Hypertension prevalence in patients attending tertiary pain management services, a registry-based Australian cohort study

Autoři: Melita J. Giummarra aff001;  Hilarie Tardif aff003;  Megan Blanchard aff003;  Andrew Tonkin aff001;  Carolyn A. Arnold aff002
Působiště autorů: Department of Epidemiology & Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia aff001;  Caulfield Pain Management and Research Centre, Caulfield Hospital, Caulfield, Victoria, Australia aff002;  Australian Health Services Research Institute, University of Wollongong, Wollongong, New South Wales, Australia aff003;  Academic Board of Anaesthesia & Perioperative Medicine, School of Medicine Nursing & Health Sciences, Monash University, Clayton, Victoria, Australia aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0228173


Persistent pain and hypertension often co-occur, and share several biological and lifestyle risk factors. The present study aimed to provide insight into the prevalence of, and factors associated with, hypertension in the largest cohort of patients seeking treatment in 43 tertiary pain clinics in Australia. Adults aged > = 18 years registered to the electronic Persistent Pain Outcomes Collaboration registry between 2013 and 2018 were included if they had persistent non-cancer pain (N = 43,789). Risk Ratios (RRs) compared prevalence of self-reported hypertension with the general and primary care Australian populations, and logistic regression examined factors associated with hypertension. One in four (23.9%) patients had hypertension, which was higher than the Australian adult population (2014–15: RR = 5.86, 95%CI: 5.66, 6.06; 2017–18: RR = 9.40, 95%CI: 9.01, 9.80), and in primary care patients (2011–13: RR = 1.17, 95%CI: 1.15, 1.20). Adjusting for covariates, patients with higher odds of hypertension were older, lived in regions with higher socioeconomic disadvantage, had higher levels of BMI, were born outside the Oceania/Australasia region, and had comorbid arthritis, diabetes, or severe-extremely severe anxiety symptoms. Female patients and those with depression symptoms had lower adjusted odds. Unadjusted analyses showed an association between widespread pain, pain duration, pain severity and interference, and lower pain self-efficacy with hypertension; however, only pain severity remained significant in adjusted analyses. Hypertension was more prevalent in people with persistent pain than in the general community, was associated with more severe pain, and commonly co-occurred with pain-related impairments. Routine hypertension screening and treatment targeting shared mechanisms of hypertension and pain may improve treatment outcomes in the pain clinic setting.

Klíčová slova:

Arthritis – Blood pressure – Diabetes mellitus – Hypertension – Obesity – Pain management – Primary care – Primary hypertension


1. Olsen RB, Bruehl S, Nielsen CS, Rosseland LA, Eggen AE, Stubhaug A. Hypertension prevalence and diminished blood pressure-related hypoalgesia in individuals reporting chronic pain in a general population: The Tromso Study. Pain. 2013;154(2):257–62. doi: 10.1016/j.pain.2012.10.020 23245863

2. Kerkhoff AC, Moreira LB, Fuchs FD, Fuchs SC. Association between hypertension and musculoskeletal complaints: a population-based study. J Hypertens. 2012;30(11):2112–7. doi: 10.1097/HJH.0b013e3283588268 22922700

3. Parsons S, McBeth J, Macfarlane GJ, Hannaford PC, Symmons DPM. Self-reported pain severity is associated with a history of coronary heart disease. Eur J Pain. 2015;19(2):167–75. doi: 10.1002/ejp.533 24890750

4. Goodson NJ, Smith BH, Hocking LJ, McGilchrist MM, Dominiczak AF, Morris A, et al. Cardiovascular risk factors associated with the metabolic syndrome are more prevalent in people reporting chronic pain: Results from a cross-sectional general population study. Pain. 2013;154(9):1595–602. doi: 10.1016/j.pain.2013.04.043 23707277

5. Fine PG. Long-Term Consequences of Chronic Pain: Mounting Evidence for Pain as a Neurological Disease and Parallels with Other Chronic Disease States. Pain Med. 2011;12(7):996–1004. doi: 10.1111/j.1526-4637.2011.01187.x 21752179

6. Kurita GP, Sjogren P, Juel K, Hojsted J, Ekholm O. The burden of chronic pain: A cross-sectional survey focussing on diseases, immigration, and opioid use. Pain. 2012;153(12):2332–8. doi: 10.1016/j.pain.2012.07.023 22959600

7. Buse DC, Manack A, Serrano D, Turkel C, Lipton RB. Sociodemographic and comorbidity profiles of chronic migraine and episodic migraine sufferers. J Neurol Neurosurg. 2010;81(4):428–32.

