Estructura de comunidades en las redes semánticas de la investigación biomédica sobre disparidades en salud y sexismo
Resumen
Introducción. Como una iniciativa para mejorar la calidad de la atención sanitaria, en la investigación biomédica se ha incrementado la tendencia centrada en el estudio de las disparidades en salud y sexismo.
Objetivo. Caracterizar la evidencia científica sobre la disparidad en salud definida como la brecha existente entre la distribución de la salud y el posible sesgo por sexo en el acceso a los servicios médicos.
Materiales y métodos. Se hizo una búsqueda simultánea de la literatura científica en la base de datos Medline PubMed de dos descriptores fundamentales: Healthcare disparities y Sexism. Posteriormente, se construyó una red semántica principal y se determinaron algunas subunidades estructurales (comunidades) para el análisis de los patrones de organización de la información. Se utilizó el programa de código abierto Cytoscape para el analisis y la visualización de las redes y el MapEquation, para la detección de comunidades. Asimismo, se desarrolló código ex profeso disponible en un repositorio de acceso público.
Resultados. El corpus de la red principal mostró que los términos sobre las enfermedades del corazón fueron los descriptores de condiciones médicas más concurrentes. A partir de las subunidades estructurales, se determinaron los patrones de información relacionada con las políticas públicas, los servicios de salud, los factores sociales determinantes y los factores de riesgo, pero con cierta tendencia a mantenerse indirectamente conectados con los nodos relacionados con condiciones médicas.
Conclusiones. La evidencia científica indica que la disparidad por sexo sí importa para la calidad de la atención de muchas enfermedades, especialmente aquellas relacionadas con el sistema circulatorio. Sin embargo, aún se percibe un distanciamiento entre los factores médicos y los sociales que dan lugar a las posibles disparidades por sexo.
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Referencias bibliográficas
Payne S. The health of women and girls: How can we address gender equality and gender equity? Semin Reprod Med. 2015;33:53-60. https://doi.org/10.1055/s-0034-1395280
Davies SE, Harman S, Manjoo R, Tanyag M, Wenham C. Why it must be a feminist global health agenda. Lancet. 2019;393:601-3. https://doi.org/10.1016/S0140-6736(18)32472-3
Schopper M, Irnich D. Gender and its implications for cardiothoracic perioperative care and anesthesia. Thorac Cardiovasc Surg. 2013;61:7-14. https://doi.org/10.1055/s-0032-1331038
Glymour MM, Spiegelman D. Evaluating public health interventions: 5. Causal inference in public health research - Do sex, race, and biological factors cause health outcomes? Am J Public Health. 2017;107:81-5. https://doi.org/10.2105/AJPH.2016.303539
Stewart M, Kushner KE, Gray J, Hart DA. Promoting gender equity through health research: Impacts and insights from a Canadian initiative. Glob Health Promot. 2013;20:25-38. https://doi.org/10.1177/1757975913476903
Heidari S, Babor TF, De Castro P, Tort S, Curno M. Sex and gender equity in research: Rationale for the SAGER guidelines and recommended use. Res Integr Peer Rev. 2016;1:2. https://doi.org/10.1186/s41073-016-0007-6
Potterat MM, Monnin Y, Pechère A, Guessous I. Women, forgotten by clinical research. Rev Med Suisse. 2015;11:1733-6.
Hamberg K. Gender bias in medicine. Womens Health. 2008;4:237-43. https://doi.org/10.2217/17455057.4.3.237
Sugimoto CR, Ahn YY, Smith E, Macaluso B, Larivière V. Factors affecting sex-related reporting in medical research: A cross-disciplinary bibliometric analysis. Lancet. 2019;393:550-9. https://doi.org/10.1016/S0140-6736(18)32995-7
Ward PR, Meyer SB, Verity F, Gill TK, Luong TC. Complex problems require complex solutions: The utility of social quality theory for addressing the Social Determinants of Health. BMC Public Health. 2011;11:630. https://doi.org/10.1186/1471-2458-11-630
Diderichsen F, Evans T, Whitehead M. Bases sociales de las disparidades en salud. En: Evans T, editor. Desafío a la falta de equidad en la salud. Washington: OPS/Fundación Rockefeller; 2002. p.13-26,185-205.
