Skip to main content

Advertisement

SpringerLink
Log in

Cardiovascular diseases, risk factors and short-term heart rate variability in an elderly general population: the CARLA study 2002–2006

  • Cardiovascular Disease
  • Published:
European Journal of Epidemiology Aims and scope Submit manuscript

Abstract

Background: A reduced heart rate variability (HRV) is associated with worse prognosis, increased incidence of cardiovascular disease (CVD) and mortality. There are conflicting results and a lack of population-based data regarding the association of HRV with CVD risk factors and its potential role as independent cause or mediator of CVD risk. Methods: Cross-sectional data of a population-based cohort including 1,779 women and men aged 45–83 years were used to analyse associations of time and frequency domain measures of HRV (derived from 5-min ECG segments) with age, behavioural and biomedical risk factors and disease in the whole sample and in a “healthy” subgroup. Results: Age was inversely associated with all measures of HRV (mean standard deviation of normal intervals across 10-year age-groups 32.1, 26.9, 27.1 and 24.8 ms in women, 29.3, 25.9, 23.8 and 25.7 ms in men). There was no association of physical activity, current smoking or alcohol with HRV. In age-adjusted models, triglycerides, glucose, waist-to-hip ratio and diabetes were inversely associated with HRV in men and women, and low/high density cholesterol and hypertension in men only (up to 43% difference across risk factor quartiles). Multivariable adjustment and restriction to the “healthy” subgroup attenuated the associations. Conclusions: We found only weak and inconsistent associations of HRV with cardiovascular risk factors. However, these results as well as those from previous studies are still compatible with the hypothesis that short-term HRV may be a marker of ill health or a mediator of the effect of selected biomedical risk factors on CVD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Abbreviations

ACE:

Angiotensin-converting enzyme

AFIB:

Atrial fibrillation or flutter

BP:

Blood pressure

CARLA:

Cardiovascular disease, living and ageing in Halle

CHD:

Coronary heart disease

CHF:

Congestive heart failure

CVD:

Cardiovascular disease

DBP:

Diastolic blood pressure

DM:

Diabetes mellitus

HbA1c :

Glycated haemoglobin

HDL:

High density lipoprotein cholesterol

HF:

High frequency power

HR:

Heart rate

HRV:

Heart rate variability

LDL:

Low density lipoprotein cholesterol

LDL/HDL:

Ratio of low to high density lipoprotein cholesterol

LF:

Low frequency power

LF/HF:

Ratio of low frequency power to high frequency power

MI:

Myocardial infarction

MetSyn:

Metabolic syndrome

NS:

Statistically not significant

Q1… Q4:

First (=lowest)… fourth (=highest) quartile

RF:

Risk factors

SBP:

Systolic blood pressure

SDNN:

Standard deviation of normal intervals

WHR:

Waist-to-hip ratio

95% CI:

95% confidence interval

References

  1. National Institutes of Health NHLaBI. NHLBI fact book fiscal year 2006. http://www.nhlbi.nih.gov/about/factpdf.htm (2007). 23 Nov 2007.

  2. Bursi F, Weston SA, Redfield MM, Jacobsen SJ, Pakhomov S, Nkomo VT, et al. Systolic and diastolic heart failure in the community. JAMA. 2006;296(18):2209–16. doi:10.1001/jama.296.18.2209.

    PubMed  CAS  Google Scholar 

  3. Cowie MR, Wood DA, Coats AJ, Thompson SG, Poole-Wilson PA, Suresh V, et al. Incidence and aetiology of heart failure; a population-based study. Eur Heart J. 1999;20(6):421–8. doi:10.1053/euhj.1998.1280.

    PubMed  CAS  Google Scholar 

  4. Kannel WB. Vital epidemiologic clues in heart failure. J Clin Epidemiol. 2000;53(3):229–35. doi:10.1016/S0895-4356(99)00135-3.

    PubMed  CAS  Google Scholar 

  5. O’Connell JB. The economic burden of heart failure. Clin Cardiol. 2000;23(3 Suppl):III6–10.

    PubMed  CAS  Google Scholar 

  6. Redfield MM, Jacobsen SJ, Burnett JC Jr, Mahoney DW, Bailey KR, Rodeheffer RJ. Burden of systolic and diastolic ventricular dysfunction in the community: appreciating the scope of the heart failure epidemic. JAMA. 2003;289(2):194–202. doi:10.1001/jama.289.2.194.

    PubMed  Google Scholar 

  7. Shammas RL, Khan NU, Nekkanti R, Movahed A. Diastolic heart failure and left ventricular diastolic dysfunction: what we know, and what we don’t know! Int J Cardiol. 2007;115(3):284–92. doi:10.1016/j.ijcard.2006.03.027.

    PubMed  Google Scholar 

  8. Bigger JT, Fleiss JL, Rolnitzky LM, Steinman RC. The ability of several short-term measures of RR variability to predict mortality after myocardial infarction. Circulation. 1993;88(3):927–34.

    PubMed  CAS  Google Scholar 

  9. Huikuri HV, Jokinen V, Syvanne M, Nieminen MS, Airaksinen KE, Ikaheimo MJ, et al. Heart rate variability and progression of coronary atherosclerosis. Arterioscler Thromb Vasc Biol. 1999;19(8):1979–85.

    PubMed  CAS  Google Scholar 

  10. Janszky I, Ericson M, Mittleman MA, Wamala S, Al Khalili F, Schenck-Gustafsson K, et al. Heart rate variability in long-term risk assessment in middle-aged women with coronary heart disease: the Stockholm female coronary risk study. J Intern Med. 2004;255(1):13–21. doi:10.1046/j.0954-6820.2003.01250.x.

