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| ORIGINAL ARTICLE |
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| Year : 2018 | Volume
: 5
| Issue : 2 | Page : 152-158 |
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Diabetes: A risk factor for poor mental health in aging population
Rishav Bansal1, Prasun Chatterjee1, Avinash Chakrawarty1, Sujata Satpathy2, Nand Kumar2, Sada Nand Dwivedi3, Aparajit Ballav Dey1
1 Department of Geriatric Medicine, All India Institute of Medical Sciences, New Delhi, India
2 Department of Psychiatry, All India Institute of Medical Sciences, New Delhi, India
3 Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
| Date of Web Publication | 27-Dec-2018 |
Correspondence Address:
Dr. Aparajit Ballav Dey
Department of Geriatric Medicine, All India Institute of Medical Sciences, Ansari Nagar, New Delhi - 110 029
India
 Source of Support: None, Conflict of Interest: None  | Check |
DOI: 10.4103/jgmh.jgmh_5_18
Background: Data on diabetes as a risk factor for mental health disorders in older population is limited. The health systems need to assess the burden on mental health disorders secondary to chronic diseases for better care provision. This study aims to assess the burden of depression, generalized anxiety disorder (GAD), and cognitive impairment among older patients with diabetes compared to age- and sex-matched nondiabetes and study the impact of diabetes on quality of life (QOL). Subjects and Methods: Cross-sectional comparative study was performed in Geriatric Medicine Outpatient Department (OPD) from November 2014 to June 2016. Ambulatory patients from OPD who provided informed consent were the participants of the study. They included 180 diabetic cases and 180 age- and sex-matched nondiabetic controls. The cases and controls were subjected to assessment for the presence of depression, GAD, and cognitive impairment using Geriatric Depression Scale, Mini International Neuropsychiatric Interview, and Montreal Cognitive Assessment, respectively. Health-related QOL was assessed with WHOQOL-BREF scale. They were also subjected to routine comprehensive geriatric assessment. McNemar's Chi-square test and Paired t-test was used for statistical analysis. Results: Older diabetics have significantly higher frequency of depression (35.6% vs. 16.7%), GAD (12.8% vs. 4.4%), and cognitive impairment (53.9% vs. 27.2%) compared to nondiabetics. In addition, they also report poorer health-related QOL. Conclusions: Diabetes in old age is associated with increased risk of mental health disorders and an accompanying poor health-related QOL in all domains. Thus, patients with diabetes require access to mental health support in addition to management of metabolic abnormalities. Future research to assess the impact of screening of mental health disorders on outcomes such as glycemic control, morbidity, and mortality is required.
Keywords: Diabetes, cognitive impairment, depression, elderly, generalized anxiety disorder, health-related quality of life, older people
How to cite this article:
Bansal R, Chatterjee P, Chakrawarty A, Satpathy S, Kumar N, Dwivedi SN, Dey AB. Diabetes: A risk factor for poor mental health in aging population. J Geriatr Ment Health 2018;5:152-8 |
How to cite this URL:
Bansal R, Chatterjee P, Chakrawarty A, Satpathy S, Kumar N, Dwivedi SN, Dey AB. Diabetes: A risk factor for poor mental health in aging population. J Geriatr Ment Health [serial online] 2018 [cited 2023 Jun 7];5:152-8. Available from: https://www.jgmh.org/text.asp?2018/5/2/152/248631 |
| Introduction | |  |
Aging is a well-known risk factor for common mental health disorders all over the world.[1],[2] In the preceding two decades, the prevalence of mental health disorders has increased in this population group.[1] In rapidly aging low- and middle-income countries (LMICs), mental disorders in later life is also a concern.[3],[4],[5] In an epidemiological study from rural North India, the prevalence of psychiatric morbidity in older persons was 23.7%.[6] It is also observed that the prevalence of mental health disorders and availability and utilization of mental health management services shows a great disparity. In this scenario, detection of reversible risk factors of late-life mental ill health in early and mid-adulthood and their control can be of great relevance for active and healthy aging.
