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Syndemic and syndemogenesis of low back pain in Latin-American population: a network and cluster analysis.

Alfonso Gastelum StrozziIngris Pelaez-BallestasYsabel GranadosRubén Burgos-VargasRosana QuintanaJohn LondoñoSergio GuevaraOscar Vega-HinojosaJosé Alvarez-NemegyeiVicente JuarezCésar Pacheco-TenaLigia CedeñoMario Garza-ElizondoAna María SantosMaría Victoria Goycochea-RoblesAstrid FeicánHazel GarcíaFlor Julian-SantiagoMaría Elena CrespoJacqueline Rodriguez-AmadoJuan Camilo RuedaAdriana SilvestreJorge Esquivel-ValerioCelenia RosilloSusana Gonzalez-ChavezEverardo Alvarez-HernándezAdalberto Loyola SanchezEduardo Navarro-ZarzaMarco MaradiagaJulio Casasola-VargasNatalia SanatanaImelda Garcia-OliveraMario GoñiLuz Helena SaninRocío GamboaMario Humberto CardielBernardo A Pons-Estelnull nullnull null
Published in: Clinical rheumatology (2020)
LBP is a highly prevalent condition in Latin-American populations with a high impact on the quality of life of young adults. It is particularly debilitating for women, indigenous individuals, and those with low educational level, and is further exacerbated by the presence of comorbidities, especially those in the mental health domain. Thus, the study findings demonstrate that syndemic and syndemogenesis have the potential to widen the health inequities stemming from LBP in vulnerable populations. Key points • Syndemic and syndemogenesis evidence health disparities in Latin-American populations, documenting the complexity of suffering from a disease such as low back pain that is associated with comorbidities, unhealthy habits, and the social and regional context where they live. • The use of network and cluster analyses are useful tools for documenting the complexity and the multifaceted impact in health in large populations as well as the differences between countries. • The variability and impact of socioeconomic indicators (e.g., Gini index) related to low back pain and comorbidities could be felt through the use of cluster analysis, which generates evidence of regional inequality in Latin America. • Populations can be studied from different models (network and cluster analysis) and grouping, presenting new interpretations beyond geographical groupings, such as syndemic and inequity in health.
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