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Emerging Themes in Epidemiology
Published in: Emerging Themes in Epidemiology 1/2016

Open Access 01-12-2016 | Research article

Assessing delivery practices of mothers over time and over space in Uganda, 2003–2012

Authors: Daniel A. Sprague, Caroline Jeffery, Nadine Crossland, Thomas House, Gareth O. Roberts, William Vargas, Joseph Ouma, Stephen K. Lwanga, Joseph J. Valadez

Published in: Emerging Themes in Epidemiology | Issue 1/2016

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Abstract

Background

It is well known that safe delivery in a health facility reduces the risks of maternal and infant mortality resulting from perinatal complications. What is less understood are the factors associated with safe delivery practices. We investigate factors influencing health facility delivery practices while adjusting for multiple other factors simultaneously, spatial heterogeneity, and trends over time.

Methods

We fitted a logistic regression model to Lot Quality Assurance Sampling (LQAS) data from Uganda in a framework that considered individual-level covariates, geographical features, and variations over five time points. We accounted for all two-covariate interactions and all three-covariate interactions for which two of the covariates already had a significant interaction, were able to quantify uncertainty in outputs using computationally intensive cluster bootstrap methods, and displayed outputs using a geographical information system. Finally, we investigated what information could be predicted about districts at future time-points, before the next LQAS survey is carried out. To do this, we applied the model to project a confidence interval for the district level coverage of health facility delivery at future time points, by using the lower and upper end values of known demographics to construct a confidence range for the prediction and define priority groups.

Results

We show that ease of access, maternal age and education are strongly associated with delivery in a health facility; after accounting for this, there remains a significant trend towards greater uptake over time. We use this model together with known demographics to formulate a nascent early warning system that identifies candidate districts expected to have low prevalence of facility-based delivery in the immediate future.