Diabetes mellitus (DM) is a chronic metabolic disease of public health significance in aging population due to rapidly rising prevalence and association with time-related multisystemic complications. The number of people living with diabetes has risen from 108 million (4.7%) in 1980–422 million (8.5%) globally in 2014, especially in LMICs.[7] China and India accounted for 109.6 and 69.2 million patients with diabetes in 2015 occupying top two positions in the list of countries. These numbers will rise to 150.7 and 123.5 million, respectively, in 2040. Worldwide in 2015, there were 94.2 million people aged 65–79 with diabetes, that is, 23% of patients with diabetes were older persons, which is expected to increase to 200.5 million (32%) by 2040.[8] Older adults are at high risk for the development of type 2 diabetes due to the combined effects of increasing insulin resistance and impaired pancreatic islet function with aging.
Diabetes, though a common problem in clinical practice, remains a challenge for the health system. Vague and atypical presentations are common in advancing years. With increase in age, micro- and macro-vascular complications dominate the clinical picture often unusually with painless myocardial infarction and limb ischemia. Poor response and adherence to nonpharmacological interventions (such as weight reduction and physical exercise) are frequent and have very low success rate in older diabetic population. Older adults with diabetes have the highest rates of major lower-extremity amputation, myocardial infarction (MI), visual impairment, and end-stage renal disease of any age group.[9]
The relationship between depression and type 2 diabetes is bidirectional [Figure 1]. Depression may impair DM-2 self-care and increase physical inactivity and other behavioral risk factors such as smoking and obesity.[10] Depression can lead to noncompliance and poor health behaviors.[11] Depression led to abnormally elevated blood glucose levels and insulin responses to glucose tolerance testing.[12] Poor glycemic control increases the risk of diabetes complications.[13] The long-term stress and strain of diabetes management, multiple finger sticks to check blood sugar levels, daily injections of insulin, and the worry of complications, can lead to a decreased quality of life (QOL) and an increased likelihood of depression.
Recent evidence suggests that the rate of anxiety disorders is elevated in people with diabetes. It is estimated that 14% diabetic patients have generalized anxiety disorder (GAD).
Many hypotheses with supporting evidence exist, including potential causative roles for hyperglycemia, vascular disease, hypoglycemia, insulin resistance, and amyloid deposition in cognitive impairment due to diabetes [Figure 2].[14]
The effect of DM-2 on mental health is due to the combined effect of vascular damage, metabolic changes, and chronic nature of the disease. Most studies report poor QOL for people with diabetes compared to the general population, especially regarding physical functioning and well-being due to multiple finger pricks, worry about complications, dietary restrictions, etc.
Most of the previous studies have either focused only on depression or anxiety disorder or cognition, but studies assessing all of them comprehensively along with QOL together in diabetes are limited. Comparative studies in LMIC that are dedicated to older persons are lacking. It is important for developing countries to estimate the prevalence of anxiety and depression and their associated factors among older people with diabetes, thereby to initiate early treatment so as to improve the clinical outcomes and decrease the associated resource utilization and costs. The main aims of this study were to find the frequency of Depression, GAD, cognitive impairment, and QOL in older patients with diabetes as compared to nondiabetics in Indian population.