    PubMed  CAS  Google Scholar 

  11. Nolan J, Batin PD, Andrews R, Lindsay SJ, Brooksby P, Mullen M, et al. Prospective study of heart rate variability and mortality in chronic heart failure: results of the United Kingdom heart failure evaluation and assessment of risk trial (UK-heart). Circulation. 1998;98(15):1510–6.

    PubMed  CAS  Google Scholar 

  12. Kleiger RE, Miller JP, Bigger JT Jr, Moss AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol. 1987;59(4):256–62. doi:10.1016/0002-9149(87)90795-8.

    PubMed  CAS  Google Scholar 

  13. Zuanetti G, Neilson JM, Latini R, Santoro E, Maggioni AP, Ewing DJ. Prognostic significance of heart rate variability in post-myocardial infarction patients in the fibrinolytic era. The GISSI-2 results. Gruppo Italiano per lo Studio della Sopravvivenza nell’ Infarto Miocardico. Circulation. 1996;94(3):432–6.

    PubMed  CAS  Google Scholar 

  14. Hohnloser SH, Klingenheben T, Zabel M, Li YG. Heart rate variability used as an arrhythmia risk stratifier after myocardial infarction. Pacing Clin Electrophysiol. 1997;20(10 Pt 2):2594–601. doi:10.1111/j.1540-8159.1997.tb06109.x.

    PubMed  CAS  Google Scholar 

  15. La Rovere MT, Pinna GD, Hohnloser SH, Marcus FI, Mortara A, Nohara R, et al. Baroreflex sensitivity and heart rate variability in the identification of patients at risk for life-threatening arrhythmias: implications for clinical trials. Circulation. 2001;103(16):2072–7.

    PubMed  Google Scholar 

  16. Kearney MT, Fox KA, Lee AJ, Prescott RJ, Shah AM, Batin PD, et al. Predicting death due to progressive heart failure in patients with mild-to-moderate chronic heart failure. J Am Coll Cardiol. 2002;40(10):1801–8. doi:10.1016/S0735-1097(02)02490-7.

    PubMed  Google Scholar 

  17. La Rovere MT, Pinna GD, Maestri R, Mortara A, Capomolla S, Febo O, et al. Short-term heart rate variability strongly predicts sudden cardiac death in chronic heart failure patients. Circulation. 2003;107(4):565–70. doi:10.1161/01.CIR.0000047275.25795.17.

    PubMed  Google Scholar 

  18. Hadase M, Azuma A, Zen K, Asada S, Kawasaki T, Kamitani T, et al. Very low frequency power of heart rate variability is a powerful predictor of clinical prognosis in patients with congestive heart failure. Circ J. 2004;68(4):343–7. doi:10.1253/circj.68.343.

    PubMed  Google Scholar 

  19. Guzzetti S, La Rovere MT, Pinna GD, Maestri R, Borroni E, Porta A, et al. Different spectral components of 24 h heart rate variability are related to different modes of death in chronic heart failure. Eur Heart J. 2005;26(4):357–62. doi:10.1093/eurheartj/ehi067.

    PubMed  Google Scholar 

  20. Stein PK, Domitrovich PP, Huikuri HV, Kleiger RE. Traditional and nonlinear heart rate variability are each independently associated with mortality after myocardial infarction. J Cardiovasc Electrophysiol. 2005;16(1):13–20. doi:10.1046/j.1540-8167.2005.04358.x.

    PubMed  Google Scholar 

  21. Moore RK, Groves DG, Barlow PE, Fox KA, Shah A, Nolan J, et al. Heart rate turbulence and death due to cardiac decompensation in patients with chronic heart failure. Eur J Heart Fail. 2006;8(6):585–90. doi:10.1016/j.ejheart.2005.11.012.

    PubMed  Google Scholar 

  22. de Bruyne MC, Kors JA, Hoes AW, Klootwijk P, Dekker JM, Hofman A, et al. Both decreased and increased heart rate variability on the standard 10-second electrocardiogram predict cardiac mortality in the elderly: the Rotterdam study. Am J Epidemiol. 1999;150(12):1282–8.

    PubMed  Google Scholar 

  23. Dekker JM, Schouten EG, Klootwijk P, Pool J, Swenne CA, Kromhout D. Heart rate variability from short electrocardiographic recordings predicts mortality from all causes in middle-aged and elderly men. The Zutphen study. Am J Epidemiol. 1997;145(10):899–908.

    PubMed  CAS  Google Scholar 

  24. Dekker JM, Crow RS, Folsom AR, Hannan PJ, Liao D, Swenne CA, et al. Low heart rate variability in a 2-minute rhythm strip predicts risk of coronary heart disease and mortality from several causes: the ARIC study. Atherosclerosis Risk in Communities. Circulation. 2000;102(11):1239–44.

    PubMed  CAS  Google Scholar 

  25. Liao D, Cai J, Rosamond WD, Barnes RW, Hutchinson RG, Whitsel EA, et al. Cardiac autonomic function and incident coronary heart disease: a population-based case-cohort study. The ARIC study. Atherosclerosis Risk in Communities study. Am J Epidemiol. 1997;145(8):696–706.

    PubMed  CAS  Google Scholar 

  26. Liao D, Carnethon M, Evans GW, Cascio WE, Heiss G. Lower heart rate variability is associated with the development of coronary heart disease in individuals with diabetes: the Atherosclerosis Risk in Communities (ARIC) study. Diabetes. 2002;51(12):3524–31. doi:10.2337/diabetes.51.12.3524.

