A Network Analysis of Cardiovascular Risk Factors in Patients With Heart Disease: The Role of Socioeconomic Status and Sex.
Journal
Psychosomatic medicine
ISSN: 1534-7796
Titre abrégé: Psychosom Med
Pays: United States
ID NLM: 0376505
Informations de publication
Date de publication:
01 06 2023
01 06 2023
Historique:
medline:
1
6
2023
pubmed:
4
4
2023
entrez:
3
4
2023
Statut:
ppublish
Résumé
Diverse risk factors influence the development and prognosis of coronary heart disease (CHD) independently and mutually. Low socioeconomic status (SES) seems to exacerbate these risk factors' influences. In addition, sex differences have been identified for individual risk factors. Network analysis could provide in-depth insight into the interrelatedness of the risk factors, their predictability, and the moderating role of sex, to ultimately contribute to more refinement in prevention and cardiac rehabilitation. A total of 1682 participants (78% male; mean [standard deviation] age = 69.2 [10.6] years) with CHD completed questionnaires on psychosocial factors and health behaviors. Cardiometabolic data were retrieved through medical records. An SES index was created based on self-reported occupation, education, and area (i.e., postal code)-based median family income. Using R, we conducted a mixed graphical model network analysis on all risk factors combined with and without the moderating role of sex. SES belonged to the more influential risk factors with moderate to high levels of expected influence and degree centrality, indicating that it plays a considerable role in the risk factor network. When considering the moderating role of sex, relationships between SES and most risk factors were found to be stronger for women ( b = 0.06-0.48). The current study provided an insight into an interrelated network of psychosocial and medical risk factors among CHD patients. With SES belonging to the more influential risk factors and female sex influencing the strength of all the SES-risk factor relationships, cardiac rehabilitation and prevention techniques could be more refined by accounting for both influences.
Identifiants
pubmed: 37010207
doi: 10.1097/PSY.0000000000001196
pii: 00006842-202306000-00006
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
417-430Informations de copyright
Copyright © 2023 by the American Psychosomatic Society.
Références
Piepoli MF, Hoes AW, Agewall S, Albus C, Brotons C, Catapano AL. 2016 European Guidelines on cardiovascular disease prevention in clinical practice: The Sixth Joint Task Force of the European Society of Cardiology and Other Societies on Cardiovascular Disease Prevention in Clinical Practice (constituted by representatives of 10 societies and by invited experts) developed with the special contribution of the European Association for Cardiovascular Prevention & Rehabilitation (EACPR). Eur Heart J 2016;37:2315–81.
Ladwig KH, Lederbogen F, Albus C, Angermann C, Borggrefe M, Fischer D, et al. Position paper on the importance of psychosocial factors in cardiology: update 2013. Ger Med Sci 2014;12:Doc09.
Steptoe A, Kivimäki M. Stress and cardiovascular disease: an update on current knowledge. Annu Rev Public Health 2013;34:337–54.
Rozanski A, Blumenthal JA, Davidson KW, Saab PG, Kubzansky LD. The epidemiology, pathophysiology, and management of psychosocial risk factors in cardiac practice: the emerging field of behavioral cardiology. J Am Coll Cardiol 2005;45:637–51.
Hare DL, Toukhsati SR, Johansson P, Jaarsma T. Depression and cardiovascular disease: a clinical review. Eur Heart J 2014;35:1365–72.
Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, et al. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004;364:937–52.
von Känel R, Hari R, Schmid JP, Saner H, Begré S. Distress related to myocardial infarction and cardiovascular outcome: a retrospective observational study. BMC Psychiatry 2011;11:98.
Van Montfort E, Denollet J, Vermunt JK, Widdershoven J, Kupper N. The tense, the hostile and the distressed: multidimensional psychosocial risk profiles based on the ESC interview in coronary artery disease patients—the THORESCI study. Gen Hosp Psychiatry 2017;47:103–11.
Kupper N, Denollet J. Type D personality as a risk factor in coronary heart disease: a review of current evidence. Curr Cardiol Rep 2018;20:104.
Maser JD, Cloninger CR. Comorbidity of Mood and Anxiety Disorders. Washington, DC: American Psychiatric Association; 1990.
Suls J, Bunde J. Anger, anxiety, and depression as risk factors for cardiovascular disease: the problems and implications of overlapping affective dispositions. Psychol Bull 2005;60:627–36.
Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry 2005;62:617–27.
