Impact of the social context on the prognosis of Chagas disease patients: Multilevel analysis of a Brazilian cohort

Carregando...
Imagem de Miniatura
Citações na Scopus
13
Tipo de produção
article
Data de publicação
2020
Título da Revista
ISSN da Revista
Título do Volume
Editora
PUBLIC LIBRARY SCIENCE
Autores
FERREIRA, Ariela Mota
OLIVEIRA, Claudia Di Lorenzo
CARDOSO, Clareci Silva
RIBEIRO, Antonio Luiz Pinho
DAMASCENO, Renata Fiuza
NUNES, Maria do Carmo Pereira
HAIKAL, Desiree Sant' Ana
Citação
PLOS NEGLECTED TROPICAL DISEASES, v.14, n.6, 2020
Projetos de Pesquisa
Unidades Organizacionais
Fascículo
Resumo
Author summary Chagas disease (CD) is a serious public health problem in Latin America and has a strong social impact worldwide. Up to 30% of the infected people may have cardiac alterations, which are associated with a worse prognosis and with high mortality rates. The occurrence of CD is associated with contexts of social vulnerability. However, no studies have been identified that assessed whether unfavorable social contexts are related to the prognosis and evolution of CD, which is the purpose of our study. We evaluated 1,637 patients with CD who lived in 21 municipalities located in regions to which CD is endemic in Brazil, over a two-year period. Of these people, 12.5% evolved into a worse prognosis. Our study revealed that socio-demographic and clinical characteristics of individuals were not isolated protagonists of the evolution of CD. The context in which individuals lived was also a determining factor of a worse prognosis, including living in municipalities with a smaller rural population, fewer physicians, and a smaller Primary Health Care (PHC) coverage. Thus, we observed that characteristics related to the health care available in the municipalities influenced the evolution of CD. This knowledge has the potential to support health care planning that is more appropriate for the evolution of patients with CD, especially considering poor and remote regions. The present study aims to investigate how the social context contributes to the prognosis of Chagas disease (CD). This is a multilevel study that considered individual and contextual data. Individual data came from a Brazilian cohort study that followed 1,637 patients who lived in 21 municipalities to which CD is endemic, over two years. Contextual data were collected from official Brazilian government databases. The dependent variable wasthe occurrence of cardiovascular events in CDduring the two-year follow-up, defined from the grouping of three possible combined events: death, development of atrial fibrillation, or pacemaker implantation. Analysis was performed using multilevel binary logistic regression. Among the individuals evaluated, 205 (12.5%) manifested cardiovascular events in CD during two years of follow-up. Individuals living in municipalities with a larger rural population had protection for these events (OR = 0.5; 95% CI = 0.4-0.7), while those residing in municipalities with fewer physicians per thousand inhabitants (OR = 1.6; 95% CI = 1.2-2.5) and those living in municipalities with lower Primary Health Care (PHC) coverage (OR = 1.4; 95% CI = 1.1-2.1) had higher chances of experiencing cardiovascular events. Among the individual variables, the probability of experiencing cardiovascular events was higher for individuals aged over 60 years (OR = 1.4; 95% CI = 1.01-2.2), with no stable relationship (OR = 1.4; 95% CI = 0.98-2.1), without previous treatment with Benznidazole (OR = 1.5; 95% CI = 0.98-2.9), with functional class limitation (OR = 2.0; 95% CI = 1.4-2.9), with a QRS complex duration longer than 120 ms (OR = 1.5; 95% CI = 1.1-2.3), and in individuals with high NT-proBNP levels (OR = 6.4; 95% CI = 4.3-9.6). CONCLUSION: The present study showed that the occurrence of cardiovascular events in individuals with CD is determined by individual conditions that express the severity of cardiovascular involvement. However, these individual characteristics are not isolated protagonists of this outcome, and the context in which individuals live, are also determining factors for a worse clinical prognosis.
