[Skip to Content]
[Skip to Content Landing]

Association Between Idiopathic Intracranial Hypertension and Risk of Cardiovascular Diseases in Women in the United Kingdom

Educational Objective
To determine whether the risk of cardiovascular disease is greater in woman with idiopathic intracranial hypertension compared with women with similar age and body mass index but without idiopathic intracranial hypertension.
1 Credit CME
Key Points

Question  Is the risk of cardiovascular disease greater in women with idiopathic intracranial hypertension than in women of the same age and body mass index but without idiopathic intracranial hypertension?

Findings  In this population-based matched controlled cohort study of 2760 female patients with idiopathic intracranial hypertension and 27 125 control patients, women with this condition had twice the risk for cardiovascular disease compared with their counterparts with similar body mass index and age. Between 2005 and 2017, the incidence and prevalence of idiopathic intracranial hypertension have tripled.

Meaning  Idiopathic intracranial hypertension appeared to be a risk factor for cardiovascular disease in women; changing patient management to address the risk factors for cardiovascular disease may reduce long-term morbidity.


Importance  Cardiovascular disease (CVD) risk has not been previously evaluated in a large matched cohort study in idiopathic intracranial hypertension (IIH).

Objectives  To estimate the risk of composite cardiovascular events, heart failure, ischemic heart disease, stroke/transient ischemic attack (TIA), type 2 diabetes, and hypertension in women with idiopathic intracranial hypertension and compare it with the risk in women, matched on body mass index (BMI) and age, without the condition; and to evaluate the prevalence and incidence of IIH.

Design, Setting, and Participants  This population-based matched controlled cohort study used 28 years of data, from January 1, 1990, to January 17, 2018, from The Health Improvement Network (THIN), an anonymized, nationally representative electronic medical records database in the United Kingdom. All female patients aged 16 years or older were eligible for inclusion. Female patients with IIH (n = 2760) were included and randomly matched with up to 10 control patients (n = 27 125) by BMI and age.

Main Outcomes and Measures  Adjusted hazard ratios (aHRs) of cardiovascular outcomes were calculated using Cox regression models. The primary outcome was a composite of any CVD (heart failure, ischemic heart disease, and stroke/TIA), and the secondary outcomes were each CVD outcome, type 2 diabetes, and hypertension.

Results  In total, 2760 women with IIH and 27 125 women without IIH were included. Age and BMI were similar between the 2 groups, with a median (interquartile range) age of 32.1 (25.6-42.0) years in the exposed group and 32.1 (25.7-42.1) years in the control group; in the exposed group 1728 women (62.6%) were obese, and in the control group 16514 women (60.9%) were obese. Higher absolute risks for all cardiovascular outcomes were observed in women with IIH compared with control patients. The aHRs were as follows: composite cardiovascular events, 2.10 (95% CI, 1.61-2.74; P < .001); heart failure, 1.97 (95% CI, 1.16-3.37; P = .01); ischemic heart disease, 1.94 (95% CI, 1.27-2.94; P = .002); stroke/TIA, 2.27 (95% CI, 1.61-3.21; P < .001); type 2 diabetes, 1.30 (95% CI, 1.07-1.57; P = .009); and hypertension, 1.55 (95% CI, 1.30-1.84; P < .001). The incidence of IIH in female patients more than tripled between 2005 and 2017, from 2.5 to 9.3 per 100 000 person-years. Similarly, IIH prevalence increased in the same period, from 26 to 79 per 100 000 women. Incidence increased markedly with BMI higher than 30.

Conclusions and Relevance  Idiopathic intracranial hypertension in women appeared to be associated with a 2-fold increase in CVD risk; change in patient care to modify risk factors for CVD may reduce long-term morbidity for women with IIH and warrants further evaluation.

Sign in to take quiz and track your certificates

Buy This Activity

JN Learning™ is the home for CME and MOC from the JAMA Network. Search by specialty or US state and earn AMA PRA Category 1 CME Credit™ from articles, audio, Clinical Challenges and more. Learn more about CME/MOC

Article Information

Accepted for Publication: April 26, 2019.

Published Online: July 8, 2019. doi:10.1001/jamaneurol.2019.1812

Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2019 Adderley NJ et al. JAMA Neurology.

Corresponding Author: Alexandra J. Sinclair, PhD, Metabolic Neurology, Institute of Metabolism and Systems Research, University of Birmingham, Birmingham B15 2TT, United Kingdom (A.B.Sinclair@bham.ac.uk).

