The variability and volatility of sleep: An ARCHetypal behavior.

Using 1975-2005 Dutch time-diary data covering over 10,000 respondents for 7 consecutive days each, we show that sleep time exhibits non-constant variability, or volatility, characterized by stationary autoregressive conditional heteroscedasticity: The absolute values of deviations from a person's average sleep on one day are positively correlated with those on adjacent days. Sleep is more variable on weekends and among younger people, those without young children, or with less education. Volatility is greater among parents with young children, slightly greater among men, but independent of other demographics. Economic incentives to minimize the dispersion of sleep imply higher-wage workers will exhibit less dispersion, which we observe. Sleep volatility spills over onto volatility in other personal activities, with no reverse causation onto sleep. The results illustrate a novel dimension of inequality among people and could be applied to a wide variety of human behavior and biological processes.

Health and income: a meta-analysis to explore cross-country, gender and age differences.

BACKGROUND: Evidence of an effect of income on self-reported poor health (SRPH) is widely available in the literature. We compare this effect across age, different countries and between men and women using meta-analysis. Studies that report on an effect of income lack a homogenous effect size. To overcome this problem we propose a method to derive a homogenous effect size to enable us to compare the effect of income across groups. METHODS: We take a meta-analytical approach to examine the effect of income on SRPH. The data consists of reported and calculated odds ratios as a measure of effect for SRPH outcomes across different income categories. Self-reported health outcomes are dichotomised into 'good' and 'poor'. With least-squares techniques, we estimate the functional parameters that describe the log-linear association between income and SRPH. Subsequently, F-tests are performed to show variations between the groups. RESULTS: The relationship between income and SRPH is log-linear for most countries but not significantly for Sweden and the Netherlands. Our results show significant differences in the effect of income between countries. We find that men require a higher income than women to achieve comparable SRPH outcomes, and that the effect of income depends on age. CONCLUSIONS: There is significant income related variation in SRPH between different countries even if the levels of income or the standards of living are comparable. For women income affects SRPH differently than for men. The effect of income on SRPH depends on the age of the individual respondent.

Individual vulnerability and the nurturing state: the case of self-reported health and relative income.

This paper develops a method to model the effect of income on self-reported health at the individual level. The model is estimated using the meta-analytic data of 68 studies from 13 countries, and is used to test two hypotheses. The first hypothesis is that income affects health at the individual level. If this is the case, the incidence of poor health will differ across people from different income groups. The second hypothesis is that income differentials are associated with differential vulnerability to poor health. If so, the influence of income on health outcomes will differ across members of different income groups in different countries. The collected data are best described by a log-linear relationship between income and self-reported health. The empirical results confirm both hypotheses. We have found that (a) income inequality affects health at the individual level; (b) the level of self-reported poor health in the bottom deciles of the income distribution increases with the level of inequality in the country's income distribution; and (c) the relative income hypothesis has a stronger explanatory power for our results than the absolute income hypothesis. These results confirm the idea that for comparisons at the individual level, relative income matters more than absolute income. These findings have important policy implications.