Palavras-chave
Referências
  1. Alkmim MB, 2012, B WORLD HEALTH ORGAN, V90, P373, DOI 10.2471/BLT.11.099408
  2. Andersen R, 2007, CHANGING US HLTH CAR, P3
  3. [Anonymous], 2015, Wkly Epidemiol Rec, V90, P33
  4. [Anonymous], 2005, CYBERPSYCHOL BEHAV, V8, P7
  5. [Anonymous], 2018, CIRCULATION, V138, pe751, DOI 10.1161/CIR.0000000000000636
  6. Ayres JRCM, 2009, PROMOCAO SAUDE
  7. Barreto SM, 2013, REV SAUDE PUBL, V47, P79, DOI 10.1590/S0034-8910.2013047003836
  8. Benjamin EJ, 2018, CIRCULATION, V137, pE67, DOI 10.1161/CIR.0000000000000558
  9. Borde E, 2014, CAD SAUDE PUBLICA, V30, P2081, DOI 10.1590/0102-311X00162513
  10. Brasil. Ministerio da Saude, 1997, SAUD FAM ESTR REOR M
  11. Camm AJ, 2013, EUR HEART J, V34, P2850
  12. Capuani L, 2017, PLOS NEGLECT TROP D, V11, DOI 10.1371/journal.pntd.0005542
  13. Cardoso CS, 2018, PLOS NEGLECT TROP D, V12, DOI 10.1371/journal.pntd.0006814
  14. Cardoso CS, 2016, BMJ OPEN, V6, DOI 10.1136/bmjopen-2016-011181
  15. CHACKO KA, 1995, CIRCULATION, V92, P2003
  16. Cucunuba ZM, 2016, PARASITE VECTOR, V9, DOI 10.1186/s13071-016-1315-x
  17. Ferreira AM, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0165950
  18. Francisco Priscila Maria Stolses Bergamo, 2011, Rev. bras. epidemiol., V14, P5, DOI 10.1590/S1415-790X2011000500002
  19. Freitas HFG, 2005, INT J CARDIOL, V102, P239, DOI 10.1016/j.ijcard.2004.05.025
  20. Johnson NJ, 2000, ANN EPIDEMIOL, V10, P224, DOI 10.1016/S1047-2797(99)00052-6
  21. Kennedy BP, 1996, BRIT MED J, V312, P1004, DOI 10.1136/bmj.312.7037.1004
  22. Lima-Costa MF, 2010, AM J EPIDEMIOL, V172, P190, DOI 10.1093/aje/kwq106
  23. Maisel A, 2008, EUR J HEART FAIL, V10, P824, DOI 10.1016/j.ejheart.2008.07.014
  24. Malta DC, 2016, CIENC SAUDE COLETIVA, V21, P327, DOI 10.1590/1413-81232015212.23602015
  25. Mamas MA, 2009, EUR J HEART FAIL, V11, P676, DOI 10.1093/eurjhf/hfp085
  26. Martinelli Filho Martino, 2003, Arq. Bras. Cardiol., V81, P2, DOI 10.1590/S0066-782X2003002000002
  27. Martins-Melo FR, 2019, INT J PARASITOL, V49, P301, DOI 10.1016/j.ijpara.2018.11.008
  28. Mendes EV, 2012, CUIDADO CONDICOES CR
  29. Morillo CA, 2015, NEW ENGL J MED, V373, P1295, DOI 10.1056/NEJMoa1507574
  30. Murphy M, 2007, POP STUD-J DEMOG, V61, P287, DOI 10.1080/00324720701524466
  31. Nadruz W, 2018, HEART, V104, P1522, DOI 10.1136/heartjnl-2017-312869
  32. OMS-OrganizacAo Mundial Da Saude, 2011, C MUND DET SOC SAUD
  33. OMS-OrganizacAo Mundial Da Saude . Departamento de Recursos Humanos para a Saude, 2009, DEP REC HUM SAUD
  34. Pastore CA, 2016, ARQ BRAS CARDIOL, V107, P392, DOI 10.5935/abc.20160173
  35. Nunes MCP, 2013, J AM COLL CARDIOL, V62, P767, DOI 10.1016/j.jacc.2013.05.046
  36. Nunes MDP, 2010, REV ESP CARDIOL, V63, P788, DOI 10.1016/S0300-8932(10)70181-0
  37. Dias JCP, 2016, EPIDEMIOL SERV SAUDE, V25, P7, DOI [10.5123/S1679-49742016000500002, 10.5123/s1679-49742016000500002]
  38. Rassi Salvador, 2005, Arq. Bras. Cardiol., V84, P309, DOI 10.1590/S0066-782X2005000400007
  39. Ribeiro AL, 2012, NAT REV CARDIOL, V9, P576, DOI 10.1038/nrcardio.2012.109
  40. Ribeiro ALP, 2014, J AM HEART ASSOC, V3, DOI 10.1161/JAHA.113.000632
  41. Ribeiro ALP, 2008, J CARDIOVASC ELECTR, V19, P502, DOI 10.1111/j.1540-8167.2007.01088.x
  42. Sabino EC, 2013, CIRCULATION, V127, P1105, DOI 10.1161/CIRCULATIONAHA.112.123612
  43. Scheffer M., 2018, DEMOGRAFIA MED BRASI
  44. Shi L, 1992, J Health Care Poor Underserved, V3, P321
  45. Shi L, 2004, J EPIDEMIOL COMMUN H, V58, P374, DOI 10.1136/jech.2003.013078
  46. Starfield B, 2001, BRIT J GEN PRACT, V51, P303
  47. Victora CG, 2003, LANCET, V362, P233, DOI 10.1016/S0140-6736(03)13917-7
  48. Braga JCV, 2008, INT J CARDIOL, V126, P276, DOI 10.1016/j.ijcard.2007.01.097
  49. WHO- World Health Organization, 2002, ARS CAS DET MAN SURV, P4