Author Contributions: Dr Adderley and Ms Subramanian had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Adderley and Nirantharakumar and Ms Subramanian contributed equally and are joint first coauthors.

Concept and design: Adderley, Nirantharakumar, Sinclair.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: All authors.

Critical revision of the manuscript for important intellectual content: Adderley, Nirantharakumar, Yiangou, Mollan, Sinclair.

Statistical analysis: Adderley, Subramanian, Nirantharakumar, Yiangou, Gokhale.

Obtained funding: Sinclair.

Administrative, technical, or material support: Adderley, Nirantharakumar, Yiangou, Gokhale.

Supervision: Nirantharakumar, Mollan, Sinclair.

Conflict of Interest Disclosures: Dr Nirantharakumar reported personal fees from Sanofi, Merck Sharp & Dohme Corp, and Boehringer Ingelheim as well as grants from AstraZeneca, National Institute for Health Research (NIHR), Health Data Research UK (Medical Research Council), and British Heart Foundation outside of the submitted work. Dr Subramanian reported grants from AstraZeneca outside of the submitted work. Dr Mollan reported personal fees from Roche, Santen, Allergan, Santhera, and Chugai outside of the submitted work. Dr Sinclair reported grant NIHR-CS-011-028 from the NIHR Clinician Scientist Fellowship, grant MR/K015184/1 from the Medical Research Council, and Registered Charity in England and Wales grant 1143522 and Scotland grant SCO43294 from the Idiopathic Intracranial Hypertension UK Charity. No other disclosures were reported.

