Co-existing Non-communicable Diseases and Mental Illnesses Amongst the Elderly in Punjab, India

Abstract

Background: There is scant literature from India assessing the burden of mental disorders among elderly patients with non-communicable diseases (NCDs). This study aimed to determine the prevalence of depression and generalised anxiety disorder (GAD) among the elderly population with diabetes and/or hypertension and risk factors for psychiatric morbidity. Methodology: A cross-sectional study was conducted between September-December 2017 by using a semi-structured questionnaire amongst an elderly population (n=320), who were attending an NCD clinic in a rural district in the northern state of Punjab, India. The Geriatric Depression Scale (30-item) and GAD-7 scale were used to assess depression and GAD. Result: Depression was found in 58.1% (95% confidence interval [CI] 52.6-63.4%) of the study participants; of whom, 34.1% had severe depression. The proportion of GAD was found to be 38.7% (95% CI 33.6-44.2%), with 19.7% scoring in the severe range. Both GAD and depression was found in 37.8% (95% CI 32.7-43.2%). Female gender, nuclear family, being single/separated/divorced/widowed, low-income status and comorbid NCDs (especially hypertension) were found to be risk factors associated with depression and GAD. Conclusion: NCDs with co-morbid mental illness are a growing public health problem amongst the elderly population of the country. The NCD programme should make immediate efforts to provide mental-health care as part of a holistic care package to elderly with NCDs.

Full text

TOUCH MEDICAL MEDIA
2
ORIGINAL RESEARCH Diabetes
Print Publication Date: In Press
Globally, non-communicable diseases (NCDs) are currently
the leading cause of mortality and morbidity. Of the 56.4
million global deaths in 2015, nearly 39.5 million (70%) were
due to NCDs.1 Mental health disorders are one of the known
major contributors to NCD burden. They are responsible for
7.4% of global disability adjusted life years (DALYs) and 22.9%
of years lived with disabilities (YLDs), making them the fifth
leading cause of DALYs and YLDs.2 Depression is one of the
most common mental health disorders and is the leading
cause of ill health and disability worldwide. Nearly 300 million
people are now living with depression, an increase of more
than 18% between 2005–2015.3 Similarly, anxiety disorders
are also very common, being the sixth leading cause of
disability, in terms of YLDs.4
The world is undergoing rapid cultural and social changes,
which include aging populations, increasing urbanisation,
dietary changes, reduced physical activity, unhealthy lifestyle
and limited capacity of the health system to manage the
existing burden and prevent further cases.5 This changing
scenario has augmented the disease burden transition from
communicable to NCDs. Many studies indicate that the co-
existence of NCDs, such as hypertension and diabetes, with
depression and other psychological morbidities is detrimental
to care and prognosis leading to poor glycaemic control,
uncontrolled hypertension, greater risk of cardiovascular
complications and higher mortality rates.6 A survey conducted
by the World Health Organization (WHO) across 60 countries,
found that between 9.3–23.0% of patients with chronic
diseases had comorbid depression.7
Co-existing Non-communicable Diseases
and Mental Illnesses Amongst the Elderly
in Punjab, India
Madhur Verma,1,2 Sandeep Grover,3 Jaya Prasad Tripathy,4,5,6 Tarundeep Singh,2 Sharath Burugina Nagaraja,7
Soundappan Kathirvel,2 Gopal Singh,2 Ritu Nehra3
1. Department of Community Medicine, Kalpana Chawla Government Medical College, Karnal, Haryana, India; 2. Department of Community
Medicine, School of Public Health, Post Graduate Institute of Medical Education and Research, Chandigarh, India; 3. Department of Psychiatry,
Post Graduate Institute of Medical Education and Research, Chandigarh, India; 4. International Union Against Tuberculosis and Lung Disease,
The Union South East Asia Office, New Delhi, India; 5. International Union Against Tuberculosis and Lung Disease, Paris, France; 6. Department of
Community Medicine, AIIMS Nagpur, India; 7. Department of Community Medicine, ESIC Medical College, Bengaluru, India.
