A 100-year Projection of Population Aging in Iran Through the Decomposition of Population Momentum

Two elderly people engaged in conversation in an institutional interior space with a wall clock, fluorescent lighting, and doorways visible in the background.
Image Credit: Photo by Age Cymru on Unsplash (SourceLicense)

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🌐 The original paper was published in Persian. This summary was generated from a Persian-language abstract.

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SHILAP Revista de lepidopterología·2026-03-01·Follow this topic (RSS)
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Overview

This study projects population aging in Iran over a 100-year period through decomposition of population momentum, focusing on the dynamics of age structure transformation. Population momentum, the tendency for population growth to continue even after fertility decline due to the age structure of the existing population, serves as the analytical framework for understanding Iran's demographic trajectory. The research addresses the demographic transition occurring in Iran, where declining fertility rates interact with existing age structures to produce distinct patterns of population aging. Using fertility and mortality data spanning 1996 to 2016, the analysis examines how momentum components contribute to future elderly population growth and eventual stabilization.

Methods and approach

The study employs the cohort-component method implemented in R software to generate a 100-year population projection based on fertility and mortality estimates from Iran covering the period 1996 to 2016. Population momentum is calculated and decomposed to isolate age-specific contributions to future population dynamics. The analysis examines momentum values at four temporal points (1996, 2006, 2011, and 2016) and conducts age-specific momentum decomposition to identify which age groups contribute most substantially to overall momentum. The cohort-component approach tracks cohorts through time, applying age-specific fertility and mortality rates to project future population size and structure. Age distribution trends are analyzed throughout the projection period to characterize the progression of population aging.

Key Findings

Population momentum in Iran remained positive across all examined time points (1996, 2006, 2011, 2016) but exhibited gradual magnitude decline. Age-specific momentum decomposition revealed that the elderly population contributed the highest momentum values. The projection indicates a fourfold increase in Iran's elderly population, driven substantially by population momentum effects. The aging index is projected to increase from approximately 25 in 2016 to 110 by 2061, representing a dramatic shift in age structure. Beyond 2061, the elderly population growth trajectory reverses as momentum approaches zero and subsequently becomes negative, attributable to sustained low fertility rates. This temporal pattern indicates a distinct demographic phase structure, with rapid aging followed by stabilization and eventual decline in elderly population growth.

Implications

The findings demonstrate that Iran faces a compressed timeline of population aging, with implications for social infrastructure and policy development. The projected fourfold increase in the elderly population by 2061 presents substantial challenges for systems currently underprepared for aging populations. The declining and ultimately negative momentum after 2061 suggests a demographic transition to a mature age structure with implications for long-term population sustainability. The analysis indicates urgent requirements for policy reform across retirement systems, healthcare infrastructure, elderly care provision, and family support structures. The temporal concentration of aging—rapid growth until 2061 followed by stabilization—creates a critical window for institutional adaptation and resource allocation planning.

Disclosure

  • Research title: A 100-year Projection of Population Aging in Iran Through the Decomposition of Population Momentum
  • Authors: Nazanin Aghaei, Rasoul Sadeghi, Majid Koosheshi, Hassan Eini Zeinab
  • Publication date: 2026-03-01
  • OpenAlex record: View
  • Image credit: Photo by Age Cymru on Unsplash (SourceLicense)
  • Disclosure: This post was generated by Claude (Anthropic). The original authors did not write or review this post.

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