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Rev Esp Salud Publica. 2018 Dec 10;92. pii: e201812087.

[Construction of a deprivation index by Basic Healthcare Area in Aragon using Population and Housing Census 2011].

[Article in Spanish; Abstract available in Spanish from the publisher]

Author information

1
Dirección General de Salud Pública. Gobierno de Aragón. Zaragoza. España.
2
Instituto Aragonés de Estadística. Gobierno de Aragón. Zaragoza. España.
3
Departamento de Microbiología, Medicina Preventiva y Salud Pública. Universidad de Zaragoza. Zaragoza. España.

Abstract

in English, Spanish

OBJECTIVE:

The measurement of inequalities using composite indicators facilitates the prioritization and implementation of public health actions. The most commonly source of information used for this has been the Population and Housing Census of 2011 (PCH_2011).The objective of this study was to evaluate the use of PHC_2011 and develop a deprivation index (DI) by Basic Healthcare Area (BHA) and to analyse its association with mortality in Aragon.

METHODS:

Ecological study by BHA. Since PHC_2011 was a sample of the population it was validated by the Chi-square test for homogeneity. 26 socioeconomic indicators were calculated. Spearman correlation coefficients were used to evaluate the relationship between socioeconomic indicators and Standardized Mortality Ratios (SMR). Principal Component Analyses (PCA) were conducted using the indicators in which a significant correlation was found. Components with eigenvalues higher than 1 were extracted, and the rotated matrix (Varimax) was obtained. PCA from each component were conducted, extracting only one factor. BHA were grouped into, according to the deprivation index values. Mortality rates adjusted to the European Standard Population by age, sex and quartile were calculated. The most discriminant factor by quartiles was considered DI. A different DI for urban areas was obtained from the same variables.

RESULTS:

The validation of PHC sample detected 4 underrepresented BHA. 17 socioeconomic indicators were significatively correlated with SMR. From the first PCA, 3 components were obtained. The DI included %unemployment, %eventual workers, % insufficient education 16-64 years old and %foreigners. The % of variance explained by the DI was 59.7% and 73.8% in urban areas. In men, mortality in the quartile with the lowest deprivation (544,7 per 105; CI95%: 515,8-573,6) was significatively lower than in the most deprivated areas(618,7 per 105;CI95%:589,4-648,0).

CONCLUSIONS:

This new DI allows us to identify deprived BHA. This is a useful tool to bring to light health inequalities and to plan interventions according to population´s needs.

KEYWORDS:

Census; Factor analysis; Health inequalities; Socieconomic factors; Spain; Statistical

PMID:
30531710
[Indexed for MEDLINE]
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