderated association of noise with self-reported hypotension, predominantly in weather sensitive women with symptoms of exhaustion. Further and larger studies are needed to replicate the potential moderating effect of noise on persons with constitutional hypotension. Keywords: Effect modification, fatigue, hypotension, traffic noise, weather sensitivity
How to cite this article:
Lercher P, Widmann U. Association and moderation of self-reported hypotension with traffic noise exposure: A neglected relationship. Noise Health 2013;15:205-16 |
| Introduction | |  |
Cardiovascular effects of traffic noise exposure are an important area of research in environmental epidemiology. Among them, the effects of noise on blood pressure, diagnosis or medication of hypertension are the best studied potential adverse health outcomes. However, the associations found between transportation noise and blood pressure readings in both, studies of children and adults remain inconsistent. [1],[2] More consistent results were obtained with hypertension as an outcome, particularly with aircraft noise but also with road traffic noise in more recent studies. [3],[4],[5],[6],[7],[8],[9],[10],[11],[12],[13]
Furthermore, the observed impact on sex is inconsistent. [11],[13] Several methodological reasons for this inconsistency between the results with blood pressure readings versus reports/diagnoses of hypertension have been discussed. [7],[13],[14]
Another possible reason for this inconsistency-observed in older experimental work-has been largely neglected: studies reported not only increases, but also no change and decreases, especially of systolic blood pressure. [15],[16],[17] Laboratory research, however, often fails to be replicated under field conditions since their focus is directed at detecting short-term blood pressure changes while field studies look at long-term effects. A series of carefully conducted field experiments under naturalistic working conditions at the Environmental Agency in Berlin shed more light on this issue: [18],[19],[20] The participants worked up to 5 working days under different noise exposure conditions (95 dBA brewery noise, 85 and 60 dBA traffic noise) and their blood pressure readings were compared with those under less noisy conditions (with ear plugs, <50 dBA). The maximum decrease in blood pressure readings after the daily exposure to noise was up to 15 mm systolic and 10 mmHg diastolic. Overall, up to 25% of the subjects experienced decreases in blood pressure under noise. Thus, mean blood pressure readings may not be telling the whole story. The number of subjects reacting with a decrease in blood pressure may undermine the establishment of a stable relation of noise with high blood pressure.
However, in practice, a diagnosis of hypotension and its associated symptoms is difficult to establish based on measured blood pressure using the recommended absolute (110 (100)/60 mmHg) or relative criteria (5 th percentile) for cut-off only. [21] Therefore, we asked additional questions on self-reported hypotension in our noise and health surveys - but never made a full analysis due to controversies regarding hypotension as a health outcome in Anglo-Saxon countries in contrast to German speaking or Romanic countries. [21],[22],[23],[24],[25],[26]
Only later, constitutional and orthostatic hypotension has received more attention as potential risk-factor and relevant health end-point not only in general practice. [27],[28],[29],[30],[31],[32],[33],[34],[35],[36] Longitudinal studies were able to confirm the symptom complex around hypotension. [34],[37],[38] Orthostatic impairment was also found to be an independent cerebro- and cardio-vascular risk-factor in the elderly. [39],[40],[41],[42],[43],[44],[45] This observed change in both scientific evidence and Public-health relevance of hypotension as health related moderator gave us a new rationale to reanalyze our older data sets in relation to noise within the EU-funded 7 th Framework project European Network on Noise and Health ( http://www.ennah.eu/home?lang = en ).
The aim of this reanalysis was therefore, to evaluate the relationship between noise and hypotension with an extended methodological frame-work (non-linear multiple regression, full consideration of potential confounders and effect modification) based on earlier experimental work showing decreases of blood pressure after noise exposure.
| Methods | | |
Areas, sampling, subjects and design
In this cross-sectional noise and health survey, conducted in fall 1989, adults (age 25-65, N = 1989, overall participation = 62%) with permanent residence (>1 year) were sampled systematically or based on clusters from five selected communities in the Tyrol area along two major through-traffic routes in the Austrian part of the Alps. [46],[47] Although, the participation varied between the communities (50-75%) and across the noise exposure classes a recruitment analysis did not reveal an exposure related sampling bias in the overall study sample. The sex-age-education proportions remained in the range of the micro-census values for the study region - except for a slightly lower participation in the oldest group (≥60 years). Three communities were situated along a highway, two communities along a busy main road. The residents had experienced an increasing traffic load (tripling) since, the mid-1970s. A specific exposure feature was the high proportion of heavy traffic during night (nearly 50%) at all traffic routes due to through-traffic. Two of the highway communities experienced also railway traffic exposure. Therefore, overall noise exposure was used in the analyses.
