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1.
Geriatr Gerontol Int ; 22(7): 511-515, 2022 Jul.
Article in English | MEDLINE | ID: mdl-35670130

ABSTRACT

AIMS: This study contributes to previous initiatives examining healthy and active aging in the Philippines. METHODS: We employed the Sullivan method to calculate healthy life expectancy (HLE) and active life expectancy (ALE) using the 2007 Philippine Survey on Aging and the 2018 Longitudinal Study of Ageing and Health. We compared the estimates at two time points, providing evidence of change over time. RESULTS: There was no statistically significant change in the relative proportion of HLE over time for both sexes, suggesting dynamic equilibrium. For men, the increase in life expectancy was mainly an increase in unhealthy state (UHLE). The slight increases in HLE for all ages were not statistically significant. The differences in relative increase in HLE were not statistically significant. HLE for women increased over time, with statistically significant increases at ages 60 and 70 years. ALE declined in all age groups for both sexes, but the decline was statistically significant only among women in their 60s and 70s. There was also a statistically significant decline in the proportion of remaining life in an active state for all ages among both men and women, suggesting an expansion of morbidity. CONCLUSIONS: Findings suggest no evidence of compression of morbidity in the Philippines from 2007 to 2018. The HLE results suggest a dynamic equilibrium, while ALE results indicate an expansion of morbidity. The findings emphasize the need for the government to promote life course interventions that foster healthy choices and conduct further research to understand the factors influencing longevity and active aging in the Philippines. Geriatr Gerontol Int 2022; 22: 511-515.


Subject(s)
Health Status , Life Expectancy , Aged , Female , Humans , Longitudinal Studies , Male , Morbidity , Philippines/epidemiology
2.
PLoS One ; 15(6): e0235306, 2020.
Article in English | MEDLINE | ID: mdl-32589645

ABSTRACT

This paper investigates the profile of COVID-19 cases in Hong Kong, highlighting the unique age structure of confirmed cases compared to other territories. While the majority of cases in most territories around the world have fitted an older age profile, our analysis shows that positive cases in Hong Kong have been concentrated among younger age groups, with the largest incidence of cases reported in the 15-24 age group. This is despite the population's rapidly aging structure and extremely high levels of population density. Using detailed case data from Hong Kong's Centre for Health Department and Immigration Department, we analyze the sex and age distribution of the confirmed cases along with their recent travel histories and immigration flows for the period January to April 2020. Our analysis highlights Hong Kong's high proportion of imported cases and large overseas student population in developing COVID-19 hotspot areas such as the United Kingdom. Combined with community action and targeted and aggressive early policy measures taken to contain the virus, these factors may have contributed to the uniquely younger age structure of COVID-19 cases in the city. Consequently, this young profile of confirmed cases may have prevented fatalities in the territory. Recent research has highlighted the importance of a demographic approach to understanding COVID-19 transmission and fatality rates. The experience in Hong Kong shows that while an older population age structure may be important for understanding COVID-19 fatality, it is not a given. From a social science perspective at least, there is 'no easy answer' to why one area should experience COVID-19 differently from another.


Subject(s)
Coronavirus Infections/epidemiology , Emigration and Immigration , Pneumonia, Viral/epidemiology , Travel , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Betacoronavirus , COVID-19 , Child , Child, Preschool , Communicable Disease Control , Female , Hong Kong/epidemiology , Humans , Infant , Infant, Newborn , Male , Middle Aged , Pandemics , Population Dynamics , SARS-CoV-2 , Sex Distribution , Young Adult
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