Monitoring socioeconomic health inequalities using a High Poverty Neighbourhood Index
Abstract
Background: Public health monitoring needs timely and comparable indicators of socioeconomic health inequalities. Yet administrative health data rarely include individual-level socioeconomic variables, such as income, education or occupation. Using national Czech data, this study illustrates a transferable approach to monitoring contextual health inequalities through linkage to a small-area High Poverty Neighbourhood Index (HPNI).
Methods: The framework links routinely collected health data with a contextual deprivation measure. In this case, the HPNI is constructed at the level of basic settlement units and categorizes areas into six ordered groups according to the proportion of residents receiving the subsistence allowance, based on data from the Ministry of Labour and Social Affairs. Individuals in the National Health Information System in 2023 are linked to HPNI categories through their residential address. The framework includes address-based linkage, small-area aggregation, exclusion of uninhabited and low-population areas, and identification of biased units, such as institutional addresses. The resulting stratification supports routine monitoring, standardized reporting and comparison of health outcomes across deprivation gradients.
Results: Applying the HPNI reveals a pronounced socioeconomic gradient in health in Czechia. In 2023, life expectancy at birth differed by approximately 8 years among men and 5 years among women between the least and most disadvantaged areas. The framework supports regular reporting of inequalities in mortality, morbidity and other health indicators, and enables monitoring of trends over time.
Conclusions: The HPNI provides a practical, transferable way to monitor socioeconomic health inequalities when individual socioeconomic data are unavailable. By capturing contextual disadvantage, it supports consistent reporting on health inequalities and helps identify populations and areas where targeted public health action may be needed.
Key messages: • A small-area High Poverty Neighbourhood Index helps monitor and report socioeconomic health inequalities using administrative health data.
• Linking health records with contextual deprivation measures offers a transferable approach to health inequality surveillance in Czechia and beyond.
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BibTeX
@article{lustigova2026monitoring,
title = {{Monitoring socioeconomic health inequalities using a High Poverty Neighbourhood Index}},
author = {M Lustigova and P Netrdova and K Hulikova Tesarkova and K Benesova and D Dzurova},
journal = {The European Journal of Public Health},
year = {2026},
month = oct,
doi = {10.1093/eurpub/ckag169.870},
url = {https://doi.org/10.1093/eurpub/ckag169.870},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - Monitoring socioeconomic health inequalities using a High Poverty Neighbourhood Index
AU - M Lustigova
AU - P Netrdova
AU - K Hulikova Tesarkova
AU - K Benesova
AU - D Dzurova
PY - 2026
DA - 2026/10/01
JO - The European Journal of Public Health
DO - 10.1093/eurpub/ckag169.870
UR - https://doi.org/10.1093/eurpub/ckag169.870
AB - Background: Public health monitoring needs timely and comparable indicators of socioeconomic health inequalities. Yet administrative health data rarely include individual-level socioeconomic variables, such as income, education or occupation. Using national Czech data, this study illustrates a transferable approach to monitoring contextual health inequalities through linkage to a small-area High Poverty Neighbourhood Index (HPNI). Methods: The framework links routinely collected health data with a contextual deprivation measure. In this case, the HPNI is constructed at the level of basic settlement units and categorizes areas into six ordered groups according to the proportion of residents receiving the subsistence allowance, based on data from the Ministry of Labour and Social Affairs. Individuals in the National Health Information System in 2023 are linked to HPNI categories through their residential address. The framework includes address-based linkage, small-area aggregation, exclusion of uninhabited and low-population areas, and identification of biased units, such as institutional addresses. The resulting stratification supports routine monitoring, standardized reporting and comparison of health outcomes across deprivation gradients. Results: Applying the HPNI reveals a pronounced socioeconomic gradient in health in Czechia. In 2023, life expectancy at birth differed by approximately 8 years among men and 5 years among women between the least and most disadvantaged areas. The framework supports regular reporting of inequalities in mortality, morbidity and other health indicators, and enables monitoring of trends over time. Conclusions: The HPNI provides a practical, transferable way to monitor socioeconomic health inequalities when individual socioeconomic data are unavailable. By capturing contextual disadvantage, it supports consistent reporting on health inequalities and helps identify populations and areas where targeted public health action may be needed. Key messages: • A small-area High Poverty Neighbourhood Index helps monitor and report socioeconomic health inequalities using administrative health data. • Linking health records with contextual deprivation measures offers a transferable approach to health inequality surveillance in Czechia and beyond.
SN - 1101-1262
SN - 1464-360X
ER -