Confounder, moderator and health endpoint assessment
An extensive standardized questionnaire (45-60 min interview) covered socio-demographic data, housing, satisfaction with the environment, general noise annoyance, attitudes toward transportation, interference of activities, coping with noise, occupational exposures, life-styles, dispositions such as noise and weather sensitivity, health status and sleep. In addition a check list of doctor diagnosed diseases and prescribed medications (referring to the past 12 months) were presented.
Education was measured with 5 grades (basic, skilled labor, vocational school, A-level, University degree). The last two grades were combined in the category "higher education." Density is calculated as people/room. Noise and weather sensitivity and health worry were assessed with a one-item verbal intensity scale (not at all, little, moderate, rather, strongly, very strongly) and dichotomized in the analysis (strongly and very strongly). Health status was judged on a standard 5-grade scale. [1],[2],[3],[4],[5] Family history of hypertension: "Did one of your parents have hypertension? (Yes, no)." Hypertension treatment: "Do you currently take anti-hypertensive medication? (Yes, no)."
Mental-health was assessed with the von Zerssen symptom scale. [48] The 4-grade symptom frequencies were dichotomized (often + sometimes vs. seldom + never). Only symptoms of fatigue, exhaustion and depression are used in this analysis. Sleep problems were obtained (unrelated to noise) with a 7-grade verbal frequency type question ("Do you currently have sleeping difficulties (falling asleep, awakening, early wakeup): Never, almost never, once a month, twice a month, once per week, more than once per week, daily"). Participants who experienced more than one sleep disturbance/week were coded as having "sleep problems" in the analysis.
Hypotension was queried: "During the past 12 months did you experience or do you suffer currently from one of the following illnesses? Hypotension (yes, no)."
Blood pressure was measured twice by resident doctors in the home of the subject in a sitting position on the right arm.
Doctors were carefully trained to follow a standardized protocol. [49] Calibrated mercury sphygmomanometers (Sysditon, Fa F. Bosch) were used with a large scale. The measurements were based on the first and fifth Korotkoff phase using a fixed deflation rate of 3 mm Hg/sec and reporting to 1 mmHg to avoid digit preference. A uniform cuff-size (12 cm × 28 cm) was used (only 5 persons had arm circumferences >35 cm-thus, no correction was applied). The second measurement was used for the classification of hypotension. According to Owens et al. [32] the 5 th percentile was used as cut-off point.
Exposure assessment
Residential noise exposure is usually assessed by an index that describes the average noise exposure (in decibels, dBA) over a specified time period (Leq, day or night or 24 h).
In this study, the propagation results were calculated by national guidelines ([VDI] guideline 2714-noise propagation outdoors, VDI 2720-Noise control by barriers outdoors). As the topography in Alpine valleys is very complex we adjusted the calculated noise exposure from highway, main road, and railway with a large number of short and long-term day/night recordings simultaneously taken in the respective communities. Since some homes were further away and not covered by the mapping a final check was made based on short-term measurements and expert's local assessment to account for reflection and shielding in these cases. In case of differences between calculated and measured noise levels the measured noise level was taken.
Based on the adjusted maps each participant's home was individually assigned in to 5-dBA categories. Interviewers were blind to the interviewee's ambient noise exposure.
Since the number of traffic sources differed in the five communities and sources run often in parallel we used the overall 24 h noise level as indicator. The exposure distribution was slightly skewed to the left with a dip in the 55-59 dBA categories. The 50-54 dBA and the 60-64 dBA categories contain the highest number of participants [Figure A1], [Additional file 1] web only).
Statistical analysis and procedures
Exposure and survey data were linked through a Geographical information system and statistical analysis was conducted with F. Harrell's Harrell Miscellaneous, and Regression Modeling Strategies-libraries [50],[51] with R versions 2.10.2 and R 2.12.2. [52] Epicalc was used to examine dichotomous variables for [Table 1] by the Pearson Chi-square test; mixed data types by the rank sum test to identify the relevant confounders to consider in the analysis. [53] | Table 1: Description of main confounding and moderating variables by self-reported hypotension during the past 12 months among study subjects
Click here to view |
For modeling exposure-effect relationships multiple logistic regression techniques and splines were applied to account for non-linearity in selected predictors. [51] Approximate 95% confidence intervals were estimated using smoothing spline routines with three knots and exposure-effect plots generated with the RMS-library. [50] Predicted probabilities are derived from the estimated odds with a specific function in the RMS-library (plogis).The predicted probabilities of self-reported hypotension in the exposure-effect plots are adjusted to the median (continuous variables) or the reference category (non-continuous variables) of the other variables in the model. Since the choice of adjustment or cut-off points may influence results, plots using a log odds ratio scale are added as supplementary files [Figure A2], [Additional file 2] [Figure A3],[Additional file 3] [Figure A4] [Additional file 4] and [Figure A5], [Additional file 5] web only) to allow your own judgment. They will provide shapes that are independent of settings of non-interacting factors.
