Evidence map›Paper›PMID 25268951›Full record

ArticlePloS one2014

Multidimensional poverty in rural Mozambique: a new metric for evaluating public health interventions.

Bart Victor, Meridith Blevins, Ann F Green, Elisée Ndatimana, Lázaro González-Calvo, Edward F Fischer, Alfredo E Vergara, Sten H Vermund, Omo Olupona, Troy D Moon

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
3.3field-weighted citation impact, top 9% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 42 citations in OpenAlex.

  1. Tuberculosis patients with higher levels of poverty face equal or greater costs of illness.The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors at 3 institutions in 2 countries.

Bart VictorOwen Graduate School of Management, Vanderbilt University, Nashville, Tennessee, United States of America; Vanderbilt Institute for Global Health, Vanderbilt University, Nashville, Tennessee, United States of America.
Meridith BlevinsVanderbilt Institute for Global Health, Vanderbilt University, Nashville, Tennessee, United States of America; Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
Ann F GreenVanderbilt Institute for Global Health, Vanderbilt University, Nashville, Tennessee, United States of America.
Elisée NdatimanaFriends in Global Health, Maputo, Mozambique.
Lázaro González-CalvoFriends in Global Health, Maputo, Mozambique.
Edward F FischerVanderbilt Center for Latin American Studies and Department of Anthropology, Vanderbilt University, Nashville, Tennessee, United States of America.
Alfredo E VergaraVanderbilt Institute for Global Health, Vanderbilt University, Nashville, Tennessee, United States of America; Department of Preventive Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America.
Sten H VermundVanderbilt Institute for Global Health, Vanderbilt University, Nashville, Tennessee, United States of America; Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America; Friends in Global Health, Maputo, Mozambique.
Omo OluponaWorld Vision International, Maputo, Mozambique.
Troy D MoonVanderbilt Institute for Global Health, Vanderbilt University, Nashville, Tennessee, United States of America; Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee, United States of America; Friends in Global Health, Maputo, Mozambique.
Vanderbilt University · USOne World University · MZVanderbilt Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPoverty is a multidimensional phenomenon and unidimensional measurements have proven inadequate to the challenge of assessing its dynamics. Dynamics between poverty and public health intervention is among the most difficult yet important problems faced in development. We sought to demonstrate how multidimensional poverty measures can be utilized in the evaluation of public health interventions; and to create geospatial maps of poverty deprivation to aid implementers in prioritizing program planning.

methodsSurvey teams interviewed a representative sample of 3,749 female heads of household in 259 enumeration areas across Zambézia in August-September 2010. We estimated a multidimensional poverty index, which can be disaggregated into context-specific indicators. We produced an MPI comprised of 3 dimensions and 11 weighted indicators selected from the survey. Households were identified as "poor" if were deprived in >33% of indicators. Our MPI is an adjusted headcount, calculated by multiplying the proportion identified as poor (headcount) and the poverty gap (average deprivation). Geospatial visualizations of poverty deprivation were created as a contextual baseline for future evaluation.

resultsIn our rural (96%) and urban (4%) interviewees, the 33% deprivation cut-off suggested 58.2% of households were poor (29.3% of urban vs. 59.5% of rural). Among the poor, households experienced an average deprivation of 46%; thus the MPI/adjusted headcount is 0.27 ( = 0.58×0.46). Of households where a local language was the primary language, 58.6% were considered poor versus Portuguese-speaking households where 73.5% were considered non-poor. Living standard is the dominant deprivation, followed by health, and then education.

conclusionsMultidimensional poverty measurement can be integrated into program design for public health interventions, and geospatial visualization helps examine the impact of intervention deployment within the context of distinct poverty conditions. Both permit program implementers to focus resources and critically explore linkages between poverty and its social determinants, thus deriving useful findings for evidence-based planning.

Indexed as

AdultChild, PreschoolEducational StatusFamily CharacteristicsFemaleHealth StatusHumansInfantMaleMozambiquePovertyPublic HealthRural PopulationSocioeconomic FactorsSurveys and QuestionnairesUrban Population

Identifiers

PMID25268951
PMCPMC4182519
OpenAlexW2061734988

What OpenQuestion holds

Textmetadata
LicenceCC0
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.