8. Bruehl S, Chung OY, Jirjis JN, Biridepalli S. Prevalence of clinical hypertension in patients with chronic pain compared to nonpain general medical patients. Clin J Pain. 2005;21(2):147–53. doi: 10.1097/00002508-200503000-00006 15722808

9. Edwards RR, Dworkin RH, Sullivan MD, Turk DC, Wasan AD. The Role of Psychosocial Processes in the Development and Maintenance of Chronic Pain. J Pain. 2016;17(9):T70–T92.

10. Mundal I, Bjorngaard JIK, Nilsen TIL, Nichol BI, Grawe RW, Forst EA. Long-Term Changes in Musculoskeletal Pain Sites in the General Population: The HUNT Study. J Pain. 2016;17(11):1246–56. doi: 10.1016/j.jpain.2016.08.006 27578444

11. Bruehl S, Olsen RB, Tronstad C, Sevre K, Burns JW, Schirmer H, et al. Chronic Pain-Related Changes in Cardiovascular Regulation and Impact on Comorbid Hypertension in a General Population: The Tromso Study. Pain. 2018;159(1):119–27. doi: 10.1097/j.pain.0000000000001070 28953193

12. Chung OY, Bruehl S. The impact of blood pressure and baroreflex sensitivity on wind-up. Anesth Analg. 2008;107(3):1018–25. doi: 10.1213/ane.0b013e31817f8dfe 18713923

13. Tracy LM, Ioannou L, Baker KS, Gibson SJ, Georgiou-Karistianis N, Giummarra MJ. Meta-analytic evidence for decreased heart rate variability in chronic pain implicating parasympathetic nervous system dysregulation. Pain. 2016;157(1):7–29. doi: 10.1097/j.pain.0000000000000360 26431423

14. Burns JW, Quartana PJ, Bruehl S, Janssen I, Dugan SA, Appelhans B, et al. Chronic pain, body mass index and cardiovascular disease risk factors: Tests of moderation, unique and shared relationships in the Study of Women's Health Across the Nation (SWAN). Journal of Behavioral Medicine. 2015;38(372–383). doi: 10.1007/s10865-014-9608-z 25427423

15. McLean SA. The Potential Contribution of Stress Systems to the Transition to Chronic Whiplash-Associated Disorders. Spine. 2011;36(25):S226–S32.

16. Britt HC, Harrison CM, Miller GC, Knox SA. Prevalence and patterns of multimorbidity in Australia. Med J Aust. 2008;189:72–7. 18637770

17. Tardif H, Arnold C, Hayes C, Eagar K. Establishment of the Australasian Electronic Persistent Pain Outcomes Collaboration. Pain medicine (Malden, Mass). 2016.

18. Australian Bureau of Statistics. Standard Australian Classification of Countries (SACC). 2011.

19. Australian Bureau of Statistics. Socio-Economic Indexes for Areas (SEIFA). Canberra, Australia: Australian Bureau of Statistics; 2013.

20. World Health Organization. Body mass index (BMI) classifications. Copenhagen, Denmark: World Health Organisation; 2013.

21. Cleeland CS. Measurement of pain by subjective report. In: Chapman CR, Loeser JD, editors. Advances in Pain Research and Therapy, Volume 12: Issues in Pain Measurement. 12. New York: Raven Press; 1989. p. 391–403.

22. Cleeland C. The Brief Pain Inventory: User guide. Texas: MD Anderson Cancer Centre; 1991.

23. Atkinson TM, Mendoza TR, Sit L, Passik S, Scher HI, Cleeland C, et al. The Brief Pain Inventory and Its "Pain At Its Worst in the Last 24 Hours" Item: Clinical Trial Endpoint Considerations. Pain Med. 2010;11(3):337–46. doi: 10.1111/j.1526-4637.2009.00774.x 20030743

24. Gerbershagen HJ, Rothaug J, Kalkman CJ, Meissner W. Determination of moderate-to-severe postoperative pain on the numeric rating scale: a cut-off point analysis applying four different methods. BJA. 2011;107(4):619–26. doi: 10.1093/bja/aer195 21724620