Markey  KA, Mollan  SP, Jensen  RH, Sinclair  AJ.  Understanding idiopathic intracranial hypertension: mechanisms, management, and future directions.  Lancet Neurol. 2016;15(1):78-91. doi:10.1016/S1474-4422(15)00298-7PubMedGoogle ScholarCrossref
Mulla  Y, Markey  KA, Woolley  RL, Patel  S, Mollan  SP, Sinclair  AJ.  Headache determines quality of life in idiopathic intracranial hypertension.  J Headache Pain. 2015;16:521. doi:10.1186/s10194-015-0521-9PubMedGoogle ScholarCrossref
Mollan  S, Aguiar  M, Evison  F, Frew  E, Sinclair  AJ.  The expanding burden of idiopathic intracranial hypertension.  Eye (Lond). 2019;33(3):478-485. doi:10.1038/s41433-018-0238-5PubMedGoogle Scholar
Friedman  DI, Liu  GT, Digre  KB.  Revised diagnostic criteria for the pseudotumor cerebri syndrome in adults and children.  Neurology. 2013;81(13):1159-1165. doi:10.1212/WNL.0b013e3182a55f17PubMedGoogle ScholarCrossref
Mollan  SP, Davies  B, Silver  NC,  et al.  Consensus guidance for adult idiopathic intracranial hypertension.  J Neurol Neurosurg Psychiatry. 2018;89(10):1088-1100. doi:10.1136/jnnp-2017-317440Google Scholar
Mollan  SP, Ali  F, Hassan-Smith  G, Botfield  H, Friedman  DI, Sinclair  AJ.  Evolving evidence in adult idiopathic intracranial hypertension: pathophysiology and management.  J Neurol Neurosurg Psychiatry. 2016;87(9):982-992. doi:10.1136/jnnp-2015-311302PubMedGoogle ScholarCrossref
Daniels  AB, Liu  GT, Volpe  NJ,  et al.  Profiles of obesity, weight gain, and quality of life in idiopathic intracranial hypertension (pseudotumor cerebri).  Am J Ophthalmol. 2007;143(4):635-641. doi:10.1016/j.ajo.2006.12.040PubMedGoogle ScholarCrossref
Guh  DP, Zhang  W, Bansback  N, Amarsi  Z, Birmingham  CL, Anis  AH.  The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis.  BMC Public Health. 2009;9:88. doi:10.1186/1471-2458-9-88PubMedGoogle ScholarCrossref
Lu  Y, Hajifathalian  K, Ezzati  M, Woodward  M, Rimm  EB, Danaei  G; Global Burden of Metabolic Risk Factors for Chronic Diseases Collaboration (BMI Mediated Effects).  Metabolic mediators of the effects of body-mass index, overweight, and obesity on coronary heart disease and stroke: a pooled analysis of 97 prospective cohorts with 1.8 million participants.  Lancet. 2014;383(9921):970-983. doi:10.1016/S0140-6736(13)61836-XPubMedGoogle ScholarCrossref
Fontana  L, Hu  FB.  Optimal body weight for health and longevity: bridging basic, clinical, and population research.  Aging Cell. 2014;13(3):391-400. doi:10.1111/acel.12207PubMedGoogle ScholarCrossref
O’Reilly  MW, Westgate  CSJ, Hornby  C,  et al.  A unique androgen excess signature in idiopathic intracranial hypertension is linked to cerebrospinal fluid dynamics.  JCI Insight. 2019;4(6):e125348. doi:10.1172/jci.insight.125348PubMedGoogle Scholar
Ding  EL, Song  Y, Malik  VS, Liu  S.  Sex differences of endogenous sex hormones and risk of type 2 diabetes: a systematic review and meta-analysis.  JAMA. 2006;295(11):1288-1299. doi:10.1001/jama.295.11.1288PubMedGoogle ScholarCrossref
Dalmasso  C, Maranon  R, Patil  C,  et al.  Cardiometabolic effects of chronic hyperandrogenemia in a new model of postmenopausal polycystic ovary syndrome.  Endocrinology. 2016;157(7):2920-2927. doi:10.1210/en.2015-1617PubMedGoogle ScholarCrossref
Azziz  R, Carmina  E, Dewailly  D,  et al; Androgen Excess Society.  Positions statement: criteria for defining polycystic ovary syndrome as a predominantly hyperandrogenic syndrome: an Androgen Excess Society guideline.  J Clin Endocrinol Metab. 2006;91(11):4237-4245. doi:10.1210/jc.2006-0178PubMedGoogle ScholarCrossref
Morgan  CL, Jenkins-Jones  S, Currie  CJ, Rees  DA.  Evaluation of adverse outcome in young women with polycystic ovary syndrome versus matched, reference controls: a retrospective, observational study.  J Clin Endocrinol Metab. 2012;97(9):3251-3260. doi:10.1210/jc.2012-1690PubMedGoogle ScholarCrossref
Mani  H, Levy  MJ, Davies  MJ,  et al.  Diabetes and cardiovascular events in women with polycystic ovary syndrome: a 20-year retrospective cohort study.  Clin Endocrinol (Oxf). 2013;78(6):926-934. doi:10.1111/cen.12068PubMedGoogle ScholarCrossref
Randeva  HS, Tan  BK, Weickert  MO,  et al.  Cardiometabolic aspects of the polycystic ovary syndrome.  Endocr Rev. 2012;33(5):812-841. doi:10.1210/er.2012-1003PubMedGoogle ScholarCrossref
