OBJECTIVES: The aim of the study was to create an index of socio-economic deprivation (SESDI) and to analyse correlation between SESDI and mortality data. METHODS: The SESDI components were selected from the census data (2001) at enumeration district and district level. Two methods were used for creating the SESDI: 1/ a sum of Z-scores of specific components (INDEX1); and 2/ standardized score - average values of specific components were divided by a maximum value of the specific component at the corresponding geographical level (INDEX2). Pearson's correlation coefficient was used for assessing the relationship between indices, and between indices and mortality data (SMR). RESULTS: The final indices were applied to districts in the Czech Republic (N = 77). The correlation of INDEX1 and INDEX2 was high (r = 0.99). Analysis of relationships between degree of deprivation and total and selected specific SMR in the Czech Republic confirmed that mortality was associated with degree of deprivation. CONCLUSION: The use of socio-economic deprivation indices in analysis of routinely collected mortality data in public health might help to explain health inequalities.
OBJECTIVES: The aim of the study was to create an index of socio-economic deprivation (SESDI) and to analyse correlation between SESDI and mortality data. METHODS: The SESDI components were selected from the census data (2001) at enumeration district and district level. Two methods were used for creating the SESDI: 1/ a sum of Z-scores of specific components (INDEX1); and 2/ standardized score - average values of specific components were divided by a maximum value of the specific component at the corresponding geographical level (INDEX2). Pearson's correlation coefficient was used for assessing the relationship between indices, and between indices and mortality data (SMR). RESULTS: The final indices were applied to districts in the Czech Republic (N = 77). The correlation of INDEX1 and INDEX2 was high (r = 0.99). Analysis of relationships between degree of deprivation and total and selected specific SMR in the Czech Republic confirmed that mortality was associated with degree of deprivation. CONCLUSION: The use of socio-economic deprivation indices in analysis of routinely collected mortality data in public health might help to explain health inequalities.
Authors: Min Hyeok Choi; Kyu Seok Cheong; Byung Mann Cho; In Kyung Hwang; Chang Hun Kim; Myoung Hee Kim; Seung Sik Hwang; Jeong Hun Lim; Tae Ho Yoon Journal: J Prev Med Public Health Date: 2011-11
Authors: Maciej Polak; Agnieszka Genowska; Krystyna Szafraniec; Justyna Fryc; Jacek Jamiołkowski; Andrzej Pająk Journal: Int J Environ Res Public Health Date: 2019-05-21 Impact factor: 3.390
Authors: Elodie Guillaume; Carole Pornet; Olivier Dejardin; Ludivine Launay; Roberto Lillini; Marina Vercelli; Marc Marí-Dell'Olmo; Amanda Fernández Fontelo; Carme Borrell; Ana Isabel Ribeiro; Maria Fatima de Pina; Alexandra Mayer; Cyrille Delpierre; Bernard Rachet; Guy Launoy Journal: J Epidemiol Community Health Date: 2015-12-11 Impact factor: 3.710
Authors: Katarina Rosicova; Sijmen A Reijneveld; Andrea Madarasova Geckova; Roy E Stewart; Martin Rosic; Johan W Groothoff; Jitse P van Dijk Journal: Int J Equity Health Date: 2015-11-05