    PubMed  CAS  Google Scholar 

  27. Tsuji H, Venditti FJ Jr, Manders ES, Evans JC, Larson MG, Feldman CL, et al. Reduced heart rate variability and mortality risk in an elderly cohort. The Framingham heart study. Circulation. 1994;90(2):878–83.

    PubMed  CAS  Google Scholar 

  28. Tsuji H, Larson MG, Venditti FJ Jr, Manders ES, Evans JC, Feldman CL, et al. Impact of reduced heart rate variability on risk for cardiac events. The Framingham heart study. Circulation. 1996;94(11):2850–5.

    PubMed  CAS  Google Scholar 

  29. Britton A, Hemingway H. Heart rate variability in healthy populations: correlates and consequences. In: Malik M, Camm A, editors. Dynamic electrocardiography. New York: Futura/Blackwell; 2004. p. 90–111.

    Google Scholar 

  30. Fagard RH, Pardaens K, Staessen JA. Influence of demographic, anthropometric and lifestyle characteristics on heart rate and its variability in the population. J Hypertens. 1999;17(11):1589–99. doi:10.1097/00004872-199917110-00013.

    PubMed  CAS  Google Scholar 

  31. Felber Dietrich D, Schindler C, Schwartz J, Barthelemy JC, Tschopp JM, Roche F, et al. Heart rate variability in an ageing population and its association with lifestyle and cardiovascular risk factors: results of the SAPALDIA study. Europace. 2006;8(7):521–9. doi:10.1093/europace/eul063.

    PubMed  Google Scholar 

  32. Felber Dietrich D, Schwartz J, Schindler C, Gaspoz JM, Barthelemy JC, Tschopp JM, et al. Effects of passive smoking on heart rate variability, heart rate and blood pressure: an observational study. Int J Epidemiol. 2007;36(4):834–40. doi:10.1093/ije/dym031.

    PubMed  Google Scholar 

  33. Hemingway H, Shipley M, Brunner E, Britton A, Malik M, Marmot M. Does autonomic function link social position to coronary risk? The Whitehall II study. Circulation. 2005;111(23):3071–7. doi:10.1161/CIRCULATIONAHA.104.497347.

    PubMed  Google Scholar 

  34. Kuch B, Hense HW, Sinnreich R, Kark JD, von Eckardstein A, Sapoznikov D, et al. Determinants of short-period heart rate variability in the general population. Cardiology. 2001;95(3):131–8. doi:10.1159/000047359.

    PubMed  CAS  Google Scholar 

  35. Stolarz K, Staessen JA, Kuznetsova T, Tikhonoff V, State D, Babeanu S, et al. Host and environmental determinants of heart rate and heart rate variability in four European populations. J Hypertens. 2003;21(3):525–35. doi:10.1097/00004872-200303000-00018.

    PubMed  CAS  Google Scholar 

  36. Stein PK, Barzilay JI, Domitrovich PP, Chaves PM, Gottdiener JS, Heckbert SR, et al. The relationship of heart rate and heart rate variability to non-diabetic fasting glucose levels and the metabolic syndrome: the cardiovascular health study. Diabet Med. 2007;24(8):855–63. doi:10.1111/j.1464-5491.2007.02163.x.

    PubMed  CAS  Google Scholar 

  37. Carney RM, Blumenthal JA, Freedland KE, Stein PK, Howells WB, Berkman LF, et al. Low heart rate variability and the effect of depression on post-myocardial infarction mortality. Arch Intern Med. 2005;165(13):1486–91. doi:10.1001/archinte.165.13.1486.

    PubMed  Google Scholar 

  38. Sloan RP, Bagiella E, Shapiro PA, Kuhl JP, Chernikhova D, Berg J, et al. Hostility, gender, and cardiac autonomic control. Psychosom Med. 2001;63(3):434–40.

    PubMed  CAS  Google Scholar 

  39. van der Kooy KG, van Hout HP, van Marwijk HW, de Haan M, Stehouwer CD, Beekman AT. Differences in heart rate variability between depressed and non-depressed elderly. Int J Geriatr Psychiatry. 2006;21(2):147–50. doi:10.1002/gps.1439.

    PubMed  Google Scholar 

  40. Vrijkotte TG, Van Doornen LJ, De Geus EJ. Effects of work stress on ambulatory blood pressure, heart rate, and heart rate variability. Hypertension. 2000;35(4):880–6.

    PubMed  CAS  Google Scholar 

  41. Collins SM, Karasek RA, Costas K. Job strain and autonomic indices of cardiovascular disease risk. Am J Ind Med. 2005;48(3):182–93. doi:10.1002/ajim.20204.

    PubMed  Google Scholar 

  42. Martens EJ, Nyklicek I, Szabo BM, Kupper N. Depression and anxiety as predictors of heart rate variability after myocardial infarction. Psychol Med. 2008;38(3):375–83.

    PubMed  CAS  Google Scholar 

  43. Ziegler D, Zentai CP, Perz S, Rathmann W, Haastert B, Doring A, et al. Prediction of mortality using measures of cardiac autonomic dysfunction in the diabetic and nondiabetic population: the MONICA/KORA Augsburg cohort study. Diabetes Care. 2008;31(3):556–61. doi:10.2337/dc07-1615.

    PubMed  Google Scholar 

  44. Stein PK, Ehsani AA, Domitrovich PP, Kleiger RE, Rottman JN. Effect of exercise training on heart rate variability in healthy older adults. Am Heart J. 1999;138(3 Pt 1):567–76. doi:10.1016/S0002-8703(99)70162-6.

