Using a multivariate model to assess the interactive effects of demographics and lifestyle on the hematological profile

Abstract

Aim: To assess the extent to which a multivariate approach to modeling interrelated hematological indices provides more informative results than the traditional approach of modeling each index separately. Materials & methods: The effects of demographics and lifestyle on ten hematological indices collected from a Dutch population-based sample (n = 3278) were studied, jointly using multivariate distance matrix regression and separately using linear regression. Results: The multivariate approach highlighted the main effects of all predictors and several interactions; the traditional approach highlighted only main effects. Conclusion: The multivariate approach provides more power than traditional methods to detect effects on interrelated biomarkers, suggesting that its use in future research may help identify subgroups that benefit from different treatment or prevention measures.