This was a cross-sectional study conducted in three clinical settings of urban Nepal. The aim of the study was to find the prevalence of depression among persons living with diabetes and to identify probable risk factors. Patients who were diagnosed with diabetes at least three months prior to the study were included. Patients with other chronic medical illnesses before detection of diabetes, pregnant women with diabetes, people having psychiatric problems before diagnosis of diabetes, people who were taking anti-depressants and people who had a family history of depression were excluded. The goal of these criteria was to minimize the likelihood of depression as a pre-existing condition and instead identity depression that occurred secondary to diabetes.
In the present study, the proportion of participants with BDI-Ia scores above the clinically validated cutoff in Nepal (BDI ≥ 20) was 40.3%. This rate is comparable to prevalence of depression (36.6%), as reported in a worldwide meta-analysis of studies among persons with diabetes in clinical settings . The rate is higher than that observed in the United States, where prevalence of depression among persons with diabetes ranges from 2%-28% [14.] Our observed rate is comparable to Mexican-born Americans in the Texas who display a 40% prevalence rate  and comparable to a German study with a depression prevalence among persons with diabetes of 41.9% also using the BDI . The observed rate in this study was at the upper range of other studies conducted in South Asia. Hospital-based studies from India showed prevalence ranging from 8.5%-32.5% . Asghar et al. did a community based study in Bangladesh, which showed 27.9% depression among type 2 diabetes patients . A tertiary hospital based study conducted in Bangladesh showed 34.8% depression in persons living with diabetes .
Risk indicators for depression in patients with type 2 diabetes
As expected, complications of diabetes were significantly associated with depression. This has been observed across most studies of depression and diabetes in both high [44, 45] and low-income settings including South Asia [21, 22]. Erectile dysfunction was one of the strongest predictors of depression, which is consistent with De Groot et al. and Lustman et al.,. In this study family history of diabetes was associated with lower depressive symptoms than those who had no family history. While the study does not have quantitative or qualitative data to illuminate the association, it is speculated that family history may reduce fear and anxiety related to the disorder as well as normalize the experience, resulting in lower psychological distress. As with other studies, insulin use predicted greater depression, with insulin likely a proxy for greater disease severity [4, 14, 22, 41, 46–49]. The study showed non-adherence to at least one aspect of the diabetes management plan (life style, diet, medication) was strongly associated (p < 0.001) with depression, consistent with studies in high-income countries [3, 17, 50, 51]. Studies showed not checking blood sugar , lack of regular exercise , lack of medical vigilance, and lack of dietary modification  were associated with depression. Time since diabetes diagnosis was inversely associated with depression severity, suggesting that the early experience of the disease is the period of greatest psychological distress and adjustments in lifestyle. High blood pressure, either systolic or diastolic, was associated with greater depression severity, similar to other findings [21, 22]. Glycemic status (glycated hemoglobin) was consistently associated with depression in almost all studies done so far in research related to depression among type 2 diabetes [10, 22, 47, 52–55]. HbA1c was strongly associated with depression in this study as well, which is also a likely proxy for disease severity.
A number of risk factors associated with depression in Nepal were not significantly associated with depression among this clinical population with diabetes. For example, gender was not a significant predictor of depression among persons with diabetes in the multivariable regression model. This contrasts with community studies of depression that show a consistently greater prevalence among Nepalese women compared to men [32, 33]. In a study of women with diabetes in India, Weaver and Hadley  found that not fulfilling gender-specific social roles predicted greater levels of depression. In this sample, there may be no gender differences between men and women because diabetes impairs gender-role performance for both sexes, as suggested by greater depression among men living with diabetes with erectile dysfunction. Diabetes may have comparable functional consequences for both genders, whereas women in Nepal are more vulnerable socially even in the absence of physical disease .
Age is a strong predictor of depression in the general community in Nepal [32, 33, 35]. However, it was not a significant predictor in this Nepali clinical population with diabetes. Age has shown an inconsistent relationship with depression and in people with diabetes with depression in a number of studies: Goldney et al. also did not find an association of age with depression among persons living with diabetes . Ravel et al. did found depression to be strongly associated with age above 54 years .
In this study, caste and ethnicity were not significantly associated with depression. However, community-based samples in rural Nepal show a greater preponderance of depression among low-caste Dalit groups [3, 35, 57–59]. In other countries, ethnic minorities with diabetes display more depression than majority groups [44, 48, 60, 61]. Marital status also was not significant, despite being a predictor in rural Nepal and in studies of persons living with diabetes in other countries (Pakistan) . This study showed participants from urban area were more depressed (p < 0.001) which is not consistent with other studies where rural population was more depressed [20, 51]. It is important to note that the prevalence of depression in this sample of persons living with diabetes (40%) is comparable to rates of depression observed among other risk groups in Nepal such as low caste Dalit groups (BDI-Ia-based depression prevalence, 50%) , populations with high political violence exposure including both adult civilians (Dang district, BDI-Ia-based depression prevalence, 43%)  and child soldiers (depression prevalence, 53%) , and populations with high rates of structural violence including poverty, lack of education, lack of health care, and high rates of gender discrimination (Jumla district, BDI-based depression prevalence, 41%) .
In this study, greater personal income was associated with greater depression. Although this study showed participants with high income were more depressed (p < 0.01) than their lower income counterparts, Bell et al., Egede et al., Everson et al. suggests patients with lower income have more depression. In India, mixed methods research by Mendenhall and colleagues  suggests that depression is greater among low-income persons with diabetes, likely influenced by both greater financial stressors and also by impaired access to diabetes care. In urban Nepal, wealth may be a proxy for poorer health overall. Whereas obesity, metabolic syndrome, and diabetes are greater risks among poor populations in high income countries, affluence is associated with these poor health outcomes in some studies in South Asia .
However, the rapid economic transitions in India are demonstrating that high-income groups are able to mobilize behavioral and medical resources while a growing burden of chronic health problems falls upon the middle and lower class, which is the pattern observed in high-income countries [63, 64]. Therefore, wealth may be a proxy for poor health habits, poor nutrition, limited exercise, excessive caloric intake, and smoking and drinking  at a specific moment in time in Nepal as the burden shifts to other groups. Alternatively, the selection criteria may have confounded the association of wealth and depression, as discussed in the limitations section below.
The present study did not reveal any association between behavioral characteristics of tobacco, alcohol, and other drug use. However, this may be because personal income was a stronger proxy for a constellation of poor behaviors in this population. Most other studies have shown an association of these behaviors with depression among persons living with diabetes [17, 21]. One reason that smoking may not be associated with poorer outcomes is the epidemic of respiratory disorders in Kathmandu given the overwhelming burden of pollution in the city. The present study showed an association between waist hip ratio and depression (p = 0.001), which is consistent with findings from Lustman et al. and Larijani et al..