These new ageing studies, which share a comparable template, provide rich sources of information for researchers interested in the dynamics of health, socioeconomic status, retirement, and wellbeing among ageing populations. Their panel nature allows us to investigate the nature and determinants of within-person and within-household experiences in retirement and health onsets, and the manner in which these central life domains co-relate. There are now more than 25 countries in the world who have initiated such comparable longitudinal ageing studies and more countries are certainly on the way.An important concern with all panel studies, and particularly those focused on an older population, is the potential for bias caused by individuals non-randomly dropping out of the survey over time. If attrition from a survey is systematically related to outcomes of interest or to variables correlated with these outcomes, then not only will the survey cease to be representative of the population of interest, but estimates of the relationships between different key outcomes, especially in a longitudinal context, may also be biased.The issue of non-response in longitudinal surveys-both initial non-response and subsequent attrition-has a distinguished history in survey research and statistics (Sudman and Bradburn, 1974, Groves and Couper, 1998, Little and Rubin, 1987. Most of the existing literature has focused on non-ageing panels in the United States, especially during earlier time periods when attrition rates typically were considerably lower (Becketti et al., 1988;Fitzgerald et al., 1998;Lillard and Panis, 1998; Zapel, 1998).In this paper we present results of an investigation into observable characteristics associated with attrition in ELSA and the HRS, with a particular focus on whether attrition is systematically related to health outcomes and socioeconomic status (SES) links between health and SES is one of the primary goals of the ELSA and HRS, so attrition correlated with these outcomes is a critical concern.We begin by looking at raw rates of attrition in the two surveys, and show that panel attrition is a far greater problem in ELSA than in HRS. We consider several possible explanations for ELSA's poorer retention rates, including the greater 'maturity' of HRS (which has been running for ten years longer than ELSA), differences in sampling rules and procedures used in the two surveys, the 'quality' of the two respective survey organizations, and differences in incentives offered to respondents. We conclude that none of these explanations alone or together seems sufficient to account for the disparity in attrition rates between the two surveys.Having documented raw attrition rates in ELSA and HRS, we then consider the possible bias such attrition could introduce into estimates of disease prevalence derived from the two surveys. In recent papers, we have used data from these surveys to demonstrate that middleaged and older Americans are substantially less healthy than their English counterparts, across a range of impo...

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We nd that both disease incidence and disease prevalence are higher among Americans in age groups 55-64 and 70-80, indicating nternational comparisons of health outcomes have risen in importance as a method of gaining insight into social and economic determinants of health status. This is partly because some key institutions-such as the way health insurance or income security is provided-vary more systematically and perhaps exogenously across rather than within countries. In a recent, widely cited paper, we compared disease prevalence among middleaged adults 55-64 years old in England and in the United States (Banks et al. 2006). Based on self-reported prevalence of seven important illnesses (diabetes, heart attack, hypertension, heart disease, cancer, diseases of the lung, and stroke), Americans were much less healthy than their English counterparts, differences that were large along all points of the socioeconomic status distribution.Moreover, using biological markers of disease, we found similar health disparities between Americans and the English, suggesting that these large health differences are not simply a result of differential reporting of illness in the two countries. They also exist with equal force among both men and women ). Since we purposely excluded minorities (African Americans and Latinos in the United States and immigrants in England), these differences were not solely due to U.S. health issues in the African American or Latino populations or the growing immigrant population in England. Finally, these disparities in prevalence of chronic illness were not the consequence of differences between the

This Briefing Note provides an update on trends in living standards, income inequality and poverty. It uses the same approach to measuring income and poverty as the government employs in its Households Below Average Income (HBAI) publication. The analysis is based on the latest HBAI figures (published on 27 March 2007), providing information about incomes up to the year 2005-06. The measure of income used is net household weekly income, which has been adjusted to take account of family size ('equivalised'). The income amounts provided below are expressed as the equivalent for a couple with no children, and all changes given are in real terms (i.e. after adjusting for inflation). For the first time in recent years, data are available for the whole of the United Kingdom, not just Great Britain, but data for Northern Ireland are only available from 2002-03. Some comparisons over time are provided for Great Britain only, but others will compare statistics for GB before 2002-03 with those for the UK afterwards. Living standards and inequality Median equivalised disposable income in Great Britain in 2005-06 was £363 per week: half the population have higher incomes than this and half lower. This amount is considerably lower than the average (mean) income of £445 per week. For the fourth year in a row, both mean and median income grew modestly compared with the growth during Labour's first term: median income was 1.0% higher in 2005-06 than in 2004-05, and mean income 1.3% higher. These represent much smaller rises than the average annual rises since 1996-97, which have been 2.0% for median income and 2.3% for the mean. There is now clear evidence that the rapid growth in household disposable income experienced in the government's first term came to a halt after 2001-02. Income growth since 2004-05 has tended to be faster the higher are incomes: while median income grew by 1.0%, incomes amongst the poorest fifth of the UK fell by 0.4%, and incomes of the richest fifth rose by 1.5%, though it should be noted that none of these changes is significantly different from the others or from zero. Many measures of income inequality rose slightly between 2004-05 and 2005-06. According to the most common measure, the Gini coefficient, income inequality in 2005-06 has reached its highest level since 2001-02, and is once again statistically significantly higher than that which the Labour government inherited. On the other hand, other measures of inequality that do not take into account incomes at the very top and very bottom of the income distribution, such as the 90:10 ratio, have fallen since 1996-97.

In this paper we present results of an investigation into observable characteristics associated with attrition in ELSA and the HRS, with a particular focus on whether attrition is systematically related to health outcomes and socioeconomic status (SES). Investigating the links between health and SES is one of the primary goals of the ELSA and HRS, so attrition correlated with these outcomes is a critical concern. We explored some possible reasons for these differences. Survey maturity, mobility, respondent burden, interviewer quality, and differing sampling methods all fail to account for the gap. Differential respondent incentives may play some role, but the impact of respondent incentive is difficult to test. Apparently, cultural differences between the US and Europe population in agreeing to participate and remain in scientific surveys are a more likely explanation.