Watson D, Clark LA, Carey G. Positive and negative affectivity and their relation to anxiety and depressive disorders. J Abnorm Psychol 1988;97:346–53.
Van den Houdt SCM, Mommersteeg PMC, Widdershoven J, Kupper N. Sex and gender differences in psychosocial risk profiles among patients with coronary heart disease – the THORESCI-Gender study. Int J Behav Med 2023. In press.
Bonnet F, Irving K, Terra J-L, Nony P, Berthezène F, Moulin P. Anxiety and depression are associated with unhealthy lifestyle in patients at risk of cardiovascular disease. Art Ther 2005;178:339–44.
van den Berk-Clark C, Secrest S, Walls J, Hallberg E, Lustman PJ, Schneider FD, et al. Association between posttraumatic stress disorder and lack of exercise, poor diet, obesity, and co-occuring smoking: a systematic review and meta-analysis. Health Psychol 2018;37:407–16.
Ginty AT, Carroll D, Roseboom TJ, Phillips AC, de Rooij SR. Depression and anxiety are associated with a diagnosis of hypertension 5 years later in a cohort of late middle-aged men and women. J Hum Hypertens 2013;27:187–90.
Liu M-Y, Li N, Li WA, Khan H. Association between psychosocial stress and hypertension: a systematic review and meta-analysis. Neurol Res 2017;39:573–80.
Fisekovic Kremic MB. Factors associated with depression, anxiety and stress among patients with diabetes mellitus in primary health care: many questions, few answers. Malays Fam Physician 2020;15:54–61.
Kaur G, Tee GH, Ariaratnam S, Krishnapillai AS, China K. Depression, anxiety and stress symptoms among diabetics in Malaysia: a cross sectional study in an urban primary care setting. BMC Fam Pract 2013;14:69.
Bagherian-Sararoudi R, Sanei H, Attari A, Afshar H. Type D personality is associated with hyperlipidemia in patients with myocardial infarction. J Res Med Sci 2012;17:543–7.
Kahn EB, Ramsey LT, Brownson RC, Heath GW, Howze EH, Powell KE, et al. The effectiveness of interventions to increase physical activity. A systematic review. Am J Prev Med 2002;22:73–107.
Kaplan GA. Where do shared pathways lead? Some reflections on a research agenda. Psychosom Med 1995;57:208–12.
Schultz WM, Kelli HM, Lisko JC, Varghese T, Shen J, Sandesara P, et al. Socioeconomic status and cardiovascular outcomes. Circulation 2018;137:2166–78.
Businelle MS, Mills BA, Chartier KG, Kendzor DE, Reingle JM, Shuval K. Do stressful events account for the link between socioeconomic status and mental health? J Public Health 2014;36:205–12.
Gallo LC, Matthews KA. Understanding the association between socioeconomic status and physical health: do negative emotions play a role? Psychol Bull 2003;129:10–51.
McLeod JD, Kessler RC. Socioeconomic status differences in vulnerability to undesirable life events. J Health Soc Behav 1990;31:162–72.
Matthews KA, Raikkonen K, Everson SA, et al. Do the daily experiences of healthy men and women vary according to occupational prestige and work strain? Psychosom Med 2000;62:346–53.
Lantz PM, House JS, Mero RP, et al. Stress, life events, and socioeconomic disparities in health: results from the Americans’ changing lives study. J Health Soc Behav 2005;46:274–88.
Dedele A, Miskinyte A, Andrušaitytė S, Bartkute Z. Perceived stress among different occupational groups and the interaction with sedentary behaviour. Int J Environ Res Public Health 2019;16:4595.
Clougherty JE, Souza K, Cullen MR. Work and its role in shaping the social gradient in health. Ann N Y Acad Sci 2010;1186:102–24.
Chandola T, Britton A, Brunner E, Hemingway H, Malik M, Kumari M, et al. Work stress and coronary heart disease: what are the mechanisms? Eur Heart J 2008;29:640–8.
Wamala SP, Mittleman MA, Schenck-Gustafsson K, Orth-Gomer K. Potential explanations for the educational gradient in coronary heart disease: a population-based case-control study of Swedish women. Am J Public Health 1999;89:315–21.
Kaplan GA, Keil JE. Socioeconomic factors and cardiovascular disease: a review of the literature. Circulation 1993;88:1973–98.
Cockerham WC, Abel T, Lüschen G. Max Weber, formal rationality, and health lifestyles. Sociol Q 1993;34:413–28.
