How do age and major risk factors for mortality interact over the life-course? Implications for health disparities research and public health policy

Abstract

A critical question in life-course research is whether the relationship between a risk factor and mortality strengthens, weakens, or remains constant with age. The objective of this paper is to shed light on the importance of measurement scale in examining this question. Many studies address this question solely on the multiplicative (relative) scale and report that the hazard ratio of dying associated with a risk factor declines with age. A wide set of risk factors have been shown to conform to this pattern including those that are socioeconomic, behavioral, and physiological in nature. Drawing from well-known principles on interpreting statistical interactions, we show that evaluations on the additive (absolute) scale often lead to a different set of conclusions about how the association between a risk factor and mortality changes with age than interpretations on the multiplicative scale. We show that on the additive scale the excess death risks posed by key socio-demographic and behavioral risk factors increase with age. Studies have not generally recognized the additive interpretation, but it has relevancy for testing life-course theories and informing public health interventions. We discuss these implications and provide general guidance on choosing a scale. Data from the U.S. National Health Interview Survey are used to provide empirical support.

Keywords: Health inequalities; Life-course; Mortality; Obesity; Smoking; Socioeconomic status; Statistical interaction.

Fig. 1

Additivitiy and multiplicativity along a continuum. Note: ${\mu }_{11}^A$ is the additive prediction of a statistical interaction between two risk factors and ${\mu }_{11}^M$ it the multiplicative prediction. Sub-multiplicativity and super-multiplicativity are mutually exclusive concepts, as are sub-additivity and super-additivity. Strictly multiplicative and super-multiplicative relationships necessarily implies super-additivity. Sub-multiplicativity and all three types of additivity (super-, strictly-, and sub-additivity) may co-exist.

Fig. 2

Hazard ratios and rate differences (per 1000 person-years) by 10-year age group for each risk factor. Note: Lines are regression lines based on OLS regression. Coefficients for age (95% confidence intervals) from the regression models shown. Regression line for the rate difference associated with obesity excluded ages 80-9. Low education defined as having a HS degree or GED. Data from 1997-2009 National Health Interview Survey with death information through 2011.

Fig. 3

Rate difference (per 1000 person-years) for each risk factor estimated from the Poisson regression models shown in Panel B in Table 4. Note: Low education defined as having a HS degree or GED. Data from the 1997-2009 National Health Interview Survey with death information through 2011.

Fig. 4

Hazard ratios and rate differences (per 1000 person-years) by 10-year age group for cohorts born during 1920-9, 193-9, and 1940-9. Note: Low education defined as having a HS degree or GED. Data from 1986-2009 National Health Interview Survey with death information through 2011.