Dependency Ratios and the Changing Geography of Intergenerational Burden in Taraba State, Nigeria

Authors

Karma Magaji

Department of General Studies, College of Agriculture, Science and Technology, Jalingo, Taraba State (Nigeria)

Oliver Philip

Department of General Studies, College of Agriculture, Science and Technology, Jalingo, Taraba State (Nigeria)

Abdulhamid Sabo

Department of General Studies, College of Agriculture, Science and Technology, Jalingo, Taraba State (Nigeria)

Paul Yakojo

Department of General Studies, College of Agriculture, Science and Technology, Jalingo, Taraba State (Nigeria)

Article Information

DOI: 10.51244/IJRSI.2026.1307000213

Subject Category: geography

Volume/Issue: 13/7 | Page No: 2854-2868

Publication Timeline

Submitted: 2026-07-22

Accepted: 2026-07-28

Published: 2026-08-07

Abstract

This study examined dependency ratio dynamics and their demographic, spatial, and fiscal implications across the sixteen Local Government Areas (LGAs) of Taraba State, Nigeria, with reference to national development priorities and the Sustainable Development Goals (SDGs). The study adopted a sequential explanatory mixed-methods research design, integrating secondary demographic data with a structured household survey. Secondary data were obtained from the National Population Commission, National Bureau of Statistics, Taraba State Government publications, and international demographic databases, while primary data were collected from 450 household heads across the sixteen LGAs of Taraba State, of which 437 questionnaires (97.1%) were valid for analysis. Descriptive statistics, dependency ratio estimation, and spatial classification techniques were employed to analyse the data. The findings revealed that 51.0% of surveyed households were classified as having high dependency, while 32.7% had moderate dependency, indicating that 83.7% of households experienced moderate-to-high demographic burden. Spatial analysis further showed marked geographical disparities, with eight LGAs (50.0%) classified as high dependency, seven LGAs (43.8%) as moderate dependency, and only Jalingo (6.3%) classified as low dependency. The findings support the propositions of Demographic Dividend Theory and Fiscal Federalism Theory, demonstrating that demographic structure significantly influences household welfare, public service demand, and fiscal sustainability. The study concludes that reducing dependency burden through demographic-sensitive planning is essential for accelerating progress towards SDG 1, SDG 3, SDG 4, and SDG 8. It recommends the integration of dependency indicators into fiscal allocation frameworks, increased investment in reproductive health, education, and employment generation, and the institutionalisation of routine LGA-level demographic monitoring to support evidence-based development planning in Taraba State.

Keywords

Dependency ratio; intergenerational burden; demographic burden; demographic dividend

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