eprintid: 10121931
rev_number: 16
eprint_status: archive
userid: 608
dir: disk0/10/12/19/31
datestamp: 2021-02-18 14:46:52
lastmod: 2021-12-06 00:56:31
status_changed: 2021-02-18 14:46:52
type: article
metadata_visibility: show
creators_name: Poirier, MJP
creators_name: Bärnighausen, T
creators_name: Harling, G
creators_name: Sié, A
creators_name: Grépin, KA
title: Is the lack of smartphone data skewing wealth indices in low-income settings?
ispublished: pub
divisions: UCL
divisions: B02
divisions: D01
keywords: Burkina Faso, Development, Education, Health inequality, Household expenditures, Principal components analysis, Smartphones, Socioeconomic status, Wealth index
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abstract: BACKGROUND: Smartphones have rapidly become an important marker of wealth in low- and middle-income countries, but international household surveys do not regularly gather data on smartphone ownership and these data are rarely used to calculate wealth indices. METHODS: We developed a cross-sectional survey module delivered to 3028 households in rural northwest Burkina Faso to measure the effects of this absence. Wealth indices were calculated using both principal components analysis (PCA) and polychoric PCA for a base model using only ownership of any cell phone, and a full model using data on smartphone ownership, the number of cell phones, and the purchase of mobile data. Four outcomes (household expenditure, education level, and prevalence of frailty and diabetes) were used to evaluate changes in the composition of wealth index quintiles using ordinary least squares and logistic regressions and Wald tests. RESULTS: Households that own smartphones have higher monthly expenditures and own a greater quantity and quality of household assets. Expenditure and education levels are significantly higher at the fifth (richest) socioeconomic status (SES) quintile of full model wealth indices as compared to base models. Similarly, diabetes prevalence is significantly higher at the fifth SES quintile using PCA wealth index full models, but this is not observed for frailty prevalence, which is more prevalent among lower SES households. These effects are not present when using polychoric PCA, suggesting that this method provides additional robustness to missing asset data to measure underlying latent SES by proxy. CONCLUSIONS: The lack of smartphone data can skew PCA-based wealth index performance in a low-income context for the top of the socioeconomic spectrum. While some PCA variants may be robust to the omission of smartphone ownership, eliciting smartphone ownership data in household surveys is likely to substantially improve the validity and utility of wealth estimates.
date: 2021-02-01
date_type: published
official_url: http://dx.doi.org/10.1186/s12963-021-00246-3
oa_status: green
full_text_type: pub
pmcid: PMC7852097
language: eng
primo: open
primo_central: open_green
verified: verified_manual
elements_id: 1846985
doi: 10.1186/s12963-021-00246-3
pii: 10.1186/s12963-021-00246-3
lyricists_name: Harling, Guy
lyricists_id: GHARL54
actors_name: Harling, Guy
actors_id: GHARL54
actors_role: owner
full_text_status: public
publication: Population Health Metrics
volume: 19
number: 1
article_number: 4
event_location: England
citation:        Poirier, MJP;    Bärnighausen, T;    Harling, G;    Sié, A;    Grépin, KA;      (2021)    Is the lack of smartphone data skewing wealth indices in low-income settings?                   Population Health Metrics , 19  (1)    , Article 4.  10.1186/s12963-021-00246-3 <https://doi.org/10.1186/s12963-021-00246-3>.       Green open access   
 
document_url: https://discovery.ucl.ac.uk/id/eprint/10121931/1/Is%20the%20lack%20of%20smartphone%20data%20skewing%20wealth%20indices%20in%20low-income%20settings.pdf