Literature DB >> 21740660

Measuring socio-economic data in tuberculosis prevalence surveys.

F van Leth1, R S Guilatco2, S Hossain3, A H Van't Hoog4, N B Hoa5, M J van der Werf6, K Lönnroth7.   

Abstract

Addressing social determinants in the field of tuberculosis (TB) has received great attention in the past years, mainly due to the fact that worldwide TB incidence has not declined as much as expected, despite highly curative control strategies. One of the objectives of the World Health Organization Global Task Force on TB Impact Measurement is to assess the prevalence of TB disease in 22 high-burden countries by active screening of a random sample of the general population. These surveys provide a unique opportunity to assess socio-economic determinants in relation to prevalent TB and its risk factors. This article describes methods of measuring the socio-economic position in the context of a TB prevalence survey. An indirect measurement using an assets score is the most feasible way of doing this. Several examples are given from recently conducted prevalence surveys of the use of an assets score, its construction, and the analyses of the obtained data.

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Year:  2011        PMID: 21740660     DOI: 10.5588/ijtld.10.0417

Source DB:  PubMed          Journal:  Int J Tuberc Lung Dis        ISSN: 1027-3719            Impact factor:   2.373


  8 in total

Review 1.  The epidemiological advantage of preferential targeting of tuberculosis control at the poor.

Authors:  J R Andrews; S Basu; D W Dowdy; M B Murray
Journal:  Int J Tuberc Lung Dis       Date:  2015-04       Impact factor: 2.373

2.  Socio economic position in TB prevalence and access to services: results from a population prevalence survey and a facility-based survey in Bangladesh.

Authors:  Shahed Hossain; Mohammad Abdul Quaiyum; Khalequ Zaman; Sayera Banu; Mohammad Ashaque Husain; Mohammad Akramul Islam; Erwin Cooreman; Martien Borgdorff; Knut Lönnroth; Abdul Hamid Salim; Frank van Leth
Journal:  PLoS One       Date:  2012-09-27       Impact factor: 3.240

3.  Prevalence of self-reported tuberculosis, knowledge about tuberculosis transmission and its determinants among adults in India: results from a nation-wide cross-sectional household survey.

Authors:  Chandrashekhar T Sreeramareddy; H N Harsha Kumar; John T Arokiasamy
Journal:  BMC Infect Dis       Date:  2013-01-17       Impact factor: 3.090

4.  Socio-economic gradients in prevalent tuberculosis in Zambia and the Western Cape of South Africa.

Authors:  Tom A Yates; Helen Ayles; Finbarr P Leacy; A Schaap; Delia Boccia; Nulda Beyers; Peter Godfrey-Faussett; Sian Floyd
Journal:  Trop Med Int Health       Date:  2018-03-24       Impact factor: 2.622

5.  Asset and consumption gradient of health estimates in India: Implications for survey and public health research.

Authors:  Sanjay K Mohanty; S K Singh; Santosh Kumar Sharma; Kajori Banerji; Rajib Acharya
Journal:  SSM Popul Health       Date:  2022-10-04

6.  Risk factors for inadequate TB case finding in Rural Western Kenya: a comparison of actively and passively identified TB patients.

Authors:  Anna H Van't Hoog; Barbara J Marston; John G Ayisi; Janet A Agaya; Odylia Muhenje; Lazarus O Odeny; John Hongo; Kayla F Laserson; Martien W Borgdorff
Journal:  PLoS One       Date:  2013-04-25       Impact factor: 3.240

7.  Screening strategies for tuberculosis prevalence surveys: the value of chest radiography and symptoms.

Authors:  Anna H van't Hoog; Helen K Meme; Kayla F Laserson; Janet A Agaya; Benson G Muchiri; Willie A Githui; Lazarus O Odeny; Barbara J Marston; Martien W Borgdorff
Journal:  PLoS One       Date:  2012-07-06       Impact factor: 3.240

8.  Care seeking in tuberculosis: results from a countrywide cluster randomised survey in Bangladesh.

Authors:  Shahed Hossain; K Zaman; Abdul Quaiyum; Sayera Banu; Ashaque Husain; Akramul Islam; Martien Borgdorff; Frank van Leth
Journal:  BMJ Open       Date:  2014-05-28       Impact factor: 2.692

  8 in total

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