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Is recent Afghanistan survey data suitable for fertility analysis? A regional investigation based on fertility inhibiting determinants


Autoři: Jamal Abdul Nasir aff001;  Sohail Akhtar aff001;  Syed Arif Ahmed Zaidi aff002;  Andleeb Rani aff001;  Hina Bano aff003;  Andrew Hinde aff004
Působiště autorů: Department of Statistics, Government College University, Lahore, Pakistan aff001;  Department of Community Medicine, Quaid-e-Azam Medical College, Bahawalpur, Pakistan aff002;  National College of Business Administration & Economics, Rahim Yar Khan, Pakistan aff003;  Department of Social Statistics and Demography, University of Southampton, Southampton, United Kingdom aff004
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0223111

Souhrn

Afghanistan has been a country blighted by war over the past five decades and limited research is available on its demography. This study seeks to assess the suitability of recent survey data for Afghanistan (the 2010 Afghanistan Mortality Survey (AMS)and the 2015 Afghanistan Demographic and Health Survey (ADHS)) for estimating levels and trends in fertility. As several fertility measures rely on the quality of age data, we first apply demographic tools for the identification of age misreporting, finding evidence that it is severe. We then explore the consistency of fertility reporting across the two surveys, finding that the 2015 ADHS reports higher fertility among older women than the 2010 AMS although the seasonal pattern of fertility is consistent across the two surveys. We then estimate total fertility rates in 2008–2010 and 2012–2015 and measures of Bongaarts’s key proximate determinants of fertility for Afghanistan and its provinces for urban and rural areas separately. The results show that fertility is similar in urban and rural Afghanistan. Although most of the provincial data on the proximate determinants is reasonably consistent with the fertility rates, there are anomalies in some provinces which indicate the possible under-reporting of births. Overall, we conclude that the fertility data in the two surveys can be used with care to give an indication of broad regional fertility patterns and trends in the country.

Klíčová slova:

Age groups – Female contraception – Fertility rates – Health surveys – Rural areas – Urban areas – Afghanistan


Zdroje

1. Central Statistics Organization, Islamic Republic of Afghanistan (2019) Estimated Population of Afghanistan 2019–2010. Kabul: Central Statistics Organization.

2. Population Reference Bureau (2018) World Population Data Sheet 2018. Washington DC: Population Reference Bureau.

3. Spoorenberg T (2013) An evaluation of the recent fertility changes in Afghanistan: a period-specific analysis. Journal of Population Research 30: 133–149.

4. Bongaarts J (2015) Modeling the fertility impact of the proximate determinants: Time for a tune-up. Demographic Research 33: 535–560.

5. Bongaarts J (1978) A Framework for Analyzing the Proximate Determinants of Fertility. Population and Development Review 4: 105–132.

6. Schoumaker B (2014) Quality and consistency of DHS fertility estimates, 1990 to 2012 (DHS Methodological Reports No.12). Rockville: ICF International.

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8. Afghan Public Health Institute, Ministry of Public Health (APHI/MoPH) [Afghanistan], Central Statistics Organization (CSO) [Afghanistan], ICF Macro, Indian Institute of Health Management Research (IIHMR) [India], et al. (2011) Afghanistan Mortality Survey 2010. Calverton, Maryland, USA: APHI/MoPH, CSO, ICF Macro, IIHMR and WHO/EMRO.

9. Central Statistics Organization (CSO), Ministry of Public Health (MoPH), ICF (2017) Afghanistan Demographic and Health Survey 2015. Kabul, Afghanistan: Central Statistics Organization.

10. Siegel J, Swanson D (2008) The Methods and Materials of Demography. Bingley. United Kingdom: Emerald Group Publishing Ltd.

11. Nasir JA, Hinde A (2014) An extension of modified whipple index-Further modified whipple index. Pakistan Journal of Statistics 30: 265–272.

12. Spoorenberg T, Dutreuilh C (2007) Quality of age reporting: extension and application of the modified Whipple’s Index. Population (English edition) 4: 729–741.

13. Myers RJ (1940) Errors and Bias in the Reporting of Ages in Census Data. Transactions of the Actuarial Society of America 41: 395–415.

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Článek vyšel v časopise

PLOS One


2019 Číslo 10
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