Evidence map›Paper›PMID 37182114›Full record

ArticleInternational journal of MCH and AIDS2023

Zubairu Iliyasu, Amina A Umar, Fatima S Gaya, Nafisa S Nass, Hadiza M Abdullahi, Aminatu A Kwaku, Taiwo G Amole, Fatimah I Tsiga-Ahmed, Hadiza S Galadanci, Hamisu M Salihu and 1 more

Open access · goldAbstract read
In one paragraph

Article in International journal of MCH and AIDS, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
4.1field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 2 countries.

Zubairu IliyasuDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Amina A UmarDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Fatima S GayaDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Nafisa S NassDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Hadiza M AbdullahiDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Aminatu A KwakuDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Taiwo G AmoleDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Fatimah I Tsiga-AhmedDepartment of Community Medicine, Bayero University, Kano, Nigeria.
Hadiza S GaladanciAfrican Center of Excellence for Population Health and Policy, Bayero University, Kano, Nigeria.
Hamisu M SalihuDepartment of Family and Community Medicine, Baylor College of Medicine, Houston, Texas, USA.
Muktar H AliyuDepartment of Health Policy & Vanderbilt Institute for Global Health, Vanderbilt University Medical Center, Tennessee, USA.
Bayero University Kano · NGBaylor College of Medicine · USVanderbilt Health · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Objective: The COVID-19 pandemic response overwhelmed health systems, disrupting other services, including maternal health services. The disruptive effects on the utilization of maternal health services in low-resource settings, including Nigeria have not been well documented. We assessed maternal health service utilization, predictors, and childbirth experiences amidst COVID-19 restrictions in a rural community of Kumbotso, Kano State, in northern Nigeria. Methods: Using an explanatory mixed methods design, 389 mothers were surveyed in January 2022 using validated interviewer-administered questionnaires, followed by in-depth interviews with a sub-sample (n=20). Data were analyzed using logistic regression models and the framework approach. Results: Less than one-half (n=165, 42.4%) of women utilized maternal health services during the period of COVID-19 restrictions compared with nearly two-thirds (n=237, 65.8%) prior to the period (p<0.05). Non-utilization was mainly due to fear of contracting COVID-19 (n=122, 54.5%), clinic overcrowding (n=43, 19.2%), transportation challenges (n=34, 15.2%), and harassment by security personnel (n=24, 10.7%). The utilization of maternal health services was associated with participant's post-secondary education (aOR=2.06, 95% CI:1.14- 11.40) (p=0.02), and employment type (civil service, aOR=4.60, 95% CI: 1.17-19.74) (p<0.001), business aOR=1.94, 95% CI:1.19- 4.12) (p=0.032) and trading aOR=1.62, 95% CI:1.19-2.94) (p=0.04)). Women with higher household monthly income (≥ N30,000, equivalent to 60 US Dollars) (aOR=1.53, 95% CI:1.13-2.65) (p=0.037), who adhered to COVID-19 preventive measures and utilized maternal health services before the COVID-19 pandemic were more likely to utilize those services during the COVID-19 restrictions. In contrast, mothers of higher parity (≥5 births) were less likely to use maternal health services during the lockdown (aOR=0.30, 95% CI:0.10-0.86) (p=0.03). Utilization of maternal services was also associated with partner education and employment type. Conclusion and Global Health Implications: The utilization of maternal health services declined during the COVID-19 restrictions. Utilization was hindered by fear of contracting COVID-19, transport challenges, and harassment by security personnel. Maternal and partner characteristics, adherence to COVID-19 preventive measures, and pre-COVID maternity service utilization influenced attendance. There is a need to build resilient health systems and contingent alternative service delivery models for future pandemics.

Indexed as

COVID-19Maternal HealthMaternal Health ServicesMixed Methods Study DesignNigeriaRural Nigeria

Identifiers

PMID37182114
PMCPMC10172809
OpenAlexW4375852578

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.