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Health literacy strengths and challenges among residents of a resource-poor village in rural India: Epidemiological and cluster analyses.

Reetu PassiManmeet KaurPinnaka Venkata Maha LakshmiChristina ChengMelanie HawkinsRichard H Osborne
Published in: PLOS global public health (2023)
Cluster analysis can complement and extend the information learned through epidemiological analysis. The aim of this study was to determine the relative merits of these two data analysis methods for describing the multidimensional health literacy strengths and challenges in a resource poor rural community in northern India. A cross-sectional survey (N = 510) using the Health Literacy Questionnaire (HLQ) was undertaken. Descriptive epidemiology included mean scores and effect sizes among sociodemographic characteristics. Cluster analysis was based on the nine HLQ scales to determine different health literacy profiles within the population. Participants reported highest mean scores for Scale 4. Social support for health (2.88) and Scale 6. Ability to actively engage with healthcare professionals (3.66). Lower scores were reported for Scale 3. Actively managing my health (1.81) and Scale 8. Ability to find good health information (2.65). Younger people (<35 years) had much higher scores than older people (ES >1.0) for social support. Eight clusters were identified. In Cluster A, educated younger men (mean age 27 years) reported higher scores on all scales except one (Scale 1. Feeling understood and supported by a healthcare professional) and were the cluster with the highest number (43%) of new hypertension diagnoses. In contrast, Cluster H also had young participants (mean age 30 years) but with low education (72% illiterate) who scored lowest across all nine scales. While epidemiological analysis provided overall health literacy scores and associations between health literacy and other characteristics, cluster analysis provided nuanced health literacy profiles with the potential to inform development of solutions tailored to the needs of specific population subgroups.
Keyphrases
  • health information
  • healthcare
  • social support
  • social media
  • depressive symptoms
  • data analysis
  • mental health
  • public health
  • magnetic resonance
  • quality improvement
  • risk assessment
  • middle aged
  • psychometric properties