Abstract
BackgroundThe new subgroup screening tool “subscreen” aims to understand the unclear and complex association between socioeconomic status (SES) and childhood allergy. This software R package has been successfully used in clinical trials but not in large population-based studies.ObjectiveTo screen and identify subgrouping factors explaining their impact on the association between SES and respiratory allergies in childhood and youth.MethodsUsing the national German childhood and youth survey dataset (KiGGS Wave 2), we included 56 suspected subgrouping factors to investigate the association between SES (low vs. high) and allergic rhinitis and/or asthma in an exploratory manner. The package enabled a comprehensive overview of odds ratios when considering the SES impact per subgroup and analogously all disease proportions per subgroup.ResultAmong the 56 candidate factors, striking subgrouping factors were identified; e.g., if mothers were younger and in the low SES group, their children had a higher risk of asthma. In addition children of the teen’s age were associated with increased risks in the low SES group. For the crude proportions, factors such as (parental) smoking or having had no “contact with farm animals” were identified as strong risk factors for rhinitis.SignificanceThe “subscreen” package enabled the detection of notable subgroups for further investigations exemplarily for similar epidemiological research questions.
Highlights
Since the consistency of study results across all participants cannot generally be assumed, analyses considering subgroups of participants are frequently used and discussed, with remarkably varying approaches [1,2,3,4]
Even though the socioeconomic status (SES) impact was less profound in the 12-month prevalence of bronchial asthma and allergic rhinitis compared to general health, we aimed to assess the scientific question of analyses and multiplicity reasons [20, 21]
More than one million 1–3 factorial subgroups could be technically handled; already the 1–2 factorial subgroups in Fig. 2 offered a good display of the subgroup dispersion while 1–3 factorial subgroups would result in too much overlap of dots
Summary
Since the consistency of study results across all participants cannot generally be assumed, analyses considering subgroups of participants are frequently used and discussed, with remarkably varying approaches [1,2,3,4]. The new subgroup screening tool “subscreen” aims to understand the unclear and complex association between socioeconomic status (SES) and childhood allergy. This software R package has been successfully used in clinical trials but not in large population-based studies. OBJECTIVE: To screen and identify subgrouping factors explaining their impact on the association between SES and respiratory allergies in childhood and youth. METHODS: Using the national German childhood and youth survey dataset (KiGGS Wave 2), we included 56 suspected subgrouping factors to investigate the association between SES (low vs high) and allergic rhinitis and/or asthma in an exploratory manner. SIGNIFICANCE: The “subscreen” package enabled the detection of notable subgroups for further investigations exemplarily for similar epidemiological research questions
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