An evolution of socioeconomic related inequality in teenage pregnancy and childbearing in Malawi
Autoři:
Gowokani Chijere Chirwa aff001; Jacob Mazalale aff001; Gloria Likupe aff002; Dominic Nkhoma aff003; Levison Chiwaula aff001; Jesman Chintsanya aff004
Působiště autorů:
Department of Economics, University of Malawi, Chancellor College, Zomba, Malawi
aff001; Health Nursing and Midwifery, University of Hull, Hull, United Kingdom
aff002; Health Policy Unit, University of Malawi, College of Medicine, Lilongwe, Malawi
aff003; Department of Population Studies, University of Malawi, Chancellor College, Zomba, Malawi
aff004
Vyšlo v časopise:
PLoS ONE 14(11)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0225374
Souhrn
Background
Teenage pregnancies and childbearing are important health concerns in low-and middle-income countries (LMICs) including Malawi. Addressing these challenges requires, among other things, an understanding of the socioeconomic determinants of and contributors to the inequalities relating to these outcomes. This study investigated the trends of the inequalities and decomposed the underlying key socioeconomic factors which accounted for the inequalities in teenage pregnancy and childbearing in Malawi.
Methods
The study used the 2004, 2010 and 2015–16 series of nationally representative Malawi Demographic Health Survey covering 12,719 women. We used concentration curves to examine the existence of inequalities, and then quantified the extent of inequalities in teenage pregnancies and childbearing using the Erreygers concentration index. Finally, we decomposed concentration index to find out the contribution of the determinants to socioeconomic inequality in teenage pregnancy and childbearing.
Results
The teenage pregnancy and childbearing rate averaged 29% (p<0.01) between 2004 and 2015–16. Trends showed a “u-shape” in teenage pregnancy and childbearing rates, albeit a small one (34.1%; p<0.01) in 2004: (25.6%; p<0.01) in 2010, and (29%; p<0.01) in 2016. The calculated concentration indices -0.207 (p<0.01) in 2004, -0.133 (p<0.01) in 2010, and -0.217 (p<0.01) in 2015–16 indicated that inequality in teenage pregnancy and childbearing worsened to the disadvantage of the poor in the country. Additionally, the decomposition exercise suggested that the primary drivers to inequality in teenage pregnancy and child bearing were, early sexual debut (15.5%), being married (50%), and wealth status (13.8%).
Conclusion
The findings suggest that there is a need for sustained investment in the education of young women concerning the disadvantages of early sexual debut and early marriages, and in addressing the wealth inequalities in order to reduce the incidences of teenage pregnancies and childbearing.
Klíčová slova:
Adolescents – Contraception – Economic analysis – Female contraception – Child health – Malawi – Pregnancy – Socioeconomic aspects of health
Zdroje
1. Ganchimeg T, Ota E, Morisaki N, Laopaiboon M, Lumbiganon P, Zhang J, et al. Pregnancy and childbirth outcomes among adolescent mothers: a World Health Organization multicountry study. BJOG An Int J Obstet Gynaecol. Wiley/Blackwell (10.1111); 2014;121: 40–48. doi: 10.1111/1471-0528.12630 24641534
2. Owolabi OO, Wong KLM, Dennis ML, Radovich E, Cavallaro FL, Lynch CA, et al. Comparing the use and content of antenatal care in adolescent and older first-time mothers in 13 countries of west Africa: a cross-sectional analysis of Demographic and Health Surveys. Lancet Child Adolesc Heal. 2017;1: 203–212. https://doi.org/10.1016/S2352-4642(17)30025-1
3. WHO. Global accelerated action for the health of adolescents ( AA-HA!): guidance to support country implementation. World Health Organization; 2017. Available: http://apps.who.int/iris/bitstream/handle/10665/255415/9789241512343-annexes?sequence=5
4. Fall CHD, Sachdev HS, Osmond C, Restrepo-Mendez MC, Victora C, Martorell R, et al. Association between maternal age at childbirth and child and adult outcomes in the offspring: a prospective study in five low-income and middle-income countries (COHORTS collaboration). Lancet Glob Heal. 2015;3: e366–e377. https://doi.org/10.1016/S2214-109X(15)00038-8
5. Azevedo WF de, Diniz MB, Fonseca ESVB da, Azevedo LMR de, Evangelista CB. Complications in adolescent pregnancy: systematic review of the literature. Einstein (São Paulo). SciELO Brasil; 2015;13: 618–626.
