Combined effects of multiple risk factors on asthma in school-aged children

Szentpetery, Sylvia S.; Gruzieva, Olena; Forno, Erick; Han, Yueh‐Ying; Bergström, Anna; Kull, Inger; Acosta‐Pérez, Edna; Colón-Semidey, Angel; Alvarez, María; Canino, Glorisa; Melén, Erik; Celedón, Juan C.

doi:10.1016/j.rmed.2017.11.002

Cited by 23 publications

(24 citation statements)

References 30 publications

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“…Our findings add strong evidence to the only previously published study that investigated the association between childhood asthma and a combination of several adverse lifestyle factors 12. This small case–control study conducted among 609 Puerto Rican children aged 6–14 years showed that the presence of three risk factors compared with none was associated with 10-fold to 11-fold increased odds of asthma.…”

Section: Discussionsupporting

confidence: 81%

Combined impact of healthy lifestyle factors on risk of asthma, rhinoconjunctivitis and eczema in school children: ISAAC phase III

Morales

Strachan

Asher

et al. 2019

Thorax

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BackgroundAsthma is not the key focus of prevention strategies. A Healthy Lifestyle Index (HLI) was developed to examine the combined effect of modifiable lifestyle factors on asthma, rhinoconjunctivitis and eczema using data from the International Study of Asthma and Allergies in Childhood (ISAAC) phase III.MethodsInformation on symptoms of asthma, rhinoconjunctivitis, eczema and several lifestyle factors was obtained from children aged 6–7 years through written questionnaires. The HLI combined five lifestyle factors: no parental smoking, child’s adherence to Mediterranean diet, child’s healthy body mass index, high physical activity and non-sedentary behaviour. The association between the HLI and risk of asthma, rhinoconjunctivitis and eczema was evaluated using multilevel mixed-effects logistic regression models.FindingsData of 70 795 children from 37 centres in 19 countries were analysed. Each additional healthy lifestyle factor was associated with a reduced risk of current wheeze (OR 0.87, 95% CI 0.84 to 0.89), asthma ever (OR 0.89, 95% CI 0.87 to 0.92), current symptoms of rhinoconjunctivitis (OR 0.95, 95% CI 0.92 to 0.97) and current symptoms of eczema (OR 0.92, 95% CI 0.92 to 0.98). Theoretically, if associations were causal, a combination of four or five healthy lifestyle factors would result into a reduction up to 16% of asthma cases (ranging from 2.7% to 26.3 % according to region of the world).ConclusionsThese findings should be interpreted with caution given the limitations to infer causality from cross-sectional observational data. Efficacy of interventions to improve multiple modifiable lifestyle factors to reduce the burden asthma and allergy in childhood should be assessed.

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Section: Discussionsupporting

confidence: 81%

Combined impact of healthy lifestyle factors on risk of asthma, rhinoconjunctivitis and eczema in school children: ISAAC phase III

Morales

Strachan

Asher

et al. 2019

Thorax

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“…For example, Szentpetery et al initially developed a diagnostic model, identifying gun violence and an unhealthy diet as predictors of childhood asthma in a Puerto Rican population. However, when validated as a prediction model in a Swedish cohort, data for these two predictors were unavailable, potentially due to low concern for these risk factors in this population, and were excluded from the model 37 …”

Section: Discussionmentioning

confidence: 99%

Prediction models for childhood asthma: A systematic review

Kothalawala

Kadalayil

Weiss

et al. 2020

Pediatric Allergy Immunology

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Background The inability to objectively diagnose childhood asthma before age five often results in both under‐treatment and over‐treatment of asthma in preschool children. Prediction tools for estimating a child's risk of developing asthma by school‐age could assist physicians in early asthma care for preschool children. This review aimed to systematically identify and critically appraise studies which either developed novel or updated existing prediction models for predicting school‐age asthma. Methods Three databases (MEDLINE, Embase and Web of Science Core Collection) were searched up to July 2019 to identify studies utilizing information from children ≤5 years of age to predict asthma in school‐age children (6‐13 years). Validation studies were evaluated as a secondary objective. Results Twenty‐four studies describing the development of 26 predictive models published between 2000 and 2019 were identified. Models were either regression‐based (n = 21) or utilized machine learning approaches (n = 5). Nine studies conducted validations of six regression‐based models. Fifteen (out of 21) models required additional clinical tests. Overall model performance, assessed by area under the receiver operating curve (AUC), ranged between 0.66 and 0.87. Models demonstrated moderate ability to either rule in or rule out asthma development, but not both. Where external validation was performed, models demonstrated modest generalizability (AUC range: 0.62‐0.83). Conclusion Existing prediction models demonstrated moderate predictive performance, often with modest generalizability when independently validated. Limitations of traditional methods have shown to impair predictive accuracy and resolution. Exploration of novel methods such as machine learning approaches may address these limitations for future school‐age asthma prediction.

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“…AR represents a considerable burden on public health, impacting daily activities, quality of life and productivity . It is also frequently associated with various comorbidities, including asthma . AR often precedes asthma, with the progression from AR to asthma considered part of the “allergic march”, while uncontrolled AR may be associated with worsening of coexisting asthma …”

Section: Introductionmentioning

confidence: 99%