The sensitivity and stability analyses followed several approaches outlined in Harrell [54] and Royston and Sauerbrei. [55] Based on these analyses we found the model results obtained with the blood pressure readings too unstable to be reported.
Model building was based on prior substantive knowledge with a common model that always included the outcome, one exposure indicator, age, sex, education, body mass index (BMI), family history, hypertension treatment, health status and vulnerabilities (noise, weather). Since differences in hypotension prevalence were noted in the communities, a factor indicating the different study areas was included in the baseline model. Further variables related to housing (distance to traffic lines, house type, density, location of sleeping room), health behavior (smoking), work exposure (noise, vibration), mental-health (symptoms, sleep disturbance) were added separately together with selected interaction terms (age, sex, noise). Interactions (IA) were tested one by one and kept in the model when the fit improved or the adjusted R increased. Only one three-way interaction was tested (age × sex × noise). After assessment of model fit-in a last step-several final models were formulated including a limited number of relevant interaction terms. The final four models (one without splines) were validated by bootstrapping to check for over-fitting and evaluated against multiple discrimination criteria (Akaike information criterion, R, model χ, Somers' Dxy, Spearman's ρ, Gamma, Tau-a, C (area under Receiver operating characteristic curve). The criterion for the statistical consideration of IA in the model was relaxed since departure from additivity is considered of relevance for accurate prediction in a public-health context when involved exposures and outcomes are sufficiently prevalent. [56],[57]
| Results | | |
Baseline data description
Univariate socio-demographic, health and exposure characteristics are described in relation to the main health outcome in [Table 1]. Insignificant relations were observed only with education, age, family history of hypertension and sound level. Anti-hypertensive treatment was a rare event - but in some cases - hypotension seems to be a consequence. Women and persons reporting exhaustion, fatigue, depression or rating high on noise or weather sensitivity did exhibit the highest prevalence of reported hypotension. Furthermore, sleep problems were significantly associated with self-reported hypotension.
The observed prevalence of hypotension varies strongly with age, sex and type of diagnostic assessment [Table A1, [Additional file 6] web only]. In the younger age group, the measured percentages agree closely in both sexes while the self-reported suffering from hypotension shows a more than four-fold excess in women. This large difference in the reported sex prevalence disappears nearly in the older age group.
Multivariate model description
The statistical description of the selected final model is outlined in [Table 2].
The noise exposure (Leq24, dBA) does exhibit a near significant non-linear component in the presence of some IA. However, in the presence of variables showing strong IA with noise it is not advisable to interpret this result in isolation. The strongest model determinants, based on the Wald Chi-square are in this order: sex, age, community, BMI, weather sensitivity. Noise sensitivity was significant and did show an interaction with weather sensitivity ( P = 0.02) but not with sound level. Among the reported effect modifications sex × age is the most important contributor ( P < 0.001). Another significant moderation was observed between noise and exhaustion ( P = 0.03). The interaction between age and weather sensitivity was of border-line significance ( P = 0.065).
Exposure-effect relationships
[Figure 1] shows the exposure-effect relationship between sound level and self-reported hypotension with the most important determinants sex and age and adjusted for the other variables of [Table 1]. Outstanding is the change of the relationship for sex with increasing age (IA P < 0.001). At age 60 men and women exhibit a similar relationship while up to age 42 the relation with noise is evident only in women and the prevalence of self-reported hypotension is much higher in women. Although overall a non-linear relation, the slope starts to ascend linearly around 55 dBA. | Figure 1: Predicted probability of hypotension associated with overall sound exposure (road and rail traffic, Leq 24 h) by age and sex. Adjusted for body mass index, family history of hypertension, anti - hypertensive treatment, education, community, weather and noise sensitivity, sleep problems, symptoms of fatigue, exhaustion and depression. Including interaction terms age × sex, age × weather sensitivity, noise sensitivity×weather sensitivity, Leq 24 ×exhaustion, Leq 24 × sleep problems. Grey shaded areas represent 95% confidence limits
Click here to view |
In [Figure 2], the exposure-effect relationship is shown by age for the two larger communities (Vomp and Steinach). Note the substantial difference in the prevalence of self-reported hypotension, which decreases only slightly at age 60. The shape and the slope of the relation with noise do, however, not really change. | Figure 2: Predicted probability of hypotension associated with overall sound exposure (road and rail traffic, Leq 24 h) by age and community. Adjusted for body mass index, family history of hypertension, anti - hypertensive treatment, education, weather and noise sensitivity, sleep problems, symptoms of fatigue, exhaustion and depression. Including interaction terms age×sex, age × weather sensitivity, noise sensitivity×weather sensitivity, Leq 24×exhaustion, Leq 24×sleep problems. Grey shaded areas represent 95% confidence limits
