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Recurrent use of the Housing Enabler instrument has highlighted methodological challenges of broader scientific interest, namely interactions between personal functional capacity ( P ) and exposures to features (here potential barriers) in the built housing environment ( E ). This study aimed to propose and illustrate an analytic approach, separating P  ×  E interaction effects (here accessibility problems) from main effects of P and E , in studies where P and P  ×  E are strongly interrelated. Four datasets representing different populations of older people in the context of housing were used. The datasets ( N  = 1910) comprised data on P , E and P  ×  E interactions as well as health-related variables. A two-step analytic procedure was performed: (1) a measure of environmental barriers net of functional capacity was obtained from residuals of linear regression analysis between P (independent) and P  ×  E (dependent); (2) logistic regression analyses with self-rated general health and I-ADL, respectively, as dependent variables to explore interaction effects using the P  ×  E residuals from the previous step. The association between P and P  ×  E was similar across the four datasets ( r  ≥ 0.80,   p  &lt; 0.001). In the logistic regression analyses, including P , both categorized and continuous P  ×  E residuals were clearly associated with self-rated general health ( p  &lt; 0.001 and p  = 0.026), whereas the associations with I-ADL were less consistent ( p  = 0.275 and p  = 0.002, respectively). The new two-step-instead of single-step-analytic approach proposed for investigating P  ×  E interaction effects in studies involving health outcomes emerged as promising. The new approach has the potential of increasing the possibilities to adequately represent theoretical concepts and assumptions and rigorously test their effects.

A new approach for investigation of person–environment interaction effects in research involving health outcomes