IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0219860.html
   My bibliography  Save this article

Service environment link and false discovery rate correction: Methodological considerations in population and health facility surveys

Author

Listed:
  • Teketo Kassaw Tegegne
  • Catherine Chojenta
  • Theodros Getachew
  • Roger Smith
  • Deborah Loxton

Abstract

Background: Geospatial data are important in monitoring many aspects of healthcare development. Geographically linking health facility data with population data is an important area of public health research. Examining healthcare problems spatially and hierarchically assists with efficient resource allocation and the monitoring and evaluation of service efficacy at different levels. This paper explored methodological issues associated with geographic data linkage, and the spatial and multilevel analyses that could be considered in analysing maternal health service data. Methods: The 2016 Ethiopia Demographic and Health Survey and the 2014 Ethiopia Service Provision Assessment data were used. Two geographic data linking methods were used to link these two datasets. Administrative boundary link was used to link a sample of health facilities data with population survey data for analysing three areas of maternal health service use. Euclidean buffer link was used for a census of hospitals to analyse caesarean delivery use in Ethiopia. The Global Moran’s I and the Getis-Ord Gi* statistics need to be carried out for identifying hot spots of maternal health service use in ArcGIS software. In addition to this, since the two datasets contain hierarchical data, a multilevel analysis was carried out to identify key determinants of maternal health service use in Ethiopia. Results: Administrative boundary link gave more types of health facilities and more maternal health services as compared to the Euclidean buffer link. Administrative boundary link is the method of choice in case of sampled health facilities. However, for a census of health facilities, the Euclidean buffer link is the appropriate choice as this provides cluster level service environment estimates, which the administrative boundary link does not. Applying a False Discovery Rate correction enables the identification of true spatial clusters of maternal health service use. Conclusions: A service environment link minimizes the methodological issues associated with geographic data linkage. A False Discovery Rate correction needs to be used to account for multiple and dependent testing while carrying out local spatial statistics. Examining maternal health service use both spatially and hierarchically has tremendous importance for identifying geographic areas that need special emphasis and for intervention purposes.

Suggested Citation

  • Teketo Kassaw Tegegne & Catherine Chojenta & Theodros Getachew & Roger Smith & Deborah Loxton, 2019. "Service environment link and false discovery rate correction: Methodological considerations in population and health facility surveys," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-17, July.
    • Handle: RePEc:plo:pone00:0219860
    DOI: 10.1371/journal.pone.0219860
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0219860
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0219860&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0219860?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. Luc Anselin & Sanjeev Sridharan & Susan Gholston, 2007. "Using Exploratory Spatial Data Analysis to Leverage Social Indicator Databases: The Discovery of Interesting Patterns," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 82(2), pages 287-309, June.
    2. Barbara Entwisle & Ronald Rindfuss & Stephen Walsh & Tom Evans & Sara Curran, 1997. "Geographic information systems, spatial network analysis, and contraceptive choice," Demography, Springer;Population Association of America (PAA), vol. 34(2), pages 171-187, May.
    3. Teketo Kassaw Tegegne & Catherine Chojenta & Deborah Loxton & Roger Smith & Kelemu Tilahun Kibret, 2018. "The impact of geographic access on institutional delivery care use in low and middle-income countries: Systematic review and meta-analysis," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-16, August.
    Full references (including those not matched with items on IDEAS)

