6533b852fe1ef96bd12aac4b

RESEARCH PRODUCT

Network analysis of the relationship between depressive symptoms, demographics, nutrition, quality of life and medical condition factors in the Osteoarthritis Initiative database cohort of elderly North-American adults with or at risk for osteoarthritis – CORRIGENDUM

Trevor ThompsonNicola VeroneseMichele FornaroMarco SolmiChristoph U. CorrellAi Koyanagi

subject

GerontologyMale*elderlyMediterranean dietDatabases FactualEpidemiologyHealth StatusOsteoarthritisComorbidityBody Mass IndexCohort Studies0302 clinical medicineQuality of lifeSurveys and QuestionnairesMedicineNutritional Physiological Phenomena*functioningnetwork analysiseducation.field_of_study*Depressive symptomsDepressive symptomsAge FactorsMiddle AgedDepressive symptomPsychiatry and Mental healthincomeCohortFemaleCorrigendumRiskPopulationBF*network analysiselderlyfunctioning03 medical and health sciencesSex FactorsOsteoarthritisnetwork analysiHumanseducation*quality of lifePartial correlationDemographyDepressive Disorderbusiness.industryPublic Health Environmental and Occupational HealthOriginal Articles*incomemedicine.disease030227 psychiatrySocioeconomic FactorsNorth AmericaQuality of LifeCentralitybusinessBody mass index030217 neurology & neurosurgery

description

Abstract Aims A complex interaction exists between age, body mass index, medical conditions, polypharmacotherapy, smoking, alcohol use, education, nutrition, depressive symptoms, functioning and quality of life (QoL). We aimed to examine the inter-relationships among these variables, test whether depressive symptomology plays a central role in a large sample of adults, and determine the degree of association with life-style and health variables. Methods Regularised network analysis was applied to 3532 North-American adults aged ⩾45 years drawn from the Osteoarthritis Initiative. Network stability (autocorrelation after case-dropping), centrality of nodes (strength, M, the sum of weight of the connections for each node), and edges/regularised partial correlations connecting the nodes were assessed. Results Physical and mental health-related QoL (M = 1.681; M = 1.342), income (M = 1.891), age (M = 1.416), depressive symptoms (M = 1.214) and education (M = 1.173) were central nodes. Depressive symptoms’ stronger negative connections were found with mental health-related QoL (−0.702), income (−0.090), education (−0.068) and physical health-related QoL (−0.354). This latter was a ‘bridge node’ that connected depressive symptoms with Charlson comorbidity index, and number of medications. Physical activity and Mediterranean diet adherence were associated with income and physical health-related QoL. This latter was a ‘bridge node’ between the former two and depressive symptoms. The network was stable (stability coefficient = 0.75, i.e. highest possible value) for all centrality measures. Conclusions A stable network exists between life-style behaviors and social, environmental, medical and psychiatric variables. QoL, income, age and depressive symptoms were central in the multidimensional network. Physical health-related QoL seems to be a ‘bridge node’ connecting depressive symptoms with several life-style and health variables. Further studies should assess such interactions in the general population.

10.1017/s2045796019000064http://europepmc.org/articles/PMC8546729