BMC Public Health 2005, 5:65 http://www.biomedcentral.com/1471-2458/5/65 through disease prevention and health promotion [7]. However, it is difficult to calculate and monitor HE for health policy planning and evaluation, especially at the local level, because of a lack of data on morbidity. Although previous studies have calculated HE at the pre- fectural level in Japan, these calculations used inconsist- ent and various databases of disability prevalence, and could not be applied at the municipal level because of limited availability of data [8-10]. In Japan, long-term care insurance (LTCI) was introduced in 2000 for older people needing nursing care, and citi- zens aged 40 years or over can receive insurance benefits after application and certification that they need nursing care. Since LTCI unions are managed by municipalities, it is theoretically possible to calculate HE using the munici- pal data of LTCI as morbidity. However, municipal HE has been calculated in only one prefecture [11], because the sex- and age-specific prevalence of those certificated as needing nursing care for LTCI by municipalities is not rou- tinely published. It was confirmed by previous studies that socio-demo- graphic factors influence mortality, morbidity, and other health conditions of older people [12-15]. Socioeconomic status such as education level, occupational social class, and income has been demonstrated to be a critical factor predicting the health status of older people [13,15]. Fam- ily structure and living arrangement have been elicited as other critical factors influencing the health of older peo- ple, and conditions such as living alone and being wid- owed/divorced are related to poorer health status [16,17]. There was little relation between HE and socio-demo- graphic indicators related to income and family structure at the prefectural level in Japan [18], while a municipal- level study in one prefecture showed a weak but signifi- cant relation between HE and socio-demographic indica- tors such as the percentage of nuclear households [11]. The relation between health status and regional character- istics might have been obscured due the higher level anal- ysis which included heterogeneous smaller level regions, as a previous study demonstrated that the relation differed according to the area classification by urban-rural differ- ence [19]. Analysis at different levels could lead to an inconsistent relation, and the smaller-area analysis more directly reflects the relation at the individual and house- hold levels [20,21]. Therefore, studies examining the rela- tion between socio-demographic factors and health including not only death but also morbidity at a smaller level will provide reliable evidence of the influence of socio-demographic factors on health in older people. The purposes of this study were to estimate HE of older people at the municipal level across Japan, and to eluci- date the association between HE and area socio-demo- graphic factors. Methods Study units Japan consists mainly of four islands (a map is shown in Figures 1 and 2). Hokkaido Island is located in the north- ern part, and includes only one prefecture (Hokkaido pre- fecture). The mainland (Honshu) includes several metropolitan areas such as Tokyo, Nagoya, and Osaka. The other islands are Shikoku and Kyushu. According to Local Autonomy Law, local public entities in Japan are divided into two categories. The first category consists of cities, towns, and villages. The second category consists of prefectures (N = 47). All districts in the country belong to one of the municipalities and at the same time fall within the boundaries of one of the prefectures. As specific cases, the Tokyo prefecture (Tokyo Metropolis) includes 23 special wards ("ku") in addition to cities, towns and villages, and 12 large cities ("cities designated by ordinance") such as Nagoya and Osaka consist of wards ("ku"). In total, there were 3361 units of cities, towns and villages as well as Tokyo special wards and wards of cities designated by ordinance in December 2001. Estimation of health expectancy Calculation of HE by the Sullivan method requires life- table data and the sex- and age-specific morbidity [6]. However, municipal data of the sex- and age-specific number of those certificated as needing nursing care for LTCI are not available, and only the total number was available by insurance union. Therefore, this study esti- mated HE at 65 years (HE65) by a linear regression for- mula using life expectancy at 65 years (LE65) and the certificated rate in LTCI (P): HE65 = a + b × LE65 + c × P. The formula was drawn from prefectural data (N = 47) of precise HE65, which was calculated by the Sullivan method with the prefectural life-table in 2000 [22] and the sex- and age-specific certification rate of LTCI in 2002 [23]. The coefficient of determinant (R2) for the regression with LE65 and the crude certification rate was 0.913 for men and 0.906 for women. When the standardized certi- fication ratio (SCR), which was age-standardised by the indirect method, was used as a predictor, R2 was increased to 0.986 for men and 0.982 for women. The validity of this estimation was confirmed by the municipal data (N = 59) of one prefecture (Shimane pre- fecture), in which the precise HE65 had been calculated by the Sullivan method [11]. The correlation coefficient between the precise HE65 and estimated HE65 predicted Page 2 of 9 (page number not for citation purposes)