BackgroundWhat are the factors that affect the survival probability of becoming a centenarian for those aged 70? Do the factors include income, health expenditure, the use of mobile telephones, or sanitation? The survival probability of becoming a centenarian (SPBC) is defined as an estimate of the production of centenarians by a population. The SPBC (70) is the survival probability of becoming a centenarian for those aged 70. This study estimates the associations between the SPBC (70), and the gross national income, health expenditure, telecommunications, and sanitation facilities in 32 countries.MethodsThe socioeconomic indicators for this study were obtained from the database of the United Nations Development Programme. In addition, the data for the analysis of centenarians in 32 countries were obtained from the Human Mortality Database, which is maintained by the Department of Demography at the University of California, Berkeley, USA, and the Max Planck Institute for Demographic Research in Rostock, Germany. Associations between socioeconomic indicators and SPBC (70) were assessed using Pearson’s correlation coefficients and multiple regression models.ResultsSignificant positive correlations were found between the SPBC (70), and the socioeconomic factors of gross national income (GNI), public expenditure on health as a percentage of gross domestic product (PEHGDP), fixed and mobile telephone subscribers (FMTS) as the standard of living, and improved sanitation facilities (ISF). Overall, the SPBC (70) of female and male predictors were used, in order to form a model production of centenarians, with higher GNI and PEHGDP, as well as higher FMTS and ISF as the socioeconomic factors (R2= 0.422, P< 0.001).ConclusionsThe socioeconomic level in all 32 countries appears to have an important latent effect on the production of centenarians in both females and males. This study has identified the following four important aspects of socioeconomic indicators in the survival probability of becoming a centenarian for those aged 70: higher overall economic development level, public expenditure on health, mobile telephone subscribers as the standard of living, and the use of improved sanitation facilities for healthy aging. Thus, the socioeconomic level seems to affect an important on the survival probability of becoming a centenarian.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2318-14-113) contains supplementary material, which is available to authorized users.

This study confirms the associations between healthy life expectancy (HLE) and country-level socioeconomic factors. Our analysis is based on HLE data of 178 countries obtained from the World Health Organization. Data on country-level socioeconomic indicators were obtained from the World Bank database and the United Nations. The associations between socioeconomic indicators and HLE are assessed using Pearson's correlation coefficients and multiple regression models. Our findings show significant positive correlations between HLE and the following country-level socioeconomic factors: national income level (INI: r = 0.775, p = 0.001), urban population (UP: r = 0.711, p = 0.001), mean years of schooling (MYS: r = 0.756, p = 0.001), and internet users (IU: r = 0.795, p = 0.001). Predictors of female and male HLE are used to build a model that predicts HLE by overall higher levels of INI, UP, MYS, and IU (R 2 = 0.724, p \ 0.001). Based on our results, country-level socioeconomic indicators seem to have an important effect on healthy life expectancy.

BackgroundWhat is the factor that affects healthy life expectancy? Healthy life expectancy (HLE) at birth may be influenced by components of the gender inequality index (GII). Notably, this claim is not tested on the between components of the GII, such as population at least secondary education (PLSE) with ages 25 and older, labor force participation rate (LFPR) with ages 15 and older, and the HLE in the world’s countries. Thus, this study estimates the associations between the PLSE, LFPR of components of the GII and the HLE.MethodsThe data for the analysis of HLE in 148 countries were obtained from the World Health Organization. Information regarding the GII indicators for this study was obtained from the United Nations database. Associations between these factors and HLE were assessed using Pearson correlation coefficients and regression models.ResultsAlthough significant negative correlations were found between HLE and the LFPR, positive correlations were found between HLE and PLSE. Finally, the HLE predictors were used to form a model of the components of the GII, with higher PLSE as secondary education and lower LFPR as labor force (R2 = 0.552, P <0.001).ConclusionsGender inequality of the attainment secondary education and labor force participation seems to have an important latent effect on healthy life expectancy at birth. Therefore, in populations with high HLE, the gender inequalities in HLE are smaller because of a combination of a larger secondary education advantage and a smaller labor force disadvantage in male-females.

This study estimated the associations between community-level socioeconomic conditions and survival probability of becoming a centenarian (SPBC) for those aged 65 to 69 in South Korea to determine the social structural influences on healthy aging. The indicators of socioeconomic and data of centenarians were obtained from Statistics Korea database 2014: population census and social survey. Significant positive correlations were found between SPBC and community-level socioeconomic conditions (minimum cost of living and economically active population, water supply and sewerage, pave a road with asphalt, and urbanization). SPBC male and female predictors had higher economic level and base facilities (R2)=0.578, p<.001). The study provides evidence that community-level socioeconomic conditions are important correlates of SPBC for those aged 65 to 69 in South Korea. These strategies should include social structural influences on successful aging in the overall socioeconomic conditions.

The remaining years of healthy life expectancy (RYH) at age 65 years can be calculated as RYH (65) = healthy life expectancy-aged 65 years. This study confirms the associations between socioeconomic indicators and the RYH (65) in 148 countries. The RYH data were obtained from the World Health Organization. Significant positive correlations between RYH (65) in men and women and the socioeconomic indicators national income, education level, and improved drinking water were found. Finally, the predictors of RYH (65) in men and women were used to build a model of the RYH using higher socioeconomic indicators (R(2 )= 0.744, p < .001). Overall country-level educational attainment, national income level, and improved water quality influenced the RYH at 65 years. Therefore, policymaking to improve these country-level socioeconomic factors is expected to have latent effects on RYH in older age.