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Enregistrement W3183833358 · doi:10.1371/journal.pone.0255534

Older adults with non-communicable chronic conditions and their health care access amid COVID-19 pandemic in Bangladesh: Findings from a cross-sectional study

2021· article· en· W3183833358 sur OpenAlexaff
Sabuj Kanti Mistry, ARM Mehrab Ali, Uday Narayan Yadav, Saruna Ghimire, Md. Belal Hossain, Suvasish Das Shuvo, Manika Saha, Sneha Sarwar, Md. Mohibur Hossain Nirob, Varalakshmi Chandra Sekaran, Mark Harris

Notice bibliographique

RevuePLoS ONE · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueChronic Disease Management Strategies
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésMedicineNon-communicable diseasePandemicCross-sectional studyPublic healthHealth careChronic conditionMultimorbidityCommunicable diseaseGerontologyDiseaseEnvironmental healthFamily medicineChronic diseaseCoronavirus disease 2019 (COVID-19)NursingInfectious disease (medical specialty)Internal medicine

Résumé

récupéré en direct d'OpenAlex

BACKGROUND: Burgeoning burden of non-communicable disease among older adults is one of the emerging public health problems. In the COVID-19 pandemic, health services in low- and middle-income countries, including Bangladesh, have been disrupted. This may have posed challenges for older adults with non-communicable chronic conditions in accessing essential health care services in the current pandemic. The present study aimed at exploring the challenges experienced by older Bangladeshi adults with non-communicable chronic conditions in receiving regular health care services during the COVID-19 pandemic. MATERIALS AND METHODS: The study followed a cross-sectional design and was conducted among 1032 Bangladeshi older adults aged 60 years and above during October 2020 through telephone interviews. Self-reported information on nine non-communicable chronic conditions (osteoarthritis, hypertension, heart disease, stroke, hypercholesterolemia, diabetes, chronic respiratory diseases, chronic kidney disease, cancer) was collected. Participants were asked if they faced any difficulties in accessing medicine and receiving routine medical care for their medical conditions during the COVID-19 pandemic. The association between non-communicable chronic conditions and accessing medication and health care was analysed using binary logic regression model. RESULTS: Most of the participants aged 60-69 years (77.8%), male (65.5%), married (81.4%), had no formal schooling (58.3%) and resided in rural areas (73.9%). Although more than half of the participants (58.9%) reported having a single condition, nearly one-quarter (22.9%) had multimorbidity. About a quarter of the participants reported difficulties accessing medicine (23%) and receiving routine medical care (27%) during the pandemic, and this was significantly higher among those suffering from multimorbidity. In the adjusted analyses, participants with at least one condition (AOR: 1.95, 95% CI: 1.33-2.85) and with multimorbidity (AOR: 4.75, 95% CI: 3.17-7.10) had a higher likelihood of experiencing difficulties accessing medicine. Similarly, participants with at least one condition (AOR: 3.08, 95% CI: 2.11-4.89) and with multimorbidity (AOR: 6.34, 95% CI: 4.03-9.05) were significantly more likely to face difficulties receiving routine medical care during the COVID-19 pandemic. CONCLUSIONS: Our study found that a sizeable proportion of the older adults had difficulties in accessing medicine and receiving routine medical care during the pandemic. The study findings highlight the need to develop an appropriate health care delivery pathway and strategies to maintain essential health services during any emergencies and beyond. We also argue the need to prioritise the health of older adults with non-communicable chronic conditions in the centre of any emergency response plan and policies of Bangladesh.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,018
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,081
Tête enseignante GPT0,364
Écart entre enseignants0,283 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations60
Publié2021
Routes d'admission1
Résumé présentoui

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