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Record W4381512370 · doi:10.9734/indj/2023/v20i1385

A Comparison of Antenatal Depressive Disorders in Urban and Rural Pregnant Women in Nigeria

2023· article· en· W4381512370 on OpenAlexaff
Fawaz Babandi, Z. G. Habib, UmarMusa Usman, Mustapha I. Gudaji, Abdulwahab Salihu, Maryam A. Habib, Sumayya I. Inuwa, Kawther I. Inuwa, Abdulfatai Tomori Bakare

Bibliographic record

VenueInternational Neuropsychiatric Disease Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsHealth Care FoundationSt. Michael's Hospital
Fundersnot available
KeywordsMedicineSocioeconomic statusDepression (economics)Edinburgh Postnatal Depression ScaleDeveloping countryEthnic groupAntenatal depressionPopulationRural areaEnvironmental healthPregnancyMental healthDemographyGeographyDepressive symptomsPsychiatryAnxietyEconomic growth

Abstract

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Background: The prevalence of antenatal depression (AND) is consistently higher in urban areas in developed counties while the reverse is the case in developing counties developing countries. This highlights that socioeconomic gaps and health disparities between different settings could have important implications on perinatal mental health. Nigeria, the most populous nation in Africa, is home to multiple ethnic and cultural groups and about half of the population is rural. But then a majority of Nigerian studies on and were conducted in the urban and semi-urban southern regions. Few, if any, such studies were ever conducted in the urban or rural settings of northern Nigeria. The study aimed to determine and compare the prevalence and factors associated with AND among pregnant women in urban and rural northern Nigeria settings. A descriptive comparative cross-sectional study was conducted among antenatal clinic attendees of an urban and a rural health facility in Kano State, northern Nigeria. Data were collected from pregnant mothers. A socio-demographic and clinical characteristics questionnaire was used to obtain the relevant data. Edinburgh Postnatal Depression Scale (EPDS), Hamilton Depression Rating Scale (HDRS) and the major depression module of the Mini International Neuropsychiatric Interview (MINI-7) were used to screen, rate and diagnose depression among the respondents respectively. Results: The urban pregnant women were older (28.3±5.7 versus 26.0±5.6 years, p=0.001), better educated (12.8±2.8 versus 8.9±4.3 years of schooling, p<0.001), earning higher average monthly income (36.0 USD vs 13.0 USD, p<0.001), in the second trimester of the pregnancy (22% versus 9.7%, p=0.004). While the rural women were more likely to have planned to get pregnant (84.1% versus 69.3%, p=0.003) and used psychoactive substances while pregnant (20.7% versus 8.7%, p=0.003). The prevalence of AND was significantly higher among the rural respondents as compared to the urban respondents (33.1% versus 14.7% p<0.001). Anaemia in pregnancy (AIP), a history of a background medical problem (BMP) was significantly associated with AND in the urban setting (p= 0.032 and p= 0.001 respectively). While in the rural setting, AIP and a history of BMP were significantly associated with AND (p=0.0063 and p=0.008 respectively). Furthermore, among the multigravid urban and rural respondents, previous pregnancy complication was found to be significantly associated with AND (p=0.030). Among the urban women, the predictor for AND was a history of BMP (OR=5.049, 95%CI=1.451-17.570). The significant predictors for AND in the rural setting were AIP (OR=3.337, 95%CI=1.468-7.798) and history of BMP (OR=3.298, 95%CI=1.267-8.885). Conclusion: Rural prevalence of AND was significantly much higher than the urban rate. Certain factors, such as BMP and AIP, were associated with AND in both urban and rural settings.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.011
GPT teacher head0.316
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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