Sen G, George A, Östlin P. The case for gender equity in health research. J Health Manag. 2002;4:99-117.
Sakaguchi AM. Health equities worldwide. J Health Polit Policy Law. 2003;28:552-6.
Graham H. Unequal lives: Health and socioeconomic inequalities. Maidenhead: McGraw-Hill Education; 2007. p. 82-113.
Golden TL, Wendel ML. Public health’s next step in advancing equity: Re-evaluating epistemological assumptions to move social determinants from theory to practice. Front Public Health. 2020;8:131. https://doi.org/10.3389/fpubh.2020.00131
Piccini P, Montagnani C, de Martino M. Gender disparity in pediatrics: A review of the current literature. Ital J Pediatr. 2018;44:1-6 https://doi.org/10.1186/s13052-017-0437-x
Martínez-García M, Salinas-Ortega M, Estrada-Arriaga I, Hernández-Lemus E, García-Herrera R, Vallejo M. A systematic approach to analyze the social determinants of cardiovascular disease. PLoS ONE. 2018;13:e0190960. https://doi.org/10.1371/journal.pone.0190960
Martínez-García M, Vallejo M, Hernández-Lemus E, Álvarez-Díaz JA. Novel methods of qualitative analysis for health policy research. Health Res Policy Syst. 2019;17:6. https://doi.org/10.1186/s12961-018-0404-z
Perl Y, Chen Z, Halper M, Geller J, Zhang L, Peng Y. The cohesive metaschema: A higherlevel abstraction of the UMLS Semantic Network. J Biomed Inform. 2002;35:194-212. https://doi.org/10.1016/s1532-0464(02)00528-2
Siqueiros-García JM, Hernández-Lemus E, García-Herrera R, Robina-Galatas A. Mapping the structure and dynamics of genomics-related MeSH terms complex networks. PLoS ONE. 2014;9:e92639. https://doi.org/10.1371/journal.pone.0092639
Barabási AL. Network science. Cambridge, UK: Cambridge University Press; 2016. p. 45-50.
Tang L, Bie B, Zhi D. Tweeting about measles during stages of an outbreak: A semantic network approach to the framing of an emerging infectious disease. Am J Infect Control. 2018;46:1375-80. https://doi.org/10.1016/j.ajic.2018.05.019
Utsumi A. A complex network approach to distributional semantic models. PLoS ONE. 2015;10:e0136277. https://doi.org/10.1371/journal.pone.0136277
Theodosiou T, Vizirianakis IS, Angelis L, Tsaftaris A, Darzentas N. MeSHy: Mining unanticipated PubMed information using frequencies of occurrences and concurrences of MeSH terms. J Biomed Inform. 2011;44:919-926. https://doi.org/10.1016/j.jbi.2011.05.009
Yang H, Lee HJ. Research trend visualization by MeSH terms from PubMed. Int J Environ Res Public Health. 2018;15:1113. https://doi.org/10.3390/ijerph15061113
Zhang H, Fiszman M, Shin D, Miller CM, Rosemblat G, Rindflesch TC. Degree centrality for semantic abstraction summarization of therapeutic studies. J Biomed Inform. 2011;44:830-8. https://doi.org/10.1016/j.jbi.2011.05.001
Ruiz JB, Barnett GA. Exploring the presentation of HPV information online: A semantic network analysis of websites. Vaccine. 2015;33:3354-9. https://doi.org/10.1016/j.vaccine.2015.05.017
Zemla JC, Austerweil JL. Modeling semantic fluency data as search on a semantic network. Cogsci. 2017;2017:3646-51.
