Dataset Information

The influence of travel time to health facilities on stillbirths: A geospatial case-control analysis of facility-based data in Gombe, Nigeria.

ABSTRACT: Access to quality emergency obstetric and newborn care (EmONC); having a skilled attendant at birth (SBA); adequate antenatal care; and efficient referral systems are considered the most effective interventions in preventing stillbirths. We determined the influence of travel time from mother's area of residence to a tertiary health facility where women sought care on the likelihood of delivering a stillbirth. We carried out a prospective matched case-control study between 1st January 2019 and 31st December 2019 at the Federal Teaching Hospital Gombe (FTHG), Nigeria. All women who experienced a stillbirth after hospital admission during the study period were included as cases while controls were consecutive age-matched (ratio 1:1) women who experienced a live birth. We modelled travel time to health facilities. To determine how travel time to the nearest health facility and the FTHG were predictive of the likelihood of stillbirths, we fitted a conditional logistic regression model. A total of 318 women, including 159 who had stillborn babies (cases) and 159 age-matched women who had live births (controls) were included. We did not observe any significant difference in the mean travel time to the nearest government health facility for women who had experienced a stillbirth compared to those who had a live birth [9.3 mins (SD 7.3, 11.2) vs 6.9 mins (SD 5.1, 8.7) respectively, p = 0.077]. However, women who experienced a stillbirth had twice the mean travel time of women who had a live birth (26.3 vs 14.5 mins) when measured from their area of residence to the FTHG where deliveries occurred. Women who lived farther than 60 minutes were 12 times more likely of having a stillborn [OR = 12 (1.8, 24.3), p = 0.011] compared to those who lived within 15 minutes travel time to the FTHG. We have shown for the first time, the influence of travel time to a major tertiary referral health facility on the occurrence of stillbirths in an urban city in, northeast Nigeria.

SUBMITTER: Wariri O

PROVIDER: S-EPMC7790442 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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The influence of travel time to health facilities on stillbirths: A geospatial case-control analysis of facility-based data in Gombe, Nigeria.

Wariri Oghenebrume O Onuwabuchi Egwu E Alhassan Jacob Albin Korem JAK Dase Eseoghene E Jalo Iliya I Laima Christopher Hassan CH Farouk Halima Usman HU El-Nafaty Aliyu U AU Okomo Uduak U Dotse-Gborgbortsi Winfred W

PloS one 20210107 1

Access to quality emergency obstetric and newborn care (EmONC); having a skilled attendant at birth (SBA); adequate antenatal care; and efficient referral systems are considered the most effective interventions in preventing stillbirths. We determined the influence of travel time from mother's area of residence to a tertiary health facility where women sought care on the likelihood of delivering a stillbirth. We carried out a prospective matched case-control study between 1st January 2019 and 31 ...[more]

PMID: 33411850

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Project description:IntroductionUganda with 17.8 stillbirths per 1,000 deliveries in 2021, is among the countries with a high burden of stillbirths globally. In 2014, Uganda adopted the World Health Organization Every New-born Action Plan (ENAP), which targets < 10 stillbirths per 1,000 deliveries by 2035. Little is known about the trends of stillbirth burden since ENAP was introduced. We assessed the temporal, and spatial distribution of stillbirths, in Uganda, 2014-2020, to inform programming for safe pregnancies and deliveries.MethodsWe obtained and analysed stillbirth surveillance data from the District Health Information System, 2014-2020. A stillbirth was defined as the death of a foetus > 28 weeks of pregnancy or weighing > 1000 g before or during birth and reported to a health facility. We calculated annual incidence rates of stillbirths per 1,000 deliveries at district, regional, and national levels. We used logistic regression to determine the significance of trends.ResultsThe overall national annual incidence of stillbirths decreased from 24/1,000 deliveries in 2014 to 17/1,000 deliveries in 2020. During the same period, reporting rates declined from 71% in 2014 to 46% in 2020. The central region continuously had the highest incidence rate for the past 5 years despite the largest decline (OR = 0.79; CI = 0.77-0.83, P < 0.001) while the eastern region had the smallest decline (OR = 0.59; CI = 0.57-0.61, P < 0.001). Districts with persistently high annual incidence rates of stillbirths (> 30/1000) included Mubende, Kalangala, Hoima, and Nebbi. There was no difference in the reporting rates of the most- vs. least-affected districts.ConclusionEven with suboptimal reporting, the incidence of stillbirths remained above the national target. Specific areas in the country appear to have particularly high stillbirth rates. We recommend continuous capacity building in managing pregnant women with an emphasis on the most affected districts, and investigation into the reasons for low reporting.