Click here to view |
Relevant effect modification
Weather sensitivity was not only a strong main predictor. It exhibited also an effect modification with age and noise sensitivity. In [Figure 3] most strikingly is the difference in hypotension prevalence among the weather sensitive with age (IA P = 0.065). | Figure 3: Predicted probability of hypotension associated with overall sound exposure (road and rail traffic, Leq 24 h) by age and weather sensitivity. Adjusted for family history of hyper - tension, education, community, noise sensitivity, sleep problems, symptoms of fatigue, exhaustion and depression. Including interaction terms age × sex, age × weather sensitivity, noise sensitivity × weather sensitivity, Leq 24 × exhaustion, Leq 24 × sleep problems Grey shaded areas represent 95% confidence limits
Click here to view |
Another significant moderation is shown in [Figure 4] regarding sound exposure and exhaustion (IA P = 0.03). The relationship among those reporting exhaustion exhibits already a fast increase from lower sound levels up to 55 to 59 dBA where the curve starts to transit to reach saturation. Those not reporting exhaustion show a linear increase in the predicted probability of hypotension only from 55 to 59 dBA on-but join the exposure-response curve of the highly exhausted subjects around levels of 70 dBA. Thus, the main difference in the predicted effect occurs between 50 and 65 dBA, where the prevalence of the population exposure to noise is highest. | Figure 4: Predicted probability of hypotension associated with overall sound exposure (road and rail traffic, Leq 24 h) by age and symptoms of exhaustion. Adjusted for family history of hypertension, education, community, weather and noise sensitivity, sleep problems, symptoms of fatigue and depression. Including interaction terms age × sex, age × weather sensitivity, noise sensitivity × weather sensitivity, Leq 24×exhaustion, Leq 24×sleep problems Grey shaded areas represent 95% confidence limits
Click here to view |
Eventually, we could not establish a sufficiently stable model for the relation between noise and the casual blood pressure readings due to the small number of subjects.
| Discussion | | |
Our analysis followed-up on earlier short-term experimental studies that observed decreases in blood pressure readings under noise exposure in up to 25% of the study subjects.
In our field study, we observed a statistically significant non-linear relationship of overall noise exposure with self-reports of hypotension in the presence of some strong effect modifications. The relationship with noise was strongest in younger women up to the age of 42 years, while there is no evidence for men at younger age [Figure 1]. This may be related to the much lower prevalence in men at lower age, since at age 60 men exhibit about the same prevalence of hypotension and even show a similar, although weaker relationship with noise exposure.
This relationship could also be demonstrated in a subset of the two largest communities in spite of quite diverging hypotension prevalence's [Figure 2]. This indicates that in spite of probably different diagnostic handling of hypotension in general practice the observed moderated relationship with sound exposure remained stable.
In addition to the strong age × sex interaction further effect modifications are observed between weather sensitivity and age [Figure 3] and noise sensitivity. Weather sensitivity is considered as indicator of vegetative instability- mainly in European practical medicine [58] and part of established questionnaires (FBL of Fahrenberg, 1975 [59] ). Although, the direct relationship between sensitivity to weather and hypotension is not well-studied, it has been shown that under weather changes (e.g., hot weather) the associated symptoms of hypotension tend to worsen. [60],[61] Furthermore, subjects reporting sensitivity to weather show the strongest relation (OR = 7.12 (4.81-10.53) with "circulatory problems" out of a list of 17 reported co-morbidities. [62]
Noticeable is also the finding of a stronger effect of weather sensitivity compared to noise sensitivity, which is known to be negatively associated with blood pressure. [13]
The results support the idea that noise exposure may further disturb the homeostasis of the autonomous nervous system, especially, in people suffering from hypotension and reacting strongly to weather changes. Since weather sensitivity and symptoms of fatigue and depression are highly associated with hypotension [Table 1] in this study sample, it is ensuring that weather sensitivity shows an even stronger relation in a model adjusted for these other factors.
The significant moderation in subjects reporting exhaustion adds further credence to the stability of the noise relation with hypotension [Figure 4]. Symptoms of exhaustion are signs of extreme disturbance of the energy balance typically associated with vegetative dystonia or the chronic fatigue syndrome. While subjects without exhaustion mimic the observed overall exposure-response, those reporting exhaustion already show an increase in hypotension prevalence at noise levels below 55 dBA.