Nédo E, Paulik E. Association of smoking, physical activity, and dietary habits with socioeconomic variables: a cross-sectional study in adults on both sides of the Hungarian-Romanian border. BMC Public Health 2012;12.
Wang J, Geng L. Effects of socioeconomic status on physical and psychological health: lifestyle as a mediator. Int J Environ Res Public Health 2019;16:281.
Lee H, Park JH, Floyd JS, Park S, Kim HC. Combined effect of income and medication adherence on mortality in newly treated hypertension: nationwide study of 16 million person-years. J Am Heart Assoc 2019;8:e013148.
Krieger N. Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology. Am J Public Health 1992;82:703–10.
Leng B, Jin Y, Li G, Chen L, Jin N. Socioeconomic status and hypertension: a meta-analysis. J Hypertens 2015;33:221–9.
Woodward M, Peters SA, Batty GD, Ueshima H, Woo J, Giles GG, et al; Asia Pacific Cohort Studies Collaboration. Socioeconomic status in relation to cardiovascular disease and cause-specific mortality: a comparison of Asian and Australasian populations in a pooled analysis. BMJ Open 2015;5:e006408.
Alter DA, Iron K, Austin PC, Naylor CD; SESAMI Study Group. Socioeconomic status, service patterns, and perceptions of care among survivors of acute myocardial infarction in Canada. JAMA 2004;291:1100–7.
Yusuf S, Joseph P, Rangarajan S, Islam S, Mente A, Hystad P, et al. Modifiable risk factors, cardiovascular disease, and mortality in 155 722 individuals from 21 high-income, middle-income, and low-income countries (PURE): a prospective cohort study. Lancet 2020;395:795–808.
Lazzarino AI, Hamer M, Stamatakis E, Steptoe A. Low socioeconomic status and psychological distress as synergistic predictors of mortality from stroke and coronary heart disease. Psychosom Med 2013;75:311–6.
Jenkins KR, Ofstedal MB. The association between socioeconomic status and cardiovascular risk factors among middle-aged and older men and women. Women Health 2014;54:15–34.
Talaei M, Rabiei K, Talaei Z, Amiri N, Zolfaghari B, Kabiri P, et al. Physical activity, sex, and socioeconomic status: a population based study. ARYA Atheroscler 2013;9:51–60.
Shaw LJ, Merz CN, Bittner V, Kip K, Johnson BD, Reis SE, et al; WISE Investigators. Importance of socioeconomic status as a predictor of cardiovascular outcome and costs of care in women with suspected myocardial ischemia. Results from the National Institutes of Health, National Heart, Lung and Blood Institute-sponsored Women’s Ischemia Syndrome Evaluation (WISE). J Womens Health (Larchmt) 2008;17:1081–92.
Shanmugasegaram S, Oh P, Reid RD, McCumber T, Grace SL. Cardiac rehabilitation barriers by rurality and socioeconomic status: a cross-sectional study. Int J Equity Health 2013;12:72.
Samayoa L, Grace SL, Gravely S, Scott LB, Marzolini S, Colella TJ. Sex differences in cardiac rehabilitation enrollment: a meta-analysis. Can J Cardiol 2014;30:793–800.
Wenger NK. Current status of cardiac rehabilitation. J Am Coll Cardiol 2008;51:1619–31.
Hevey D. Network analysis: a brief overview and tutorial. Health Psychol Behav Med 2018;6:301–28.
Cramer AOJ, Waldorp LJ, Van der Maas HLJ, Borsboom D. Comorbidity: a network perspective. Behav Brain Sci 2010;33:137–50.
Borsboom D, Cramer AOJ. Network analysis: an integrative approach to the structure of psychopathology. Annu Rev Clin Psychol 2013;9:91–121.
Borsboom D. Psychometric perspectives on diagnostic systems. J Clin Psychol 2008;64:1089–109.
Haslbeck JMB, Waldorp LJ. How well do network models predict observations? On the importance of predictability in network models. Behav Res Methods 2018;50:853–61.
Hoorelbeke K, Van den Bergh N, Wichers M, Koster EHW. Between vulnerability and resilience: a network analysis of fluctuations in cognitive risk and protective factors following remission from depression. Behav Res Ther 2019;116:1–9.
van Borkulo C, Boschloo L, Borsboom D, Penninx BW, Waldorp LJ, Schoevers RA. Association of symptom network structure with the course of [corrected] depression. JAMA Psychiatry 2015;75:1219–26.