Conclusions

Our results support the hypothesis that increased development, particularly related to education and access to health facilities, will act to increase facility-based deliveries, a factor associated with reducing perinatal associated mortality. We provide a statistical method for using inexpensive and routinely collected monitoring and evaluation data to answer complex epidemiology and public health questions in a resource-poor setting. We produced a model based on this data that explained the spatial distribution of facility-based delivery in Uganda. Finally, we used this model to make a prediction about the future priority of districts that was validated by monitoring and evaluation data collected in the next year.
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Literature
1.
World Health Organization, United Nations Children and Education Fund. Countdown to 2015. Maternal, Newborn & Child Survival: Building a Future for Women and Children, The 2012 Report. Geneva: World Health Organization, 2012 Contract No.: Report.
2.
The World Bank Group. Over 99 percent of maternal deaths occur in developing countries. 2013.
3.
United Nations Development Programme. Human Development Report. New York: United Nations Development Programme, 2013 Contract No.: Web Page.
4.
UNICEF. State of the World’s Children 2013. New York: United Nations Children’s Fund (UNICEF), Division of Communication; 2013 May 2013. Report No.
5.
World Health Organization, Unicef, Unfpa, The World B. Trends in maternal mortality: 1990 to 2012. Geneva: World Health Organization, 2012 Contract No.: Report.
6.
World Health Organization. Newborns: reducing mortality. Geneva: World Health Organization; 2013.
7.
Darmstadt G, Bhutta Z, Cousens S, Adam T, Walker N, de Bernis L. Evidence-based, cost-effective interventions: How many newborn babies can we save? The Lancet. 2005;365(9463):977–88.CrossRef
8.
Ministry of Health. Situation analysis of newborn health in Uganda: current status and opportunities to improve care and survival. Kampala: Government of Uganda. Save the Children, UNICEF, WHO; 2008.
9.
United Nations Population Fund. Skilled attendance at birth. New York: United Nations Population Fund, 2008 Contract No.: Web Page.
10.
Lee A, Cousens S, Darmstadt G, Blencowe H, Pattinson R, Moran N, et al. Care during labor and birth for the prevention of intrapartum-related neonatal deaths: a systematic review and Delphi estimation of mortality effect. BMC Public Health. 2011;11(Supp 3):S10.
11.
Family Care International. Safe Motherhood: a review. New York: Family Care International, 2007 Contract No.: Report.
12.
Aminu M. Reducing neonatal mortality through skilled birth attendance. Amsterdam: Elsevier Limited; 2014.
13.
Hodgins S. Achieving better maternal and newborn outcomes: coherent strategy and pragmatic, tailored implementation. Glob Health Sci Pract. 2013;1(2):146–53.CrossRefPubMedPubMedCentral
14.
Nabudere H, Asiimwe D, Amandua J. Improving Access to Skilled Attendance at Delivery (SURE policy brief). Kampala, Uganda: College of Health Sciences, Makerere University, 2011 Contract No.: Report.
15.
Uganda Ministry of Finance, Planning, Economic Development. Special theme: accelerating progress towards improving maternal health. Kampala, Uganda: Uganda Ministry of Finance, Planning and Economic Development, 2010 Contract No.: Report.
16.
Afsana K, Rashid S. The challenges of meeting rural Bangladeshi women’s needs in delivery care. Reprod Health Matters. 2001;9(18):79–89.CrossRefPubMed
17.
Amooti-Kaguna B, Nuwaha F. Factors Influencing choice of delivery sites in Rakai district of Uganda. Soc Sci Med. 2000;50:203–13.CrossRefPubMed
18.
Anyait A, Mukanga D, Oundo GB, Nuwaha F. Predictors for health facility delivery in Busia district of Uganda: a cross sectional study. BMC Pregnancy Childbirth. 2012;12:132. doi:10.​1186/​1471-2393-12-132.
19.
Metcalfe R, Adegoke A. Strategies to increase facility-based skilled birth attendance in South Asia: a literature review. Int Health. 2013;5(2):96–105.CrossRefPubMed
20.
Uganda Bureau of Statistics, ICF International Inc. Kampala. Kampala: Uganda Bureau of Statistics and ICF International Inc.; 2011. p. 2012.
21.
Tann C, Kizza M, Morison L, Mabey D, Muwanga M, Grosskurth H, et al. Use of antenatal services and delivery care in Entebbe, Uganda: a community survey. BMC Pregnancy Childbirth. 2007;7:23. doi:10.​1186/​1471-2393-7-23.
22.
Joharifard S, Rulisa S, Niyonkuru F, Weinhold A, Sayinzoga F, Wilkinson J, et al. Prevalence and predictors of giving birth in health facilities in Bugesera district, Rwanda. BioMed Central Public Health. 2012;12(1049).
23.
Mpembeni R, Zillewo J, Leshabari M, Massawe S, Jahn A, Mushi D, et al. Use pattern of maternal health services and determinants of skilled care during delivery in Southern Tanzania: implications for achievement of MDG-5 targets. BMC Pregnancy Childbirth. 2007;7(29).
24.
Ellis C, Schummers L, Rostoker J. Reducing maternal mortality in Uganda: applying the “three delays” framework. Int J Childbirth. 2011;1(4):218–26.CrossRef
25.
Parkhurst JO, Rahman SA, Ssengooba F. Overcoming access barriers for facility-based delivery in low-income settings: insights from Bangladesh and Uganda. J Health Popul Nutr. 2006;24(4):438–45.PubMedPubMedCentral
26.
Boudreaux C, Chanthala P, Lindelow M. Assessing the elimination of user fees for delivery services in Laos. PLoS ONE. 2014;9(3):1–8.CrossRef
27.
Essendi H, Mills S, Fotso J. Barriers to formal emergency obstetric care services’ utilization. J Urban Health. 2010;88(2):S356–69.
28.
Hodge A, Byrne A, Morgan A, Jimenez-Soto E. Utilisation of health services and geography: Deconstructing regional differences in barriers to facility-based delivery in Nepal. Matern Child Health J. 2015;19:566–77.
29.
30.
Silal SP, Penn-Kekana L, Bärnighausen T, Schneider H. Local level inequalities in the use of hospital-based maternal delivery in rural South Africa. Glob Health. 2014;10(60):(15 July 2014)–(15 July).