    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. Sridharan, Sanjeev & Jones, Bobby & Caudill, Barry & Nakaima, April, 2016. "Steps towards incorporating heterogeneities into program theory: A case study of a data-driven approach," Evaluation and Program Planning, Elsevier, vol. 58(C), pages 88-97.
    2. Cutrini, Eleonora & Mendez, Carlos, 2023. "Convergence clubs and spatial structural change in the European Union," Structural Change and Economic Dynamics, Elsevier, vol. 67(C), pages 167-181.
    3. Ragdad Cani Miranti, 2021. "Is regional poverty converging across Indonesian districts? A distribution dynamics and spatial econometric approach," Asia-Pacific Journal of Regional Science, Springer, vol. 5(3), pages 851-883, October.
    4. Noah Kaiser & Christina K. Barstow, 2022. "Rural Transportation Infrastructure in Low- and Middle-Income Countries: A Review of Impacts, Implications, and Interventions," Sustainability, MDPI, vol. 14(4), pages 1-48, February.
    5. Felipe Santos‐Marquez & Carlos Mendez, 2021. "Regional convergence, spatial scale, and spatial dependence: Evidence from homicides and personal injuries in Colombia 2010–2018," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(4), pages 1162-1184, August.
    6. Ye Seul Choi & Up Lim, 2015. "Effects of Regional Creative Milieu on Interregional Migration of the Highly Educated in Korea: Evidence from Hierarchical Cross-Classified Linear Modeling," Sustainability, MDPI, vol. 7(12), pages 1-18, December.
    7. Biswajit Mohanty & N. R. Bhanumurthy, 2018. "Regional growth policy experience in India: the spatial dimension," Asia-Pacific Journal of Regional Science, Springer, vol. 2(2), pages 479-505, August.
    8. Michael Poulsen & Ron Johnston & James Forrest, 2010. "The Intensity of Ethnic Residential Clustering: Exploring Scale Effects Using Local Indicators of Spatial Association," Environment and Planning A, , vol. 42(4), pages 874-894, April.
    9. Chavez, Alicia & Paredes, Dusan, 2023. "Public spending and economies of scale in partial fiscal decentralized governments: The case of Chile," Socio-Economic Planning Sciences, Elsevier, vol. 87(PB).
    10. Kai Li & Zhili Ma & Jinjin Liu, 2019. "A New Trend in the Space–Time Distribution of Cultivated Land Occupation for Construction in China and the Impact of Population Urbanization," Sustainability, MDPI, vol. 11(18), pages 1-23, September.
    11. Arnab Bhattacharjee & Cornilius Chikwama & João Lourenço Marques, 2021. "Connections between research and policy: The case of fertility diffusion and regional demographic policy in Portugal," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(3), pages 729-743, June.
    12. Nattapong Puttanapong & Amornrat Luenam & Pit Jongwattanakul, 2022. "Spatial Analysis of Inequality in Thailand: Applications of Satellite Data and Spatial Statistics/Econometrics," Sustainability, MDPI, vol. 14(7), pages 1-25, March.
    13. Sridharan, Sanjeev & Tunstall, Helena & Lawder, Richard & Mitchell, Richard, 2007. "An exploratory spatial data analysis approach to understanding the relationship between deprivation and mortality in Scotland," Social Science & Medicine, Elsevier, vol. 65(9), pages 1942-1952, November.
    14. Carlos Mendez & Felipe Santos‐Marquez, 2021. "Regional convergence and spatial dependence across subnational regions of ASEAN: Evidence from satellite nighttime light data," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(6), pages 1750-1777, December.
    15. Abhishek Dureja & Digvijay S. Negi, 2024. "Birth Order Effects in Maternal Health-Seeking Behavior: Evidence from India," Working Papers 118, Ashoka University, Department of Economics.
    16. Zelong Xia & Hao Li & Yuehong Chen, 2018. "Assessing Neighborhood Walkability Based on Usage Characteristics of Amenities under Chinese Metropolises Context," Sustainability, MDPI, vol. 10(11), pages 1-18, October.
    17. Chávez, Alicia & Rodríguez-Puello, Gabriel, 2022. "Commodity price shocks and the gender wage gap: Evidence from the Metal Mining Prices Super-Cycle in Chile," Resources Policy, Elsevier, vol. 76(C).
    18. Akio Kusakabe & Jinhwan Oh, 2010. "Spatial Analysis Of The Japanese Gas Industry," Review of Urban & Regional Development Studies, Wiley Blackwell, vol. 22(2‐3), pages 143-164, July.
    19. Michael F. Goodchild & Luc Anselin & Richard P. Appelbaum & Barbara Herr Harthorn, 2000. "Toward Spatially Integrated Social Science," International Regional Science Review, , vol. 23(2), pages 139-159, April.
    20. Paul Voss, 2007. "Demography as a Spatial Social Science," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 26(5), pages 457-476, December.

    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:pone00:0219860. 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.