Depression among people living with type 2 diabetes in an urbanizing community of Nepal

Sunny, Avinash K; Khanal, Vijay Kumar; Sah, Ram Bilakshan; Ghimire, Anup

doi:10.1371/journal.pone.0218119

Cited by 30 publications

(56 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Various studies have documented that factors associated with depression among diabetes patients using the classical logistic regression. Risk factors were age [ 10 , 15 , 34 ], gender [ 14 , 15 , 35 – 38 ], marital status [ 15 , 35 , 37 , 39 ], educational status [ 34 , 37 , 40 ], hazardous drinking [ 38 , 39 ], medication adherence [ 13 , 39 ], duration lived with DM [ 9 , 14 , 35 ], fasting blood sugar [ 41 ], DM complication [ 10 , 12 , 14 , 36 , 37 ], chronic illness other than DM [ 14 , 34 ], and types of medication [ 34 ].…”

Section: Discussionmentioning

confidence: 99%

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach

Tusa

Alemayehu

Weldesenbet

et al. 2020

Depression Research and Treatment

View full text Add to dashboard Cite

Background. Depression is one of the most pressing public health problems and also highly prevalent comorbid condition among diabetes mellitus (DM) patients. Depression may impact lifestyle decisions and ability to poorly perform tasks which are risk factors for DM. For reducing the impact of depression among DM patients in developing countries, it is crucial to identify and assess associated risk factors of depression among DM patients, thereby designing effective management techniques. In line with this, the current study applies the Bayesian framework, which pools prior information and current data, to find factors associated with depression among DM patients. Methods. A hospital-based cross-sectional study was conducted at Adama Hospital and Medical College (AHMC) from March to April 2019. Data was entered into the Epi-data 3.1 then exported to the R software 3.4.4. Bayesian logistic regression models were fitted to the data using the Markov chain Monte Carlo (MCMC) algorithm. Estimates of model parameters including adjusted odds ratio (AOR) with 95% credible intervals (CI) were calculated. Results. A total of 359 adults with DM were included in the analysis. The prevalence of depression among diabetic patients was 9.22% (95% CI: 6.4% to 12.7%). Higher fasting blood sugar level ( AOR = − 1.012 ; HPD CI: (1.0020, 1.025)), having diabetic complication ( AOR = 0.1876 ; HPD CI: (0.0214, 0.671)), history of hospital admission ( AOR = 0.2865 ; HPD CI: (0.0711, 0.7318)), low medication adherence ( AOR = 29.29 ; HPD CI: (3.383, 92.26)), and taking both insulin and oral antidiabetic medication ( AOR = 24.46 ; HPD CI: (15.20, 49.37) were significantly and strongly associated with depression among DM patients. Conclusions. Prevalence of depression among diabetes patients in the catchment area of Adama Hospital, Ethiopia, was found to be very low. Higher fasting blood sugar level, diabetic complication, history of hospital admission, low medication adherence, and taking both insulin and oral antidiabetic medication were found to be strong predictors of prevalence of depression among DM patients. Based on the findings, we recommend that integrating screening and treating of depression, early detection and management of diabetic complication, and giving counseling to improve medication adherence is an effective approach for lowering the impact of depression on DM patients.

show abstract

Section: Discussionmentioning

confidence: 99%

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach

Tusa

Alemayehu

Weldesenbet

et al. 2020

Depression Research and Treatment

View full text Add to dashboard Cite

show abstract

“…However, the positive effects of social interaction on health have been confirmed by many studies ( 28 , 29 ). Psychologically, social interaction can help older patients with diabetes find emotional support, enhance self-efficacy and reduce psychological problems, as older patients with diabetes report more depression ( 30 , 31 ). Physically, social interaction benefits the health of older patients with diabetes by keeping them physically active.…”

Section: Discussionmentioning

confidence: 99%

Physical Exercise, Social Interaction, Access to Care, and Community Service: Mediators in the Relationship Between Socioeconomic Status and Health Among Older Patients With Diabetes