31.
Chambers V, Booth D. Delivering Maternal Health; why is Rwanda doing better than Malawi, Niger and Uganda? London: Overseas Development Institute, 2012 Contract No.: Report.
32.
MacDonagh S. Achieving skilled attendance for all; a synthesis of current knowledge and recommended actions for scaling up. London: Department for International Development, Health Resource Centre, 2005 Contract No.: Report.
33.
Kyomuhendo GB. Low use of rural maternity services in Uganda: impact of women’s status, traditional beliefs and limited resources. Reprod Health Matters. 2003;11(21):16–26.CrossRefPubMed
34.
UNOCHA. Humanitarian response: common and fundamental operational datasets registry Uganda. In: UNOCHA, editor. COD-FOD Registry 2011.
35.
Valadez JJ, Weiss W, Leburg C, Davis R. Assessing community health programs: a trainer’s guide. Using LQAS for baseline surveys and regular monitoring. St Albans: Teaching-aids At Low Cost; 2007.
36.
Valadez JJ, Jeffery C, Davis R, Ouma J, Lwanga SK, Moxon S. Putting the C back into the ABCs: a multi-year, multi-region investigation of condom use by Ugandan youths 2003–2010. PLoS ONE. 2014;9(4):e93083.CrossRefPubMedPubMedCentral
37.
Turner AG, Magnani RJ, Shuaib M. A not quite as quick but much cleaner alternative to the Expanded Programme on Immunization (EPI) Cluster Survey design. Int J Epidemiol. 1996;25(1):198–203.CrossRefPubMed
38.
Magnani R. Sampling guide. Washington: Food and Nutritional Technical Assistance Project (FANTA); 1997.
39.
SMART. Measuring mortality, nutritional status and food security in crisis situations: SMART methodology. US: Standardised Monitoring and Assessment of Relief and Transitions; 2006.
40.
World Health Organization. Immunization coverage cluster survey—reference manual. Geneva: World Health Organization; 2005.
41.
Beckworth CA, Davis RH, Faragher B, Valadez JJ. Can health workers reliably assess their own work? A test-retest study of bias among data collectors conducting a lot quality assurance sampling survey in Uganda. Health Policy Plan. 2015;30(2):181–6.CrossRefPubMed
42.
Anoke SC, Mwai P, Jeffery C, Valadez JJ, Pagano M. Comparing two survey methods of measuring health-related indicators: lot quality assurance sampling and demographic health surveys. Trop Med Int Health. 2015;20(12):1756–70.
43.
US Department of the Interior. USGS Science for a Changing World: Earth Resources Observation and Science (EROS) Center. Washington, DC: US Department of the Interior, 2010 Contract No.: Web Page.
44.
45.
Bivand R, Lewin-Koh N, Pebesma E, Archer E, Baddeley A, Bibiko H-J, et al. Maptools: tools for reading and handling spatial objects. In: R-Core Team, editor. 0.8-25 ed2013.
46.
Davison AC, Hinkley DV. Bootstrap methods and their application. Cambridge: Cambridge University Press; 1997.CrossRef
47.
Agresti A. Categorical data analysis. 3rd ed. Hoboken: Wiley; 2013 (xvi, 714 p. p.).
48.
Jones CM, Athanasiou T. Summary receiver operating characteristic curve analysis techniques in the evaluation of diagnostic tests. Ann Thorac Surg. 2005;79(1):16–20.CrossRefPubMed
49.
Arlot S, Celisse A. A survey of cross-validation procedures for model selection. Stat Surv. 2010;4:40–79.CrossRef
50.
Ministry of Health. Annual health sector performance report 2011–2012. Kampala: Government of UGadna; 2012.
51.
Bohren M, Hunter E, Munthe-Kaas H, Souza J, Vogel J, Gülmezoglu A. Facilitators and barriers to facility-based delivery in low- and middle-income countries: a qualitative evidence synthesis. Reprod Health. 2014;11(1):71.CrossRefPubMedPubMedCentral
52.
Bolam A, Manandhar DS, Shrestha P, Ellis M, Malla K, Costello AM. Factors affecting home delivery in the Kathmandu Valley, Nepal. Health Policy Plan. 1998;13(2):152–8.CrossRefPubMed
53.
Gabrysch S, Campbell O. Still too far to walk: Literature review of the determinants of delivery service use. BioMed Central Pregnancy Childbirth. 2009;9:34. doi:10.​1186/​1471-2393-9-34.
54.
Gage AJ, Guirlène Calixte M. Effects of the physical accessibility of maternal health services on their use in rural Haiti. Popul Stud. 2006;60(3):271–88.CrossRef
55.
Interagency Health Team. Global Health Initiative Uganda: a strategy for accelerating reductions in maternal and neonatal mortality. Kampala: US Mission Uganda, 2011 Dec 9, 2011. Report No.
56.
57.
Woldemicael G, Tenkorang EY. Women’s autonomy and maternal health-seeking behavior in Ethiopia. Matern Child Health J. 2010;14(6):988–98.CrossRefPubMed
58.
Celik Y, Hotchkiss DR. The socio-economic determinants of maternal health care utilization in Turkey. Social Sci Med (1982). 2000;50(12):1797–806.CrossRef
59.
Mrisho M, Schellenberg JA, Mushi AK, Obrist B, Mshinda H, Tanner M, et al. Factors affecting home delivery in rural Tanzania. Trop Med Int Health. 2007;12(7):862–72.CrossRefPubMed
60.
Asante AD, Zwi AB, Ho MT. Equity in resource allocation for health: a comparative study of the Ashanti and Northern Regions of Ghana. Health Policy. 2006;78(2–3):135–48.CrossRefPubMed
61.
Valadez JJ. Learning to be creative with HIV/AIDS studies: looking for the variation—not only the average. Int J Epidemiol. 2009;38(1):214–6.CrossRefPubMed
62.
Nanda P. Gender dimensions of user fees: implications for women’s utilization of health care. Reprod Health Matters. 2002;10(20):127–34.CrossRefPubMed
63.
MacNab YC. Hierarchical Bayesian modeling of spatially correlated health service outcome and utilization rates. Biometrics. 2003;59(2):305–16.CrossRefPubMed
Metadata
Title
Assessing delivery practices of mothers over time and over space in Uganda, 2003–2012
Authors
Daniel A. Sprague
Caroline Jeffery
Nadine Crossland
Thomas House
Gareth O. Roberts
William Vargas
Joseph Ouma
Stephen K. Lwanga
Joseph J. Valadez
Publication date
01-12-2016
Publisher
BioMed Central
Published in
Emerging Themes in Epidemiology / Issue 1/2016
Electronic ISSN: 1742-7622
DOI
https://doi.org/10.1186/s12982-016-0049-8

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