Spatial analysis of completeness of death registration in Egypt

Springer Science and Business Media LLC - Tập 95 Số 1 - 2020
Nesma Lotfy1
1Department of Biostatistics, High Institute of Public Health, Alexandria University, Alexandria, Egypt

Tóm tắt

Abstract Purpose Civil registration and vital statistics (CRVS) systems should be the primary source of routine mortality data. However, there is lack of information about the completeness of death registration at the sub-national level of Egypt. The current study was conducted to estimate the completeness of death registration at the national and sub-national levels of Egypt, to investigate the spatial patterns of the completeness, and to examine the factors that influence it. Methods Data from the Central Agency for Public Mobilization and Statistics (CAPMAS, 2018) and Egypt Demographic and Health Survey (EDHS 2008, 2014) were used to estimate the completeness of death registration using an empirical method (random-effects models); hot spot analysis was conducted using Moran’s I and Getis-Ord Gi*; and the geographically weighted regression (GWR) model has been also carried out. Results The study estimates show that Egypt has 96% completeness of death registration, and all governorates have completeness of more than 90% except for Beni-Suef, Menia, Aswan, Suhag, Luxor, ELWadi ELGidid, and South Sinai. According to sex, the death registration of females is slightly better than that of males (96.8% compared to 95.4%). Concerning residence, urban area has almost complete death registration compared to rural area (99.5% and 85.4%, respectively). Hot spot analysis shows that all hot spots are centered on the north of Egypt, while all cold spots are focused on the south. However, according to the geographically weighted regression (GWR) model, poverty, illiteracy, and health office density are considered major factors for the completeness of death registration. Conclusion Although the completeness in Egypt is almost 100%, this analysis suggests that it may not be, and that it could be somewhat lower in some rural areas. However, there is uncertainty in the sub-national estimates because deaths are only reported by place of occurrence and not place of usual residence. Thus, efforts should focus on improving the quality of data of the vital registration system in some rural areas and in lower Egyptian governorates.

Từ khóa


Tài liệu tham khảo

World Health Organization. Strengthening civil registration and vital statistics for births, deaths and causes of death: resource kit. 2013.

Mills SL, Abouzahr C, Kim JH, Rassekh BM, Sarpong D. Civil registration and vital statistics (CRVS) for monitoring the sustainable development goals (SDGS), vol. 10. Washington, DC: World Bank Group; 2017. p. 27533.

Rao C, Bradshaw D, Mathers CD. Improving death registration and statistics in developing countries: lessons from sub-Saharan Africa. Southern Afr J Demog. 2004;9(2):81–99.

United Nations. Principles and recommendations for a vital statistics system (Revision 2). New York: Department of Economic and Social Affairs Statistics Division; 2001.

United Nations Statistics Division Demographic Statistics. Status of civil registration and vital statistics: African English speaking countries. 2016.

United Nations. Technical report on the status of civil registration and vital statistics in ESCWA region. 2009.

Abdel Shakour MA. CRVS system in Egypt. In: The Technical Seminar on Legal Framework for Civil Registration, Vital Statistics and Identity Management Systems. Philippines: United Nations, Statistics Division; 2017.

Adair T, Lopez AD. Estimating the completeness of death registration: an empirical method. PLoS One. 2018;13(5).

Silva R. Death registration and mortality statistics in the Arab Region. Beirut: Statistics Division of the United Nations Economic and Social Commission for Western Asia; 2015.

Institute for Health Metrics and Evaluation (IHME). Global burden of disease (GBD) results tool. 2017. http://ghdx.healthdata.org/gbd-results-tool.

El-Shalakani M. Estimating the completeness of births and deaths registration in Egypt through dual record systems. Genus. 1985;41(1/2):119–32.

AbouZahr C, de Savigny D, Mikkelsen L, Setel PW, Lozano R, Nichols E, et al. Civil registration and vital statistics: progress in the data revolution for counting and accountability. Lancet. 2015;386(10001):1373–85.

United Nations. Report on the status of civil registration and vital statistics in Africa.2017.

Central Agency for Public Mobilization and Statistics. Egypt in figures. Egypt; 2018.

Ministry of H, Population/Egypt, El Z, Associates/Egypt, International ICF. Egypt Demographic and Health Survey 2014. Cairo: Ministry of Health and Population and ICF International; 2015.

Central Agency for Public Mobilization and Statistics. Population. Egypt; 2018.

Central Agency for Public Mobilization and Statistics. Annual bulletin of births and deaths statistics. Egypt; 2018.

Central Agency for Public Mobilization and Statistics. Income, expenditure and consumption survey. Egypt; 2018.

Ministry of Health and Population [Egypt] and ICF International. Egypt Demographic and Health Survey 2014.EGBR61.DTA. Calverton: Ministry of Health and Population and ICF International.ICF International; 2014.

Ministry of Health and Population [Egypt] and Macro International. Egypt Demographic and Health Survey 2008.EGBR5A.DTA. Calverton: Ministry of Health and Population and Macro International. Macro International; 2008.

Ministry of Planning Monitoring and Administrative Reform. Rate your services and improve your life. 2018. http://www.rateyourservices.gov.eg/.

Brass W, editor. Uses of census or survey data for the estimation of vital rates. Addis Ababa: UN. ECA African Seminar on Vital Statistics; 1964. p. 1964.

United Nations. Dept of International Economic and Social Affairs. Step-by-step guide to the estimation of child mortality. Population studies. New York: United Nations; 1990.

Elkasabi M. Calculating fertility and childhood mortality rates from survey data using the DHS.rates R package. PLoS One. 2019;14(5).

Environmental Systems Research Institute (ESRI). Spatial autocorrelation (Global Moran's I). 2018. http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-statistics-toolbox/h-how-spatial-autocorrelation-moran-s-i-spatial-st.htm.

Environmental Systems Research Institute (ESRI). Hot spot analysis (Getis-Ord Gi*). 2018. http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-statistics-toolbox/hot-spot-analysis.htm.

Fotheringham AS, Brunsdon C, Charlton M. Geographically weighted regression. Chichester: Wiley; 2002.

Hurvich CM, Simonoff JS, Tsai C-L. Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion. J Royal Stat Soc Ser B. 1998;60(2):271–93. https://doi.org/10.1111/1467-9868.00125.

Brunsdon C, Fotheringham AS, Charlton ME. Geographically weighted regression: a method for exploring spatial nonstationarity. Geograph Anal. 1996;28(4):281–98.

Herrera S, Badr K. Internal migration in Egypt: levels, determinants, wages, and likelihood of employment: The World Bank; 2012.

Thông tin
Thông tin xuất bản

Springer Science and Business Media LLC

Tập 95 Số 1

Thông tin tác giả