Factors associated with the use of oral health services in older peruvian adults: Secondary analysis of population survey, 2018

Diego Azañedo, Rodrigo Vargas-Fernández, Carlos Rojas-Roque

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

Objectives. To identify the prevalence and factors associated with the use of oral health services in Peruvian older adults (OA) during 2018. Materials and Methods. Secondary analysis of data on 4,874 Peruvian OAs from the Demographic and Family Health Survey (ENDES) carried out in 2018. The use of oral health services was considered (yes/no) based on the six months prior to the application of the survey as a dependent variable. The independent variables were sex, age, area of residence, educational level, marital status, geographical domain, physical limitation, health insurance, spoken language, and welfare index quintile. A descriptive analysis was performed using absolute frequencies and weighted proportions, and a multivariate analysis using generalized linear models (Poisson regression). Results. From the total of OAs, 52.6% were women, 52.9% belonged to the 60-69 age group, 77% belonged to the urban area, and 81.1% had a health insurance. The prevalence of the use of dental care services in the last six months was 24.9%. Multivariate analysis found association with area of residence (p<0.001), higher educational level (p=0.001), health insurance affiliation (p<0.001), geographic domain (p=0.019), and all welfare index quintiles (p<0.001). Conclusions. The prevalence of the use of dental care services in OAs was low, and its associated factors were the area of residence, educational level, health insurance, geographic domain, and welfare index quintiles.

Original languageEnglish
Pages (from-to)553-561
Number of pages9
JournalRevista Peruana de Medicina Experimental y Salud Publica
Volume36
Issue number4
DOIs
StatePublished - 2019
Externally publishedYes

Keywords

  • Aged
  • Health services accessibility
  • Oral health
  • Peru (source: MeSH NLM)

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