Thus, the strong points of this study are the replication of reports from short-term experiments in a representative study population. The results are in agreement with the main literature on constitutional hypotension and its associated symptom complex-but in addition uncover a hitherto not reported moderated relationship with sound exposure from transportation sources.
Eventually, the observed effect modifications also fit with the literature on constitutional hypotension: Younger women, rating themselves as weather sensitive and extremely fatigued (exhausted) are more strongly affected.
This study was, however, not able to replicate the finding with the available casual blood pressure readings. This is, however, not a surprising finding, since occasional blood pressure readings in general practice also failed to explain the occurrence of the typical symptoms (e.g. fatigue, low mood, etc.) associated with suffering from "hypotension." [21] Even sitting and standing measurements are not accurate enough to diagnose orthostatic hypotension. [63] Only a 24-h blood pressure monitoring in a small study was successful in detecting subjects with hypotensive events and the associated symptom complex. [32] Furthermore, the obtained prevalence of hypotension based on blood pressure readings in large population studies (e.g.: Pemberton 1989 [24] ) is much lower (between 1 and 3%). In our survey, based on the 5 th percentile, the respective prevalence's were 2.4% systolic and 3.7% diastolic respectively. The associated power is therefore, much smaller compared with the prevalence of self-reported hypotension (26.3% in this study). The sensitivity of this casual approach of two readings on one occasion was assumingly too low. However, the evaluation and therapy in practice are primarily driven by symptoms, since not all subjects with positive physical finding exhibit symptoms. [64]
From a clinical point of view, a methodological limitation may be that no specific tests have been conducted to differentiate this group with self-reported hypotension. We feel confident, however, that the subjects reporting to suffer from hypotension are persons labeled as "constitutional" or "essential hypotension" in general practice. [24],[65],[66],[67]
The obtained reported prevalence of hypotension in this study (26.3%) is also in agreement with both general population (22% in a population of aged 16-70 years [68] ) and general practice studies in a German general practice study, [21] 17% of all patients attending were reported as hypotensive either by their doctor or by themselves. Furthermore, the proportion was twice as high among women as among men and more common among the young.
The noise related association found predominantly in young women in this study should be interpreted with caution, because a limitation of our sample is the smaller proportion of older participants. Since hypotension in men increases with age the power of this study was likely to low to evaluate the relation with noise for the elderly with sufficient power.
Although, an overall exposure related selection could be excluded by analysis of non-participants, [46] no information was available to test potential health related selection in to the study.
Since this was the first study to evaluate hypotension as health related outcome in noise effects research, a replication of the findings is needed from other studies.
Eventually, caution in interpretation is needed due to the cross-sectional design of this study. Nothing can be said about the direction of the noise - hypotension relationship.
Recent studies observed both a reduced cortical activity and a decrease in cerebral blood-flow in subjects with mild hypotension (systolic pressures below 110 mmHg). The observations were paralleled with a decline in cognitive function. [69],[70],[71],[72],[73],[74] These data are challenging since hitherto conventional wisdom held that cerebral-vascular auto-regulation prevents reduced cerebral perfusion even at lower systolic blood pressures. Above findings provide a direct physiologic basis for the observed impairment in cognitive functions at low blood pressure [75] but could also be taken as explanation for the associations with low mood and energy [37] and cerebral- and cardio-vascular risk. [39],[43]
On the other hand, due to the close relation of fatigue, depression and hypotension similar mechanisms that work in the chronic fatigue syndrome have been proposed. [76] However, the autonomous mechanisms leading to hypotension are not yet well understood and the treatment still may not be appropriate. [77],[26]
The finding that noise exposure may act as an additional determinant on hypotension in synergy with other established risk-factors should trigger further interest to study this complex syndrome in relation to sound and other environmental exposure.
| References | | |
| 1. | van Kempen E, van Kamp I, Fischer P, Davies H, Houthuijs D, Stellato R, et al. Noise exposure and children′s blood pressure and heart rate: The RANCH project. Occup Environ Med 2006;63:632-9. 
|
| 2. | Babisch W. Cardiovascular effects of noise. In: Nriagu JO, editor. Encyclopedia of Environmental Health. Burlington: Elsevier; 2011. p. 532-42.
|
| 3. | Leon Bluhm G, Berglind N, Nordling E, Rosenlund M. Road traffic noise and hypertension. Occup Environ Med 2007;64:122-6.
|
| 4. | de Kluizenaar Y, Gansevoort RT, Miedema HM, de Jong PE. Hypertension and road traffic noise exposure. J Occup Environ Med 2007;49:484-92.
|
| 5. | Eriksson C, Rosenlund M, Pershagen G, Hilding A, Ostenson CG, Bluhm G. Aircraft noise and incidence of hypertension. Epidemiology 2007;18:716-21.
