Notice bibliographique
Résumé
It is well documented that socioeconomic status, whether described by income, education or occupation, is an important determinant of health outcomes and the use of health services (1,2). Children living in poverty are at risk for poor physical and mental health outcomes (3–5). Research suggests that childhood poverty has an impact on both child and adult health, and, that for certain health outcomes later in life, the deprivation need not be continuous into adulthood (6,7). In Canada, rates of low birth weight (LBW), infant mortality, childhood mortality from accidental causes and respiratory disease, hospitalization for injuries, and psychosocial, psychiatric and behavioural problems are higher in children living in low compared with high income households (8–11). In general, the relationship between many health outcomes and poverty tends to be linear, such that with every incremental increase in income there is an improvement in outcome; although, for some conditions there seems to be a threshold level of deprivation under which the association is strongest. For example, work on psychosocial morbidity in a cohort of Ontario children revealed an important threshold level of deprivation at less than $10,000/year in family income (12). A brief review of the most recent statistics revealed that, in the international context, Canada places an abysmal 17th in the industrialized countries in terms of percentage of children living in ‘relative poverty’ (households with incomes below 50% of the national median) (13), with over 20% of children living in poverty (14). The rates of child poverty are higher among single parent households (59.2%), Aboriginal households (43.4%) and households of visible minorities (35.9%). Younger children are more likely to live in poor households, and there is a greater percentage of poor households in urban centres (15). There are very few data on some of the most vulnerable of Canada's urban poor, but estimates from Toronto, Ontario suggest that approximately 19% of the homeless population and 31% to 54% of those who rely on foodbanks are children (16,17). The child poverty rate increased from 14.9% in 1981 to 21% in 1996 (the last year for which census data are available) (14), with the disparity between the highest and lowest income quintiles also widening. In that time period, there was a concomitant increase in disparities in health outcomes, such as LBW, between those children in the lowest compared with the highest income quintiles (10). The literature on the determinants of health, which seeks to explicate the complex set of personal, community and societal forces that have an impact on the health of individuals, suggests that such disparities in income are more important predictors of health than absolute rates of deprivation (18–23). Access to health care is one such determinant, although it may be argued that in a universal first-dollar health insurance system such as Canada's, health care is more of a modulator of the other important determinants of health. A first glance at whether there are important differences in how children in low income neighbourhoods access care suggests that low income children are less likely to receive care from the same provider over time and less likely to access the care of a paediatrician (24). Two recent reports from Manitoba (25,26) shed light on some important issues on the interplay between socioeconomic deprivation, health status and health care services use among children. The first report by Manitoba's Centre for Health Policy and Evaluation (25) is an exhaustive review of the markers of health status and health services use by children available largely from administrative data in Manitoba. With respect to health services use, the findings suggest that in urban areas, the number of visits that children make to physicians is inversely proportional to the neighbourhood income level, although the opposite was true in rural areas. However, for both urban and rural children, the likelihood of accessing the care of a specialist (including a general paediatrician) increased in tandem with neighbourhood income. A similar gradient by neighbourhood income existed for two measures of quality of care: continuity of provider care and rates of immunization, with poor children having lower rates of both. The effect of this difference of care was shown by a documented higher rate of hospitalizations for immunizable, preventable infections with decreasing neighbourhood income. There is evidence from the literature that provider continuity of care can help improve health outcomes and reduce admissions for children with chronic diseases such as asthma (27). The second report (26) focused on the use of health care services by a high risk group of Manitoba children who were living in single parent families receiving income assistance in Manitoba. Children in income-assisted households had higher numbers of physician visits than children in nonassisted households, including those living in poor neighbourhoods. However, the children in income-assisted households were more likely to receive treatment for acute conditions, but less likely to receive preventative medical services. Among young children (one to 10 years of age) not on assistance, this trend toward acute rather than preventative care was also seen in the lower income group. Particularly striking was the observation that of those children whose morbidity burden was considered to be a permanent or recurrent condition, children on social assistance had the lowest rates of physician contacts. The children from income-assisted households were hospitalized 60% to 80% more frequently than other children, mainly for acute conditions. In children from urban areas, assistance status was related to an additional risk of hospitalization over that predicted by the child being from a low income neighbourhood. This result is similar to findings on the mental health of children living in single parent families from an analysis of the National Longitudinal Survey of Children and Youth (NLSCY) (28). This study showed single motherhood to be a significant and independent risk factor for problems such as hyperactivity, conduct disorder, school difficulties and emotional disorders when controlling for the effects of low income. The main limitations of the two Manitoba studies (25,26), as with most research based on administrative data, are that most of the description of socioeconomic status is at the neighbourhood level and that health care utilization is both the outcome of interest and the tool for measuring health status. Nevertheless, these studies are remarkable for their comprehensiveness, their attempt to try to classify physician visits on the basis of morbidity type (a type of risk adjustment) and quality of care, and for the technical aspects of merging a cohort from social services with administrative health records. This research clearly points to an inequality in the access of appropriate preventative and specialty health care among the most vulnerable children, and to hospital utilization and morbidity, which may be avoidable. Important questions remain around which health outcomes are most amenable to appropriate ambulatory care, the nature of the barriers to such care and how to address them at the level of the patient, the physician's practice and the overall structure of the predominantly fee-for-service health care system. Ideally, this will require research that will account for individual-level biological, social and economic factors. Input from vulnerable patients and their parents, as well as health care providers, will be important. The NLSCY, although rich in its content about important individual, family and community factors that influence health, has limitations in terms of data on health services use and longitudinal health status. The path to the eradication of poverty is ultimately political. Although there was all-party consensus in 1989 to end child poverty by 2000, it is clear that more than just a consensus is required. Child health care professionals, as individuals or as members of professional societies, should play a role in advocating for this goal. However, they can play an important role as physicians to attenuate some of the effects that poverty or socioeconomic deprivation has on child health. Clearly, the use of appropriate health care services is not the only answer to child poverty and its health consequences, nor is the issue of continuity of care or seeking preventative care solely in the hands of the health care professional. While researchers and policy makers grapple with these issues, individual health care providers can focus on their own patients, location and structure of their practice, and evaluate whether there are strategies that may improve the care received by the children in our society who are most at risk for poor health.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,011 |
| Études des sciences et des technologies | 0,004 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».