| Subjects and Methods | | |
In this cross-sectional comparative study, 180 cases of diabetes diagnosed as per the ADA-2015 criteria were recruited from the Geriatric Medicine Outpatient Department (OPD) of tertiary care hospital between November 2014 and June 2016. An equal number of age- and sex-matched persons without diabetes were recruited as control. First, two nondiabetic patients, who were age and sex matched with cases, were recruited from OPD as controls daily, irrespective of their comorbidity. Cases and controls were recruited using nonprobability sampling method, where the first two cases and first two controls fulfilling the inclusion and exclusion criteria were recruited daily. Inclusion criteria for cases were diabetes diagnosed as per the ADA-2015 criteria in Geriatric Medicine OPD and willing to participate in the study. Inclusion criteria for controls were nondiabetic patients visiting Geriatric Medicine OPD for other complaints such as joint pain, hypertension, and dyspnea. Exclusion criteria for both cases and controls were participants incapable of communication for complete assessment and withdrawing consent. Permission for ethical clearance was taken from local ethical body of the institution. After recruitment, cases and controls were subjected to detailed assessment which included demographic details, anthropometric measurements, standard clinical assessment comprising of historical details, symptoms, physical examination, and other health issues. State of control and chronic complications of diabetes were diagnosed as per the ADA-2015 guidelines. Cases and controls were also subjected to a comprehensive geriatric assessment to detect the presence of any geriatric syndrome. Assessment of mental health status was carried out by validated scales. For diagnosis of depression, 15 items Geriatric Depression Scale[15] was used with score >5 suggestive of depression and above 10 almost always indicated the presence of depression. It is a validated instrument for screening depression in elderly. For diagnosis of anxiety, Mini-International Neuropsychiatric Interview[16] was used. For diagnosis of cognitive impairment, Montreal Cognitive Assessment (MoCA)[17] was used with score of 26 or more was graded as normal. To adjust the MoCA scores with education; 2 points were added to the total MoCA score for those with 4–9 years of education and 1 point for 10–12 years of education. MoCA score <26 was considered as cognitive impairment and MoCA score <18 as severe cognitive impairments. MoCA has very good sensitivity and is better than Mini-Mental State Examination (MMSE) for screening mild cognitive dysfunction. QOL was assessed with a generic scale World Health Organization Quality of Life-BREF (WHOQOL-BREF).[18]
Frequency of depression, GAD, and cognitive impairment were compared between patients with diabetes and nondiabetics using McNemar's Chi-square test. Mean health-related QOL scores in different domains of the scale and total scores were compared by Paired t-test.
| Results | | |
Demographic and clinical characteristics of cases and controls are presented in [Table 1]. Mean age of patients with diabetes is 64.68 (+4.89) years; 72.8% patients are <65 years old, 13.9% are 66–70 years old, and 13.3% are >70 years old. Of them, 59.4% cases were male. Mean body mass index in patients with diabetes is 24.11 (±4.07) kg/m2. Among patients with diabetes, 56.1% are overweight or obese. Among patients with diabetes, 83.3% cases have some other comorbidity and 16.7% have >two comorbidities. Among patients with diabetes, 26.7% cases are smokers and 22.2% consumed alcohol at least occasionally. Both diabetic cases and nondiabetic controls are comparable in terms of baseline characteristics [Table 1]. Both cases and controls are also comparable in terms of comorbidities except chronic obstructive pulmonary disease and coronary artery disease [Table 2]. Mean HbA1c and mean duration of diabetes in cases are 8.39 (±1.90) % and 8.05 (±6.78) years, respectively. 20% have HbA1c level ≤7% and 23.9% have HbA1c >9%. 45.6% have diabetic duration of ≤5 years [Table 3]. | Table 3: Association of diabetes with mental health disorders and quality of life
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There is significantly higher frequency of depression in diabetic as compared to nondiabetic (35.6% vs. 16.7%; P < 0.001). There is significant higher frequency of GAD in diabetic as compared to nondiabetic (12.8% vs. 4.4%; P < 0.001). There is significant higher frequency of cognitive impairment in diabetic as compared to nondiabetic (53.9% vs. 27.2%; P < 0.001) [Table 3].
