Running head: PHQ‐9 SCORES IN LOW‐INCOME DIABETIC ADULTS Comparing PHQ-9 Scores between Low-income Adults With and Without Self-Reported Type 2 Diabetes

Objective: Depression and diabetes often co-exist and result in worsening health outcomes. Low-income and demographic variables have been shown to have an effect on both diabetes and depression. The presence of a relationship between low-income, demographic variables, and comorbid diabetes and depression is unclear. This pilot study was designed to compare depressive symptoms as measured by PHQ-9 scores between low-income adults with selfreported type 2 diabetes and those without in relation to gender, age, ethnicity, and education level. Methods: Low-income adults at a food pantry were given a demographic questionnaire and PHQ-9 to complete. Presence of diabetes was based on self-report. Wilcoxon signed-rank test was used to compare means and medians of the groups. Results: Each age, ethnicity, education, and gender cohort’s PHQ-9 scores were compared to the scores of those with diabetes in the same cohort. No statistical significance was found in any category. Discussion: Limitations included small sample size and reliance on self-report. Research confirms the link between diabetes and depression and confirms as well that low-income and demographic variables impact both diabetes and depression separately. More research needs to be done to examine the impact of low income and demographic variables on comorbid depression and diabetes. PHQ‐9 SCORES IN LOW INCOME DIABETIC ADULTS 3 Comparing PHQ-9 Scores between Low-income Adults With and Without Self-Reported Type 2 Diabetes At any given time, 12-18% of individuals with type 2 diabetes meet criteria for a diagnosis of depression (Park, Katon, & Wolf, 2013). Conversely, individuals with depression have a significantly higher risk of developing diabetes type 2 (Ali, Stone, Peters, Davies, & Khunti, 2006; Park et al., 2013). It is hypothesized that diabetes and depression are associated with similar metabolic and chemical changes in the body (Ali et al., 2006). Comorbid diabetes and depression increase the risk for diabetic complications, mortality, and disability (Ali et al., 2006; Katon et al., 2010; Park et al., 2013). Katon et al. (2008) found the increase in mortality to be as high as 38%. Egede & Ellis (2010) and Simon et al. (2005) found that depressed persons with diabetes had higher health care costs, spent more time receiving healthcare, and spent more time in inpatient facilities. It is hypothesized that there appears to be a multifactorial relationship between depression, diabetes, and situational and demographic variables. (Auchincloss et al., 2009; Kanjilal et al., 2006; Lysy et. al, 2013; Osborn et al., 2011; & Mezuk et al, 2013; & World Federation for Mental Health, 2012). However, it is unclear what role these variables might play in this relationship (Auchincloss et al., 2009; Kanjilal et al., 2006; Lysy et. al, 2013; & Mezuk et al., 2013). Lenz, Pugh, Milligan, Gift & Suppe’s 1997 “Theory Of Unpleasant Symptoms” was adapted to illustrate the synergistic effect of physiologic, psychological, and situational factors on symptom manifestation, functionality, and quality of life (figure 1). Figure 1 Multifactorial and Synergistic Relationship of Depression, Diabetes, and Situational/Demographic Variables PHQ‐9 SCORES IN LOW INCOME DIABETIC ADULTS 4 Note. Adapted from Lenz, Pugh, Milligan, Gift, & Suppe’s Theory of Unpleasant Symptoms (1997). Objective The primary objective of this pilot study was to describe depressive symptoms as measured by the 9-item Patient Health Questionnaire (PHQ-9) between low-income adults with self-reported type 2 diabetes and those without self-reported type 2 diabetes. The research question for this pilot study was ”Is there a difference in PHQ‐9 scores in low‐income adults PHQ‐9 SCORES IN LOW INCOME DIABETIC ADULTS 5 with and without self‐reported type 2 diabetes in relation to gender, age, ethnicity, or education level? ” Prompt detection and treatment of depression in patients with type 2 diabetes can positively impact clinical, quality, and cost outcomes. (Mitchell et al., 2009). However, there are many barriers to depression screening in patients with diabetes including culture, communication, and physician attitude (Leng, Changrani, Tseng, & Gany, 2009; Sorkin et al., 2011; Swenson, Rose, Vittinghoff, Stewart, & Schillinger, 2008). Ethnic minorities, for example, receive less depression screening (Leng et al., 2009; Sorkin et al., 2011) despite a higher incidence of depression in these populations (Wagner, Tsimikas, Abbott, de Groot, & Heapy, 2007). Primary care providers rarely use formal depression screening tools when screening does occur (Baik et al., 2010; Osborn, Kozak, & Wagner, 2010). Few depression screening tools have been validated in patients with diabetes. Four screening tools appear most frequently in the literature for use with diabetes: the Beck Depression Inventory (BDI), the PHQ-9, the Hospital Anxiety and Depression Scale (HADS) and the CES-D (Roy, Lloyd, Pouwers, Holt, & Sartorius, 2011). The BDI, CES-D, and PHQ-9 all include questions on somatic complaints that may occur commonly in those with diabetes without depression. This may increase the false positive rate (Reddy, Philpot, Ford, & Dunbar, 2010; Roy et al., 2011; van der Feltz-Cornelis, 2011). Several studies examined ways to overcome this problem, including raising the cutoff values used for interpretation (Roy et al., 2011; van der Feltz-Cornelis, 2011; van Steenbergen-Weijenburg et al., 2010). Table 1 summarizes research studies examining the sensitivity and specificity of each test in regards to different cut-off values. PHQ‐9 SCORES IN LOW INCOME DIABETIC ADULTS 6 Roy et al.’s (2011) systematic review examined 234 studies on depression screening in persons with diabetes. They found the BDI, CES-D, HADS and PHQ-9 to have similar sensitivity and specificity. All four tools evidenced high rates of false positives and low rates of false negatives. Roy et al. recommend the BDI and the HADS, but note that these tools can be cost prohibitive. Though the CES-D had the highest specificity for depression in patients with type 2 diabetes, its length might be prohibitive in a primary care setting (McHale, Hendrikz, Dann, & Kenardy, 2008; Roy et al., 2011). Roy et al. also note that the PHQ-9 has similar sensitivity, reliability, and validity, though it is less specific than the CES-D. Table 1 Summary of Primary Screening Tool Validation Studies in Diabetic Patients Test Samp le Size Type of Repor t No . of ? Sensitivity (%) Specificity (%) NPV (%) PP V (%) Cut Off Scor e PHQ-9 Twist et al. (2013) van Steenbergen -Weijenburg et al. (2010) 1500