General Practitioners Committee. NHS Employers and NHS England. 2016/17 General Medical Services (GMS) Contract Quality and Outcomes Framework (QOF) Guidance for GMS Contract 2016/17. https://www.http://nhsemployers.org/-/media/Employers/Documents/Primary-care-contracts/QOF/2016-17/2016-17-QOF-guidance-documents.pdf. Published April 2016. Accessed May 31, 2019.
Doran  T, Fullwood  C, Gravelle  H,  et al.  Pay-for-performance programs in family practices in the United Kingdom.  N Engl J Med. 2006;355(4):375-384. doi:10.1056/NEJMsa055505PubMedGoogle ScholarCrossref
Lewis  JD, Schinnar  R, Bilker  WB, Wang  X, Strom  BL.  Validation studies of the health improvement network (THIN) database for pharmacoepidemiology research.  Pharmacoepidemiol Drug Saf. 2007;16(4):393-401. doi:10.1002/pds.1335PubMedGoogle ScholarCrossref
Lévesque  LE, Hanley  JA, Kezouh  A, Suissa  S.  Problem of immortal time bias in cohort studies: example using statins for preventing progression of diabetes.  BMJ. 2010;340:b5087. doi:10.1136/bmj.b5087PubMedGoogle ScholarCrossref
NHS Digital. Business Rules for Quality and Outcomes Framework (QOF)2017/18. Secondary Prevention of Coronary Heart Disease (CHD). Leeds, England: NHS Digital; 2017.
Adams  J, Ryan  V, White  M.  How accurate are Townsend deprivation scores as predictors of self-reported health? a comparison with individual level data.  J Public Health (Oxf). 2005;27(1):101-106. doi:10.1093/pubmed/fdh193PubMedGoogle ScholarCrossref
Frič  R, Pripp  AH, Eide  PK.  Cardiovascular risk factors in Chiari malformation and idiopathic intracranial hypertension.  Brain Behav. 2017;7(5):e00677. doi:10.1002/brb3.677PubMedGoogle ScholarCrossref
Best  J, Silvestri  G, Burton  B, Foot  B, Acheson  J.  The incidence of blindness due to idiopathic intracranial hypertension in the UK.  Open Ophthalmol J. 2013;7(7):26-29. doi:10.2174/1874364101307010026PubMedGoogle ScholarCrossref
Bigal  ME, Kurth  T, Santanello  N,  et al.  Migraine and cardiovascular disease: a population-based study.  Neurology. 2010;74(8):628-635. doi:10.1212/WNL.0b013e3181d0cc8bPubMedGoogle ScholarCrossref
Yiangou  A, Mitchell  J, Markey  KA,  et al.  Therapeutic lumbar puncture for headache in idiopathic intracranial hypertension: minimal gain, is it worth the pain?  Cephalalgia. 2019;39(2):245-253. doi:10.1177/0333102418782192PubMedGoogle Scholar
Canoy  D, Luben  R, Welch  A,  et al.  Fat distribution, body mass index and blood pressure in 22,090 men and women in the Norfolk cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Norfolk) study.  J Hypertens. 2004;22(11):2067-2074. doi:10.1097/00004872-200411000-00007PubMedGoogle ScholarCrossref
Yusuf  S, Hawken  S, Ounpuu  S,  et al; INTERHEART Study Investigators.  Obesity and the risk of myocardial infarction in 27,000 participants from 52 countries: a case-control study.  Lancet. 2005;366(9497):1640-1649. doi:10.1016/S0140-6736(05)67663-5PubMedGoogle ScholarCrossref
Grundy  SM, Adams-Huet  B, Vega  GL.  Variable contributions of fat content and distribution to metabolic syndrome risk factors.  Metab Syndr Relat Disord. 2008;6(4):281-288. doi:10.1089/met.2008.0026PubMedGoogle ScholarCrossref
Hornby  C, Botfield  H, O’Reilly  MW,  et al.  Evaluating the fat distribution in idiopathic intracranial hypertension using dual-energy X-ray absorptiometry scanning.  Neuroophthalmology. 2017;42(2):99-104. doi:10.1080/01658107.2017.1334218PubMedGoogle ScholarCrossref
Sinclair  AJ, Burdon  MA, Nightingale  PG,  et al.  Low energy diet and intracranial pressure in women with idiopathic intracranial hypertension: prospective cohort study.  BMJ. 2010;341:c2701. doi:10.1136/bmj.c2701PubMedGoogle ScholarCrossref
NCD Risk Factor Collaboration (NCD-RisC).  Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19.2 million participants.  Lancet. 2016;387(10026):1377-1396. doi:10.1016/S0140-6736(16)30054-XPubMedGoogle ScholarCrossref
Kilgore  KP, Lee  MS, Leavitt  JA,  et al.  Re-evaluating the incidence of idiopathic intracranial hypertension in an era of increasing obesity.  Ophthalmology. 2017;124(5):697-700. doi:10.1016/j.ophtha.2017.01.006PubMedGoogle ScholarCrossref
Curry  WT  Jr, Butler  WE, Barker  FG  II.  Rapidly rising incidence of cerebrospinal fluid shunting procedures for idiopathic intracranial hypertension in the United States, 1988-2002.  Neurosurgery. 2005;57(1):97-108. doi:10.1227/01.NEU.0000163094.23923.E5PubMedGoogle ScholarCrossref