Senger K, Heider J, Kleinstäuber M, Sehlbrede M, Witthöft M, Schröder A. Network analysis of persistent somatic symptoms in two clinical patient samples. Psychosom Med 2022;84:74–85.
Hoang T, Lee J, Kim J. Network analysis of demographics, dietary intake, and comorbidity interactions. Nutrients 2021;13.
Visseren FLJ, Mach F, Smulders YM, Carballo D, Koskinas KC, Bäck M, et al. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J 2021;42:3227–337.
Borsboom D, Deserno MK, Rhemtulla M, Epskamp S, Fried EI, McNally RJ, et al. Network analysis of multivariate data in psychological science. Nat Rev Methods Primers 2021;1:58.
Luke DA, Harris JK. Network analysis in public health: history, methods, and applications. Annu Rev Public Health 2007;28:69–93.
Haslbeck JMB, Borsboom D, Waldorp LJ. Moderated network models. Multivar Behav Res 2021;56:256–87.
Hamburg MA, Collins FS. The path to personalized medicine. N Engl J Med 2010;363:301–4.
Barabási AL. The network takeover. Nat Phys 2012;8:14–6.
van Montfort E, Denollet J, Widdershoven J, Kupper N. Validity of the European Society of Cardiology’s psychosocial screening interview in patients with coronary artery disease—the THORESCI study. Psychosom Med 2017;79:404–15.
Kroenke K, Spitzer RL, Williams JBW. The PHQ-9—validity of a brief depression severity measure. J Gen Intern Med 2001;16:606–13.
Spitzer RL, Kroenke K, Williams JB, Löwe B. A brief measure for assessing generalized anxiety disorder: the GAD-7. Arch Intern Med 2006;166:1092–7.
Denollet J. DS14: standard assessment of negative affectivity, social inhibition, and type D personality. Psychosom Med 2005;67:89–97.
Keller A, Litzelman K, Wisk LE, Maddox T, Cheng ER, Creswell PD, et al. Does the perception that stress affects health matter? The association with health and mortality. Health Psychol 2012;31:677–84.
Doedee F, Van den Houdt S, Widdershoven J, Kupper N. Chronic stress exposure in men and women, and implications for the course of fatigue after percutaneous coronary intervention; the THORESCI study. Gen Hosp Psychiatry 2021;72:45–52.
Garnefski N, Kraaij V. Levensgebeurtenissen Vragenlijst. 2001. Available at: http://www.cerq.leidenuniv.nl/ .
Williams RB Jr., Haney TL, Lee KL, Kong YH, Blumenthal JA, Whalen RE. Type a behavior, hostility, and coronary atherosclerosis. Psychosom Med 1980;42:539–49.
Cook WW, Medley DM. Proposed hostility and pharisaic-virtue scales for the MMPI. J Appl Psychol 1954;38:414–8.
Wong JM, Sin NL, Whooley MA. A comparison of Cook-Medley hostility subscales and mortality in patients with coronary heart disease: data from the heart and soul study. Psychosom Med 2014;76:311–7.
Smith TW, Glazer K, Ruiz JM, Gallo LC. Hostility, anger, aggressiveness, and coronary heart disease: an interpersonal perspective on personality, emotion, and health. J Pers 2004;72:1217–70.
Cabrera JC, Karl SR, Roohr KC, Klieger DM, Rodriguez MC, editors. Asking About Socioeconomic Status Differently: Effects on Classification and Inferences. Trumbell, CT: Northeastern Educational Research Association; 2014.
Cirino PT, Chin CE, Sevcik RA, Wolf M, Lovett M, Morris RD. Measuring socioeconomic status: reliability and preliminary validity for different approaches. Assessment 2002;9:145–55.
Mueller CW, Parcel TL. Measures of socioeconomic status: alternatives and recommendations. Child Dev 1981;52:13–30.
Wheeler DC, Czarnota J, Jones RM. Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence. PloS One 2017;12:e0179272.
Darin-Mattsson A, Fors S, Kåreholt I. Different indicators of socioeconomic status and their relative importance as determinants of health in old age. Int J Equity Health 2017;16:173.
Winkleby MA, Cubbin C. Influence of individual and neighbourhood socioeconomic status on mortality among black, Mexican-American, and White women and men in the United States. J Epidemiol Community Health 2003;57:444–52.
Central Bureau for Statistics. Kerncijfers per postcode. 2016. Available at: https://www.cbs.nl/nl-nl/dossier/nederland-regionaal/geografische-data/gegevens-per-postcode . Accessed September 1, 2021.