Mean score of WHOQOL-BREF (physical, psychological, social, and environmental domains) in diabetic patients is lower than nondiabetics (59.04 ± 17.13 vs 74.61 ± 17.1 [P < 0.001], 65.96 ± 19.81 vs. 77.71 ± 17.00 [P < 0.001], 74.11 ± 17.98 vs. 78.68 ± 16.66 [P = 0.018] and 71.08 ± 15.10 vs. 78.50 ± 14.42 [P < 0.001], respectively) [Table 3] and [Annexure 1].
| Discussion | | |
The pandemic of diabetes has emerged as a major health problem for the human race. The age of onset is getting younger and with availability of effective treatment many older participants now live with diabetes to their 80s and 90s. Diabetes has a special relevance to LMICs, like India, which is emerging as the diabetic capital of the world. Combined with rapid population aging, the health system in India needs to prepare to care for large older diabetic patients with a plethora of chronic complications; both metabolic and vascular. As indicated earlier, reports of mental illness in younger patients with diabetes are available in literature, while that in aging population is scarce. The adverse impact of long-standing diabetes on physical health has been well documented along with its socioeconomic implications. Older patients are more vulnerable to chronic diabetic complications due to longer exposure to adverse metabolic and vascular influence. The risk of hypoglycemia and its adverse consequence have been well recognized necessitating a liberal glycemic control target. However, the poor mental health status of older diabetic patients has failed to receive adequate attention either in geriatric practice or in mental health practice. In this cross-sectional, comparative study, various mental health and QOL issues have been compared among older persons with or without diabetes.
Among patients with diabetes, 56.1% are overweight or obese. Incidence of obesity among diabetes in this study is much lower than in the USA, where the incidence of obese or overweight in diabetes is 84.7% suggesting that Indian diabetics are comparatively thinner than Western counterpart.[19] More than 70% are nonsmokers and nonalcoholic suggesting that older diabetic patients are mostly nonsubstance abusers, which is in contrast to younger adults.[19] Among diabetic patients, 83.3% have some other comorbidity and 16.7% have more than two comorbidities. In this study, the most common comorbidity in diabetes is hypertension (64.4%) similar to the Western population in which the frequency of hypertension in diabetes is 71%.[20]
In this study, only 20% have good glycemic control (HbA1c level <7%) and 23.9% have very poor glycemic control (HbA1c >9%) which is worse than their Western counterpart in whom 67.2% have good glycemic control (HbA1c <7%) and only 13% have very poor control (HbA1c >9%).[19] This suggests that older diabetic patients may have poor hyperglycemic control and are thus at higher risk of metabolic effects on mental health than Western counterpart.
In this study, a total of 94.4% diabetic patients are receiving some form of antidiabetic medications and 14.4% are on insulin, which is similar to Western counterpart, where 85.3% are taking some antidiabetic medications and 17.8% are on insulin.[19] This suggests that coverage of treatment in older diabetics from LMICs is comparable to high and upper-middle income counterparts. Most common medications used for diabetes is metformin (78.3%) followed by sulfonylureas (62.8%) and DPP inhibitors (16.7%). This can be biased due to social factors as both metformin and few sulfonylureas are supplied free of cost by the hospital. Hence, doctors are mostly prescribing these medications as most of the patients are unable to afford other types of medications.
In this study, the frequency of depression in diabetic patient is greater than nondiabetic (35.6% vs. 16.7%). Among 35.6% depressed diabetic patients, 27.8% are probable depression and 7.8% are definite depression. Previous studies have ranged the prevalence of depression in diabetes from 4.1% to 56%. Studies from India have ranged the prevalence from 11.6% to 49%. In older persons with diabetes, this has ranged from 15.7% to 40.3%.[21] Depression and chronic psychological stress can activate the hypothalamic–pituitary–adrenal axis, stimulate the sympathetic nervous system, increase inflammatory and platelet aggregation responses, and contribute to poor diabetes control.[14] DM-2-associated insulin resistance may interfere with depression treatment, thus worsening the depression prognosis and increasing the time spent in depression.
