{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T10:02:25Z","timestamp":1790503345963,"version":"4.1.0"},"reference-count":17,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T00:00:00Z","timestamp":1635897600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100009633","name":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","doi-asserted-by":"publisher","award":["R01HD090082"],"award-info":[{"award-number":["R01HD090082"]}],"id":[{"id":"10.13039\/100009633","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>The infant mortality rate (IMR) is a critical indicator of population health, but its measurement is subject to response bias in countries without complete vital registration systems who rely instead on birth histories collected via sample surveys. One of the most salient bias is the fact that child deaths in these birth histories tend to be reported with a large amount of heaping at age 12 months. Because of this issue, analysts and international agencies do not directly use IMR estimates based on surveys such as Demographic and Health Surveys (DHS); they rely instead on mortality models such as model life tables. The use of model life tables in this context, however, is arbitrary, and the extent to which this approach appropriately addresses bias in DHS-based IMR estimates remains unclear. This hinders our ability to monitor IMR levels and trends in low-and middle-income countries. The objective of this study is to evaluate age heaping bias in DHS-based IMR estimates and propose an improved method for adjusting this bias.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods and findings<\/jats:title>\n                    <jats:p>Our method relies on a recently-developed log-quadratic model that can predict age-specific mortality by detailed age between 0 and 5. The model\u2019s coefficients were derived from a newly constituted database, the Under-5 Mortality Database (U5MD), that represents the mortality experience of countries with high-quality vital registration data. We applied this model to 204 DHS surveys, and compared unadjusted IMR values to IMR values adjusted with the log-quadratic model as well as with the classic model life table approach. Results show that contrary to existing knowledge, age heaping at age 12 months rarely generates a large amount of bias in IMR estimates. In most cases, the unadjusted IMR values were not deviating by more than +\/- 5% from the adjusted values. The model life table approach, by contrast, introduced an unwarranted, downward bias in adjusted IMR values. We also found that two regions, Sub-Saharan Africa and South Asia, present age patterns of under-5 mortality that strongly depart from the experience represented in the U5MD. For these countries, neither the existing model life tables nor the log-quadratic model can produce empirically-supported IMR adjustments.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Age heaping at age 12 months produces a smaller amount of bias in DHS-based IMR estimates than previously thought. If a large amount of age heaping is present in a survey, the log-quadratic model allows users to evaluate, and whenever necessary, adjust IMR estimates in a way that is more informed by the local mortality pattern than existing approaches. Future research should be devoted to understanding why Sub-Saharan African and South Asian countries have such distinct age patterns of under-five mortality.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0259304","type":"journal-article","created":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T13:26:56Z","timestamp":1635946016000},"page":"e0259304","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":14,"title":["Estimating the infant mortality rate from DHS birth histories in the presence of age heaping"],"prefix":"10.1371","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8131-7821","authenticated-orcid":true,"given":"Julio","family":"Romero Prieto","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Verhulst","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michel","family":"Guillot","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,11,3]]},"reference":[{"key":"pone.0259304.ref001","unstructured":"UNSD. Coverage of Birth and Death Registration (consulted on Feb 1, 2021); 2017. Available from: https:\/\/unstats.un.org\/unsd\/demographic-social\/crvs\/index.cshtml."},{"key":"pone.0259304.ref002","unstructured":"UN IGME. Explanatory Notes Child mortality trend series to 2018; 2019. Available from: https:\/\/childmortality.org\/methods."},{"key":"pone.0259304.ref003","volume-title":"Guide to DHS Statistics","author":"TN Croft","year":"2018"},{"key":"pone.0259304.ref004","volume-title":"Regional Model Life Tables and Stable Populations","author":"AJ Coale","year":"1966"},{"key":"pone.0259304.ref005","volume-title":"Model Life Tables for Developing Countries","author":"UN","year":"1982"},{"issue":"8","key":"pone.0259304.ref006","doi-asserted-by":"crossref","first-page":"e1001299","DOI":"10.1371\/journal.pmed.1001299","article-title":"A Global Overview of Infant and Child Mortality Age Patterns in Light of New Empirical Data","volume":"9","author":"M Guillot","year":"2012","journal-title":"PLoS Medicine"},{"key":"pone.0259304.ref007","article-title":"Modeling Age Patterns of Under-5 Mortality: Results From a Log-Quadratic Model Applied to High-Quality Vital Registration Data","author":"M Guillot","journal-title":"Demography (forthcoming)"},{"issue":"1","key":"pone.0259304.ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/00324728.2011.611411","article-title":"A flexible two-dimensional mortality model for use in indirect estimation","volume":"66","author":"J Wilmoth","year":"2012","journal-title":"Population Studies"},{"issue":"8","key":"pone.0259304.ref009","doi-asserted-by":"crossref","first-page":"e1001298","DOI":"10.1371\/journal.pmed.1001298","article-title":"Child Mortality Estimation: Methods Used to Adjust for Bias due to AIDS in Estimating Trends in Under-Five Mortality","volume":"9","author":"N Walker","year":"2012","journal-title":"PLOS Medicine"},{"key":"pone.0259304.ref010","volume-title":"Direct estimation of child mortality from birth histories","author":"K Hill","year":"2013"},{"key":"pone.0259304.ref011","volume-title":"An Assessment of DHS-1 Data Quality, DHS Methodological Reports No. 1","author":"JM Sullivan","year":"1990"},{"key":"pone.0259304.ref012","volume-title":"further analysis of Demographic and Health Surveys data","author":"K Johnson","year":"2005"},{"issue":"8","key":"pone.0259304.ref013","doi-asserted-by":"crossref","first-page":"e1001296","DOI":"10.1371\/journal.pmed.1001296","article-title":"Child Mortality Estimation: Consistency of Under-Five Mortality Rate Estimates Using Full Birth Histories and Summary Birth Histories","volume":"9","author":"R Silva","year":"2012","journal-title":"PLOS Medicine"},{"key":"pone.0259304.ref014","unstructured":"Human Mortality Database. University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany);. Available from: www.mortality.org or www.humanmortality.de."},{"issue":"1","key":"pone.0259304.ref015","doi-asserted-by":"crossref","first-page":"1904","DOI":"10.3402\/gha.v2i0.1904","article-title":"Epidemiological transition in rural Bangladesh, 1986\u20132006","volume":"2","author":"Z Ahsan Karar","year":"2009","journal-title":"Global Health Action"},{"issue":"3","key":"pone.0259304.ref016","doi-asserted-by":"crossref","first-page":"e1002757","DOI":"10.1371\/journal.pmed.1002757","article-title":"Age distribution, trends, and forecasts of under-5 mortality in 31 sub-Saharan African countries: A modeling study","volume":"16","author":"I Mej\u00eda-Guevara","year":"2019","journal-title":"PLOS Medicine"},{"key":"pone.0259304.ref017","volume-title":"DHS Methodological Reports No. 11","author":"TW Pullum","year":"2014"}],"container-title":["PLOS ONE"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0259304","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,11,3]],"date-time":"2021-11-03T13:27:12Z","timestamp":1635946032000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pone.0259304"}},"subtitle":[],"editor":[{"given":"Jos\u00e9 Antonio","family":"Ortega","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2021,11,3]]},"references-count":17,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,11,3]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pone.0259304","relation":{},"ISSN":["1932-6203"],"issn-type":[{"value":"1932-6203","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,3]]}}}