A systematic approach to analyze the social determinants of cardiovascular disease

PLoS One. 2018 Jan 25;13(1):e0190960. doi: 10.1371/journal.pone.0190960. eCollection 2018.

Abstract

Cardiovascular diseases are the leading cause of human mortality worldwide. Among the many factors associated with the etiology, incidence, and evolution of such diseases; social and environmental issues constitute an important and often overlooked component. Understanding to a greater extent the scope to which such social determinants of cardiovascular diseases (SDCVD) occur as well as the connections among them would be useful for public health policy making. Here, we will explore the historical trends and associations among the main SDCVD in the published literature. Our aim will be finding meaningful relations among those that will help us to have an integrated view on this complex phenomenon by providing historical context and a relational framework. To uncover such relations, we used a data mining approach to the current literature, followed by network analysis of the interrelationships discovered. To this end, we systematically mined the PubMed/MEDLINE database for references of published studies on the subject, as outlined by the World Health Organization's framework on social determinants of health. The analyzed structured corpus consisted in circa 1190 articles categorized by means of the Medical Subheadings (MeSH) content-descriptor. The use of data analytics techniques allowed us to find a number of non-trivial connections among SDCVDs. Such relations may be relevant to get a deeper understanding of the social and environmental issues associated with cardiovascular disease and are often overlooked by traditional literature survey approaches, such as systematic reviews and meta-analyses.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Cardiovascular Diseases / epidemiology
  • Cardiovascular Diseases / etiology*
  • Cardiovascular Diseases / mortality
  • Data Interpretation, Statistical
  • Data Mining / methods
  • Female
  • Global Health
  • Humans
  • MEDLINE
  • Male
  • Risk Factors
  • Semantic Web
  • Social Determinants of Health*
  • World Health Organization

Grants and funding

This work was supported by CONACYT (grant no.179431/2012) [EHL], as well as by federal funding from the National Institute of Cardiology (Mexico) [MV] and the National Institute of Genomic Medicine (Mexico) [EHL]. Mireya Martínez-García is a doctoral candidate in the Ph.D. Programme in Collective Health supported by a CONACYT Fellowship. [EHL] acknowledges additional support from the 2016 Marcos Moshinsky Chair in the Physical Sciences. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.