Hostname: page-component-76fb5796d-wq484 Total loading time: 0 Render date: 2024-04-30T07:07:26.663Z Has data issue: false hasContentIssue false
  • English
  • Français

Age heaping among adults in Nigeria: evidence from the Nigeria Demographic and Health Surveys 2003–2013

Published online by Cambridge University Press:  24 July 2019

Olufunke Fayehun ,
Anthony I. Ajayi Open the ORCID record for Anthony I. Ajayi [Opens in a new window] ,
Chinwe Onuegbu  and
Daniel Egerson
Olufunke Fayehun
Affiliation:
Department of Sociology, University of Ibadan, Ibadan, Nigeria
Anthony I. Ajayi*
Affiliation:
Sociology Department, University of Fort Hare, East London, South Africa Population Dynamics and Reproductive Health Unit, African Population and Health Research Centre, Nairobi, Kenya
Chinwe Onuegbu
Affiliation:
Warwick Medical School, University of Warwick, UK
Daniel Egerson
Affiliation:
Department of Sociology, University of Ibadan, Ibadan, Nigeria
*
*Corresponding author. Email: ajayianthony@gmail.com
Get access Rights & Permissions [Opens in a new window]

Abstract

Age, as a variable, represents a critical basis for demographic classification; thus, its misrepresentations or misreporting alter the accuracy of demographic estimates. This paper examines the extent and pattern of age heaping in the age data for adults, collected in the Nigerian Demographic Health Survey (NDHS). The study used the NDHS data for 2003, 2008, and 2013 to compute a Whipple’s and Meyers’ blended index for each survey year, by gender, geopolitical zones, states and place of residence. The analysis shows that age heaping was higher than the acceptable levels in all three data sets. The Whipple’s index puts the rate of age heaping in the 2003 dataset at 271.3, whilst the rates declined slightly in the 2008 and 2013 datasets to reach 204.2 and 202.5 respectively. Similarly, the Myers’ blended index portrayed that age heaping in the 2003 data was highest at 47.0 while the subsequent years were lower at 38.60 and 38.66, respectively. Digits ending in 0 and 5 were mostly reported in all three surveys and higher rates of age heaping were observed among males, the uneducated and rural dwellers. Age heaping was prominent in all three surveys, thus affecting the data quality gathered at these surveys. Thus, future studies should assess the extent to which age misreporting could bias the estimate of fertility rate.

Keywords

Age heapingMyers’ indexWhipple’s index
Type
Research Article
Information
Journal of Biosocial Science , Volume 52 , Issue 1 , January 2020 , pp. 132 - 139
Copyright
© Cambridge University Press 2019 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