|
| 6. | Belojeviæ GA, Jakovljeviæ BD, Stojanov VJ, Slepceviæ VZ, Paunoviæ KZ. Nighttime road-traffic noise and arterial hypertension in an urban population. Hypertens Res 2008;31:775-81.
|
| 7. | Jarup L, Babisch W, Houthuijs D, Pershagen G, Katsouyanni K, Cadum E, et al. Hypertension and exposure to noise near airports: The HYENA study. Environ Health Perspect 2008;116:329-33.
|
| 8. | Bodin T, Albin M, Ardö J, Stroh E, Ostergren PO, Björk J. Road traffic noise and hypertension: Results from a cross-sectional public health survey in southern Sweden. Environ Health 2009;8:38.
|
| 9. | Barregard L, Bonde E, Ohrström E. Risk of hypertension from exposure to road traffic noise in a population-based sample. Occup Environ Med 2009;66:410-5.
|
| 10. | Eriksson C, Bluhm G, Hilding A, Ostenson CG, Pershagen G. Aircraft noise and incidence of hypertension - Gender specific effects. Environ Res 2010;110:764-72.
|
| 11. | Barregard L. Traffic noise and hypertension. Environ Res 2011;111:186-7.
|
| 12. | Bluhm G, Eriksson C. Cardiovascular effects of environmental noise: Research in Sweden. Noise Health 2011;13:212-6.
[PUBMED]  |
| 13. | Lercher P, Botteldooren D, Widmann U, Uhrner U, Kammeringer E. Cardiovascular effects of environmental noise: Research in Austria. Noise Health 2011;13:234-50.
[PUBMED] |
| 14. | Babisch W. Transportation noise and cardiovascular risk: Updated review and synthesis of epidemiological studies indicate that the evidence has increased. Noise Health 2006;8:1-29.
[PUBMED] |
| 15. | Cartwright LB, Thompson RN. The effects of broadband noise on the cardiovascular system on normal resting adults. Am Ind Hyg Assoc J 1975;36:653-8.
|
| 16. | Andrén L, Hansson L, Björkman M, Jonsson A, Borg KO. Hemodynamic and hormonal changes induced by noise. Acta Med Scand Suppl 1979;625:13-8.
|
| 17. | Andrén L, Hansson L, Björkman M. Haemodynamic effects of noise exposure before and after beta 1-selective and non-selective beta-adrenoceptor blockade in patients with essential hypertension. Clin Sci (Lond) 1981;61:89s-91s.
|
| 18. | Ising H, Dienel D, Günther T, Markert B. Health effects of traffic noise. Int Arch Occup Environ Health 1980;47:179-90.
|
| 19. | Ising H, Gunther T. Effects of a several hour noise exposure on human wellbeing, body functions and performance. [Article in German]. Z Lärmbekämpfung 1983;30:11-5.
|
| 20. | Ising H. Stress reactions and health risks due to traffic noise exposure. [Report in German] WaBoLu-Berichte; 1983. pp. 1-46.
|
| 21. | Donner-Banzhoff N, Kreienbrock L, Baum E. Hypotension - Does it make sense in family practice? Fam Pract 1994;11:368-74.
|
| 22. | Robinson SC. Hypotension: The ideal normal blood pressure. N Engl J Med 1940;223:407-16.
|
| 23. | Robbins JM, Korda H, Shapiro MF. Treatment for a nondisease: The case of low blood pressure. Soc Sci Med 1982;16:27-33.
|
| 24. | Pemberton J. Does constitutional hypotension exist? BMJ 1989;298:660-2.
|
| 25. | Wessely S, Nickson J, Cox B. Symptoms of low blood pressure: A population study. BMJ 1990;301:362-5.
|
| 26. | Grosch S, Saint-Remy A, Krzesinski JM. Blood pressure variability.[Article in French]. Rev Med Liege 2005;60:147-53.
|
| 27. | Pilgrim JA, Stansfeld S, Marmot M. Low blood pressure, low mood? BMJ 1992;304:75-8.
|
| 28. | Rosengren A, Tibblin G, Wilhelmsen L. Low systolic blood pressure and self perceived wellbeing in middle aged men. BMJ 1993;306:243-6.
|
| 29. | Barrett-Connor E, Palinkas LA. Low blood pressure and depression in older men: A population based study. BMJ 1994;308:446-9.
|
| 30. | Pilgrim JA. Psychological aspects of high and low blood pressure. Psychol Med 1994;24:9-14.
|
| 31. | Owens PE, O′Brien ET. Hypotension: A forgotten illness?. Blood Press Monit 1997;2:3-14.