Background: There is scant literature from India assessing the burden of mental disorders among elderly patients with
non-communicable diseases (NCDs). This study aimed to determine the prevalence of depression and generalised anxiety disorder
(GAD) among the elderly population with diabetes and/or hypertension and risk factors for psychiatric morbidity. Methodology:
A cross-sectional study was conducted between September–December 2017 by using a semi-structured questionnaire amongst elderly
population (n=320), who were attending an NCD clinic in a rural district in the northern state of Punjab, India. The Geriatric Depression Scale
(30-item) and GAD-7 scale were used to assess depression and GAD. Result: Depression was found in 58.1% (95% confidence interval
[CI] 52.6–63.4%) of the study participants; of whom, 34.1% had severe depression. The proportion of GAD was found to be 38.7% (95%
CI 33.6–44.2%), with 19.7% scoring in the severe range. Both GAD and depression was found in 37.8% (95% CI 32.7–43.2%). Female gender,
nuclear family, being single/separated/divorced/widowed, low-income status and comorbid NCDs (especially hypertension) were found to
be risk factors associated with depression and GAD. Conclusion: NCDs with co-morbid mental illness are a growing public health problem
amongst the elderly population of the country. The NCD programme should make immediate efforts to provide mental-health care as part of
a holistic care package to elderly with NCDs.
Keywords
Anxiety, depression, elderly, geriatric, non-communicable diseases
Disclosures: Madhur Verma, Sandeep Grover, Jaya Prasad Tripathy, Tarundeep Singh,
Sharath Burugina Nagaraja, Soundappan Kathirvel, Gopal Singh and Ritu Nehra
have no conflicts of interest to declare in relation to this article.
Acknowledgments: This research was conducted through the Structured Operational
Research and Training Initiative (SORT IT), a global partnership led by the Special Programme
for Research and Training in Tropical Diseases at the World Health Organization (WHO/
TDR). The model is based on a course developed jointly by the International Union Against
Tuberculosis and Lung Disease (The Union) and Medécins sans Frontières (MSF/Doctors
Without Borders). The specic SORT IT programme which resulted in this publication was
jointly developed and implemented by: The Union South-East Asia Ofce, New Delhi, India;
the Centre for Operational Research, The Union, Paris, France; Médecins Sans Frontières,
Operational Research Unit, Luxembourg; Department of Preventive and Social Medicine,
Jawaharlal Institute of Postgraduate Medical Education and Research, Puducherry, India;
Department of Community Medicine, GMERS Medical College, Vadodara, India; Department
of Community Medicine, ESIC Medical College and PGIMSR, Bengaluru, India; Department of
Community Medicine, Sri ManakulaVinayagar Medical College and Hospital, Puducherry, India;
Department of Community Medicine, Velammal Medical College Hospital and Research Institute,
Madurai, Tamil Nadu; and National Institute for Research in Tuberculosis, Chennai, India.
Review Process: Double-blind peer review.
Compliance with Ethics: Ethics approval was obtained from the Institutional
Ethics Committee of Post Graduate Institute of Medical Education and Research,
Chandigarh, India, and The Union Ethics Advisory Group, Paris, France. Written
informed consent was obtained from the participants before the interview.
Authorship: All named authors meet the criteria of the International Committee of Medical
Journal Editors for authorship for this manuscript, take responsibility for the integrity of
the work as a whole and have given nal approval for the version to be published.
Received: 14 December, 2018
Accepted: 18 March, 2019
Citation: European Endocrinology, 2018;15(2):ePub ahead of print.
Corresponding Author: Madhur Verma, Assistant Professor, Room No. 412, Department of
Community Medicine, Kalpana Chawla Government Medical College, Karnal, Haryana, India.
