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

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.

Keywords: Depressive symptoms; elderly; functioning; income; network analysis; quality of life.

Fig. 1.

Network 1 of multidimensional variables in a sample of 3532 North-American adults aged >45 years old. BMI, body mass index; Depression, Center for Epidemiologic Studies – Depression score; drinkweek, drinks per week; education, college completers; Income, yearly income >US$50 000; Medical conditions, Charlson comorbidity index; N_meds, number of medications; medit_diet, adherence to Mediterranean diet; Physical activity, PASE – Physical activity Scale for the Elderly; SF12 phys/ment, Short-Form Health Survey 12 physical/mental score; Smoking, life-time smokers.

Fig. 2.

Centrality indices of multidimensional variables in a sample of 3532 North-American adults aged >45 years old. BMI, body mass index; Ch_, Charlson comorbiditiy index; cll, college completers; CES, Center for Epidemiologic Studies-Depression; drn, drinks per week; i > 5, yearly income >US$50 000; mds, number of medications; md_, adherence to Mediterranean diet; PAS, PASE – Physical activity Scale for the Elderly; SF12p/SF12m, Short-Form Health Survey 12 physical/mental score, smk, life-time smokers.

Fig. 3.

Average correlations between centrality indices of networks sampled with persons dropped and in the original sample of 3532 North-American adults aged >45 years old. Lines indicate the means and areas indicate the range from the 2.5th quantile to the 97.5th quantile.