    PubMed  CAS  Google Scholar 

  45. Rennie KL, Hemingway H, Kumari M, Brunner E, Malik M, Marmot M. Effects of moderate and vigorous physical activity on heart rate variability in a British study of civil servants. Am J Epidemiol. 2003;158(2):135–43. doi:10.1093/aje/kwg120.

    PubMed  Google Scholar 

  46. De Meersman RE, Stein PK. Vagal modulation and aging. Biol Psychol. 2007;74(2):165–73. doi:10.1016/j.biopsycho.2006.04.008.

    PubMed  Google Scholar 

  47. Gademan MG, Swenne CA, Verwey HF, van der Laarse A, Maan AC, Van de Vooren H, et al. Effect of exercise training on autonomic derangement and neurohumoral activation in chronic heart failure. J Card Fail. 2007;13(4):294–303. doi:10.1016/j.cardfail.2006.12.006.

    PubMed  Google Scholar 

  48. Dreifus LS, Agarwal JB, Botvinick EH, Ferdinand KC, Fisch C, Fisher CD, et al. Heart rate variability for risk stratification of life-threatening arrhythmias. American College of Cardiology Cardiovascular Technology Assessment Committee. J Am Coll Cardiol. 1993;22(3):948–50.

    Google Scholar 

  49. Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Task force of the European society of cardiology and the North American society of pacing and electrophysiology. Eur Heart J. 1996;17(3):354–81.

    Google Scholar 

  50. Bigger JT Jr, Fleiss JL, Steinman RC, Rolnitzky LM, Schneider WJ, Stein PK. RR variability in healthy, middle-aged persons compared with patients with chronic coronary heart disease or recent acute myocardial infarction. Circulation. 1995;91(7):1936–43.

    PubMed  Google Scholar 

  51. Huikuri HV, Makikallio T, Airaksinen KE, Mitrani R, Castellanos A, Myerburg RJ. Measurement of heart rate variability: a clinical tool or a research toy? J Am Coll Cardiol. 1999;34(7):1878–83. doi:10.1016/S0735-1097(99)00468-4.

    PubMed  CAS  Google Scholar 

  52. Kleiger R, Stein P. Heart rate variability in ischaemic disease. In: Malik M, Camm A, editors. Dynamic electrocardiography. New York: Futura/Blackwell; 2004.

    Google Scholar 

  53. Faber TS, Staunton A, Hnatkova K, Camm AJ, Malik M. Stepwise strategy of using short- and long-term heart rate variability for risk stratification after myocardial infarction. Pacing Clin Electrophysiol. 1996;19(11 Pt 2):1845–51. doi:10.1111/j.1540-8159.1996.tb03238.x.

    PubMed  CAS  Google Scholar 

  54. Kornitzer M. Predictive value of electrocardiographic markers for autonomic nervous system dysfunction in healthy populations: more studies needed. Eur Heart J. 2001;22(2):109–12. doi:10.1053/euhj.2000.2375.

    PubMed  CAS  Google Scholar 

  55. Lombardi F. Physiological understanding of HRV components. In: Malik M, Camm A, editors. Dynamic electrocardiography. New York: Futura/Blackwell; 2004. p. 40–7.

    Google Scholar 

  56. Greiser KH, Kluttig A, Schumann B, Kors JA, Swenne CA, Kuss O, et al. Cardiovascular disease, risk factors and heart rate variability in the elderly general population: design and objectives of the cardiovascular disease, living and ageing in Halle (CARLA) study. BMC Cardiovasc Disord. 2005;5:33. doi:10.1186/1471-2261-5-33.

    PubMed  Google Scholar 

  57. Baecke JA, Burema J, Frijters JE. A short questionnaire for the measurement of habitual physical activity in epidemiological studies. Am J Clin Nutr. 1982;36(5):936–42.

    PubMed  CAS  Google Scholar 

  58. Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, et al. Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. 2000;32(9 Suppl):S498–504. doi:10.1097/00005768-200009001-00009.

    PubMed  CAS  Google Scholar 

  59. Lee IM, Paffenbarger RS Jr. Associations of light, moderate, and vigorous intensity physical activity with longevity. The Harvard alumni health study. Am J Epidemiol. 2000;151(3):293–9.

    PubMed  CAS  Google Scholar 

  60. UNESCO. International standard classification of education. ISCED 1997. Paris: UNESCO; 1997.

    Google Scholar 

  61. Leichtle A, Teupser D, Thiery J. Alpha-tocopherol distribution in lipoproteins and anti-inflammatory effects differ between CHD-patients and healthy subjects. J Am Coll Nutr. 2006;25(5):420–8.

    PubMed  CAS  Google Scholar 

  62. Kannel WB. The Framingham study: ITS 50-year legacy and future promise. J Atheroscler Thromb. 2000;6(2):60–6.

    PubMed  CAS  Google Scholar 

  63. van Bemmel JH, Kors JA, van Herpen G. Methodology of the modular ECG analysis system MEANS. Methods Inf Med. 1990;29(4):346–53.

    PubMed  Google Scholar 

  64. Prineas RJ, Crow RS, Blackburn H. The Minnesota code manual of electrocardiographic findings. Standard procedures for measurement and classification. Boston: John Wright PSB; 1982.

    Google Scholar 

  65. Dekker JM, De Vries EL, Lengton RR, Maan AC, Schouten EG, Swenne CA, et al. Reproducibility and comparability of short- and long-term heart rate variability measures in healthy young men. Ann Noninvasive Electrocardiol. 1996;1:287–92. doi:10.1111/j.1542-474X.1996.tb00281.x.