Kohl M, Wiese S, Warscheid B. Cytoscape: Software for visualization and analysis of biological networks. Methods Mol Biol. 2011;696:291-303. https://doi.org/10.1007/978-1-60761-987-1_18
Alcalá-Corona SA, Espinal-Enríquez J, de Anda-Jáuregui G, Hernández-Lemus E. The Hierarchical Modular Structure of HER2+ Breast Cancer Network. Front Physiol. 2018;9:1423. https://doi.org/10.3389/fphys.2018.01423
Alcalá-Corona SA, de Anda-Jáuregui G, Espinal-Enríquez J, Tovar H, Hernández-Lemus E. Network modularity and hierarchical structure in breast cancer molecular subtypes. En: Morales A, Gershenson C, Braha D, Minai A, Bar-Yam Y, editors. Unifying themes in complex systems IX. Springer Proceedings in Complexity. Cambridge: Springer International Publishing; 2018. p. 352-8.
Riolo MA, Newman MEJ. Consistency of community structure in complex networks. Physical Review E. 2020;101.5:052306.
Rosvall M, Bergstrom CT. Maps of random walks on complex networks reveal community structure. Proc Natl Acad Sci USA. 2008;105:1118-23. https://doi.org/10.1073/pnas.0706851105
Bohlin L, Edler D, Lancichinetti A, Rosvall M. Community detection and visualization of networks with the map equation framework. En: Ding Y, Rousseau R, Wolfram D, editors. Measuring Scholarly Impact. Cambridge: Springer International Publishing; 2014. p. 3–34.
Rosvall M, Axelsson D, Bergstrom CT. The map equation. Eur Phys J Spec Top. 2009;178:13-23. https://doi.org/10.1140/epjst/e2010-01179-1
Renganathan V. Text mining in biomedical domain with emphasis on document clustering. Healthc Inform Res. 2017;23:141-6. https://doi.org/10.4258/hir.2017.23.3.141
Simon C, Davidsen K, Hansen C, Seymour E, Barnkob MB, Olsen LR. BioReader: A text mining tool for performing classification of biomedical literature. BMC Bioinformatics. 2019;19(Suppl.13):57. https://doi.org/10.1186/s12859-019-2607-x
Araújo C, Pereira M, Laszczyńska O, Dias P, Azevedo A. Sex-related inequalities in management of patients with acute coronary syndrome-results from the EURHOBOP study. Int J Clin Pract. 2018;72:1-10. https://doi.org/10.1111/ijcp.13049
Nestler DM, Gilani WI, Anderson RT, Bellolio MF, Branda ME, LeBlanc A, et al. Does gender bias in cardiac stress testing still exist? A videographic analysis nested in a randomized controlled trial. Am J Emerg Med. 2017;35:29-35. https://doi.org/10.1016/j.ajem.2016.09.054
Jortveit J, Govatsmark RE, Langørgen J, Hole T, Mannsverk J, Olsen S, et al. Gender differences in the assessment and treatment of myocardial infarction. Tidsskr Nor Laegeforen. 2016;136:1215-22. https://doi.org/10.4045/tidsskr.16.0224
Aaberge L. Equal treatment for myocardial infarction patients? Likeverdig behandling ved hjerteinfarkt? Tidsskr Nor Laegeforen. 2016;136:1181. https://doi.org/10.4045/tidsskr.16.0532
Leurent G, Garlantézec R, Auffret V, Hacot JP, Coudert I, Filippi E, et al. Gender differences in presentation, management and inhospital outcome in patients with ST-segment elevation myocardial infarction: Data from 5000 patients included in the ORBI prospective French regional registry. Arch Cardiovasc Dis. 2014;107:291-8.
