Impact of Antidepressant Use on Healthcare Utilization among Individuals with Type 2 Diabetes and Depression Symptoms in the United States: Sociodemographic, Clinical, and Behavioral Factors Matter

Abstract

Individuals with diabetes are twice as likely to struggle from depressive symptoms than individuals without diabetes. However, this joint condition is undertreated in nearly two-thirds of patients. Failure to monitor the comorbidity may lead to suboptimal therapy. This study evaluated the association of antidepressant use with healthcare utilization in a national sample of patients with type 2 diabetes and depression symptoms in the United States. It further assessed the differences in sociodemographic, clinical, and behavioral factors between those who use antidepressants and those who do not. This study was a secondary data analysis using the National Health and Nutrition Examination Survey (NHANES) for the period 2005–2014. To assess if there were significant differences in sociodemographic, clinical, and behavioral factors between those who were taking antidepressants or not, Chi Square and independent t-tests were used. To assess if there was a significant association between antidepressant use and healthcare utilization, univariate and multivariate regression analyses were conducted. Of the 955 participants, only 33% were on antidepressants. There were significant differences in sociodemographic, clinical, and behavioral factors among those who used antidepressants and those who did not. Regardless of antidepressant use, the study population had access to health care. Those on antidepressants had fewer diabetes specialists’ visits and more mental health care. There might be underlying health care disparities related to the use of, and access to, antidepressants. Further studies are needed to comprehensively explore the management of these comorbidities.

Prevalence and characteristics of antidepressant prescribing in adults with comorbid depression and type 2 diabetes mellitus: A systematic review and meta-analysis

“…Our search yielded 14,389 unique abstracts, of which we assessed 96 full-text articles for eligibility, and selected nine studies for inclusion in the review [35] , [36] , [37] , [38] , [39] , [40] , [41] , [42] , [43] . Three studies used the same NHANES survey data [44] , and so, are expected to have significant duplication of participants: Binsalah 2018 was chosen for inclusion for the primary outcome, however, did not report data on individual antidepressant medications or classes, and so, Perez 2017 and Wang 2016 were included for this outcome, each reporting on a different exposure.…”

“…Three studies identified depression through clinical coding in health or insurance records – two of these studies had the highest prevalence rates of 85% and 87% [36 , 40] ; the third had a relatively high prevalence rate of 0.57, however, this was recorded in a population of all-male military veterans [38] . The three studies with the lowest prevalence rates, ranging from 18% to 37% all identified depression in the community as part of the research study [35 , 41 , 43] . When combined in meta-analysis, these studies gave a pooled prevalence estimate of 29% (23% – 37%) and I 2 of 62%.…”

“…Two studies reported the prevalence of antidepressant prescribing across depression severities [35 , 43] . Only one of the studies showed evidence of a difference in antidepressant prescribing, with an OR of 2.30 (95% CIs 1.73-3.06) in moderate-severe compared to mild depression [35] .…”

“…Two studies reported diabetes duration for participants prescribed antidepressants compared to those not, with no evidence of a difference [35 , 37] .…”

“…Three studies reported the difference in glycaemic control for participants who were prescribed antidepressants compared to those not, with no evidence of a difference [35] , [36] , [37] . The heterogeneity of measures used meant that meta-analysis could not be performed.…”