    Google Scholar 

  66. Bootsma M, Swenne CA, Van Bolhuis HH, Chang PC, Cats VM, Bruschke AV. Heart rate and heart rate variability as indexes of sympathovagal balance. Am J Physiol. 1994;266(4 Pt 2):H1565–71.

    PubMed  CAS  Google Scholar 

  67. Pluim BM, Swenne CA, Zwinderman AH, Maan AC, van der Laarse A, Doornbos J, et al. Correlation of heart rate variability with cardiac functional and metabolic variables in cyclists with training induced left ventricular hypertrophy. Heart. 1999;81(6):612–7.

    PubMed  CAS  Google Scholar 

  68. Bootsma M, Swenne CA, Janssen MJA, Cats VM, Schalij MJ. Heart rate variability and sympathovagal balance: pharmacological validation. Neth Heart J. 2003;11(6):250–9.

    Google Scholar 

  69. National Heart Lung and Blood Institute of the National Institutes of Health. ARIC manuals of operation. Manual 5 electrocardiography. Chapel Hill: ARIC Coordinating Center, School of Public Health, University of North Carolina; 1987. p. 5.

    Google Scholar 

  70. Meisinger C, Heier M, Doering A, Thorand B, Loewel H. Prevalence of known diabetes and antidiabetic therapy between 1984/1985 and 1999/2001 in southern Germany. Diabetes Care. 2004;27(12):2985–7. doi:10.2337/diacare.27.12.2985.

    PubMed  Google Scholar 

  71. Ziegler D, Zentai C, Perz S, Rathmann W, Haastert B, Meisinger C, et al. Selective contribution of diabetes and other cardiovascular risk factors to cardiac autonomic dysfunction in the general population. Exp Clin Endocrinol Diabetes. 2006;114(4):153–9. doi:10.1055/s-2006-924083.

    PubMed  CAS  Google Scholar 

  72. Fay MP, Feuer EJ. Confidence intervals for directly standardized rates: a method based on the gamma distribution. Stat Med. 1997;16(7):791–801. doi:10.1002/(SICI)1097-0258(19970415)16:7<791::AID-SIM500>3.0.CO;2-#.

    PubMed  CAS  Google Scholar 

  73. Dragano N, Verde PE, Moebus S, Stang A, Schmermund A, Roggenbuck U, et al. Subclinical coronary atherosclerosis is more pronounced in men and women with lower socio-economic status: associations in a population-based study. Coronary atherosclerosis and social status. Eur J Cardiovasc Prev Rehabil. 2007;14(4):568–74. doi:10.1097/HJR.0b013e32804955c4.

    PubMed  Google Scholar 

  74. Meisinger C, Heier M, Volzke H, Lowel H, Mitusch R, Hense HW, et al. Regional disparities of hypertension prevalence and management within Germany. J Hypertens. 2006;24(2):293–9. doi:10.1097/01.hjh.0000200508.10324.8e.

    PubMed  CAS  Google Scholar 

  75. Völzke H, Neuhauser H, Moebus S, Baumert J, Berger K, Stang A, et al. Regional disparities in smoking among adults in Germany. Dtsch Arztebl. 2006;103(42):A2784–90.

    Google Scholar 

  76. Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001;285(19):2486–97. doi:10.1001/jama.285.19.2486.

    Google Scholar 

  77. NCEP Expert Panel. Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) final report. Circulation 2002;106(25):3143–421.

    Google Scholar 

  78. Bansal S, Buring JE, Rifai N, Mora S, Sacks FM, Ridker PM. Fasting compared with nonfasting triglycerides and risk of cardiovascular events in women. JAMA. 2007;298(3):309–16. doi:10.1001/jama.298.3.309.

    PubMed  CAS  Google Scholar 

  79. Nordestgaard BG, Benn M, Schnohr P, Tybjaerg-Hansen A. Nonfasting triglycerides and risk of myocardial infarction, ischemic heart disease, and death in men and women. JAMA. 2007;298(3):299–308. doi:10.1001/jama.298.3.299.

    PubMed  CAS  Google Scholar 

  80. Jacobs DR Jr, Ainsworth BE, Hartman TJ, Leon AS. A simultaneous evaluation of 10 commonly used physical activity questionnaires. Med Sci Sports Exerc. 1993;25(1):81–91. doi:10.1249/00005768-199301000-00012.

    PubMed  Google Scholar 

  81. Pols MA, Peeters PH, Bueno-De-Mesquita HB, Ocke MC, Wentink CA, Kemper HC, et al. Validity and repeatability of a modified Baecke questionnaire on physical activity. Int J Epidemiol. 1995;24(2):381–8. doi:10.1093/ije/24.2.381.

    PubMed  CAS  Google Scholar 

  82. Pols MA, Peeters PH, Kemper HC, Collette HJ. Repeatability and relative validity of two physical activity questionnaires in elderly women. Med Sci Sports Exerc. 1996;28(8):1020–5. doi:10.1097/00005768-199608000-00012.

    PubMed  CAS  Google Scholar 

  83. Voorrips LE, Ravelli AC, Dongelmans PC, Deurenberg P, van Staveren WA. A physical activity questionnaire for the elderly. Med Sci Sports Exerc. 1991;23(8):974–9. doi:10.1249/00005768-199108000-00015.

    PubMed  CAS  Google Scholar 

  84. Port SC, Boyle NG, Hsueh WA, Quinones MJ, Jennrich RI, Goodarzi MO. The predictive role of blood glucose for mortality in subjects with cardiovascular disease. Am J Epidemiol. 2006;163(4):342–51. doi:10.1093/aje/kwj027.