https://doi.org/10.1016/j.acvd.2014.04.005
Rosen SE, Henry S, Bond R, Pearte C, Mieres JH. Sex-specific disparities in risk factors for coronary heart disease. Curr Atheroscler Rep. 2015;17:49. https://doi.org/10.1007/s11883-015-0523-8
Woodward M. Cardiovascular disease and the female disadvantage. Int J Environ Res Public Health. 2019;16:1165. https://doi.org/10.3390/ijerph16071165
Humphries K, Izadnegahdar M, Sedlak T, Saw J, Johnston N, Schenck-Gustafsson K, et al. Sex differences in cardiovascular disease-Impact on care and outcomes. Front Neuroendocrinol. 2017;46:46-70. https://doi.org/10.1016/j.yfrne.2017.04.001
Kane AE, Howlett SE. Differences in cardiovascular aging in men and women. Adv Exp Med Biol. 2018;1065:389-411. https://doi.org/10.1007/978-3-319-77932-4_25
Lundberg GP, Mehta LS, Sanghani RM, Patel HN, Aggarwal NR, Aggarwalet NT, et al. Heart centers for women: Historical perspective on formation and future strategies to reduce cardiovascular disease. Circulation. 2018;138:1155-65. https://doi.org/10.1161/CIRCULATIONAHA.118.035351
Goss PE, Strasser-Weippl K, Lee-Bychkovsky BL, Fan L, Li J, Chavarri-Guerra Y, et al. Challenges to effective cancer control in China, India, and Russia. Lancet Oncol. 2014;15:489-538. https://doi.org/10.1016/S1470-2045(14)70029-4
Thiels CA, Holst KA, Ubl DS, McKenzie TJ, Zielinski MD, Farley DR, et al. Gender disparities in the utilization of laparoscopic groin hernia repair. J Surg Res. 2017;210:59-68. https://doi.org/10.1016/j.jss.2016.10.028
Appelman Y, van Rijn BB, Monique E, Boersma E, Peters SA. Sex differences in cardiovascular risk factors and disease prevention. Atherosclerosis. 2015;241:211-8. https://doi.org/10.1016/j.atherosclerosis.2015.01.027
Young L, Cho L. Unique cardiovascular risk factors in women. Heart. 2019;105:1656-60. https://doi.org/10.1136/heartjnl-2018-314268
Mensah GA. Health and health care disparities in cancer and cardiovascular diseases - learning from one to improve the other. Ethn Dis. 2018;28:133-4. https://doi.org/10.18865/ed.28.3.133
Wasserman J, Palmer RC, Gómez MM, Berzon R, Ibrahim SA, Ayanian JZ. Advancing health services research to eliminate health care disparities. Am J Public Health. 2019;109(Supl.1):S64-9. https://doi.org/10.2105/AJPH.2018.304922
Martínez-García M, Vargas-Barrón J, Bañuelos-Téllez F, González-Pacheco H, Fresno C, Hernández-Lemus E, et al. Public insurance program impact on catastrophic health expenditure on acute myocardial infarction. Public Health. 2018;158:47-54. https://doi.org/10.1016/j.puhe.2018.01.025
Brindis CD, Freund KM. The ramifications of recent health policy actions for cardiovascular care of women: Progress, threats, and opportunities. Clin Cardiol. 2018;41:173-8. https://doi.org/10.1002/clc.22896
Fernández-López JA. Towards a better understanding of patients. Semergen. 2013;39,8:403-5. https://doi.org/10.1016/j.semerg.2013.06.007
Gulland A. Gender discrimination is blamed for high rates of uterine prolapse in Nepal. BMJ. 2014;348. https://doi.org/10.1136/bmj.g1756
Castilho JL, Escuder MM, Veloso V, Gomes JO, Jayathilake K, Ribeiro S, et al. Trends and predictors of non-communicable disease multimorbidity among adults living with HIV and receiving antiretroviral therapy in Brazil. J Int AIDS Soc. 2019;22:e25233. https://doi.org/10.1002/jia2.25233
Curno MJ, Rossi S, Hodges-Mameletzis I, Johnston R, Price MA, Heidari S. A systematic review of the inclusion (or exclusion) of women in HIV research: From clinical studies of antiretrovirals and vaccines to cure strategies. J Acquir Immune Defic Syndr. 2016;71:181-8. https://doi.org/10.1097/QAI.0000000000000842
Pérez CC. Invisible women: Exposing data bias in a world designed for men. New York: Random House; 2019.
Ouyang P, Wenger NK, Taylor D, Rich-Edwards JW, Steiner M, Shaw LJ, et al. Strategies and methods to study female-specific cardiovascular health and disease: A guide for clinical scientists. Biol Sex Differ. 2016;7:19. https://doi.org/10.1186/s13293-016-0073-y
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