Introduction Socioeconomic status (SES) is a critical driver of human health, but in research practice it is rarely well-defined and inconsistently measured. Latent class analysis (LCA) is a potentially useful method of characterising SES, particularly when multiple SES indicators are available. We employed LCA to better understand how SES is related to obesity in a sample of young Filipino adults; and contrasted LCA with other approaches.
Methods Data are from a cohort of young adults enrolled in the Cebu Longitudinal Health and Nutrition Survey (987 males and 819 females). Latent classes were derived using Mplus mixture modelling. Class indicators included obesity status, marital status, education level, urbanicity, household assets and income. Models were estimated under the assumption of class-conditional independence, with no further parameter constraints.
Results For both sexes, a 3-class solution was the best balance of model fit (using log-likelihood, AIC, and BIC) and parsimony. Overall obesity prevalence was 9.4% in males and 7.8% in females. One class of males (n=194) had an obesity prevalence of 22%, vs 6% in the remaining two classes (p=0.007 for H0: no difference). They were more likely to be urban, educated, and unmarried than other males (p<0.05). However, a female class (n=257) with a similar socioeconomic profile instead had the lowest prevalence of obesity (5.5%).
Conclusions LCA can contribute to our understanding of socioeconomic drivers of health. Interpretation of LCA is discussed in the context of Rothman and Greenland's model of causation.
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