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Enregistrement W4386133801 · doi:10.1016/s2468-2667(23)00174-3

Understanding multimorbidity early in life takes a step forward

2023· letter· en· W4386133801 sur OpenAlexaffabout
Mark A. Ferro

Notice bibliographique

RevueThe Lancet Public Health · 2023
Typeletter
Langueen
DomaineMedicine
ThématiqueChronic Disease Management Strategies
Établissements canadiensUniversity of Waterloo
Organismes subventionnairesnon disponible
Mots-clésMultimorbidityMedicinePublic healthPediatricsScopusGestational ageCohort studyDemographyCohortGerontologyMEDLINEPopulationEnvironmental healthPregnancyInternal medicineNursing

Résumé

récupéré en direct d'OpenAlex

Katriina Heikkilä and colleagues1Heikkilä K Metsälä J Pulakka A et al.Preterm birth and the risk of multimorbidity in adolescence: a multiregister-based cohort study.Lancet Public Health. 2023; 8: e680-e690Google Scholar used linked national registries from Finland and Norway to investigate the degree of prematurity and the development of multimorbidity (the co-occurrence of two or more health conditions, with none defined as the index condition) during adolescence. Using robust approaches to adjust for multiple testing and ignoring small effect sizes that were unlikely to be meaningful to public health or clinical practice, Heikkilä and colleagues’ findings showed that earlier gestational age at birth was consistently associated with increasingly complex multimorbidity (ie, two, three, and four co-occurring conditions) in a dose–response manner. These novel findings represent an important step forward in understanding multimorbidity early in life, and offer tangible insights for addressing current knowledge gaps and improving the lives of individuals born premature. To date, the field of multimorbidity research has largely focused on adult populations;2van den Akker M Dieckelmann M Hussain MA et al.Children and adolescents are not small adults: toward a better understanding of multimorbidity in younger populations.J Clin Epidemiol. 2022; 149: 165-171Summary Full Text Full Text PDF PubMed Scopus (0) Google Scholar, 3Head A Fleming K Kypridemos C Pearson-Stuttard J O'Flaherty M Multimorbidity: the case for prevention.J Epidemiol Community Health. 2021; 75: 242-244PubMed Google Scholar however, this study by Heikkilä and colleagues, along with the few studies conducted previously,4Ferro MA Qureshi S Van Lieshout RJ et al.Prevalence and correlates of physical-mental multimorbidity in outpatient children from a pediatric hospital in Canada.Can J Psychiatry. 2022; 67: 626-637Crossref PubMed Scopus (5) Google Scholar, 5Silva DT Hagemann E Davis JA et al.Introducing the ORIGINS project: a community-based interventional birth cohort.Rev Environ Health. 2020; 35: 281-293Crossref PubMed Scopus (0) Google Scholar suggests that predictors and development of multimorbidity often occur early in life. Medical advances will indeed continue to help prevent premature births, allowing fetuses to develop in utero; however, more upstream public health and health system strategies that target the social determinants of preterm birth are warranted.6Hong X Bartell TR Wang X Gaining a deeper understanding of social determinants of preterm birth by integrating multi-omics data.Pediatr Res. 2021; 89: 336-343Crossref PubMed Scopus (6) Google Scholar As shown in Heikkilä and colleagues’ data, the prevalence of preterm births is relatively high, and the health conditions identified represent those that are chronic in nature, which can result in substantial individual, family, system, and societal burdens of multimorbidity across the lifespan. Informing healthy public policy to address these burdens requires large-scale studies evaluating the extent to which multisectoral public health investments on key social determinants across health, education, and social services systems improve health and wellbeing and reduce costs. Examining the development of multimorbidity in adolescence is crucial; it is during adolescence that multimorbidity can compound the existing increased risk for poor mental and psychosocial health. Similarly, it is encouraging that Heikkilä and colleagues investigated the case of physical–mental multimorbidity (ie, at least one physical and one mental health condition). Research concentrating on physical–mental multimorbidity in young people is an emerging field of study that is still very much in its infancy; however, knowledge gains have been made by Tegethoff and colleagues in understanding the temporality of onset,7Tegethoff M Stalujanis E Belardi A Meinlschmidt G Chronology of onset of mental disorders and physical diseases in mental-physical comorbidity—a national representative survey of adolescents.PLoS One. 2016; 11e0165196Crossref PubMed Scopus (30) Google Scholar and by Arrondo and colleagues in quantifying condition-specific associations.8Arrondo G Solmi M Dragioti E et al.Associations between mental and physical conditions in children and adolescents: an umbrella review.Neurosci Biobehav Rev. 2022; 137104662Crossref PubMed Scopus (11) Google Scholar The study by Heikkilä and colleagues found that physical–mental multimorbidity had some of the strongest associations with preterm birth and similar dose–response effects across degree of prematurity, consistent with their overall analyses and with a previous report conducted by the investigators.9Heikkilä K Pulakka A Metsälä J et al.Preterm birth and the risk of chronic disease multimorbidity in adolescence and early adulthood: a population-based cohort study.PLoS One. 2021; 16e0261952Crossref Scopus (6) Google Scholar As physical and mental health care are often siloed within paediatric settings, leading families to navigate the health system on their own, these findings underscore the pressing need to prioritise coordinated care for individuals born premature, as well as a redoubling of efforts to seamlessly integrate physical and mental health care for children and adolescents. Indeed, previous evidence shows that young people with physical–mental multimorbidity have poorer psychosocial health compared with other morbidity groups—a finding that is in part a function of less-than-optimal health care provision for individuals with such complex multimorbidity.10Ferro MA Qureshi SA Shanahan L Otto C Ravens-Sieberer U Health-related quality of life in children with and without physical-mental multimorbidity.Qual Life Res. 2021; 30: 3449-3461Crossref PubMed Scopus (13) Google Scholar In addition to implementing integrated models of care to support timely and appropriate access to health care, system-wide studies of how integrated care is incorporated into transition planning for individuals born premature with physical–mental multimorbidity can provide the evidence needed to best support the complex care needs for these adolescents as they enter the adult health system. In their well designed study, Heikkilä and colleagues make efficient use of two national registers, reporting robust findings, which are appropriately tempered in the context of the limitations of their data sources, to infer that premature birth is an important characteristic that conditions risk for multimorbidity in adolescence. The investigators clearly articulate the need for mechanistic studies to explore the potential causal links between gestational age at birth and multimorbidity to advance this research agenda; a call that inherently requires a transdisciplinary approach with multiple stakeholders, including individuals and caregivers with lived experience. From a public health perspective, upstream strategies targeting social determinants of preterm birth and system shifts in the provision of health care are key opportunities to reduce the incidence of multimorbidity in individuals born premature and to improve health within the population. I declare no competing interests. Preterm birth and the risk of multimorbidity in adolescence: a multiregister-based cohort studyPreterm birth is associated with increased risks of diverse multimorbidity patterns at age 10–18 years. Adolescents with a preterm-born background could benefit from diagnostic vigilance directed at multimorbidity and a multidisciplinary approach to health care. Full-Text PDF Open Access

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)0,002
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Intégrité de la recherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,002
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,516
Tête enseignante GPT0,405
Écart entre enseignants0,111 · 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'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations2
Publié2023
Routes d'admission2
Résumé présentoui

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