    PubMed  Google Scholar 

  85. Kuss O, Schumann B, Kluttig A, Greiser KH, Haerting J. Time domain parameters can be estimated with less statistical error than frequency domain parameters in the analysis of heart rate variability. J Electrocardiol. 2008;41(4):287–91.

    PubMed  Google Scholar 

  86. Pinna GD, Maestri R, Torunski A, Danilowicz-Szymanowicz L, Szwoch M, La Rovere MT, et al. Heart rate variability measures: a fresh look at reliability. Clin Sci (Lond). 2007;113(3):131–40. doi:10.1042/CS20070055.

    Article  Google Scholar 

  87. Eckberg DL. Sympathovagal balance: a critical appraisal. Circulation. 1997;96(9):3224–32.

    PubMed  CAS  Google Scholar 

  88. Tulppo M, Huikuri HV. Origin and significance of heart rate variability. J Am Coll Cardiol. 2004;43(12):2278–80. doi:10.1016/j.jacc.2004.03.034.

    PubMed  Google Scholar 

  89. Stein PK, Domitrovich PP, Hui N, Rautaharju P, Gottdiener J. Sometimes higher heart rate variability is not better heart rate variability: results of graphical and nonlinear analyses. J Cardiovasc Electrophysiol. 2005;16(9):954–9. doi:10.1111/j.1540-8167.2005.40788.x.

    PubMed  Google Scholar 

  90. Labarthe DR. Stroke. In: Labarthe DR, editor. Epidemiology and prevention of cardiovascular diseases. A global challenge. Gaithersburg: Aspen; 1998. p. 73–90.

    Google Scholar 

  91. Löwel H, Janku D, Lewis M, Hörmann A, Gostomzyk J, Keil U, et al. MONICA-projekt region Augsburg, data-book coronary event register 1990. Neuherberg: GSF-Forschungszentrum für Umwelt und Gesundheit; 1993.

    Google Scholar 

  92. Gerritsen J, Dekker JM, TenVoorde BJ, Bertelsmann FW, Kostense PJ, Stehouwer CD, et al. Glucose tolerance and other determinants of cardiovascular autonomic function: the Hoorn study. Diabetologia. 2000;43(5):561–70. doi:10.1007/s001250051344.

    PubMed  CAS  Google Scholar 

  93. Liao D, Barnes RW, Chambless LE, Simpson RJ Jr, Sorlie P, Heiss G. Age, race, and sex differences in autonomic cardiac function measured by spectral analysis of heart rate variability—the ARIC study, Atherosclerosis Risk in Communities. Am J Cardiol. 1995;76(12):906–12. doi:10.1016/S0002-9149(99)80260-4.

    PubMed  CAS  Google Scholar 

  94. Antelmi I, de Paula RS, Shinzato AR, Peres CA, Mansur AJ, Grupi CJ. Influence of age, gender, body mass index, and functional capacity on heart rate variability in a cohort of subjects without heart disease. Am J Cardiol. 2004;93(3):381–5. doi:10.1016/j.amjcard.2003.09.065.

    PubMed  Google Scholar 

  95. Buchheit M, Simon C, Charloux A, Doutreleau S, Piquard F, Brandenberger G. Heart rate variability and intensity of habitual physical activity in middle-aged persons. Med Sci Sports Exerc. 2005;37(9):1530–4. doi:10.1249/01.mss.0000177556.05081.77.

    PubMed  Google Scholar 

  96. Reland S, Ville NS, Wong S, Senhadji L, Carre F. Does the level of chronic physical activity alter heart rate variability in healthy older women? Clin Sci (Lond). 2004;107(1):29–35. doi:10.1042/CS20030405.

    Google Scholar 

  97. Sajadieh A, Nielsen OW, Rasmussen V, Hein HO, Abedini S, Hansen JF. Increased heart rate and reduced heart-rate variability are associated with subclinical inflammation in middle-aged and elderly subjects with no apparent heart disease. Eur Heart J. 2004;25(5):363–70. doi:10.1016/j.ehj.2003.12.003.

    PubMed  Google Scholar 

  98. Sandercock GR, Bromley PD, Brodie DA. Effects of exercise on heart rate variability: inferences from meta-analysis. Med Sci Sports Exerc. 2005;37(3):433–9. doi:10.1249/01.MSS.0000155388.39002.9D.

    PubMed  Google Scholar 

  99. Schuit AJ, van Amelsvoort LG, Verheij TC, Rijneke RD, Maan AC, Swenne CA, et al. Exercise training and heart rate variability in older people. Med Sci Sports Exerc. 1999;31(6):816–21. doi:10.1097/00005768-199906000-00009.

    PubMed  CAS  Google Scholar 

  100. Boutcher SH, Stein P. Association between heart rate variability and training response in sedentary middle-aged men. Eur J Appl Physiol Occup Physiol. 1995;70(1):75–80. doi:10.1007/BF00601812.

    PubMed  CAS  Google Scholar 

  101. Carnethon MR, Liao D, Evans GW, Cascio WE, Chambless LE, Heiss G. Correlates of the shift in heart rate variability with an active postural change in a healthy population sample: The Atherosclerosis Risk in Communities study. Am Heart J. 2002;143(5):808–13. doi:10.1067/mhj.2002.121928.

    PubMed  Google Scholar 

  102. Loimaala A, Huikuri H, Oja P, Pasanen M, Vuori I. Controlled 5-mo aerobic training improves heart rate but not heart rate variability or baroreflex sensitivity. J Appl Physiol. 2000;89(5):1825–9.

