BMC Public Health 2005, 5:65 http://www.biomedcentral.com/1471-2458/5/65 Lower income and education are strongly related to higher morbidity of older people and shorter LE and HE in other countries [13,15,33]. In a previous study in Japan, however, area indicators related to income, educa- tion and unemployment showed little association with mortality of older people [26]. This finding was consistent with the result of this study that LE65 showed a significant but weak correlation with socio-demographic indicators. HE65 was more strongly correlated with socio-demo- graphic indicators than LE65. These findings indicated that the health status measured by not only mortality but also morbidity is more sensitive for area socioeconomic conditions than that measured by only mortality, and the health level of older people would be substantially decreased by socioeconomic conditions in disadvantaged areas. A notable finding of this study was the negative relation between HE65 and the percentage of households of a sin- gle elderly person and divorce rate. Shorter life expectancy might cause an increase in older people living alone because of an increase in widows/widowers. However, considering that the proportion of a single elderly person did not showed a negative relation to LE65, it is likely that the shorter HE was caused by an increase of older people living alone. It was confirmed by previous studies that liv- ing alone including divorce and loss of a spouse has a neg- ative impact on the health of older people [16]. In addition, since most divorced persons were in the young- and middle-aged population, and divorces among older people are more unusual than among the middle-aged population [34], it seems plausible that the increased divorce rate influence the health status of older people through decreased support in families and communities. In this study, we found a difference in the relation between HE65 and socio-demographic factors according to the size of municipalities. A previous study, also, showed that urban areas showed a stronger relation between health status and area socioeconomic conditions than rural areas [35]. The first possible reason for this urban-rural difference is the choice of indicator/index for area socioeconomic conditions. A previous study demon- strated that the traditional deprivation index (Townsend index) was related to health only in urban areas, while an index including more multiple domains was related to health in both urban and rural areas [19]. The second pos- sible explanation is the existence of other factors mediat- ing the relations, such as the social support network. The social support network has been demonstrated to influ- ence the health status, and less social support is closely linked to poorer health in older people [12,36]. Also, social factors are less associated with mortality in a socially cohesive area [37], and the relation between soci- oeconomic inequality and mortality is mediated by so- called social capital [38]. Since urban areas show less social support network than rural areas in Japan [39,40], it is likely that in urban areas, less social support network causes a decline in health status and enhances the influ- ence of other social factors on health status in the elderly population. A few weaknesses of this study should be mentioned, especially concerning the estimation of disability preva- lence and HE. First, the disability prevalence used for HE estimation was based on LTCI data. As a previous study demonstrated, utilization of LTCI services was dependent on not only the level of disability but also socioeconomic conditions such as household income and family struc- ture [41]. However, LTCI in Japan provides consistent insurance across the nation and universally covers all eld- erly persons aged over 65 years [42], and thus, the influ- ence of socioeconomic conditions on service utilization and regional variation would seem to be relatively small. In addition, LTCI data are the sole source for routine esti- mation of HE at present. Second, the disability prevalence (SCR) was estimated by hierarchal regression and MCMC procedure (fully Bayes method) [27-31]. Bayes estimation is commonly used for data smoothing in small area anal- ysis and disease mapping, while alternative methods including empirical Bayes estimation can be applied [29- 31,43-46]. Although SMCZ is generally used as a higher- level regional unit for Bayes estimation of municipal mor- tality data in Japan [24,26,47,48], an alternative hierarchi- cal setting of regional levels would result in different figures of SCR, and consequently of HE. Finally, HE65 was estimated by a simple linear regression formula based on prefectural data. The validity of the estimated HE was con- firmed by the municipal data of one prefecture, and the correlation coefficients between the precise and estimated HE were large enough to use the estimated HE for geo- graphical comparison, instead of the precise HE. How- ever, the application of this HE estimation for individual municipalities should be thought out. To expand the use of HE, the routine publication of detailed data of LTCI including the sex- and age-specific number of those certificated as needing nursing care is expected, which would enable calculation of the precise HE. The results of this study have several implications in pro- longing healthy longevity and supporting older people. The strong association between HE65 and socio-demo- graphic factors indicates the need for efforts in the social context. Especially, there should be a focus on older peo- ple living alone. Also, the strong relation between HE65 and socio-demographic factors in large municipalities indicates that older people living in urban areas lack a social support network and are vulnerable to socioeco- nomically disadvantaged conditions. The social support network including an informal network and community Page 7 of 9 (page number not for citation purposes)