Marmot  M.  Social determinants of health inequalities.  Lancet. 2005;365(9464):1099-1104. doi:10.1016/S0140-6736(05)74234-3PubMedGoogle ScholarCrossref
Wilkinson  R, Marmot  M, eds. Social Determinants of Health: The Solid Facts. 2nd edition. Geneva, Switzerland: World Health Organization; 2003:31.
Pickett  KE, Pearl  M.  Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review.  J Epidemiol Community Health. 2001;55(2):111-122. doi:10.1136/jech.55.2.111PubMedGoogle ScholarCrossref
Phillimore  P, Beattie  A, Townsend  P.  Widening inequality of health in northern England, 1981-91.  BMJ. 1994;308(6937):1125-1128. doi:10.1136/bmj.308.6937.1125PubMedGoogle ScholarCrossref
Barnett  K, Mercer  SW, Norbury  M, Watt  G, Wyke  S, Guthrie  B.  Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.  Lancet. 2012;380(9836):37-43. doi:10.1016/S0140-6736(12)60240-2PubMedGoogle ScholarCrossref
Herman  WH, Ye  W, Griffin  SJ,  et al.  Early detection and treatment of type 2 diabetes reduce cardiovascular morbidity and mortality: a simulation of the results of the Anglo-Danish-Dutch Study of Intensive Treatment in People With Screen-Detected Diabetes in Primary Care (ADDITION-Europe).  Diabetes Care. 2015;38(8):1449-1455. doi:10.2337/dc14-2459PubMedGoogle ScholarCrossref
Feldman  AL, Griffin  SJ, Fhärm  E,  et al.  Screening for type 2 diabetes: do screen-detected cases fare better?  Diabetologia. 2017;60(11):2200-2209. doi:10.1007/s00125-017-4402-4PubMedGoogle ScholarCrossref
Ottridge  R, Mollan  SP, Botfield  H,  et al.  Randomised controlled trial of bariatric surgery versus a community weight loss programme for the sustained treatment of idiopathic intracranial hypertension: the Idiopathic Intracranial Hypertension Weight Trial (IIH:WT) protocol.  BMJ Open. 2017;7(9):e017426. doi:10.1136/bmjopen-2017-017426PubMedGoogle ScholarCrossref
Hall  GC.  Validation of death and suicide recording on the THIN UK primary care database.  Pharmacoepidemiol Drug Saf. 2009;18(2):120-131. doi:10.1002/pds.1686PubMedGoogle ScholarCrossref
Seminara  NM, Abuabara  K, Shin  DB,  et al.  Validity of The Health Improvement Network (THIN) for the study of psoriasis.  Br J Dermatol. 2011;164(3):602-609.PubMedGoogle Scholar
Cooper  AR, Page  A, Fox  KR, Misson  J.  Physical activity patterns in normal, overweight and obese individuals using minute-by-minute accelerometry.  Eur J Clin Nutr. 2000;54(12):887-894. doi:10.1038/sj.ejcn.1601116PubMedGoogle ScholarCrossref
Chen  Y, Mao  Y.  Obesity and leisure time physical activity among Canadians.  Prev Med. 2006;42(4):261-265. doi:10.1016/j.ypmed.2006.01.006PubMedGoogle ScholarCrossref
Diaz  KM, Shimbo  D.  Physical activity and the prevention of hypertension.  Curr Hypertens Rep. 2013;15(6):659-668. doi:10.1007/s11906-013-0386-8PubMedGoogle ScholarCrossref
Heymsfield  SB, Gonzalez  MC, Lu  J, Jia  G, Zheng  J.  Skeletal muscle mass and quality: evolution of modern measurement concepts in the context of sarcopenia.  Proc Nutr Soc. 2015;74(4):355-366. doi:10.1017/S0029665115000129PubMedGoogle ScholarCrossref
Park  J, Ishikawa-Takata  K, Tanaka  S,  et al.  Relation of body composition to daily physical activity in free-living Japanese adult women.  Br J Nutr. 2011;106(7):1117-1127. doi:10.1017/S0007114511001358PubMedGoogle ScholarCrossref
Park  J, Ishikawa-Takata  K, Tanaka  S,  et al.  The relationship of body composition to daily physical activity in free-living Japanese adult men.  Br J Nutr. 2014;111(1):182-188. doi:10.1017/S0007114513001918PubMedGoogle ScholarCrossref
If you are not a JN Learning subscriber, you can either:
Subscribe to JN Learning for one year
Buy this activity
If you are not a JN Learning subscriber, you can either:
Subscribe to JN Learning for one year
Buy this activity
With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right

Name Your Search

Save Search
With a personal account, you can:
  • Track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience

Lookup An Activity


My Saved Searches

You currently have no searches saved.

With a personal account, you can:
  • Access free activities and track your credits
  • Personalize content alerts
  • Customize your interests
  • Fully personalize your learning experience
Education Center Collection Sign In Modal Right
State Requirements