E: drmadhurverma@gmail.com
Support: The training program, within which this paper was developed, was funded by
the Department for International Development (DFID), UK. The funders had no role in study
design, data collection, and analysis, decision to publish, or preparation of the manuscript.

Depression and Anxiety Among Elderly with Non-communicable Diseases
3
EUROPEAN ENDOCRINOLOGY
India is witnessing a steep rise in the NCD epidemic including mental
disorders. As a result of the demographic transition, the nation is
also aging with nearly 104 million elderlypersons (≥60 years) and the
proportion of elderly has increased from 5.6% in 1961 to 8.6% in 2011.8
For a country like India, with the exponential rise in NCDs along with
an increase in aging population, it is becoming increasingly important
for the healthcare providers to quantify the burden of comorbid NCDs
and mental illnesses, and to design a pragmatic healthcare delivery
model that provides holistic management for these conditions. In line
with this requirement, a healthcare delivery model was developed
and implemented at a rural secondary healthcare setting in Punjab,
India during 2015, which envisioned a comprehensive care model for
patients suffering from NCDs mainly elderly (≥60 years) with diabetes
and hypertension. To provide holistic care, patients were screened
for common mental illnesses using simple validated tools and linked
to mental healthcare services, if needed. Against this background,
we conducted this study to determine the prevalence of depression
and generalised anxiety disorder among the elderly population with
diabetes and/or hypertension and explore the risk factors associated
with it.
Methods
Study design
A cross-sectional study was conducted using a semi-structured
questionnaire at district Fatehgarh Sahib in the northern state of Punjab,
India (population 600,000; area 1,147 km2; sex ratio 871; literacy rate
80.3%). The government health infrastructure of the district includes 6
secondary level hospitals, 13 primary level health facilities, 26 subsidiary
health centres, 72 sub-centres along with the private sector with nursing
homes and practitioners who play a major role in providing health care
services.
Specic setting
The study was conducted at two Community Health Centres (Khera and
Bassi Pathana) of Fatehgarh Sahib, which is the field practice area of
the Department of Community Medicine, School of Public Health, Post
Graduate Institute of Medical Education and Research, Chandigarh.
Each facility caters to a population of around 150,000. The department
conducts a chronic disease clinic at both these public facilities once a
week which targets mostly the geriatric population. Besides preventive
and diagnostic services, the patients who are diagnosed with diabetes or
hypertension are also provided medicines and weekly follow-up free of
cost. The clinic is also supported by a charitable trust which is actively
engaged in community service in that area. Around 80 patients visit the
facility per clinic day.
Study population
All patients aged ≥60 years or above and diagnosed with diabetes
and/or hypertension attending a chronic disease clinic in Fatehgarh
Sahib district of Punjab, India.
Study period
The study was conducted between September 2017 and June 2018.
Sample size and sampling
Considering the prevalence of depression among elderly with comorbid
diabetes as 25%,9 5% precision and 10% non-response rate, the sample
size was calculated to be310. (Stat-calc, Epi Info: version 7.2.0.1) All new
patients aged ≥60 years diagnosed with diabetes and/or hypertension
were recruited at the clinic consecutively till the required sample size
was attained.
