Aluísio J D Barros1, Cesar G Victora. 1. Centro de Pesquisas Epidemiológicas, Universidade Federal de Pelotas, Pelotas, RS, Brasil. abarros@epidemio-ufpel.org.br
Abstract
OBJECTIVE: To propose an asset based indicator of wealth for Brazil using variables present in the demographic census. METHODS: The indicator, named IEN (Indicador Econômico Nacional/ National Wealth Score), was developed using 12 assets and the schooling of the household head, through principal component analysis. Data from the 2000 Brazilian Demographic sample was used for deriving the score and for the calculation of decile cut-off points. RESULTS: The indicator, first component obtained from the analysis with the 13 variables, retained 38% of the total variability, and presented a Spearman correlation of 0,74 with total family income and of 0,67 with per capita income. The necessary scores to calculate the indicator are presented, as well as reference distributions for the 27 states and their capitals, the five major regions as for the whole country. An example of use of indicator is presented. CONCLUSIONS: Differently from other economic indicators, the Indicador Econômico Nacional has local reference distributions available, along with the national distribution. It is therefore possible to compare a study sample to the municipal, state or country distribution. The small number of variables allow investigators to calculate the Indicador Econômico Nacional in research studies where economic classification is of interest.
OBJECTIVE: To propose an asset based indicator of wealth for Brazil using variables present in the demographic census. METHODS: The indicator, named IEN (Indicador Econômico Nacional/ National Wealth Score), was developed using 12 assets and the schooling of the household head, through principal component analysis. Data from the 2000 Brazilian Demographic sample was used for deriving the score and for the calculation of decile cut-off points. RESULTS: The indicator, first component obtained from the analysis with the 13 variables, retained 38% of the total variability, and presented a Spearman correlation of 0,74 with total family income and of 0,67 with per capita income. The necessary scores to calculate the indicator are presented, as well as reference distributions for the 27 states and their capitals, the five major regions as for the whole country. An example of use of indicator is presented. CONCLUSIONS: Differently from other economic indicators, the Indicador Econômico Nacional has local reference distributions available, along with the national distribution. It is therefore possible to compare a study sample to the municipal, state or country distribution. The small number of variables allow investigators to calculate the Indicador Econômico Nacional in research studies where economic classification is of interest.
Authors: Andréa D Bertoldi; Aluísio J D Barros; Aline Lins Camargo; Pedro C Hallal; Sotiris Vandoros; Anita Wagner; Dennis Ross-Degnan Journal: Am J Public Health Date: 2010-08-19 Impact factor: 9.308
Authors: Aluísio J D Barros; Iná S Santos; Alicia Matijasevich; Marlos Rodrigues Domingues; Mariângela Silveira; Fernando C Barros; Cesar G Victora Journal: Rev Saude Publica Date: 2011-06-10 Impact factor: 2.106
Authors: Tarique Md Nurul Huda; Wolf-Peter Schmidt; Amy J Pickering; Zahid Hayat Mahmud; Mohammad Sirajul Islam; Md Sajjadur Rahman; Stephen P Luby; Adam Biran Journal: Am J Trop Med Hyg Date: 2018-02-08 Impact factor: 2.345
Authors: T M Moore; I K Martin; O M Gur; C T Jackson; J C Scott; M E Calkins; K Ruparel; A M Port; I Nivar; H D Krinsky; R E Gur; R C Gur Journal: Psychol Med Date: 2015-10-23 Impact factor: 7.723
Authors: Iná S Santos; Denise M Mota; Alicia Matijasevich; Aluísio J D Barros; Fernando C F Barros Journal: J Pediatr Date: 2009-10 Impact factor: 4.406