|
| 32. | Owens PE, Lyons SP, O′Brien ET. Arterial hypotension: Prevalence of low blood pressure in the general population using ambulatory blood pressure monitoring. J Hum Hypertens 2000;14:243-7.
|
| 33. | Jorm AF. Association of hypotension with positive and negative affect and depressive symptoms in the elderly. Br J Psychiatry 2001;178:553-5.
|
| 34. | Lucas KE, Rowe PC, Coresh J, Klag MJ, Meoni LA, Ford DE. Prospective association between hypotension and idiopathic chronic fatigue. J Hypertens 2004;22:691-5.
|
| 35. | Hildrum B, Mykletun A, Stordal E, Bjelland I, Dahl AA, Holmen J. Association of low blood pressure with anxiety and depression: The Nord-Trøndelag Health Study. J Epidemiol Community Health 2007;61:53-8.
|
| 36. | Hildrum B, Mykletun A, Holmen J, Dahl AA. Effect of anxiety and depression on blood pressure: 11-year longitudinal population study. Br J Psychiatry 2008;193:108-13.
|
| 37. | Tonkin A. Low blood pressure and low energy: (How) are they related? J Hypertens 2004;22:671-3.
|
| 38. | Akahoshi M, Hida A, Imaizumi M, Soda M, Maeda R, Ichimaru S, et al. Basic characteristics of chronic hypotension cases: A longitudinal follow-up study from 1958 through 1999. Hypertens Res 2006;29:1-7.
|
| 39. | Eigenbrodt ML, Rose KM, Couper DJ, Arnett DK, Smith R, Jones D. Orthostatic hypotension as a risk factor for stroke: The atherosclerosis risk in communities (ARIC) study, 1987-1996. Stroke 2000;31:2307-13.
|
| 40. | Rose KM, Tyroler HA, Nardo CJ, Arnett DK, Light KC, Rosamond W, et al. Orthostatic hypotension and the incidence of coronary heart disease: The Atherosclerosis Risk in Communities study. Am J Hypertens 2000;13:571-8.
|
| 41. | Kario K, Eguchi K, Hoshide S, Hoshide Y, Umeda Y, Mitsuhashi T, et al. U-curve relationship between orthostatic blood pressure change and silent cerebrovascular disease in elderly hypertensives: Orthostatic hypertension as a new cardiovascular risk factor. J Am Coll Cardiol 2002;40:133-41.
|
| 42. | Rose KM, Eigenbrodt ML, Biga RL, Couper DJ, Light KC, Sharrett AR, et al. Orthostatic hypotension predicts mortality in middle-aged adults: The Atherosclerosis Risk In Communities (ARIC) Study. Circulation 2006;114:630-6.
|
| 43. | Fedorowski A, Stavenow L, Hedblad B, Berglund G, Nilsson PM, Melander O. Orthostatic hypotension predicts all-cause mortality and coronary events in middle-aged individuals (The Malmo Preventive Project). Eur Heart J 2010;31:85-91.
|
| 44. | Mancia G, Grassi G. Orthostatic hypotension and cardiovascular risk: Defining the epidemiological and prognostic relevance. Eur Heart J 2010;31:12-4.
|
| 45. | Yatsuya H, Folsom AR, Alonso A, Gottesman RF, Rose KM, ARIC Study Investigators. Postural changes in blood pressure and incidence of ischemic stroke subtypes: The ARIC study. Hypertension 2011;57:167-73.
|
| 46. | Lercher P, Kofler W. Complex responses to environmental exposure: The case of the Austrian Transit-traffic-study. [Article in German] Bundesgesundheitsblatt 1995;38:95-101.
|
| 47. | Lercher P, Kofler WW. Behavioral and health responses associated with road traffic noise exposure along alpine through-traffic routes. Sci Total Environ 1996;189-90:85-9.
|
| 48. | von Zerssen D. The symptom checklist. [Book in German]. Weinheim: Beltz; 1976.
|
| 49. | Stieber J, Sund M, Keil U. Quality assurance and quality control of blood pressure measurements. Experiences with the Munich blood pressure study. Fortschr Med 1984;102:1041-4.
|
| 50. | Harrell FE. Rms: Regression Modelling Strategies. 2011. http://cran.r-project.org/web/packages/rms/rms.pdf
|
| 51. | Harrell FE. Hmisc: Harrell Miscellaneous. 2011. http://cran.r-project.org/web/packages/Hmisc/Hmisc.pdf
|
| 52. | R Development Core Team. R: A Language and Environment for Statistical Computing. Vienna Austria: R Foundation for Statistical Computing; 2011. {ISBN} 3-900051-07-0.
|
| 53. | Chongsuvivatwong V. Epidemiological Calculator. 2012. http://cran.r-project.org/web/packages/epicalc/epicalc.pdf
|
| 54. | Harrell FE. Regression Modelling Strategies. New York: Springer; 2001.
