IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0199393.html
   My bibliography  Save this article

Measuring wealth in rural communities: Lessons from the Sanitation, Hygiene, Infant Nutrition Efficacy (SHINE) trial

Author

Listed:
  • Bernard Chasekwa
  • John A Maluccio
  • Robert Ntozini
  • Lawrence H Moulton
  • Fan Wu
  • Laura E Smith
  • Cynthia R Matare
  • Rebecca J Stoltzfus
  • Mduduzi N N Mbuya
  • James M Tielsch
  • Stephanie L Martin
  • Andrew D Jones
  • Jean H Humphrey
  • Katherine Fielding
  • the SHINE Trial Team

Abstract

Background: Poverty and human capital development are inextricably linked and therefore research on human capital typically incorporates measures of economic well-being. In the context of randomized trials of health interventions, for example, such measures are used to: 1) assess baseline balance; 2) estimate covariate-adjusted analyses; and 3) conduct subgroup analyses. Many factors characterize economic well-being, however, and analysts often generate summary measures such as indices of household socio-economic status or wealth. In this paper, a household wealth index is developed and tested for participants in the cluster-randomized Sanitation, Hygiene, Infant Nutrition Efficacy (SHINE) trial in rural Zimbabwe. Methods: Building on the approach used in the Zimbabwe Demographic and Health Survey (ZDHS), we combined a set of housing characteristics, ownership of assets and agricultural resources into a wealth index using principal component analysis (PCA) on binary variables. The index was assessed for internal and external validity. Its sensitivity was examined considering an expanded set of variables and an alternative statistical approach of polychoric PCA. Correlation between indices was determined using the Spearman’s rank correlation coefficient and agreement between quintiles using a linear weighted Kappa statistic. Using the 2015 ZDHS data, we constructed a separate index and applied the loadings resulting from that analysis to the SHINE study population, to compare the wealth distribution in the SHINE study with rural Zimbabwe. Results: The derived indices using the different methods were highly correlated (r>0.9), and the wealth quintiles derived from the different indices had substantial to near perfect agreement (linear weighted Kappa>0.7). The indices were strongly associated with a range of assets and other wealth measures, indicating both internal and external validity. Households in SHINE were modestly wealthier than the overall population of households in rural Zimbabwe. Conclusion: The SHINE wealth index developed here is a valid and robust measure of wealth in the sample.