    PubMed  CAS  Google Scholar 

  103. Uusitalo AL, Laitinen T, Vaisanen SB, Lansimies E, Rauramaa R. Physical training and heart rate and blood pressure variability: a 5-yr randomized trial. Am J Physiol Heart Circ Physiol. 2004;286(5):H1821–6. doi:10.1152/ajpheart.00600.2003.

    PubMed  CAS  Google Scholar 

  104. Verheyden B, Eijnde BO, Beckers F, Vanhees L, Aubert AE. Low-dose exercise training does not influence cardiac autonomic control in healthy sedentary men aged 55–75 years. J Sports Sci. 2006;24(11):1137–47. doi:10.1080/02640410500497634.

    PubMed  Google Scholar 

  105. Roach D, Wilson W, Ritchie D, Sheldon R. Dissection of long-range heart rate variability: controlled induction of prognostic measures by activity in the laboratory. J Am Coll Cardiol. 2004;43(12):2271–7. doi:10.1016/j.jacc.2004.01.050.

    PubMed  Google Scholar 

  106. Serrador JM, Finlayson HC, Hughson RL. Physical activity is a major contributor to the ultra low frequency components of heart rate variability. Heart. 1999;82(6):e9.

    PubMed  CAS  Google Scholar 

  107. Eryonucu B, Bilge M, Guler N, Uzun K, Gencer M. Effects of cigarette smoking on the circadian rhythm of heart rate variability. Acta Cardiol. 2000;55(5):301–5. doi:10.2143/AC.55.5.2005757.

    PubMed  CAS  Google Scholar 

  108. Horsten M, Ericson M, Perski A, Wamala SP, Schenck-Gustafsson K, Orth-Gomer K. Psychosocial factors and heart rate variability in healthy women. Psychosom Med. 1999;61(1):49–57.

    PubMed  CAS  Google Scholar 

  109. Kupari M, Virolainen J, Koskinen P, Tikkanen MJ. Short-term heart rate variability and factors modifying the risk of coronary artery disease in a population sample. Am J Cardiol. 1993;72(12):897–903. doi:10.1016/0002-9149(93)91103-O.

    PubMed  CAS  Google Scholar 

  110. Tsuji H, Venditti FJ Jr, Manders ES, Evans JC, Larson MG, Feldman CL, et al. Determinants of heart rate variability. J Am Coll Cardiol. 1996;28(6):1539–46. doi:10.1016/S0735-1097(96)00342-7.

    PubMed  CAS  Google Scholar 

  111. Janszky I, Ericson M, Blom M, Georgiades A, Magnusson JO, Alinagizadeh H, et al. Wine drinking is associated with increased heart rate variability in women with coronary heart disease. Heart. 2005;91(3):314–8. doi:10.1136/hrt.2004.035105.

    PubMed  CAS  Google Scholar 

  112. Christensen JH, Skou HA, Fog L, Hansen V, Vesterlund T, Dyerberg J, et al. Marine n-3 fatty acids, wine intake, and heart rate variability in patients referred for coronary angiography. Circulation. 2001;103(5):651–7.

    PubMed  CAS  Google Scholar 

  113. Yusuf S, Hawken S, Ounpuu S, Bautista L, Franzosi MG, Commerford P, et al. Obesity and the risk of myocardial infarction in 27, 000 participants from 52 countries: a case-control study. Lancet. 2005;366(9497):1640–9. doi:10.1016/S0140-6736(05)67663-5.

    PubMed  Google Scholar 

  114. Carnethon MR, Golden SH, Folsom AR, Haskell W, Liao D. Prospective investigation of autonomic nervous system function and the development of type 2 diabetes: the Atherosclerosis Risk in Communities study, 1987–1998. Circulation. 2003;107(17):2190–5. doi:10.1161/01.CIR.0000066324.74807.95.

    PubMed  Google Scholar 

  115. Schroeder EB, Chambless LE, Liao D, Prineas RJ, Evans GW, Rosamond WD, et al. Diabetes, glucose, insulin, and heart rate variability: the Atherosclerosis Risk in Communities (ARIC) study. Diabetes Care. 2005;28(3):668–74. doi:10.2337/diacare.28.3.668.

    PubMed  CAS  Google Scholar 

  116. Singh JP, Larson MG, O’Donnell CJ, Wilson PF, Tsuji H, Lloyd-Jones DM, et al. Association of hyperglycemia with reduced heart rate variability (the Framingham heart study). Am J Cardiol. 2000;86(3):309–12. doi:10.1016/S0002-9149(00)00920-6.

    PubMed  CAS  Google Scholar 

  117. Perciaccante A, Fiorentini A, Paris A, Serra P, Tubani L. Circadian rhythm of the autonomic nervous system in insulin resistant subjects with normoglycemia, impaired fasting glycemia, impaired glucose tolerance, type 2 diabetes mellitus. BMC Cardiovasc Disord. 2006;6:19. doi:10.1186/1471-2261-6-19.

    PubMed  Google Scholar 

  118. Schroeder EB, Liao D, Chambless LE, Prineas RJ, Evans GW, Heiss G. Hypertension, blood pressure, and heart rate variability: the Atherosclerosis Risk in Communities (ARIC) study. Hypertension. 2003;42(6):1106–11. doi:10.1161/01.HYP.0000100444.71069.73.

    PubMed  CAS  Google Scholar 

  119. Singh JP, Larson MG, Tsuji H, Evans JC, O’Donnell CJ, Levy D. Reduced heart rate variability and new-onset hypertension: insights into pathogenesis of hypertension: the Framingham heart study. Hypertension. 1998;32(2):293–7.