6. WHO. Adolescent pregnancy. 2018 [cited 24 Aug 2018]. Available: http://www.who.int/en/news-room/fact-sheets/detail/adolescent-pregnancy
7. Yakubu I, Salisu WJ. Determinants of adolescent pregnancy in sub-Saharan Africa: a systematic review. Reprod Health. London: BioMed Central; 2018;15: 15. doi: 10.1186/s12978-018-0460-4 29374479
8. Phillips JS, Mbizvo M. Empowering adolescent girls in Sub‐Saharan Africa to prevent unintended pregnancy and HIV: A critical research gap. Int J Gynecol Obstet. 2015;132: 1–3. doi: 10.1016/j.ijgo.2015.10.005 26613822
9. NSO, Macro ICF, ICF Macro, Macro ICF, ICF Macro, ICF. Malawi Demographic and Health Survey 2010. Zomba, Malawi, and Calverton, Maryland, USA: NSO and ICF; 2011. Available: http://www.measuredhs.com
10. NSO, International I. Malawi Demographic and Health Survey 2015–16: Key Indicators Report. Zomba, Malawi, and Rockville, Maryland, USA; 2016. Available: http://dhsprogram.com/pubs/pdf/PR73/PR73.pdf
11. Gunawardena N, Fantaye AW, Yaya S. Predictors of pregnancy among young people in sub-Saharan Africa: a systematic review and narrative synthesis. BMJ Glob Heal. 2019;4: e001499. doi: 10.1136/bmjgh-2019-001499 31263589
12. Glynn JR, Sunny BS, DeStavola B, Dube A, Chihana M, Price AJ, et al. Early school failure predicts teenage pregnancy and marriage: A large population-based cohort study in northern Malawi. PLoS One. Public Library of Science; 2018;13: e0196041. doi: 10.1371/journal.pone.0196041 29758040
13. McConnell C, Mupuwaliywa M. Keeping girls in school: Situation analysis for Malawi. World Bank; 2016.
14. NSO. 2018 Malawi Population & Housing Census: Preliminary Report. Zomba: National Statistical Office; 2018.
15. World Bank. The World Development Indicators. United States of America; 2017.
16. NSO, Word Bank. Methodology for poverty measurement in Malawi (2016/17). Zomba, Malawi; 2018.
17. NSO. Integrated Household Survey (IHS3) 2010–2011: Household Socio-econonomic Characteristics Report. National Statistical Office, Zomba, Malawi: National Statistical Office; 2012. Available: http://www.nsomalawi.mw/index.php?option=com_content&view=article&id=190:third-integrated-household-survey-ihs3&catid=3&Itemid=79
18. Mussa R, Masanjala W. A Dangerous Divide: The State of Inequality in Malawi. 2015. Available: https://www.oxfam.org/sites/www.oxfam.org/files/file_attachments/rr-inequality-in-malawi-261115-en.pdf