Boshuizen HC, Nusselder WN, Peters F, Verweij A. Index SES-verschillen in (gezonde) levensverwachting. Rijksinstituut voor Volksgezondheid en Milieu (RIVM), 2014 Contract No.: 2014-0034.
Dupre ME. Educational differences in age-related patterns of disease: reconsidering the cumulative disadvantage and age-as-leveler hypotheses. J Health Soc Behav 2007;48:1–15.
ILO. International Standard Classification of Occupations: ISCO-88. Geneva, Switzerland: ILO; 1990.
Bulmer M. Working-Class Images of Society (Routledge Revivals). Oxfordshire, England: Routledge; 2016.
de Prins P, Stuer D, de Vos A. Blue, white of grey collars: Hoe diep is het water wanneer het gaat om zinvol werk? Tijdschrift voor HRM. 2018:56–72.
Lips-Wiersma M, Wright S, Dik B. Meaningful work: differences among blue-, pink-, and white-collar occupations. Career Dev Int 2016;21:534–51.
Pickett KE, Pearl M. Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. J Epidemiol Community Health 2001;55:111–22.
Riva M, Gauvin L, Barnett TA. Toward the next generation of research into small area effects on health: a synthesis of multilevel investigations published since July 1998. J Epidemiol Community Health 2007;61:853–61.
IBM. IBM SPSS Statistics for Windows, Version 24.0. Armonk, NY: IBM; 2018.
Vergouwe Y, Royston P, Moons KGM, Altman DG. Development and validation of a prediction model with missing predictor data: a practical approach. J Clin Epidemiol 2010;63:205–14.
Wood AM, White IR, Royston P. How should variable selection be performed with multiply imputed data? Stat Med 2008;27:3227–46.
Beesley LJ, Taylor JMG. Accounting for not-at-random missingness through imputation stacking. Stat Med 2021;40:6118–32.
Wickham H, Miller E. Haven: import and export ‘SPSS’, ‘Stata’ and ‘SAS’ files. 2020.
Van Buuren S, Groothuis-Oudshoorn K. mice: multivariate imputation by chained equations in R. J Stat Softw 2011;45:1–67.
Haslbeck JMB, Waldorp LJ. mgm: estimating time-varying mixed graphical models in high-dimensional data. J Stat Softw 2020;93:1–46.
Epskamp S, Borsboom D, Fried EI. Estimating psychological networks and their accuracy: a tutorial paper. Behav Res Methods 2018;50:195–212.
Epskamp S, Cramer AOJ, Waldorp LJ, Schnittmann VD, Borsboom D. Qgraph: network visualizations of relationships in psychometric data. J Stat Softw 2012;48:1–18.
Li T, Levina E, Zhu J. Network cross-validation by edge sampling. Biometrika 2020;107:257–76.
Haslbeck JMB. Estimating group differences in network models using moderation analysis. Behav Res Methods 2022;54:522–40.
Zhang J, Luo Y. Degree centrality, betweenness centrality, and closeness centrality in social network. Adv Intell Syst Res 2017;132:300–3.
Van Buuren S. Flexible Imputation of Missing Data. London, United Kingdom: Chapman & Hall/CRC; 2018.
Haslbeck JMB. Moderated network models for continuous data. 2019.
Lawless MH, Harrison KA, Grandits GA, Eberly LE, Allen SS. Perceived stress and smoking-related behaviors and symptomatology in male and female smokers. Addict Behav 2015;51:80–3.
Fluharty M, Taylor AE, Grabski M, Munafò MR. The association of cigarette smoking with depression and anxiety: a systematic review. Nicotine Tob Res 2017;19:3–13.
Kotseva K, Wood D, De Bacquer D; EUROASPIRE Investigators. Determinants of participation and risk factor control according to attendance in cardiac rehabilitation programmes in coronary patients in Europe: EUROASPIRE IV survey. Eur J Prev Cardiol 2018;25:1242–51.
Brown TM, Hernandez AF, Bittner V, Cannon CP, Ellrodt G, Liang L, et al; American Heart Association Get With The Guidelines Investigators. Predictors of cardiac rehabilitation referral in coronary artery disease patients: findings from the American Heart Association’s get with the guidelines program. J Am Coll Cardiol 2009;54:515–21.