25. von Baeyer CL, Lin V, Seidman LC, Tsao JCK, Zeltzer LK. Pain charts (body maps or manikins) in assessment of the location of pediatric pain. Pain Manag. 2011;1(1):61–8. doi: 10.2217/pmt.10.2 21572558

26. Garg N, Deodhar A. New and modified fibromyalgia diagnostic criteria. J Musculoskelet Med. 2012;29:13–5.

27. Wolfe F, Clauw DJ, Fitzcharles MA, Goldenberg DL, Katz RS, Mease P, et al. The American College of Rheumatology preliminary diagnostic criteria for fibromyalgia and measurement of symptom severity. Arthritis care & research. 2010;62(5):600–10.

28. Nicholas N, editor Self-efficacy and chronic pain. Annual Conference of the British Psychological Society 1989; St Andrews, UK.

29. Sullivan MJL, Bishop SR, Pivik J. The Pain Catastrophizing Scale: Development and validation. Psychol Assess. 1995;7(4):524–32.

30. Sullivan MJL. The Pain Catastrophizing Scale user manual. Montreal, Canada: McGill University; 2009.

31. Lovibond SH, Lovibond PF. Manual for the Depression Anxiety Stress Scales. Sydney, Australia: Psychology Foundation Monograph; 1995.

32. Henry JD, Crawford JR. The short-form version of the Depression Anxiety Stress Scales (DASS-21): Construct validity and normative data in a large non-clinical sample. Br J Clin Psychol. 2005;44:227–39. doi: 10.1348/014466505X29657 16004657

33. Wood BM, Nicholas MK, Blyth F, Asghari A, Gibson S. The utility of the short version of the Depression Anxiety Stress Scales (DASS-21) in elderly patients with persistent pain: does age make a difference? Pain medicine (Malden, Mass). 2010;11(12):1780–90.

34. Parkitny L, McAuley JH, Walton D, Pena Costa LO, Refshauge KM, Wand BM, et al. Rasch analysis supports the use of the depression, anxiety, and stress scales to measure mood in groups but not in individuals with chronic low back pain. J Clin Epidemiol. 2012;65(2):189–98. doi: 10.1016/j.jclinepi.2011.05.010 21889306

35. Australian Bureau of Statistics. National Health Survey: First Results, 2014–15—Catalogue no. 4364.0.55.001: Australian Bureau of Statistics; 2016 [Available from: www.abs.gov.au/ausstats/abs@.nsf/.

36. Australian Bureau of Statistics. National Health Survey: First Results, Long term health conditions, 2017–18 (Report number 4364.0.55.001DO003_20172018) Canberra, Australia: Australian Bureau of Statistics; 2018.

37. Ghosh A, Charlton KE, Girdo L, Batterham M. Using data from patient interactions in primary care for population level chronic disease surveillance: The Sentinel Practices Data Sourcing (SPDS) project. BMC Public Health. 2014;14.

38. Smith N, Jordan M, White R, Bowman J, Hayes C. Assessment of Adults Experiencing Chronic Non-Cancer Pain: A Randomized Trial of Group Versus Individual Format at an Australian Tertiary Pain Service. Pain Med. 2016;17(2):278–94. doi: 10.1093/pm/pnv048 26814305

39. Wooden M, Watson N, Agius P, Freidin S. Assessing the Quality of the Height and Weight Data in the HILDA Survey. Melbourne, Australia: University of Melbourne; 2008.

40. van Buuren S. Multiple imputation of discrete and continuous data by fully conditional specification. Statistical methods in medical research. 2007;16(3):219–42. doi: 10.1177/0962280206074463 17621469

41. Rubin D. Multiple imputation for non-response surveys. New York: John Wiley and Sons; 1987.

42. Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code for Biology and Medicine. 2008;3:17–. doi: 10.1186/1751-0473-3-17 19087314

43. Dworkin RH, Turk DC, Wyrwich KW, Beaton D, Cleeland CS, Farrar JT, et al. Interpreting the clinical importance of treatment outcomes in chronic pain clinical trials: IMMPACT recommendations. J Pain. 2008;9(2):105–21. doi: 10.1016/j.jpain.2007.09.005 18055266

44. Shrestha PL, Shrestha PA, Vivo RP. Epidemiology of comorbidities with hypertension. Curr Opin Cardiol. 2016;31(4):376–80. doi: 10.1097/HCO.0000000000000298 27137759

45. Strine TW, Mokdad AH, Balluz LS, Gonzalez O, Crider R, Berry JT, et al. Depression and anxiety in the United States: findings from the 2006 Behavioral Risk Factor Surveillance System. Psychiatric services (Washington, DC). 2008;59(12):1383–90.