19. UNDP. Human Development Indices and Indicators: 2018 Statistical Update. 2018.
20. Abdul-Rahman L, Marrone G, Johansson A. Trends in contraceptive use among female adolescents in Ghana. Afr J Reprod Health. Women’s Health and Action Research Centre (WHARC); 2011;15: 45–55. 22590892
21. Kaphagawani NC, Kalipeni E. Sociocultural factors contributing to teenage pregnancy in Zomba district, Malawi. Glob Public Health. Taylor & Francis; 2017;12: 694–710. doi: 10.1080/17441692.2016.1229354 27687242
22. Ahorlu CK, Pfeiffer C, Obrist B. Socio-cultural and economic factors influencing adolescents’ resilience against the threat of teenage pregnancy: a cross-sectional survey in Accra, Ghana. Reprod Health. 2015;12: 117. doi: 10.1186/s12978-015-0113-9 26700638
23. Rasch V, Silberschmidt M, McHumvu Y, Mmary V. Adolescent girls with illegally induced abortion Dar es Salaam: The discrepancy between sexual behaviour and lack of access to contraception. Reprod Health Matters. Taylor & Francis; 2000;8: 52–62. doi: 10.1016/s0968-8080(00)90006-5 11424268
24. Magadi MA. Multilevel determinants of teenage childbearing in sub-Saharan Africa in the context of HIV/AIDS. Health Place. 2017;46: 37–48. https://doi.org/10.1016/j.healthplace.2017.04.006 28463709
25. Odimegwu C, Mkwananzi S. Factors associated with teen pregnancy in sub-Saharan Africa: a multi-country cross-sectional study. Afr J Reprod Health. Women’s Health and Action Research Center; 2016;20: 94–107.
26. Krugu JK, Mevissen FEF, Prinsen A, Ruiter RAC. Who’s that girl? A qualitative analysis of adolescent girls’ views on factors associated with teenage pregnancies in Bolgatanga, Ghana. Reprod Health. 2016;13: 39. doi: 10.1186/s12978-016-0161-9 27080996
27. Atuyambe LM, Kibira SPS, Bukenya J, Muhumuza C, Apolot RR, Mulogo E. Understanding sexual and reproductive health needs of adolescents: evidence from a formative evaluation in Wakiso district, Uganda. Reprod Health. 2015;12: 35. doi: 10.1186/s12978-015-0026-7 25896066
28. Omani-Samani R, Amini Rarani M, Sepidarkish M, Khedmati Morasae E, Maroufizadeh S, Almasi-Hashiani A. Socioeconomic inequality of unintended pregnancy in the Iranian population: a decomposition approach. BMC Public Health. 2018;18: 607. doi: 10.1186/s12889-018-5515-5 29739402
29. UNDP. The sustainable development goals report. New York: United Nation; 2018. Available: https://unstats.un.org/sdgs/report/2016/leaving-no-one-behind
30. ICF. Demographic health surveys. 2018. Available: https://dhsprogram.com/data/index.cfm
31. Cavazos-Rehg PA, Spitznagel EL, Bucholz KK, Nurnberger J, Edenberg HJ, Kramer JR, et al. Predictors of Sexual Debut at Age 16 or Younger. Arch Sex Behav. 2010;39: 664–673. doi: 10.1007/s10508-008-9397-y 18846417
32. Mårdh P-A, Creatsas G, Guaschino S, Hellberg D, Henry-Suchet J. Correlation between an early sexual debut, and reproductive health and behavioral factors: a multinational European study. Eur J Contracept Reprod Heal Care. Taylor & Francis; 2000;5: 177–182. doi: 10.1080/13625180008500396 11131782
33. Filmer D, Pritchett LH. Estimating Wealth Effects without Expenditure Data-or Tears: An Application to Educational Enrollments in States of India. Demography. Springer; 2001;38: 115–132. doi: 10.1353/dem.2001.0003 11227840
34. Rutstein SO, Johnson K, MEASURE ORCM. The DHS wealth index. ORC Macro, MEASURE DHS; 2004. Available: https://dhsprogram.com/pubs/pdf/cr6/cr6.pdf
35. Vyas S, Kumaranayake L. Constructing socio-economic status indices: how to use principal components analysis. Health Policy Plan. 2006;21: 459–468. Available: http://dx.doi.org/10.1093/heapol/czl029 17030551
36. Kjellsson G, Gerdtham U-GG. On correcting the concentration index for binary variables. J Health Econ. 2013;32: 659–670. https://doi.org/10.1016/j.jhealeco.2012.10.012 23522656
37. Wagstaff A, Erreygers G, Wagstaff A, Erreygers G. Correcting the Concentration Index. J Health Econ. 2009;28: 504–515. https://doi.org/10.1016/j.jhealeco.2008.02.003 18367273
38. Erreygers G, Van Ourti T. Measuring socioeconomic inequality in health, health care and health financing by means of rank-dependent indices: A recipe for good practice. J Health Econ. 2011;30: 685–694. https://doi.org/10.1016/j.jhealeco.2011.04.004 21683462
39. O’Donnell OA, Doorslaer E van, Wagstaff A, Lindelow M. Analyzing health equity using household survey data: a guide to techniques and their implementation. Washington, D.C.: World Bank Publications; 2008.