Deng

Liu

2020

Front. Public Health

View full text Add to dashboard Cite

The differences in socioeconomic status (SES) will cause a disparity in the health of the elderly. Taking diabetes as an example, previous studies have focused on risk factors of diabetes, while the relationship and mechanism between SES, multi-faceted factors, and the health of older patients with diabetes are not well-understood. This study aims to investigate the association between SES and health in older patients with diabetes and the interrelated mediators between them. Based on the data of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2018, structural equation modeling (SEM) was used to test whether physical exercise, social interaction, access to care, and community service mediated the effect of SES on the health in older patients with diabetes. We found support for the model in which SES predicted the health in older patients with diabetes (comparative fit index = 0.910, incremental fit index = 0.911, goodness-of-fit index = 0.982, adjusted goodness-of-fit index = 0.959, standardized root mean square residual = 0.037, and root mean square error of approximation = 0.061). The total indirect effect of SES on the health accounted for 55.52% of the total effect. Results indicated that physical exercise (β = 0.108, p < 0.01), social interaction (β = 0.253, p < 0.001), and community service (β = 0.111, p < 0.001) had significant positive effects on the health of older patients with diabetes. SES was positively associated with physical exercise (β = 0.417, p < 0.001) and community service (β = 0.126, p < 0.01). Although no direct effect of SES on the health was found, SES mediated the positive effect in their relationship by physical exercise (indirect effect = 0.045, p < 0.01), and community service (indirect effect = 0.014, p < 0.05). This study showed the health disparities of older patients with diabetes were influenced by individual-level (physical exercise, social interaction) and environmental-level (community service). It suggests that a lack of physical exercise and health-related community service may impair the health of older patients with diabetes with low SES, which recommends individuals' positive actions and environmental supports for promoting health of regarding population.

show abstract

“…This study did not observe other pivotal determinants for MHD in diabetics. The determinants involved physical capability, insulin, and drug usage, ethnicity, detailed civil status (married, single, divorced, widowed), residence status (living alone, nuclear family, joint/extended living), family size, family income, pensioner status, smoking, alcohol, religion, glycaemic control, other sociodemographic and clinical health factors [8,9,11,[25][26][27]. The involved determinants in the study will potentially explain other parameters that influence MHD among elderly diabetics.…”

Section: Discussionmentioning

confidence: 99%

“…Younger diabetics are more likely to get MHD [8] while another study reported that elderly diabetics more likely to get MHD, with the increased risk of other factors present [11].…”

Section: Introductionmentioning

confidence: 96%

“…Mental health disorder (MHD) is the most frequent comorbid for DM with a prevalence of 28% globally; females tend to be higher than males, i.e., 34% and 23%, respectively [7][8][9][10]. Previous mental disorder conditions such as generalized anxiety disorder (GAD), major depressive disorder (MDD), bipolar disorder, and eating disorders are the underlying comorbid for DM patients with MHD [11][12][13][14] MHD in diabetics may decrease quality of life [15], poor self-care management [16], increase disability [17], cardiovascular mortality risk [18] and all-cause mortality risk [19]. On the other side, diabetes is a risk factor for MHD [20].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prevalence of Mental Health Disorders among Elderly Diabetics and Associated Risk Factors in Indonesia

Azam

Sulistiana

Fibriana

et al. 2020

Preprint

View full text Add to dashboard Cite

This cross-sectional study aimed to explore the prevalence of mental health disorders (MHD) among elderly diabetics in Indonesia and their associated risk factors. Data were extracted from the 2018 national basic health survey, Indonesia (abbreviated as the acronym of RISKESDAS). The survey involved households randomly selected from 34 provinces, 416 districts, and 98 cities in Indonesia, with 1,017,290 respondents. The number of subjects selected in this study was 2,818 elderly diabetic subjects. MHD was determined by self-reporting assessment. Secondary data acquired from the RISKESDAS 2018 data involved age, sex, urban-rural residence status, marital status, educational level, employment status, obesity, hypertension, heart disease, stroke, family history of MHD, and duration of DM. Binary logistic regression was used to analyze the risk factors related to MHD among elderly diabetics. Prevalence of MHD among elderly diabetics in Indonesia was 19.3%. Factors associated with MHD among elderly diabetics were obesity (prevalence odds ratio [POR]=4.57; 95% CI: 3.312-6.297), family history of MHD (POR=2.43; 95% CI: 1.707-3.471), lower education (POR=1.93; 95% CI: 1.464-2.533), stroke (POR=1.76; 95% CI: 1.292-2.384), hypertension (POR=1.74; 95% CI: 1.416-2.145), heart diseases (POR=1.49; 95% CI: 1.123-1.973), female (POR=1.43; 95% CI: 1.122-1.813), and urban residence (POR=0.75; 95% CI: 0.607-1.183). The prevalence of MHD among elderly diabetics in Indonesia was 19.3%, suggesting that screening for psychological problems and educating elderly diabetic patients is essential. Obesity, family history of MHD, lower education, stroke, hypertension, heart disease, female, and rural residence altogether more likely to experience MHD in elderly diabetics.

show abstract

Depression among people living with type 2 diabetes in an urbanizing community of Nepal

Cited by 30 publications

References 33 publications

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach

Prevalence of Depression and Associated Factors among Diabetes Patients in East Shewa, Ethiopia: Bayesian Approach

Physical Exercise, Social Interaction, Access to Care, and Community Service: Mediators in the Relationship Between Socioeconomic Status and Health Among Older Patients With Diabetes

Prevalence of Mental Health Disorders among Elderly Diabetics and Associated Risk Factors in Indonesia

Contact Info

Product

Resources

About