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Record W4407978908 · doi:10.1186/s12884-025-07339-z

Prevalence and correlates of depressive and anxiety symptoms among pregnant women from an urban informal settlement in Nairobi, Kenya: a community-based cross-sectional study

2025· article· en· W4407978908 on OpenAlexafffund
Stephen Mulupi, Amina Abubakar, Moses K. Nyongesa, Vibian Angwenyi, Margaret Kabue, Paul Mwangi, Rachael Odhiambo, Joyce Marangu, Eunice Njoroge, Mercy Moraa Mokaya, Emmanuel Kepha Obulemire, Eunice Ombech, Derrick Ssewanyana, Greg Moran, Marie‐Claude Martin, Kerrie Proulx, Kofi Marfo, Stephen J. Lye

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsWestern UniversityLunenfeld-Tanenbaum Research Institute
FundersAga Khan Foundation Canada
KeywordsMedicineReproductive medicineCross-sectional studyAnxietySettlement (finance)Depressive symptomsEnvironmental healthPregnancyFamily medicinePsychiatryObstetrics

Abstract

fetched live from OpenAlex

PURPOSE: Previous research, largely from the Global North, reports high rates of common mental health disorders among women in the antenatal period, but there is paucity of such data in contexts like Kenya. This study investigated the prevalence and correlates of depressive and anxiety symptoms among pregnant women in an urban informal settlement in Kenya's capital - Nairobi. METHODS: An analysis of baseline cross-sectional data from a pilot cluster randomized trial of an integrated early childhood development programme. Participants were pregnant women in their third pregnancy trimester (N = 249), residing in an urban informal settlement in Nairobi County. Mental health measures [(Patient health questionnaire (PHQ-9) and generalized anxiety disorder scale (GAD-7)] were administered alongside other sociodemographic, pregnancy, and health-related questionnaires. Linear regression analysis was performed to investigate correlates of antenatal depressive and anxiety symptoms. RESULTS: Participant's mean age was 27.5 years (SD = 5.6). The prevalence of antenatal depressive and anxiety symptoms was 26.9% (95%CI: 21.4-32.4) and 6.4% (95%CI: 3.4-9.4), based on the PHQ-9 and GAD-7 cut-off scores of ≥ 10 respectively. Being married was a significant correlate for decreased depressive and anxiety symptoms. Higher levels of education (secondary or tertiary), history of three or more previous pregnancies, and an experience of moderate-to-extreme pain were significant correlates for elevated depressive symptoms. Similarly, tertiary level of education, history of four or more previous pregnancies, and experiencing pain were significant correlates for elevated anxiety symptoms for the pregnant women. Participants reporting feeling unwell had significantly higher anxiety symptom scores. CONCLUSION: In this setting, correlates of antenatal depressive and anxiety symptoms cut across demographic, pregnancy and health-related factors with implications for targeted interventions. Findings point to the need for screening of depression and anxiety as part of routine antenatal care. Further research is needed to understand these contextual correlates. TRIAL REGISTRATION: This study was part of the integrated early childhood development pilot cluster randomised control trial, retrospectively registered in the Pan African Clinical Trial Registry on 26/03/2021, registration number PACTR202103514565914.

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)0.001
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 score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.012
GPT teacher head0.282
Teacher spread0.271 · 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

Citations6
Published2025
Admission routes2
Has abstractyes

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