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<p>Healthcare disparities pose a critical challenge to attaining equitable human development, particularly in developing countries like India. Such disparities, entrenched in socio-economic, demographic, and geographical factors, manifest as unequal access to healthcare services and facilities across regions. Maharashtra, one of India’s most developed states and home to over 9% of the national population, presents a compelling case for analysis. This study employs multivariate statistical techniques on cross-sectional secondary data to construct a Composite Healthcare Index (CHI) integrating availability, amenities, and affordability. The analysis reveals stark regional inequalities: districts in Konkan and Western Maharashtra display robust healthcare status, while much of Vidarbha, Marathwada, and North Maharashtra face severe deficits in healthcare facilities, service provision, and affordability. Hotspot analysis (Getis-Ord Gi*) confirms spatial clusters, with high-performing clusters in the west and persistent cold spots in disadvantaged interiors. Regression results further demonstrate the significance of per capita income and literacy as key predictors of healthcare performance, underscoring the role of economic capacity and human capital in shaping outcomes. The study concludes that uniform policy measures are insufficient; instead, region-specific interventions aligned with the Sustainable Development Goals are required.</p>

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Spatial disparities of healthcare services in Maharashtra, India: a multivariate analysis

  • 期刊论文

  • 发表日期：

    2025年9月26日

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  • Komal L. Turkar,
  • Ravindra G. Jaybhaye,
  • Yogesh P. Badhe

摘要

Healthcare disparities pose a critical challenge to attaining equitable human development, particularly in developing countries like India. Such disparities, entrenched in socio-economic, demographic, and geographical factors, manifest as unequal access to healthcare services and facilities across regions. Maharashtra, one of India’s most developed states and home to over 9% of the national population, presents a compelling case for analysis. This study employs multivariate statistical techniques on cross-sectional secondary data to construct a Composite Healthcare Index (CHI) integrating availability, amenities, and affordability. The analysis reveals stark regional inequalities: districts in Konkan and Western Maharashtra display robust healthcare status, while much of Vidarbha, Marathwada, and North Maharashtra face severe deficits in healthcare facilities, service provision, and affordability. Hotspot analysis (Getis-Ord Gi*) confirms spatial clusters, with high-performing clusters in the west and persistent cold spots in disadvantaged interiors. Regression results further demonstrate the significance of per capita income and literacy as key predictors of healthcare performance, underscoring the role of economic capacity and human capital in shaping outcomes. The study concludes that uniform policy measures are insufficient; instead, region-specific interventions aligned with the Sustainable Development Goals are required.