Demographic Characteristics associated with Food Allergy in a Nationwide Canadian Study
Notice bibliographique
Résumé
Demographic Characteristics associated with Food Allergy in a Nationwide Canadian StudyTo the Editor,We conducted a nationwide Canadian telephone survey on food allergy (FA) prevalence between 02/2016 and 01/2017 (SPAACE [S urveying P revalence of FoodA llergy in A ll C anadianE nvironments] to SPAACE [S2S]1], targeting vulnerable populations (New, Indigenous, and lower-income Canadians) using 2006 Canadian Census data (Appendix). We compared prevalence between vulnerable and non-vulnerable populations2 and reported (in univariable analysis) that prevalence was lower in immigrants and less-educated adults. We now examine the independent effect of these and other characteristics (age, sex, race/ethnicity, and household size) on FA.The adult household respondent completed the Food Allergy Prevalence Questionnaire (FAPQ)1,3,4 for each household member (Appendix). Food allergy was defined as perceived (self-report of any FA) or probable (self-report of a convincing history (Appendix) and/or physician diagnosis of a peanut, tree nut, fish, shellfish, sesame, milk, egg, wheat, and/or soy allergy).1,4 The Research Ethics Boards of the Universities of Calgary and Waterloo approved the study. The association between perceived and probable FA and demographic characteristics was assessed through weighted univariable and multivariable random effects logistic regressions (Appendix).Of 11,592 eligible households, 5874 completed the FAPQ (50.7% household response rate), providing data on 14,818 individuals (Table 1).In multivariable analyses, adults ≥45 years (OR 0.69, 95% confidence interval (CI) 0.56, 0.86), New Canadians (OR 0.51, 95%CI 0.38, 0.69), those immigrating to Canada ≥10 years prior (OR 0.75, 95%CI 0.62, 0.92), and those residing in larger households (OR 0.82, 95%CI 0.75, 0.90) were less likely to report any perceived FA (Table 2). Females (OR 1.49, 95%CI 1.27, 1.74) and adults with post-secondary education (OR 1.20, 95%CI 1.02, 1.43) were more likely to reportperceived FA.New Canadians (OR 0.46, 95%CI 0.30, 0.68), those immigrating ≥10 years prior (OR 0.64, 95%CI 0.49, 0.82), and those residing in larger households (OR 0.85, 95%CI 0.77, 0.94) were less likely to reportprobable FA, whereas children (OR 1.95, 95%CI 1.38, 2.75), females (OR 1.49, 95%CI 1.22, 1.82), and adults with post-secondary education (OR 1.55, 95%CI 1.23, 1.96) were more likely to reportprobable FA.In addition to many of the characteristics associated with any FA, race/ethnicity was also associated with some individual FA (Supplemental Table 1A&B).When the sample was restricted to parents with at least one Canadian-born child, Asian-born parents were less likely to report anyperceived (OR 0.40, 95%CI 0.24, 0.66) and probable FA (OR 0.29, 95%CI 0.14, 0.61) (Supplemental Table 2). However, Canadian-born children of Asian-born parents were more likely to report anyperceived (OR 1.77, 95% CI 1.13, 2.76) and probable FA (OR 2.11, 95% CI 1.29, 3.43).We have shown that while children, females, and adults with post-secondary education were more likely to report at least oneperceived or probable FA and adults ≥ 45 years, immigrants, and those in larger households were less likely to report FA, Asian and Indigenous race/ethnicity were associated with specific foods. It is likely that our observed association between FA and higher education and Canadian birthplace is attributable to increased FA awareness, better healthcare access, and differing genetic and environmental influences. The association between larger household size and decreased FA supports the hygiene hypothesis.5 Our paradoxical finding of a lower odds of FA in Asian-born parents of Canadian-born children and a higher odds of FA in Canadian-born children of Asian-born parents suggests that early life environmental exposures, such as climate, dietary, and microbial, exert a differential effect depending on genetic background.Although our nationwide sampling frame precluded food challenges and only included households with landlines and nonresponse bias may have influenced our results, we have demonstrated clear associations between demographic characteristics and FA, potentially important clues to environmental determinants.
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 | 0,001 | 0,005 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».