46. Birk JL, Kronish IM, Moise N, Falzon L, Yoon S, Davidson KW. Depression and Multimorbidity: Considering Temporal Characteristics of the Associations Between Depression and Multiple Chronic Diseases. Health Psychol. 2019;38(9):802–11. doi: 10.1037/hea0000737 31008648

47. Licht CM, de Geus EJ, Seldenrijk A, van Hout HP, Zitman FG, van Dyck R, et al. Depression is associated with decreased blood pressure, but antidepressant use increases the risk for hypertension. Hypertension (Dallas, Tex: 1979). 2009;53(4):631–8.

48. Bhat SK, Beilin LJ, Robinson M, Burrows S, Mori TA. Relationships between depression and anxiety symptoms scores and blood pressure in young adults. J Hypertens. 2017;35(10):1983–91. doi: 10.1097/HJH.0000000000001410 28505062

49. Paterniti S, Verdier-Taillefer M-H, Geneste C, Bisserbe J-C, Alpérovitch A. Low blood pressure and risk of depression in the elderly: A prospective community-based study. British Journal of Psychiatry. 2000;176(5):464–7.

50. Hansson P. Translational aspects of central sensitization induced by primary afferent activity: What it is and what it is not. Pain. 2014;155(10):1932–4. doi: 10.1016/j.pain.2014.07.016 25067835

51. Meeus M, Goubert D, De Backer F, Struyf F, Hermans L, Coppieters I, et al. Heart rate variability in patients with fibromyalgia and patients with chronic fatigue syndrome: A systematic review. Semin Arthritis Rheum. 2013;43(2):279–87. doi: 10.1016/j.semarthrit.2013.03.004 23838093

52. Andersson HI. Increased mortality among individuals with chronic widespread pain relates to lifestyle factors: A prospective population-based study. Disabil Rehabil. 2009;31(24):1980–7. doi: 10.3109/09638280902874154 19874076

53. Bramlage P, Hasford J. Blood pressure reduction, persistence and costs in the evaluation of antihypertensive drug treatment—a review. Cardiovasc Diabetol. 2009;8.

54. Hoeper M, Markevych I, Spiekerkoetter E, Welte T, Niedermeyer J. Goal-oriented treatment and combination therapy for pulmonary arterial hypertension. Eur Respir J. 2005;26:858–63. doi: 10.1183/09031936.05.00075305 16264047

55. Babu AS, Padmakumar R, Maiya AG, Mohapatra AK, Kamath RL. Effects of Exercise Training on Exercise Capacity in Pulmonary Arterial Hypertension: A Systematic Review of Clinical Trials. Heart Lung Circ. 2016;25(4):333–41. doi: 10.1016/j.hlc.2015.10.015 26703447

56. Semlitsch T, Jeitler K, Berghold A, Horvath K, Posch N, Poggenburg S, et al. Long-term effects of weight-reducing diets in people with hypertension. Cochrane Database Syst Rev. 2016(3).

57. Pandey A, Garg S, Khunger M, Garg S, Kumbhani DJ, Chin KM, et al. Efficacy and Safety of Exercise Training in Chronic Pulmonary Hypertension Systematic Review and Meta-Analysis. Circ Heart Fail. 2015;8(6):1032–43. doi: 10.1161/CIRCHEARTFAILURE.115.002130 26185169

58. O'Connor SR, Tully MA, Ryan B, Bleakley CM, Baxter GD, Bradley JM, et al. Walking Exercise for Chronic Musculoskeletal Pain: Systematic Review and Meta-Analysis. Arch Phys Med Rehabil. 2015;96(4):724–34. doi: 10.1016/j.apmr.2014.12.003 25529265

59. Searle A, Spink M, Ho A, Chuter V. Exercise interventions for the treatment of chronic low back pain: a systematic review and meta-analysis of randomised controlled trials. Clin Rehabil. 2015;29(12):1155–67. doi: 10.1177/0269215515570379 25681408

