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February 25, 2026SHILAP Revista de lepidopterología0 citationsOpen Access

Explaining the Spatial Changes of Fertility in Iran’s Counties: Patterns and Determinants (2011-2016)

RNReza NoubakhtADAhmad Dorahaki

Key Points

  • This study aims to analyze the spatial distribution of fertility rates in Iran and identify influential socioeconomic and demographic factors.
  • Conducted secondary data analysis of national census data from 429 counties in Iran (2011-2016)
  • Utilized descriptive statistics to summarize data trends
  • Employed ordinary least squares (OLS) regression and geographically weighted regression (GWR) for analysis
  • Central counties show better economic conditions and higher female education levels
  • Highest fertility rates observed in southeastern and eastern counties with similar socioeconomic contexts
  • GWR reveals female education significantly influences fertility rates in Western, Northern, and Northeastern counties but less so in Sistan and Baluchestan.

Abstract

Background: Fertility rates in Iran have undergone significant changes in recent decades, raising concerns about population dynamics and the country’s future demographic structure. This study investigates the spatial distribution of fertility across Iranian counties and examines the impact of socioeconomic and demographic variables on fertility patterns.Methods: This study employs a secondary data analysis approach. The dataset comprised 429 counties in Iran from 2011 to 2016, derived from national census data. Descriptive statistics, ordinary least squares (OLS) regression, and geographically weighted regression (GWR) were employed to investigate the spatially varying relationships between socioeconomic and demographic factors and fertility rates.Results: T he fi ndings i ndicate t hat c entral c ounties e xhibit favorable economic and social conditions, including higher levels of female education. Fertility rates were highest in southeastern and eastern counties, which shared similar socioeconomic contexts. GWR results showed that female education had the strongest influence on fertility in Western, Northern, and Northeastern counties, while its effect was lowest in Sistan and Baluchestan.Conclusion: Although all examined variables significantly contribute to explaining fertility variation, their relative influencediffers across geographical regions. Spatial analysis methods, which emphasize the role of location and place, reveal that the effects of determinants vary locally, providing a more precise understanding of county-level fertility patterns and their spatial interconnections.

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Cite This Study

Noubakht et al. (2025) studied this question.

synapsesocial.com/papers/699e920af5123be5ed04ff5bhttps://doi.org/10.30476/jhsss.2024.103259.1934
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