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Background Despite the growing utilization of data-driven methods to investigate multimorbidity patterns, there is currently no consensus or guidance on the conditions to include when identifying patterns. This scoping review aims to systematically examine the nature of conditions included in existing studies using data-driven techniques. Methods A comprehensive search of three electronic databases (MEDLINE, Web of Science and Scopus) was conducted to identify relevant publications from inception to 28 February 2022 using predefined search terms and inclusion/exclusion criteria. The reference lists and citations of relevant papers were also searched. Results Among 7326 search results, 5444 relevant articles were identified. After screening against the eligibility criteria, 60 articles were included in the review. Half of the reviewed studies reported selection criteria for conditions, with prevalence in the population of interest being the most common criterion (40%). Most studies included at least one neurological [59 (98.3%)], musculoskeletal [58 (96.7%)], respiratory [57 (95.0%)] or mental health [56 (93.3%)] condition. In contrast, only a small proportion of studies included skin [17 (28.3%)], infections [14 (23.3%)] or autoimmune conditions [10 (16.7%)]. Nine conditions (hypertension, diabetes, cancer, arthritis, COPD, asthma, depression, stroke and osteoporosis) were included by more than half of the studies. Conclusions This review highlights the considerable heterogeneity among the conditions included in analyses of multimorbidity patterns. Researchers should provide a clear rationale for the selection of conditions to facilitate comparisons across studies and ensure reproducibility, as well as consider selecting a diverse range of conditions to capture the complexity of multimorbidity. [ABSTRACT FROM AUTHOR]

Objective: To determine age-related risk factors for chronic rhinosinusitis (CRS) with asthma. Methods: Data were obtained from a national survey of non-hospitalized civilians conducted by the Korean Center for Disease Control and Prevention. CRS diagnosis was based on the guidelines of the European Position Paper on Rhinosinusitis and Nasal Polyps 2020. Asthma was judged based on whether the patient had been diagnosed with asthma in the past. Of the 45,811 survey participants, 26,335 were included in the cross-sectional study. Participants included in the study were divided into the control, CRS, and CRS with asthma groups. Age-related risk factors were analyzed in patients aged < 60 or > 60 years. Univariate logistic analyses were performed to evaluate the relationship between groups. Risk factors included age, sex, household income, residence, education level, occupation, and body mass index (BMI). Results: Education level (Odds Ratio [OR]: 0.342, P =.0003), BMI (OR: 1.09, P =.0082), and total IgE (TIgE) levels (OR: 5.582, P =.003) were significantly different between the control and the CRS with asthma group. Education level (OR: 0.478, P =.0016) and TIgE levels (OR: 4, P =.0218) were significantly different between the CRS and CRS with asthma groups under 60 years of age. BMI (OR: 1.087, P =.0443; OR: 1.104, P =.0224) showed a significant difference between all three groups with age > 60 years. Conclusion: Progression to CRS with asthma is influenced by education level, occupation, and TIgE levels in patients under 60 years of age. BMI was the only influencing factor associated with the progression to CRS with asthma in those aged > 60 years. [ABSTRACT FROM AUTHOR]