Hierarchical Analysis of Age, Period, and Cohort Effects on Diabetes Mellitus Mortality in Colombia, 1983-2022

Background: Diabetes mellitus (DM) mortality in Colombia has varied over time, yet the individual and contextual factors driving these changes have been scarcely explored. This study aimed to analyze the associations of age, area of death, period, and birth cohort on DM mortality. Methods: Analytica...

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Autores:
Pérez Bedoya, Juan Pablo
Pérez Aguirre, Carlos Andrés
Barengo, Noël Christopher
Díaz Valencia, Paula Andrea
Tipo de recurso:
http://purl.org/coar/resource_type/c_18co
Fecha de publicación:
2025
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/46317
Acceso en línea:
https://hdl.handle.net/10495/46317
Palabra clave:
Diabetes Mellitus - Mortalidad
Diabetes Mellitus - Mortality
Factores de Riesgo
Risk Factors
Estrategias de Salud
Health Strategies
Estudio Observacional
Observational Study
Distribución por Edad y Sexo
Age and Sex Distribution
https://id.nlm.nih.gov/mesh/D003920
https://id.nlm.nih.gov/mesh/D012307
https://id.nlm.nih.gov/mesh/D064888
ODS 3: Salud y bienestar. Garantizar una vida sana y promover el bienestar de todos a todas las edades
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-sa/4.0/
Description
Summary:Background: Diabetes mellitus (DM) mortality in Colombia has varied over time, yet the individual and contextual factors driving these changes have been scarcely explored. This study aimed to analyze the associations of age, area of death, period, and birth cohort on DM mortality. Methods: Analytical, cross-sectional study based on mortality records and population projections from the statistics department. DM deaths were identified using ICD-9 and ICD-10 codes, grouped by age (A), period (P), cohort (C), sex, and area of death (urban/rural) in five-year intervals. A hierarchical APC-Cross-Classified Random Effects Model (HAPC-CCREM) with random intercepts was applied, using a negative binomial regression (log link function). Sex and age were included as fixed-effect predictors (level 1) estimating Mortality Rate Ratios (MRR). Period and cohort groups were included as contextual random effects (level 2) in a cross-classified structure interacting with the area of death. Population projections were incorporated as an offset term. Analyses were conducted in R with the glmmTMB package. Results: Sex and age were statistically significantly associated with DM mortality. Women exhibited a higher mortality rate than men (MRR: 1.21; 95% confidence interval (CI): 1.16–1.26). Additionally, mortality increased with age, with an MRR of 0.06 (95% CI: 0.05–0.08) for ages 0–4 and 87.05 (95% CI: 71.43–106.08) for ages 85 years and older, compared to the 40–44 year-old age group. Regarding random period effects, DM mortality was consistently higher in urban areas, with an increase until 1998–2002, followed by a decrease from 2003 to 2017, and a subsequent rise in 2018–2022. For random cohort effects, mortality was higher in urban areas up to the 1963–1967 cohort. However, in more recent cohorts, mortality has been higher in rural areas. Conclusions: Public health strategies to reduce DM mortality should address regional differences and prioritize healthy aging.