HealthPaths: Using functional health trajectories to quantify the relative importance of selected health determinants

Michael Wolfson; Geoff Rowe

doi:10.4054/DemRes.2014.31.31

Volume 31 - Article 31 | Pages 941–974

HealthPaths: Using functional health trajectories to quantify the relative importance of selected health determinants

By Michael Wolfson, Geoff Rowe

Date received:

8 Jul 2013

Date published:

23 Oct 2014

Word count:

6780

Keywords:

dynamics, health determinants, inequality, micro-simulation

DOI:

10.4054/DemRes.2014.31.31

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Abstract

Background: It is widely known that that there is a significant dispersion in health status, as well as a strong correlation between health status and socio-economic status. But considerable uncertainty remains as to the quantitative importance of the various explanatory factors typically cited in this context. As health status is intrinsically a reflection of co-evolving dynamic processes, it is important to take a lifetime perspective when seeking to understand its determinants. The "bottom line" measure of overall population health is, though, health-adjusted life expectancy (HALE), which is an aggregation of individuals' health-adjusted life lengths (HALLs).

Objective: In an exploratory mode, we intend to provide a realistic assessment of the relative importance of selected health determinants of HALE.

Methods: This paper first draws on very detailed estimates of the covariates of vector-valued functional health trajectories, using the National Population Health Survey (Statistics Canada). We then use longitudinal microsimulation to draw out their implications by synthesising first a realistic base case -- specifically, a representative longitudinal population sample -- and then a series of exploratory counterfactual populations. Comparisons between and among counterfactuals and the base case are then used to estimate the quantitative importance of various factors in accounting for HALE.

Results: Several surprising results emerged. Of the four risk factors explicitly examined, obesity had the smallest impacts on HALE: moving from the fifth to the 95th percentiles of BMI increased HALE 1.5 and 2.5 years for men and women, respectively. Eliminating smoking increased HALE by five and four years, while moving from the lowest to the highest levels of education had similar effects of about five years for both men and women. Perhaps surprisingly, moving from the fifth to the 95th percentiles of the psycho-social factor, Antonovsky's sense of coherence, had the greatest impact on estimated HALE, with increases of 5.5 to six years.

Conclusions: While the analysis is exploratory, the results show the analytical potential of tightly coupling detailed empirical analysis of complex longitudinal data with microsimulation modelling. Substantively, the results of the analysis contribute to the evidence that the widespread public health preoccupation with the "obesity epidemic" is over-stated, while psycho-social and mental health problems continue to be seriously under-emphasised.