60. Bertisch SM, Wee CC, Phillips RS, McCarthy EP. Alternative mind-body therapies used by adults with medical conditions. J Psychosom Res. 2009;66(6):511–219. doi: 10.1016/j.jpsychores.2008.12.003 19446710

61. Park C. Mind-Body CAM Interventions: Current Status and Considerations for Integration Into Clinical Health Psychology. J Clin Psychol. 2013;69:45–63. doi: 10.1002/jclp.21910 22936306

62. Vernooij RWM, Willson M, Gagliardi AR, Guidelines Int N. Characterizing patient-oriented tools that could be packaged with guidelines to promote self-management and guideline adoption: a meta-review. Implement Sci. 2016;11.

63. Xue J, Zhao F, Wang Y, Gu J, Gao J, Wang X, et al. Integrative Cardiac Reserve. Integrative Medicine International. 2014;1(3):162–9.

64. Okura Y, Urban LH, Mahoney DW, Jacobsen SJ, Rodeheffer RJ. Agreement between self-report questionnaires and medical record data was substantial for diabetes, hypertension, myocardial infarction and stroke but not for heart failure. J Clin Epidemiol. 2004;57(10):1096–103. doi: 10.1016/j.jclinepi.2004.04.005 15528061

65. van den Akker M, van Steenkiste B, Krutwagen E, Metsemakers JFM. Disease or no disease? Disagreement on diagnoses between self-reports and medical records of adult patients. Eur J Gen Pract. 2015;21(1):45–51. doi: 10.3109/13814788.2014.907266 24830475

66. Mentz G, Schulz AJ, Mukherjee B, Ragunathan TE, Perkins DW, Israel BA. Hypertension: Development of a prediction model to adjust self-reported hypertension prevalence at the community level. BMC Health Serv Res. 2012;12.

67. Gonçalves VSS, Andrade KRC, Carvalho KMB, Silva MT, Pereira MG, Galvao TF. Accuracy of self-reported hypertension: A systematic review and meta-analysis. J Hypertens. 2018;36:970–8. doi: 10.1097/HJH.0000000000001648 29232280

68. Goldman N, Lin IF, Weinstein M, Lin YH. Evaluating the quality of self-reports of hypertension and diabetes. J Clin Epidemiol. 2003;56(2):148–54. doi: 10.1016/s0895-4356(02)00580-2 12654409

69. Khattar RS, Swales JD, Banfield N, Dore C, Senior R, Lahiri A. Prediction of coronary and cerebrovascular morbidity and mortality by direct continuous ambulatory blood pressure monitoring in essential hypertension. Circulation. 1999;100(10):1071–6. doi: 10.1161/01.cir.100.10.1071 10477532

70. Nuttall FQ. Body Mass Index: Obesity, BMI, and Health: A Critical Review. Nutrition today. 2015;50(3):117–28. doi: 10.1097/NT.0000000000000092 27340299

71. WHO Expert Consultation. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004;363(9403):157–63. doi: 10.1016/S0140-6736(03)15268-3 14726171

72. Nolet PS, Cote P, Cassidy JD, Carroll LJ. The association between self-reported cardiovascular disorders and troublesome neck pain: A population-based cohort study. J Manipulative Physiol Ther. 2012;35(3):176–83. doi: 10.1016/j.jmpt.2012.01.006 22364915

73. Leino-Arjas P, Solovieva S, Kirjonen J, Reunanen A, Riihimaki H. Cardiovascular risk factors and low-back pain in a long-term follow-up of industrial employees. Scand J Work Environ Health. 2006;32:12–9. doi: 10.5271/sjweh.971 16539167

74. Sarink D, Nedkoff L, Briffa T, Shaw JE, Magliano DJ, Stevenson C, et al. Projected age- and sex-specific prevalence of cardiovascular diseases in Western Australian adults from 2005–2045. Eur J Prev Cardiol. 2016;23(1):23–32. doi: 10.1177/2047487314554865 25305272

75. MBF Foundation. The high price of pain: the economic impact of persistent pain in Australia. Sydney: Pain Management Research Institute, University of Sydney; 2007.

76. Deloitte Access Economics. The cost of pain in Australia. Australia: PainAustralia; 2019.

Článek vyšel v časopise


2020 Číslo 1