Once again, we do need a comprehensive definition of what is health and wellbeing, and the current issue of PNAS provides us with an interesting approach:
The dominant model of health is a disease-centered Medical Model (MM), which actively ignores many relevant domains. In contrast to the MM, we approach this issue through a Comprehensive Model (CM) of health consistent with the WHO definition, giving statistically equal consideration to multiple health domains, including medical, physical, psychological, functional, and sensory measures. We apply a data-driven latent class analysis (LCA) to model 54 specific health variables from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative sample of US community-dwelling older adults.
Although public health campaigns, such as “Choosing Wisely,” rightly emphasize the need to decrease unnecessary health interventions (52), they still accept the basic health conception of the MM as resting on organ system disease. Instead, the CM instantiates comorbidities and the equal importance of mental health, mobility, and sensory function in health and should inform policy redesign. For example, including assessments of sensory function, mental health, broken bones in middle age, and frailty in annual physician visits would enhance risk management. In addition to policies focused on reducing BMI, greater support for preventing loneliness among isolated older adults would be effective. In place of additional (expensive) new medicines for hypertension, helping older adults find social support through home care services or alternative living arrangements could be developed. In summary, taking a broad definition of health seriously and empirically identifying specific constellations of health and comorbidities in the US population provide a new way of assessing health and risk in older adults living in their homes and thereby, may ultimately inform health policy.And these are the results:
The CM of health with six distinct health classes based on 54 health measures across six dimensions (listed in column 1). The column US population (US Pop.) reports the prevalence in 2005 of each disease or condition in the older US Pop. ages 57–85 y old (definitions and validation are in Fig. S1). Within each health class (columns), the prevalence of a given disease or condition indexes the likelihood that any member of the class has that particular disease [rows; n = 54 health measures ordered by prevalence within each health domain (column 2)] and shares similar constellations of disease and health.
We should reckon on something similar with our data, just to check if it fits with the final goal of measuring health and wellbeing. As you may imagine, there are many implications. If we agree on a comprehensive model of health, then we have to focus on how decisions and priorities should be made.
PS. The return of the big questions. JM Colomer opinion;:
The achievement of a human-made plan depends 1/4 on resources, such as money, education or physical strength; 1/4 on skill and decisions; and 1/2 on unpredictable circumstances, usually called luck. A student asked me how luck can be improved: well, I said, if you keep pursuing your goal with perseverance, the probabilities to get it increase (like if you keep playing the lottery, the probability to get the prize also increases)
