Multi-morbidity, the co-occurrence of multiple physical or psychological
illnesses, is prevalent particularly among older adults. The number of Americans
with multiple chronic diseases is projected to increase from 57 million in 2000
to 81 million in 2020. However, behavioral medicine and health psychology,
while focusing on the co-occurrence of psychological/psychiatric disorders with
primary medical morbidities, have historically tended to ignore the
co-occurrence of primary medical comorbidities, such as diabetes and cancer, and
their biopsychosocial implications. This approach may hinder our ecologically
valid understanding of the etiology, prevention, and treatment of individual
patients with multi-morbidity. In this selective review, we propose a heuristic
biobehavioral framework for the etiology of multi-morbidity. More acknowledgment
and systematic research on multiple, co-existing disorders in behavioral
medicine is consistent with the biopsychosocial model’s emphasis on
treating the “whole person,” which means not considering any
single illness, its symptoms, risk factors, or mechanisms, in isolation. As
systems analytics, big data, machine learning, and mixed model trajectory
analyses, among others, come on-line and become more widely available, we may be
able to tackle multi-morbidity more holistically, efficiently and
satisfactorily.