|
| 55. | Royston P, Sauerbrei W. Interactions. In: Multivariable Model-Building: A Pragmatic Approach to Regression Anaylsis based on Fractional Polynomials for Modelling Continuous Variables. Chichester: John Wiley and Sons Ltd; 2008. p. 322.
|
| 56. | Selvin S. Statistical Analysis of Epidemiologic Data. 3 rd ed. New York: Oxford University Press; 2004. p. 208.
|
| 57. | Greenland S, Rothman K. Concepts of interaction. In: Rothman KJ, Greenland S, editors. Modern Epidemiology. New York: Lippincott-Raven; 1998. p. 329-42.
|
| 58. | Ranner R, Egger J. The weather sensitivity syndrom. [Article in German] Psychologie in der Medizin 1998;9:12-20.
|
| 59. | Fahrenberg J. [The Freiburg symptom checklist]. [Article in German] Zeitschrift für Klinische Psychologie 1975;4:79-100.
|
| 60. | Jendritzky G. Effects of weather and climate on human health. [Book chapter in German]. In: Wichmann H, Schlipkoeter H, Fulgraff G, editors. Handbook of environmental medicine. Landsberg: Ecomed; 1992. p. 1-14.
|
| 61. | Höppe P. The importance of weather and climate in environmental medicine. [Article in German] Umweltmed Forsch Prax 1999;4:101-6.
|
| 62. | von Mackensen S, Hoeppe P, Maarouf A, Tourigny P, Nowak D. Prevalence of weather sensitivity in Germany and Canada. Int J Biometeorol 2005;49:156-66.
|
| 63. | Cooke J, Carew S, O′Connor M, Costelloe A, Sheehy T, Lyons D. Sitting and standing blood pressure measurements are not accurate for the diagnosis of orthostatic hypotension. QJM 2009;102:335-9.
|
| 64. | Robertson D. The pathophysiology and diagnosis of orthostatic hypotension. Clin Auton Res 2008;18:2-7.
|
| 65. | Schwab P. The hypotonic symptom complex. [Book in German]. Göttingen: Hogrefe; 1992.
|
| 66. | Cadalbert B. Psychophysiology of low blood pressure: Circulatory regulation, life style and symptoms. [Book in German]. Frankfurt am Main: Peter Lang; 1997.
|
| 67. | De Buyzere M, Clement DL, Duprez D. Chronic low blood pressure: A review. Cardiovasc Drugs Ther 1998;12:29-35.
|
| 68. | Kunze M, Gredler B, Steinbach K. Hypotension in Austria (author′s transl). Wien Med Wochenschr 1981;131:253-6.
|
| 69. | Morris MC, Scherr PA, Hebert LE, Bennett DA, Wilson RS, Glynn RJ, et al. Association between blood pressure and cognitive function in a biracial community population of older persons. Neuroepidemiology 2002;21:123-30.
|
| 70. | Weisz N, Schandry R, Jacobs AM, Mialet JP, Duschek S. Early contingent negative variation of the EEG and attentional flexibility are reduced in hypotension. Int J Psychophysiol 2002;45:253-60.
|
| 71. | Duschek S, Weisz N, Schandry R. Reduced cognitive performance and prolonged reaction time accompany moderate hypotension. Clin Auton Res 2003;13:427-32.
|
| 72. | Duschek S, Schandry R. Cognitive performance and cerebral blood flow in essential hypotension. Psychophysiology 2004;41:905-13.
|
| 73. | Duschek S, Meinhardt J, Schandry R. Reduced cortical activity due to chronic low blood pressure: An EEG study. Biol Psychol 2006;72:241-50.
|
| 74. | Duschek S, Schandry R. Reduced brain perfusion and cognitive performance due to constitutional hypotension. Clin Auton Res 2007;17:69-76.
|
| 75. | Schatz IJ. Hypotension and cognitive defects. Clin Auton Res 2007;17:64.
|
| 76. | Rowe PC, Bou-Holaigah I, Kan JS, Calkins H. Is neurally mediated hypotension an unrecognised cause of chronic fatigue? Lancet 1995;345:623-4.
|
| 77. | Grosch S, Maillet J, Krzesinski JM. How to manage chronically low blood pressure? [Article in French]. Rev Med Liege 2006;61:374-9.
|
Correspondence Address:
Peter Lercher
Department of Hygiene, Microbiology and Social Medicine, Medical University Innsbruck, Sonnenburgstrasse 16, A-6020 Innsbruck
Austria
 Source of Support: None, Conflict of Interest: None  | Check |
PMID: 23771418 
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2] |
Search Pubmed for
