Explaining Health Risk Behaviors in the U.S. with Social Deprivation at Local and Regional Levels

Swapna S. Gokhale, Viswadeep Lebakula, Alina Peluso

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Health risk behaviors are precursors to many chronic health outcomes, and hence, they pose a challenge to public health. Social deprivation undoubtedly creates circumstances that limit access to healthy habits. Moreover, broad regional effects (weather patterns, political ideology, social norms), and local characteristics (cultural notions and barriers, urban places) also influence lifestyle choices and must be accounted for to truly understand the impact of social deprivation on risky behaviors. This research fills the knowledge gap in epidemiological modeling of health risk behaviors by leveraging machine learning to find associations between social deprivation and health risk behaviors, when adjusted by regional and local effects. Four health risk behaviors, namely, binge drinking, smoking, lack of sleep, and lack of physical activity from the CDC PLACES project are considered in a single framework to understand and compare the interplay between local/regional characteristics and seven measures of social deprivation. Our results indicate that local and/or regional factors rise to the top for three out of four risk behaviors (binge drinking, smoking and lack of sleep) out-competing social deprivation measures. Un-entangling the geographical effects reveals that poverty, educational attainment and non-employment are the three deprivation measures most significantly associated with all four health risk factors. The research thus indicates that public health policies to promote healthy lifestyle behaviors must seek to remedy social deprivation, but using socially and culturally sensitive interventions.

Original languageEnglish
Title of host publicationProceedings - 2024 IEEE 48th Annual Computers, Software, and Applications Conference, COMPSAC 2024
EditorsHossain Shahriar, Hiroyuki Ohsaki, Moushumi Sharmin, Dave Towey, AKM Jahangir Alam Majumder, Yoshiaki Hori, Ji-Jiang Yang, Michiharu Takemoto, Nazmus Sakib, Ryohei Banno, Sheikh Iqbal Ahamed
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1856-1864
Number of pages9
ISBN (Electronic)9798350376968
DOIs
StatePublished - 2024
Event48th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2024 - Osaka, Japan
Duration: Jul 2 2024Jul 4 2024

Publication series

NameProceedings - 2024 IEEE 48th Annual Computers, Software, and Applications Conference, COMPSAC 2024

Conference

Conference48th IEEE Annual Computers, Software, and Applications Conference, COMPSAC 2024
Country/TerritoryJapan
CityOsaka
Period07/2/2407/4/24

Keywords

  • Local effects
  • Machine learning
  • PLACES
  • Public health
  • Regional effects
  • Risk behaviors
  • Social deprivation

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