    PubMed  CAS  Google Scholar 

  120. Copie X, Le Heuzey JY. Effects of drugs. In: Malik M, Camm A, editors. Dynamic electrocardiography. New York: Futura/Blackwell; 2004. p. 83–9.

    Google Scholar 

Download references

Acknowledgments

This study was funded by a grant from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) as part of the Collaborative Research Center 598 “Heart failure in the elderly—cellular mechanisms and therapy” at the Medical Faculty of the Martin-Luther-University Halle-Wittenberg; by a grant of the Wilhelm-Roux programme of the Martin-Luther-University Halle-Wittenberg; and by the Federal Employment Office. We thank all participants of the CARLA study and all members of the CARLA study team who participated in the recruitment, data collection, data management, and analysis. We are also indebted to numerous colleagues who shared their instruments of data collection with us and gave advice and practical help during the design phase and implementation of the recruitment and examination (among them Dietrich Alte, Klaus Berger, Martin Bobak, Nico Dragano, Gerardo Heiss, Hans-Werner Hense, Kerstin Klipstein-Grobusch, Hannelore Loewel, Jan Luedemann, Christa Meisinger, Achim Reineke, Barbara Thorand, Henry Voelzke, Jacqueline Witteman).

Author information

Authors and Affiliations

  1. Institute of Medical Epidemiology, Biostatistics, and Informatics, Martin-Luther-University Halle-Wittenberg, Magdeburger Str. 8, 06097, Halle (Saale), Germany

    Karin Halina Greiser, Alexander Kluttig, Barbara Schumann, Oliver Kuss & Johannes Haerting

  2. Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands

    Cees A. Swenne

  3. Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands

    Jan A. Kors

  4. Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics (ILM), University of Leipzig, Leipzig, Germany

    Joachim Thiery

  5. Department of Medicine III, Martin-Luther-University Halle-Wittenberg, Halle (Saale), Germany

    Hendrik Schmidt & Karl Werdan

Authors
  1. Karin Halina Greiser
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Alexander Kluttig
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Barbara Schumann
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Cees A. Swenne
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jan A. Kors
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Oliver Kuss
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Johannes Haerting
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hendrik Schmidt
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Joachim Thiery
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Karl Werdan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Karin Halina Greiser.

Additional information

Authors’ contributions

KHG conceived of the study, designed major parts of the study, participated in the statistical analyses and drafted the manuscript. AK conducted the statistical analyses and helped drafting the manuscript. BS helped designing the interview, participated in the statistical analyses and helped drafting the manuscript. CAS designed the protocol for the ECG recordings used to derive HRV, performed the HRV analyses and helped drafting the manuscript. JAK performed the Minnesota coding and pre-processing of ECGs via MEANS for HRV analysis and helped drafting the manuscript. OK gave statistical advice, participated in the statistical analyses and helped drafting the manuscript. JH helped designing the study, selecting the statistical procedures and drafting the manuscript. HS validated ECG-based diagnoses and critically reviewed the manuscript. JT performed the laboratory analyses and helped drafting the manuscript. KW helped designing the study and drafting the manuscript.

Electronic supplementary material

Below is the link to the electronic supplementary material.

(DOC 284 kb)

Appendix

Appendix

Inclusion and exclusion criteria for the study population

All inhabitants of the city of Halle (Saale) of German nationality aged 45–80 years drawn in the random sample from the population registry in June 2002 were eligible for inclusion in the study. Exclusion criteria were: (1) subject deceased prior to invitation or planned examination date; (2) subject moved to unknown location or abroad; (3) subject unable to attend 4-h long examination and interview due to illness, frailty, or hospitalization; (4) inability to perform the interview due to language difficulties (e.g. for Russian immigrants of German descent); (5) long-term absence from the study region throughout the study period (e.g. due to remote workplace).

Definition of prevalent definite MI according to Minnesota code

Based on reference [69] and personal communication by Richard S. Crowe, Univ. of Minnesota, USA, as of 15th June 2005.

The classification as “definite prevalent MI” based on one ECG according to Minnesota code was based on the presence of any of the two following conditions:

  1. 1.

    First condition:

Minnesota code = (111 or 112 or 113 or 114 or 115 or 116 or 117) and no Minnesota code (711, left bundle branch block, LBBB; or 74, intraventricular block, IVCD);

  1. 2.

    Second condition:

Minnesota code = (121 or 122 or 124 or 125 or 127) and Minnesota code = (411 or 412 or 42 or 43 or 51 or 52 or 53) and no Minnesota code (711, LBBB; or 74, IVCD).

Table 4 Sex-specific cutpoints for categories of continuous variables in the total CARLA study population (2002–2006)
Full size table
Table 5 Sex-specific cutpoints for categories of continuous variables, CARLA study population excluding subjects with CVD, diabetes, use of betablockers, ACE-inhibitors or antiarrhythmic drugs (only “healthy” subjects, 2002–2006)
Full size table
Table 6 Age distribution of CARLA study participants by sex at the baseline examination 2002–2006
Full size table

Rights and permissions

Reprints and permissions

About this article

Cite this article

Greiser, K.H., Kluttig, A., Schumann, B. et al. Cardiovascular diseases, risk factors and short-term heart rate variability in an elderly general population: the CARLA study 2002–2006. Eur J Epidemiol 24, 123–142 (2009). https://doi.org/10.1007/s10654-009-9317-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10654-009-9317-z

Keywords

Search

Navigation