{"doi":"10.1101/2024.02.21.24303099","title":"Modelling the relative influence of socio-demographic variables on post-acute COVID-19 quality of life","abstract":"Abstract Introduction Long-term COVID-19 complications are a globally pervasive threat, but their social determinants are often understudied relative to clinical risk factors. Thus, the role that clinical comorbidities play in determining disparate long COVID outcomes across socio-demographic groups is relatively unknown. Here, we ranked social and clinical predictors of quality of life (QoL) with long COVID and measured the extent to which clinical intermediates explain any observed relationships between social factors and long COVID QoL. Methods We used demographic, comorbidity, treatment, and quality of life data from acute case reporting forms and follow-up surveys collected for a multinational prospective cohort study, with focus on data from Norway (n=1,672), the UK (n=1,064), and Russia (n=1,155). We considered the social factors employment status, educational attainment, and female sex and defined our primary outcome as QoL utility scores among subjects reporting any long COVID-associated symptoms. Results We found that, in addition to age, neuropsychological, and rheumatological comorbidities, educational attainment, employment status, and sex were consistently identified as top predictors of long COVID-associated QoL utility scores. Furthermore, 98.2% (95% CI: 87.3%, 100%) and 89.4% (74.6%, 99.6%) of the positive adjusted associations between high educational attainment or full-time employment and long COVID QoL utility scores remained unexplained by key long COVID-predicting comorbidities in Norway and the UK. The same was true for 84.2% (46%, 100%), 67.6% (45.5%, 89.7%), and 87.2% (71.3%, 100%) of the negative adjusted associations between female sex and long COVID QoL utility scores in Norway, the UK, and Russia. Conclusion Socio-economic proxies and sex are strong predictors of long COVID QoL independent of commonly emphasized comorbidity pathways and warrant increased attention in interventions focused on mitigating long COVID burden. Long COVID management efforts that target social determinants should be tailored to a specific country context, given the heterogeneity in findings observed across settings. What is already known on this topic Clinical comorbidities like asthma, chronic cardiac disease, and diabetes, are well-established long COVID risk factors; social factors, namely socioeconomic disadvantage and gender, have also been identified as important sources of long COVID risk; the relative rankings of these factors in differentiating quality of life with long COVID is less recognized Furthermore, key clinical predisposing factors have been shown to play a minimal role in confounding observed social disparities in long COVID risk; their potential role as explanatory intermediates is generally underexplored What this study adds Evaluates both social and clinical factors (individually and grouped by shared mechanisms) as predictors of long COVID-associated quality of life, an outcome measure that can capture a gradient in experiences with the condition Importantly, subverts the commonplace emphasis on differences in comorbidity burden explaining observed disparities in health outcomes by quantifying the proportion of relationships between different social factors and long COVID quality of life that are unexplained by clinical intermediates, applying flexible statistical mediation approaches How this study might affect research, practice or policy Motivates broadening the focus of long COVID prevention efforts to look beyond simply targeting clinical intermediates as a way to fully resolve social disparities and instead also explore the role of other upstream societal sources of disadvantage, for example, access to public health resources and clinical services or discrimintion","journal":"ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam)","year":2024,"id":487164,"datarank":0.20794415416798362,"base_score":1.3862943611198906,"endowment":1.3862943611198906,"self_citation_contribution":0.20794415416798362,"citation_network_contribution":0.0,"self_endowment_contribution":0.20794415416798362,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9521,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":918341,"name":"Barbara Wanjiru Citarella","orcid":"0000-0001-8968-0708","position":1,"is_corresponding":false},{"id":83867,"name":"Louise Sigfrid","orcid":"0000-0003-2764-1177","position":2,"is_corresponding":false},{"id":1331530,"name":"Yash Doshi","orcid":null,"position":3,"is_corresponding":false},{"id":318721,"name":"Luis Felipe Reyes","orcid":"0000-0003-1172-6539","position":4,"is_corresponding":false},{"id":852648,"name":"Jose Andrés Calvache","orcid":"0000-0001-9421-3717","position":5,"is_corresponding":false},{"id":1331155,"name":"Anders Benjamin Kildal","orcid":"0000-0002-1319-6511","position":6,"is_corresponding":false},{"id":1331156,"name":"Anders Benteson Nygaard","orcid":"0000-0003-1922-0751","position":7,"is_corresponding":false},{"id":632248,"name":"Jan Cato Holter","orcid":"0000-0003-1618-5022","position":8,"is_corresponding":false},{"id":1319367,"name":"Prasan Kumar Panda","orcid":"0000-0002-3008-7245","position":9,"is_corresponding":false},{"id":546770,"name":"Waasila Jassat","orcid":"0000-0003-4279-3056","position":10,"is_corresponding":false},{"id":83855,"name":"Laura Merson","orcid":"0000-0002-4168-1960","position":11,"is_corresponding":false},{"id":61115,"name":"Christl A. Donnelly","orcid":"0000-0002-0195-2463","position":12,"is_corresponding":false},{"id":105567,"name":"Mauricio Santillana","orcid":"0000-0002-4206-418X","position":13,"is_corresponding":false},{"id":228279,"name":"Caroline O. Buckee","orcid":"0000-0002-8386-5899","position":14,"is_corresponding":false},{"id":341844,"name":"Stéphane Verguet","orcid":"0000-0003-4128-0849","position":15,"is_corresponding":false},{"id":451931,"name":"Nima S. Hejazi","orcid":"0000-0002-7127-2789","position":16,"is_corresponding":false},{"id":557005,"name":"Tigist F. Menkir","orcid":"0000-0001-6070-8017","position":0,"is_corresponding":true}],"reference_count":29,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T02:08:06.013846Z","pmid":"39040190","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}