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Household Deprivation in Kazakhstan

A Factor Analysis of Regional Disparities

Bibliographic Data

ID13024314
AuthorsAisulu Moldabekova (0000-0003-4330-5595, KIMEP University, corresponding author), А А Сатыбалдин (0000-0001-7421-4472, KIMEP University), A Omir (0000-0003-4912-1578, Almaty Management University), Erkin Sadykov (KIMEP University), Aigul Beimisheva (0000-0003-3281-6859, Narxoz University)
Year2025
Volume15
Issue9
Pages254-254
Publication date2025-09-11
Open AccessYes
TypeARTICLE
VenueSocieties (JOURNAL)
Journal identifiersISSN: 2075-4698 • E-ISSN: 2075-4698
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/soc15090254
OpenAlexW4414123576
LanguageEN
References cited46

This study investigates the multidimensional nature of household deprivation in Kazakhstan within the broader context of poverty reduction and sustainable development. Based on a nationally representative household survey (sample size 2005), the data were analyzed using factor analysis in SPSS 25 to uncover latent dimensions of deprivation. The analysis identified six components: socio-cultural, educational, medical, children’s basic needs, food, and infrastructure, which were synthesized into three integrated indices: basic, institutional, and socio-cultural. The results reveal pronounced regional disparities, with the southern and western regions showing higher levels of deprivation, whereas major cities perform significantly better. Income level is a key determinant: households below the subsistence minimum face the highest deprivation risk, particularly in the basic and institutional dimensions of deprivation. Sociocultural deprivation was weakly associated with income. These findings underscore the urgent need for regionally differentiated, income-sensitive policies to mitigate poverty and promote equity. This study offers empirical insights into an underexplored area, contributing to the understanding of household vulnerability in Kazakhstan

Context (archaeology · Household income · Poverty · Poverty reduction · Subsistence agriculture · Survey data collection · Sustainable development · Vulnerability (computing · Agricultural risk and resilience · Food Security and Health in Diverse Populations · Income, Poverty, and Inequality

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