ABSTRACT
This study aims to provide a systematical introduction of age-period-cohort (APC) analysis to South Korean readers who are unfamiliar with this method (we provide an extended version of this study in Korean). As health data in South Korea has substantially accumulated, population-level studies that explore long-term trends of health status and health inequalities and identify macrosocial determinants of the trends are needed. Analyzing long-term trends requires to discern independent effects of age, period, and cohort using APC analysis. Most existing health and aging literature have used cross-sectional or short-term available panel data to identify age or period effects ignoring cohort effects. This under-use of APC analysis may be attributed to the identification (ID) problem caused by the perfect linear dependency across age, period, and cohort. This study explores recently developed three APC models to address the ID problem and adequately estimate the effects of A-P-C: intrinsic estimator-APC models for tabular age by period data; hierarchical cross-classified random effects models for repeated cross-sectional data; and hierarchical APC-growth curve models for accelerated longitudinal panel data. An analytic exemplar for each model was provided. APC analysis may contribute to identifying biological, historical, and socioeconomic determinants in long-term trends of health status and health inequalities as well as examining Korean's aging trajectories and temporal trends of period and cohort effects. For designing effective health policies that improve Korean population's health and reduce health inequalities, it is essential to understand independent effects of the three temporal factors by using the innovative APC models.
Subject(s)
Aging , Cohort Effect , Cohort Studies , Health Policy , Korea , Methods , Socioeconomic FactorsABSTRACT
This study aims to provide a systematical introduction of age-period-cohort (APC) analysis to South Korean readers who are unfamiliar with this method (we provide an extended version of this study in Korean). As health data in South Korea has substantially accumulated, population-level studies that explore long-term trends of health status and health inequalities and identify macrosocial determinants of the trends are needed. Analyzing long-term trends requires to discern independent effects of age, period, and cohort using APC analysis. Most existing health and aging literature have used cross-sectional or short-term available panel data to identify age or period effects ignoring cohort effects. This under-use of APC analysis may be attributed to the identification (ID) problem caused by the perfect linear dependency across age, period, and cohort. This study explores recently developed three APC models to address the ID problem and adequately estimate the effects of A-P-C: intrinsic estimator-APC models for tabular age by period data; hierarchical cross-classified random effects models for repeated cross-sectional data; and hierarchical APC-growth curve models for accelerated longitudinal panel data. An analytic exemplar for each model was provided. APC analysis may contribute to identifying biological, historical, and socioeconomic determinants in long-term trends of health status and health inequalities as well as examining Korean's aging trajectories and temporal trends of period and cohort effects. For designing effective health policies that improve Korean population's health and reduce health inequalities, it is essential to understand independent effects of the three temporal factors by using the innovative APC models.
Subject(s)
Aging , Cohort Effect , Cohort Studies , Health Policy , Korea , Methods , Socioeconomic FactorsABSTRACT
Abstract The aim of this research was to evaluate age-related changes in the smile of Brazilian women. The sample consisted of 249 Brazilian women who had not undergone previous orthodontic treatment or facial surgery. They were divided into four groups, according to age: G1 (20-29), G2 (30-39), G3 (40-49) and G4 (50 or older). Standardized front view photographs were taken while smiling and at rest. Measurements were evaluated by ANOVA and post-hoc Tukey. The Chi-square test was applied for qualitative variables. Upper lip thickness at rest and exposure of upper incisors on smiling decreased with age. Most individuals (60.9%) exhibited a medium smile. High smiles were more often seen in G1 (45%) and less frequently in G4 (18.8%), whereas the opposite occurred with the low smile, i.e., G4 (21.9%) and G1 (6.7%). Variations among the groups were observed in the transverse exposure of the teeth on smiling. In G1 and G3, there was a balance between tooth exposures, so that the teeth were exposed as far as the premolars and/or molars. Most of the women (56.3%) in G2 exposed their teeth as far as the first molars on smiling, whereas most of those (40.6%) in G4 exposed their teeth only as far as the first premolars on smiling. As age increased, there was decreased exposure of the upper incisors, decreased upper lip thickness and lower exposure of teeth vertically and transversely.
Subject(s)
Humans , Female , Adult , Aged , Young Adult , Smiling/physiology , Aging/physiology , Face/anatomy & histology , Reference Values , Brazil , Photography , Observer Variation , Age Factors , Esthetics, Dental , Middle Aged , OdontometryABSTRACT
The relative age effect, which is the advantage obtained by an athlete born closer to the beginning of the selection year, has been shown to be an important variable in the development of soccer players. This study aimed to evaluate the influence of the season of birth on the choice reaction time (CRT) of elite soccer athletes in the under 13 years of age category. Seventy-six athletes participated who were 13.36 ± 0.45 years old. The volunteers were tested with a CRT test, and the results were divided according to the semester of birth (S1 or S2). We conducted a t-test in order to compare the results between groups and a Pearson correlation analysis to verify the associations between variables. The results indicated no differences in reaction time (r= .033 and p = .772) or movement time (r = .0073 and p = .530). It was concluded that for this population, the season of birth does not influence the performance of the capabilities tested.
O efeito da idade relativa, que consiste na vantagem obtida pelo atleta nascido mais próximo ao início do ano de seleção, tem se mostrado uma variável importante para o processo de seleção de esportistas. Este estudo objetivou avaliar a influência da época de nascimento no tempo de reação de escolha de futebolistas presentes nas categorias de base (sub 13) de clubes profissionais futebol. Participaram 76 atletas com idade de 13,36 ± 0,45 anos. Os voluntários foram submetidos ao teste do TRE, e os resultados categorizados conforme o semestre de nascimento (S1 ou S2). Foi empregado o teste t para a comparação entre grupos, e análise de Correlação de Pearson para verificar a existência de associações entre as variáveis. Os resultados não indicaram diferenças entre os grupos no tempo de reação (r = 0,033 e p = 0,772) e no tempo de movimento (r = 0,0073 e p = 0,530). Concluiu-se que para essa população, a época de nascimento não influencia no desempenho dessa capacidade.
El efecto de la edad relativa, que consiste en el beneficio obtenido por el atleta nacido más cercano al inicio del año de selección ha sido una variable importante para el proceso de selección de los atletas. Este estudio tuvo como objetivo evaluarla influencia de la época de nacimiento en el tiempo de reacción de los jugadores presentes en los jóvenes (menores de 13) de los clubes de fútbol profesional. Participaron 76 atletas de edad 13,36 ± 0,45 años. Los voluntarios fueron sometidos a la prueba de la TRE, y se clasificaron de acuerdo con el semestre de nacimiento (S1 o S2). Se utilizó el "teste t" para la comparación entre los grupos, y el análisis de correlación de Pearson para verificar la existencia de asociaciones entre variables. Los resultados indicaron que no hubo diferencias entre los grupos en el tiempo de reacción (r = 0,033 e p = 0,772) y el Tiempo de Movimiento (r = 0,0073 e p = 0,530). Se concluyó que para esta población, la fecha de nacimiento no influye en el rendimiento de esta capacidad.