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Record W4407141527 · doi:10.1186/s12889-025-21666-y

Predictors of food security status among informal caregivers of older adults residing in slums in Ghana

2025· article· en· W4407141527 on OpenAlexaff
Dina Adei, Williams Agyemang‐Duah, Bright Osei Boateng, Anthony Acquah Mensah

Bibliographic record

VenueBMC Public Health · 2025
Typearticle
Languageen
FieldHealth Professions
TopicFood Security and Health in Diverse Populations
Canadian institutionsTrent UniversityQueen's University
Fundersnot available
KeywordsBiostatisticsMedicineEnvironmental healthPublic healthEpidemiologyFood securityGerontologyNursingPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Informal caregivers of older adults play a crucial role, positively influencing the physical, mental, and social well-being of their care recipients, while concurrently contributing to substantial cost savings in the healthcare sector. The significance of food security for these caregivers becomes paramount as it not only impacts their health but also influences the energy needed to fulfil their caregiving responsibilities. Nevertheless, there is a scant literature on the factors that predict food security status among informal caregivers of older adults residing in slum communities in Ghana. This study seeks to address this gap by examining the factors that predict food security status among informal caregivers. METHODS: A sample of 458 informal caregivers of older adults residing in slum communities in the Greater Kumasi metropolis was used for the study. The Generalized Linear Regression Model was used to estimate factors that predict food security status among informal caregivers of older adults in slum communities. Beta values and standard errors were utilised, with a significance level of 0.05 or lower. RESULTS: The analysis showed that 88.4% of the participants were females, 37.3% were aged 40-49 years, 72.7% were of Akan ethnicity, 81.4% were married, 45.4% had basic education, 96.3% did not receive pay for caregiving and 72.1% were enrolled in a national health insurance scheme. The study revealed that participants without formal education (β = 0.661, p <.05) and those aged 29 years or younger (β = 26.927, p <.001), 30-39 years (β = 27.453, p <.001), and 40-49 age group (β = 26.710, p <.001) statistically significantly exhibited an increased food security status compared to their counterparts. Additionally, participants identifying as Akan (β = -0.421, p <.05), Christians (β = -0.828, p <.001), married individuals (β = -0.500, p <.05), those who reported never being ill (β = -2.617, p <.001), those without chronic non-communicable diseases (NCDs) (β = -0.638, p <.001), and those not enrolled in the national health insurance scheme (β = -0.422, p <.01) statistically significantly experienced a decreased food security status compared to their counterparts. CONCLUSION: Considering these findings, policymakers are urged to integrate socio-economic and health characteristics of informal caregivers into food security policies. This inclusive approach is essential for enhancing the food security status of informal caregivers responsible for older adults in slum communities.

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)0.003
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 score0.017
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
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 science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.071
GPT teacher head0.390
Teacher spread0.319 · 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

Citations7
Published2025
Admission routes1
Has abstractyes

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