Abstract
BackgroundThe adverse relationship between income and health is well documented, but less is known of how income trajectories, i.e. downward or upward trends in income, determine health. We therefore link longitudinal income information to cross-sectional data on self-rated health and conduct logistic regression models in order to investigate income trends over time and their relationship with health.MethodsThe data, with the exception of income information, are derived from the Swedish Level-of-Living Survey 2000. The information on income was drawn from the income register covering the period 1995 to 2000. We used an age-restricted sample of those 30–64 years of age, and generated a series of models accounting for average income position, lagged income position, income decrease and increase, and annual periods in specific income positions. The analysis was conducted for men and women separately.ResultsApart from the overall association between income and health, we found a similar pattern when including average and lagged income in the model. The analysis of length of time in a specific income position showed substantial sex differences in poor health. Income decrease was more strongly associated with men’s poor health, whereas income increase revealed only weak associations with self-rated health.ConclusionsIt was shown that income changes and the time dimension of income are important for self-rated health. Self-rated health responds to decreases in absolute income and lowered rank position in the income distribution to a greater extent than to income gains over time. Lagged lower income position and its associations with health suggest that socio-economic disadvantages accumulate over time.
Highlights
The adverse relationship between income and health is well documented, but less is known of how income trajectories, i.e. downward or upward trends in income, determine health
Extensive research has been dedicated to demonstrating the adverse health consequences of low income position; much less attention has been paid to income dynamics and lagged effects of income [1]
Model 1: Length in time below median In Model 1 (Table 2) we explored lower income position across the period 1995 to 2000 using the pooled income information
Summary
The adverse relationship between income and health is well documented, but less is known of how income trajectories, i.e. downward or upward trends in income, determine health. We link longitudinal income information to cross-sectional data on self-rated health and conduct logistic regression models in order to investigate income trends over time and their relationship with health. The primary reason why income dynamics (i.e. downward and upward trends in income) are relatively unexplored is the common application of cross-sectional data, which are naturally limited when dealing with trends over time. A longitudinal approach by Benzeval and Judge [6] has explored income changes and their role in various health measures, combining income series with cross-sectional information on health. Using a set of self-assessed indicators, the study revealed that average income over a five-year period had the strongest effects on health, suggesting that the crosssectional approach underestimates the (true) relationship between income and health. For high-income earners, no significant increases in mortality risk were found [7]
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