A’Hearn, B., Baten, J., & Crayen, D. (2009). Quantifying quantitative literacy: Age heaping and the history of human capital. The Journal of Economic History, 69(3), 783–808.CrossRefGoogle Scholar
Bachi, R. (1951). The tendency to round off age returns: measurement and correction. Bulletin of the International Statistical Institute, 33(4), 195–222.Google Scholar
Baten, J., Ma, D., Morgan, S., & Wang, Q. (2010). Evolution of living standards and human capital in China in the 18–20th centuries: Evidences from real wages, age-heaping, and anthropometrics. Explorations in Economic History, 47(3), 347–359.CrossRefGoogle Scholar
Baten, J., & Sohn, K. (2017). Numeracy in early modern Korea, Japan, and China: The age-heaping approach. Japan and the World Economy, 43, 14–22.CrossRefGoogle Scholar
Blum, M., & Krauss, K. P. (2018). Age heaping and numeracy: looking behind the curtain. The Economic History Review, 71(2), 464–479.CrossRefGoogle Scholar
Bocquier, P., Madise, N. J., & Zulu, E. M. (2011). Is there an urban advantage in child survival in sub-Saharan Africa? Evidence from 18 countries in the 1990s. Demography, 48(2), 531–558.CrossRefGoogle ScholarPubMed
Coale, A. J., & Li, S. M. (1991). The effect of age misreporting in China on the calculation of mortality rates at very high ages. 28(2), 293–301.CrossRefGoogle Scholar
Crayen, D., & Baten, J. (2010). Global trends in numeracy 1820–1949 and its implications for long-term growth. Explorations in Economic History, 47(1), 82–99.CrossRefGoogle Scholar
Dahiru, T., & Dikko, H. G. (2013). Digit preference in Nigerian censuses data of 1991 and 2006. Epidemiology Biostatistics Public Health, 10(2).Google Scholar
Dorjee, T., & Spoorenberg, T. (2016). Fertility Transition in Bhutan: An Assessment. Population, 71(4), 659–672.Google Scholar
Földvári, P., Van Leeuwen, B., & Van Leeuwen-Li, J. (2012). How did women count? A note on gender-specific age heaping differences in the sixteenth to nineteenth centuries. The Economic History Review, 65(1), 304–313.CrossRefGoogle Scholar
Gilleard, C. (2016). The other Victorians: age, sickness and poverty in 19th-century Ireland. Ageing & Society, 36(6), 1157–1184.CrossRefGoogle Scholar
Jowett, A. J., & Li, Y.-Q. (1992). Age-heaping: contrasting patterns from China. GeoJournal, 28(4), 427–442.CrossRefGoogle ScholarPubMed
Manzel, K., Baten, J., & Stolz, Y. (2012). Convergence and divergence of numeracy: the development of age heaping in Latin America from the seventeenth to the twentieth century. The Economic History Review, 65(3), 932–960.CrossRefGoogle Scholar
Mokyr, J. (2013). Why Ireland starved: a quantitative and analytical history of the Irish economy, 1800-1850. Routledge.CrossRefGoogle Scholar
Myers, R. J. (1954). Accuracy of age reporting in the 1950 United States census. Journal of the American Statistical Association, 49(268), 826–831.CrossRefGoogle Scholar
Nasir, J.A. and Hinde, A. (2014) Extension of Whipple Index – further modified Whipple Index. Pakistan Journal of Statistics 30, 265–272.Google Scholar
National Population Commission [Nigeria] and ICF International (2014). Nigeria demographic and health survey 2013. In: Abuja, Nigeria, and Rockville, Maryland, USA: NPC and ICF International.Google Scholar
Pardeshi, G. S. (2010). Age heaping and accuracy of age data collected during a community survey in the Yavatmal district, Maharashtra. Indian Journal of Community Medicine, 35(3), 391.CrossRefGoogle ScholarPubMed
Poston, D. L. (2005). Age and sex. In Handbook of Population (pp. 19–58). Springer.CrossRefGoogle Scholar
Pullum, T. (2005) An Assessment of Age and Date Reporting in the DHS Surveys, 1985-2003. Calverton, MD, Macro International, Inc.Google Scholar
Randall, S., & Coast, E. (2016). The quality of demographic data on older Africans. Demographic Research, 34, 143–174.CrossRefGoogle Scholar
Shryock, H. S., & Siegel, J. S. (1976). The materials and methods of demography. Academic Press, New York.Google Scholar
Spennemann, D. H. (2017). Age Heaping among Indian Hawkers in South-eastern Australia and their source communities in the Punjab. JSPS, 24(1&2), 150.Google Scholar
Spoorenberg, T. (2007). Quality of age reporting: extension and application of the modified Whipple’s index. Population 62(4), 729–741.CrossRefGoogle Scholar
Szołtysek, M., Poniat, R., & Gruber, S. (2018). Age heaping patterns in Mosaic data. Historical Methods: A Journal of Quantitative Interdisciplinary History, 51(1), 13–38.CrossRefGoogle Scholar
Tollnek, F., & Baten, J. (2016). Age-heaping-based human capital estimates. Handbook of Cliometrics, 131–154.CrossRefGoogle Scholar
United Nations. (1989). Demographic yearbook New York, NY; Demographic yearbook. 39.1987 (1989). Special topic: household and family statistics: na.Google Scholar
West, K. K., Robinson, J. G., & Bentley, M. (2005). Did Proxy Respondents Cause Age Heaping in the Census 2000? URL: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.496.3645&rep=rep1&type=pdfGoogle Scholar