Project description:ObjectivesPrimary objective: to assess nine data quality metrics for 14 maternal and newborn health data elements, following implementation of an integrated, district-focused data quality intervention.Secondary objectiveto consider whether assessing the data quality metrics beyond completeness and accuracy of facility reporting offered new insight into reviewing routine data quality.DesignBefore-and-after study design.SettingPrimary health facilities in Gombe State, Northeastern Nigeria.ParticipantsMonitoring and evaluation officers and maternal, newborn and child health coordinators for state-level and all 11 local government areas (district-equivalent) overseeing 492 primary care facilities offering maternal and newborn care services.InterventionBetween April 2017 and December 2018, we implemented an integrated data quality intervention which included: introduction of job aids and regular self-assessment of data quality, peer-review and feedback, learning workshops, work planning for improvement, and ongoing support through social media.Outcome measures9 metrics for the data quality dimensions of completeness and timeliness, internal consistency of reported data, and external consistency.ResultsThe data quality intervention was associated with improvements in seven of nine data quality metrics assessed including availability and timeliness of reporting, completeness of data elements, accuracy of facility reporting, consistency between related data elements, and frequency of outliers reported. Improvement differed by data element type, with content of care and commodity-related data improving more than contact-related data. Increases in the consistency between related data elements demonstrated improved internal consistency within and across facility documentation.ConclusionsAn integrated district-focused data quality intervention-including regular self-assessment of data quality, peer-review and feedback, learning workshops, work planning for improvement, and ongoing support through social media-can increase the completeness, accuracy and internal consistency of facility-based routine data.

Project description:Background: The Gambia Demographic and Health Survey 2013 data showed that up to 63% of deliveries in the country occur in health facilities. Despite such a high rate, there are few facility-based studies on delivery outcomes in the country. This analysis ancillary to a randomized control trial describes occurrence of poor pregnancy outcomes in a cohort of women and their infants delivering in a government health facility in urban Gambia. Methods: Using clinical information obtained during the trial, we calculated rates of poor pregnancy outcomes including stillbirths, hospitalization and neonatal deaths. Logistic regression was used to calculate odds ratio (OR) and 95% confidence interval (CI) in the risk factors analysis. Results: Between April 2013 and 2014, 829 mothers delivered 843 babies, including 13 stillbirths [15.4 (7.1-23.8)] per 1,000 births. Among 830 live born infants, 7.6% (n = 63) required hospitalization during the 8-week follow-up period. Most of these hospitalizations (74.6%) occurred during the early neonatal period (<7 days of life). Severe clinical infections (i.e., sepsis, meningitis and pneumonia) (n = 27) were the most common diagnoses, followed by birth asphyxia (n = 13), major congenital malformations (n = 10), jaundice (n = 6) and low birth weight (n = 5). There were sixteen neonatal deaths, most of which also occurred during the early neonatal period. Overall, neonatal mortality rate (NMR) and perinatal mortality rate (PMR) were 19.3 (CI: 9.9-28.7) per 1,000 live births and 26.1 (CI: 15.3-36.9) per 1,000 total births, respectively. Severe clinical infections and birth asphyxia accounted for 37 and 31% of neonatal deaths, respectively. The risk of hospitalization was higher among neonates with severe congenital malformations, low birth weight, twin deliveries, and those born by cesarean section. Risk of mortality was higher among neonates with severe congenital malformations and twin deliveries. Conclusion: Neonatal hospitalization and deaths in our cohort were high. Although vertical interventions may reduce specific causes of morbidity and mortality, data indicate the need for a holistic approach to significantly improve the rates of poor pregnancy outcomes. Critically, a focus on decreasing the high rate of stillbirths is warranted. Clinical Trial Registration: ClinicalTrials.gov Identifier: NCT01800942.

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Dataset Information

The influence of travel time to health facilities on stillbirths: A geospatial case-control analysis of facility-based data in Gombe, Nigeria.

Publications

The influence of travel time to health facilities on stillbirths: A geospatial case-control analysis of facility-based data in Gombe, Nigeria.

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