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Using latent class analysis to operationalize a wholistic assessment of Inuit health and well-being
Morgen Bertheussen1, Mylene Riva1, Brittany Wenniserí Iostha Jock2
1Department of Geography, McGill University, Montreal, Canada.
Abstract:
Many indigenous cultures conceptualize health wholistically, whereby physical, mental, spiritual and relational dimensions of health are interconnected. Yet, quantitative approaches to studying Indigenous health remain anchored in western perspectives, that separate the dimensions of health. This paper aims to operationalize a wholistic indicator of health based on the IQI model of Inuit health. Variables from the 2017 Nunavik Health Survey (N = 1196) were selected based on their representativeness of IQI model. Exploratory Latent Class Analysis (LCA) was used to identify wholistic health profiles. Once participants assigned to their health profile, sociodemographic characteristics were compared across profiles, and multinomial regression models were used to examine the relationship between community-level social determinants of health and the profiles. The LCA revealed three health profiles, labelled as "excellent", "good" and "fair" based on the distribution of answers to the indicators. Nunavimmiut in "excellent" and "good" health were more likely to: rate their health positively; be over 30 years old; be in a relationship; and have participated or volunteered in community events. Nunavimmiut in "fair" health tended to report lower levels of community cohesion, family relationships, and emotional support. Intergrating culturally relevant models of health can support improved health status assessments and identify opportunities for health promotion.
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