40. Pulok MH, Sabah MN-U, Uddin J, Enemark U. Progress in the utilization of antenatal and delivery care services in Bangladesh: where does the equity gap lie? BMC Pregnancy Childbirth. BioMed Central; 2016;16: 200. doi: 10.1186/s12884-016-0970-4 27473150
41. Adeyanju O, Tubeuf S, Ensor T. Socio-economic inequalities in access to maternal and child healthcare in Nigeria: changes over time and decomposition analysis. Health Policy Plan. 2017;32: 1111–1118. Available: http://dx.doi.org/10.1093/heapol/czx049 28520949
42. Makate M, Makate C. The evolution of socioeconomic status-related inequalities in maternal health care utilization: evidence from Zimbabwe, 1994–2011. Glob Heal Res Policy. London: BioMed Central; 2017;2: 1. doi: 10.1186/s41256-016-0021-8 29202069
43. Wagstaff A, van Doorslaer E, Watanabe N. On decomposing the causes of health sector inequalities with an application to malnutrition inequalities in Vietnam. J Econom. 2003;112: 207–223. https://doi.org/10.1016/S0304-4076(02)00161-6
44. Chikalipo MC, Nyondo-Mipando L, Ngalande RC, Muheriwa SR, Kafulafula UK. Perceptions of pregnant adolescents on the antenatal care received at Ndirande Health Centre in Blantyre, Malawi. Malawi Med J. The Medical Association Of Malawi; 2018;30: 25–30. doi: 10.4314/mmj.v30i1.6 29868156
45. Machira K, Palamuleni ME. Health Care Factors Influencing Teen Mothers’ Use Of Contraceptives in Malawi. Ghana Med J. Ghana Medical Association; 2017;51: 88–93. Available: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5611910/ 28955105
46. McNeish H. Malawi’s fearsome chief, terminator of child marriages. Aljazeera. 16 May 2016. Available: https://www.aljazeera.com/
47. Heckley G, Gerdtham U-G, Kjellsson G, Ulf GG, Gerdtham U-G, Kjellsson G, et al. A general method for decomposing the causes of socioeconomic inequality in health. J Health Econ. 2016;48: 89–6296. doi: 10.1016/j.jhealeco.2016.03.006 27137844
Článek vyšel v časopise
PLOS One
2019 Číslo 11
- Tisícileté topoly, mokří psi, stárnoucí kočky a ospalé octomilky – „jednohubky“ z výzkumu 2024/41
- Jaké jsou aktuální trendy v léčbě karcinomu slinivky?
- Může hubnutí souviset s vyšším rizikem nádorových onemocnění?
- Menstruační krev má značný diagnostický potenciál, mimo jiné u diabetu
- Metamizol jako analgetikum první volby: kdy, pro koho, jak a proč?
Nejčtenější v tomto čísle
- A daily diary study on maladaptive daydreaming, mind wandering, and sleep disturbances: Examining within-person and between-persons relations
- A 3’ UTR SNP rs885863, a cis-eQTL for the circadian gene VIPR2 and lincRNA 689, is associated with opioid addiction
- A substitution mutation in a conserved domain of mammalian acetate-dependent acetyl CoA synthetase 2 results in destabilized protein and impaired HIF-2 signaling
- Molecular validation of clinical Pantoea isolates identified by MALDI-TOF
Zvyšte si kvalifikaci online z pohodlí domova
Všechny kurzy