Sunamura M, Ter Hoeve N, Geleijnse ML, Steenaard RV, van den Berg-Emons HJG, Boersma H, van Domburg RT. Cardiac rehabilitation in patients who underwent primary percutaneous coronary intervention for acute myocardial infarction: determinants of programme participation and completion. Neth Heart J 2017;25:618–28.
Mikkelsen T, Korsgaard Thomsen K, Tchijevitch O. Non-attendance and drop-out in cardiac rehabilitation among patients with ischaemic heart disease. Dan Med J 2014;61:A4919.
Davies P, Taylor F, Beswick A, Wise F, Moxham T, Rees K, et al. Promoting patient uptake and adherence in cardiac rehabilitation. Cochrane Database Syst Rev 2010:CD007131.
Beswick AD, Rees K, Griebsch I, Taylor FC, Burke M, West RR, et al. Provision, uptake and cost of cardiac rehabilitation programmes: improving services to under-represented groups. Health Technol Assess 2004;8:1–152.
Meillier LK, Nielsen KM, Larsen FB, Larsen ML. Socially differentiated cardiac rehabilitation: can we improve referral, attendance and adherence among patients with first myocardial infarction? Scand J Public Health 2012;40:286–93.
Gaalema DE, Cutler AY, Higgins ST, Ades PA. Smoking and cardiac rehabilitation participation: associations with referral, attendance and adherence. Prev Med 2015;80:67–74.
Wilson K, Gibson N, Willan A, Cook D. Effect of smoking cessation on mortality after myocardial infarction: meta-analysis of cohort studies. Arch Intern Med 2000;160:939–44.
Asthana A, Piper ME, McBride PE, Ward A, Fiore MC, Baker TB, et al. Long-term effects of smoking and smoking cessation on exercise stress testing: three-year outcomes from a randomized clinical trial. Am Heart J 2012;163:81–7.
Weinberger AH, Mazure CM, McKee SA, Caulin-Glaser T. The association of tobacco use and gender to cardiac rehabilitation outcomes: a preliminary investigation. J Subst Use 2014;19:171–5.
Cosci F, Schruers KR, Pistelli F, Griez EJ. Negative affectivity in smokers applying to smoking cessation clinics: a case-control study. Depress Anxiety 2008;26:824–30.
Sohlberg T, Bergmark KH. Lifestyle and long-term smoking cessation. Tob Use Insights 2020;13:1179173X2096306.
Garnefski N, Kraaij V, Spinhoven P. Negative life events, cognitive emotion regulation and emotional problems. Personal Individ Differ 2001;30:1311–27.
Van Ingen E, Utz S, Toepoel V. Online coping after negative life events: measurement, prevalence, and relation with internet activities and well-being. Soc Sci Comput Rev 2016;34.
Mamataz T, Ghisi GLM, Pakosh M, Grace SL. Nature, availability, and utilization of women-focused cardiac rehabilitation: a systematic review. BMC Cardiovasc Disord 2021;21:459.
Damen NL, Versteeg H, Serruys PW, van Geuns RJ, van Domburg RT, Pedersen SS, et al. Cardiac patients who completed a longitudinal psychosocial study had a different clinical and psychosocial baseline profile than patients who dropped out prematurely. Eur J Prev Cardiol 2015;22:196–9.
Kawai H, Ejiri M, Tsuruta H, Masui Y, Watanabe Y, Hirano H, et al. Factors associated with follow-up difficulty in longitudinal studies involving community-dwelling older adults. PLoS One 2020;15:e0237166.
Heer T, Hochadel M, Schmidt K, Mehilli J, Zahn R, Kuck KH, et al. Sex differences in percutaneous coronary intervention—insights from the Coronary Angiography and PCI Registry of the German Society of Cardiology. J Am Heart Assoc 2017;6:e004972.
Heer T, Schiele R, Schneider S, Gitt AK, Wienbergen H, Gottwik M, et al. Gender differences in acute myocardial infarction in the era of reperfusion (the MITRA Registry). Am J Cardiol 2002;89:511–7.
Heer T, Gitt AK, Juenger C, Schiele R, Wienbergen H, Towae F, et al; ACOS Investigators. Gender differences in acute non–ST-segment elevation myocardial infarction. Am J Cardiol 2006;98:160–6.
Daly C, Clemens F, Lopez Sendon JL, Tavazzi L, Boersma E, Danchin N, et al; Euro Heart Survey Investigators. Gender differences in the management and clinical outcome of stable angina. Circulation 2006;113:490–8.