Suggested Citation

  • Bernard Chasekwa & John A Maluccio & Robert Ntozini & Lawrence H Moulton & Fan Wu & Laura E Smith & Cynthia R Matare & Rebecca J Stoltzfus & Mduduzi N N Mbuya & James M Tielsch & Stephanie L Martin & , 2018. "Measuring wealth in rural communities: Lessons from the Sanitation, Hygiene, Infant Nutrition Efficacy (SHINE) trial," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-19, June.
  • Handle: RePEc:plo:pone00:0199393
    DOI: 10.1371/journal.pone.0199393
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0199393
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0199393&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0199393?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Angus Deaton & Salman Zaidi, 2002. "Guidelines for Constructing Consumption Aggregates for Welfare Analysis," World Bank Publications, The World Bank, number 14101, April.
    2. Oakes, J. Michael & Rossi, Peter H., 2003. "The measurement of SES in health research: current practice and steps toward a new approach," Social Science & Medicine, Elsevier, vol. 56(4), pages 769-784, February.
    3. Deon Filmer & Lant Pritchett, 2001. "Estimating Wealth Effects Without Expenditure Data—Or Tears: An Application To Educational Enrollments In States Of India," Demography, Springer;Population Association of America (PAA), vol. 38(1), pages 115-132, February.
    4. Strauss, John & Thomas, Duncan, 1995. "Human resources: Empirical modeling of household and family decisions," Handbook of Development Economics, in: Hollis Chenery & T.N. Srinivasan (ed.), Handbook of Development Economics, edition 1, volume 3, chapter 34, pages 1883-2023, Elsevier.
    5. Stanislav Kolenikov & Gustavo Angeles, 2009. "Socioeconomic Status Measurement With Discrete Proxy Variables: Is Principal Component Analysis A Reliable Answer?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 55(1), pages 128-165, March.
    6. Mark Montgomery & Michele Gragnolati & Kathleen Burke & Edmundo Paredes, 2000. "Measuring living standards with proxy variables," Demography, Springer;Population Association of America (PAA), vol. 37(2), pages 155-174, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mathieu J. P. Poirier & Karen A. Grépin & Michel Grignon, 2020. "Approaches and Alternatives to the Wealth Index to Measure Socioeconomic Status Using Survey Data: A Critical Interpretive Synthesis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 148(1), pages 1-46, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hai‐Anh Dang & Dean Jolliffe & Calogero Carletto, 2019. "Data Gaps, Data Incomparability, And Data Imputation: A Review Of Poverty Measurement Methods For Data‐Scarce Environments," Journal of Economic Surveys, Wiley Blackwell, vol. 33(3), pages 757-797, July.
    2. Patrick Ward, 2014. "Measuring the Level and Inequality of Wealth: An Application to China," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 60(4), pages 613-635, December.
    3. Lovaton Davila, Rodrigo & McCarthy, Aine Seitz & Gondwe, Dorothy & Kirdruang, Phatta & Sharma, Uttam, 2022. "Water, walls, and bicycles: wealth index composition using census microdata," Journal of Demographic Economics, Cambridge University Press, vol. 88(1), pages 79-120, March.
    4. Deon Filmer & Kinnon Scott, 2012. "Assessing Asset Indices," Demography, Springer;Population Association of America (PAA), vol. 49(1), pages 359-392, February.
    5. Kamakura, Wagner A. & Mazzon, Jose A., 2013. "Socioeconomic status and consumption in an emerging economy," International Journal of Research in Marketing, Elsevier, vol. 30(1), pages 4-18.
    6. Permanyer, Iñaki, 2013. "Using Census Data to Explore the Spatial Distribution of Human Development," World Development, Elsevier, vol. 46(C), pages 1-13.
    7. R A Arriagada & E O Sills & P J Ferraro & S K Pattanayak, 2015. "Do Payments Pay Off? Evidence from Participation in Costa Rica’s PES Program," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-17, July.
    8. Ravi Prakash & Abhishek Singh, 2014. "Who Marries Whom? Changing Mate Selection Preferences in Urban India and Emerging Implications on Social Institutions," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 33(2), pages 205-227, April.
    9. Barik, Debasis & Desai, Sonalde & Vanneman, Reeve, 2018. "Economic Status and Adult Mortality in India: Is the Relationship Sensitive to Choice of Indicators?," World Development, Elsevier, vol. 103(C), pages 176-187.
    10. Paschalis Arvanitidis & Athina Economou & Christos Kollias, 2016. "Terrorism’s effects on social capital in European countries," Public Choice, Springer, vol. 169(3), pages 231-250, December.
    11. Janina Isabel Steinert & Lucie Dale Cluver & G. J. Melendez-Torres & Sebastian Vollmer, 2018. "One Size Fits All? The Validity of a Composite Poverty Index Across Urban and Rural Households in South Africa," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 136(1), pages 51-72, February.
    12. Janz, Teresa & Augsburg, Britta & Gassmann, Franziska & Nimeh, Zina, 2023. "Leaving no one behind: Urban poverty traps in Sub-Saharan Africa," World Development, Elsevier, vol. 172(C).
    13. Brown, Joe & Hamoudi, Amar & Jeuland, Marc & Turrini, Gina, 2017. "Seeing, believing, and behaving: Heterogeneous effects of an information intervention on household water treatment," Journal of Environmental Economics and Management, Elsevier, vol. 86(C), pages 141-159.
    14. Assaad, Ragui & Hendy, Rana & Salehi-Isfahani, Djavad, 2019. "Inequality of opportunity in educational attainment in the Middle East and North Africa: Evidence from household surveys," International Journal of Educational Development, Elsevier, vol. 66(C), pages 24-43.
    15. Samia Badji, 2016. "The Wealth Paradox for Whom? Child Labor and the Identification of Households Excluded from the Land and the Labor Markets in Madagascar," Working Papers 1638, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    16. Lannes, Laurence, 2015. "Improving health worker performance: The patient-perspective from a PBF program in Rwanda," Social Science & Medicine, Elsevier, vol. 138(C), pages 1-11.
    17. Abderrahman Yassine & Fatima Bakass, 2022. "Do Education and Employment Play a Role in Youth’s Poverty Alleviation? Evidence from Morocco," Sustainability, MDPI, vol. 14(18), pages 1-25, September.
    18. Giulia Greco, 2018. "Setting the Weights: The Women’s Capabilities Index for Malawi," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(2), pages 457-478, January.
    19. Juan M Villa, 2016. "A harmonised proxy means test for Kenya’s National Safety Net programme," Global Development Institute Working Paper Series 032016, GDI, The University of Manchester.
    20. Dang,Hai-Anh H. & Kilic,Talip & Carletto,Calogero & Abanokova,Kseniya, 2021. "Poverty Imputation in Contexts without Consumption Data : A Revisit with Further Refinements," Policy Research Working Paper Series 9838, The World Bank.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0199393. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.