The frequency of GAD in diabetic patient is greater than nondiabetic (12.8% vs. 4.4%). Previous studies have shown the prevalence of GAD in diabetes from 14% to 34.1%. Most of the previous studies have looked for the presence of anxiety symptoms rather than GAD.[22] People with diabetes may potentially be anxious about how their condition will be perceived by others including friends, family, and work colleagues. Anxiety may also arise over what could happen if they experience hypoglycemia while driving or while looking after their children. Excessive worrying about the future complications of diabetes can lead to anxiety.
The frequency of cognitive impairment in diabetic patient is greater than nondiabetic (53.9% vs. 27.2). Among 53.9% cognitively impaired diabetic patients, 46.7% have mild cognitive impairment and 7.2% have severe cognitive impairment. In previous studies, diabetes was found to have increased the risk of cognitive dysfunction that ranged in older diabetics from 12.1% to 77.6%[23],[24],[25] depending on the type of scale used and cutoffs used in those scales. MMSE is less sensitive than MoCA to detect cognitive impairment in older patients.
QOL is poor in diabetic patients as compared to nondiabetic in all four domains of WHOQOL-BREF. The lowest and the highest mean scores are observed in physical health domain (59.04) and social relationship domain (74.11), respectively. Most studies report worse QOL for people with diabetes compared to the general population, especially regarding physical functioning and well-being. Diabetic may worsen social QOL through various mechanisms. In WHOQOL-BREF, social domains questionnaire includes “How satisfied are you with your sex life?” Diabetes may impair sex life through various mechanism. Diabetic autonomic neuropathy can cause erectile dysfunction. Depression can decrease libido along with decreased erections and vascular occlusion, which led to impaired sexual life in male. In female, diabetes-related nerve damage can cause vaginal dryness making intercourse uncomfortable and can also lead to loss of sensation in the genital area making orgasm difficult or impossible to achieve. Chronic high blood sugar levels can lead to reduced testosterone and may contribute to decreased sexual interest (libido). Diabetic may also worsen environmental QOL through various mechanisms. In WHOQOL-BREF, environmental domains questionnaire includes “How safe do you feel in your daily life?” and “Have you enough money to meet your needs?” In diabetic group, patients feel that their organs (kidney, nerves, and eyes) will fail and they may die due to heart attack or stroke. This excess worry will cause insecurity about the future. Furthermore, they have to spend a lot more money for medications, which may have a financial impact on their life.
Strength of this study is adequate sample size, comparative study design and instead of taking healthy controls without any ailment, controls are also taken from OPD of geriatric medicine which represents the true pool from where the cases are taken. This study is a cross-sectional comparative study so as to exclude the influence of other comorbidities on mental health and give a better perspective of association of DM with mental health unlike various previous studies which were noncomparative. Moreover, none of the previous study has assessed all the parameters of mental health comprehensively, thus interference of unmeasured mental health variable on measured mental health variable cannot be ruled out. This study includes comprehensive mental health assessment, which is similar to approach used for treating geriatric patients, although there is no such recommendation till now.
Limitations of the study are inability to establish the causative relation between diabetes and mental health for which a longitudinal study is required. Depression was diagnosed using screening questionnaire only and detailed interview was not used for diagnosing depression, although for confirming depression, detailed interview is required. This study is a single-center hospital-based study, so its results cannot be generalized to other populations or to community settings.
In summary, this study has shown that diabetes is a risk factor for mental health disorder and impaired QOL. Hence, all the diabetic patients should have a comprehensive mental health checkup routinely. In the Indian scenario, physician may not spend enough time for diagnosing mental health disorders in all patients due to time constraints. But as diabetic patients are more likely to have these mental disorders, so at least these patients should be screened for mental health disorders.
This study has shown that diabetic patients are at increased risk of mental health disorders, but whether screening and early treatment of this disorder have beneficial implications on level of glycemic control, adherence to treatment, diabetic complications, morbidity, and overall mortality is still unclear. Future studies are required to study these outcomes.
Financial support and sponsorship
Nil.
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]
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