Data collection process
Data were collected using a structured questionnaire administered
by the principal investigator (MV) and another trained public health
nurse (GS) at the chronic disease clinic. The questionnaire collected
information on socio-demographic and clinical characteristics. The
socio-demographic variables included age, gender, locality (urban/rural),
education, occupation, family income, marital status and family type. The
clinical characteristics included the body mass index (BMI) of the patients,
presence of morbidities such as diabetes, hypertension or both; duration
of the disease; history of stroke, myocardial infarction or coronary artery
disease; tobacco, alcohol or any other substance abuse as per standard
definitions; and family history of certain illnesses.10 Validated tools were
used to assess depression (Geriatric Depression Scale) and generalised
anxiety disorder (GAD-7 scale).11,12
The Geriatric Depression Scale is a 30-item scale where each question
is given a score of 0 or 1. Questions 1, 5, 7, 9, 15, 19, 21, 27, 29 and
30 have a reverse scoring where a “no” response is given a score
of 1. All other questions are given a score of 1 if the answer was
“yes”. The interpretation of the total score is as follows: normal, 0–9;
mild depression, 10–19; severe depression, 20–30. For this study, the
validated Hindi version of the scale was used.13 GAD-7 scale is a 7-item
scale where each item is given a score ranging from 0–3 (0, not at all; 1,
several days; 2, more 50% of days; 3, nearly every day). The score against
each question is added and interpreted as follows: minimal anxiety,
0–4; mild anxiety, 5–9; moderate anxiety, 10–14; severe anxiety, 15–21. A
score of ≥10 is indicative of a possible diagnosis of GAD. For this study,
Hindi version of GAD-7 was used, which has been shown to have to
acceptable level of diagnostic concordance with the diagnosis made for
a psychiatric disorder by psychiatrist.14 It has also been used in elderly
clinic population in Indian setting.15
Analysis and statistics
Quantitative data were double-entered and validated using EpiData
entry version 3.1 and subsequently analysed using EpiData analysis version
2.2.2.182 (EpiData Association, Odense, Denmark). The key outcome
variables were the prevalence of depression and GAD which were
expressed in percentages. Multivariable logistic regression was carried out
to explore factors associated with depression and GAD. Variables with a
p-value <0.2 in the univariable analysis were included in the regression
model after ruling out collinearity. Odds ratios with 95% confidence interval
(CI) were used to measure the strength of the association.
Ethics approval
Ethics approval was obtained from the Institutional Ethics Committee of
Post Graduate Institute of Medical Education and Research, Chandigarh,
India, and The Union Ethics Advisory Group, Paris, France. Written informed
consent was obtained from the participants before the interview.
Results
Socio-demographic and behavioural characteristics
Out of a total of 330 patients who attended the clinic during the study
period, 320 gave consent for the interview (response rate of 97%). Table 1
shows the socio-demographic, behavioural and clinical characteristics of
the respondents in the study. The majority of respondents were females
(55.3%; n=177), between 60–69 years of age (72.8%; n=233), residing in
rural areas (88.8%; n=284) and living in joint families (75.3%; n=241); and
nearly half were illiterate (48.4%; n=155) and unemployed (45.6%; n=146).
Fifty percent (n=161) of them were suffering from hypertension, 29.1%
(n=93) had diabetes, 20.6% (n=66) were suffering from both the diseases,
and 63.1% (n=202) were overweight/obese (BMI >23.0 kg/m2).

ORIGINAL RESEARCH Diabetes
4EUROPEAN ENDOCRINOLOGY
Depression and generalised anxiety disorder
Overall depression was found in 58.2% (95% CI 52.6–63.4%) of the study
participants; of which 34.1% had severe depression. Among females,
both depression and severe depression were found to be significantly
higher with 72.4% and 49.2%, respectively (p<0.001; Figure 1A).
Similarly, the proportion of GAD among the elderly was found to be 38.8%
(95% CI 33.6–44.2%); while 19.7% had severe GAD. GAD and severe GAD
were higher among females with 52.0% and 28.8%, respectively (p<0.001).
(Figure 1B). The risk factors associated with GAD and depression are
shown in Tables 2 and 3. Female gender, nuclear family, being single/
separated/divorced/widowed, low-income status and comorbid NCDs
especially hypertension emerged as the risk factors associated with
depression (Table 2) and GAD (Table 3) in the study population. Ironically,
stressful factors like financial loss, problems with spouse, life-threatening
illness (such as history of severe infections, myocardial infarction,
stroke, chronic obstructive pulmonary disease, benign or malignant
tumours) and living away from the family did not emerge significantly in
multinomial logistic regression; while factors like living alone and death
of spouse were not included in the model due to multicollinearity.
Discussion
This is one of the first studies conducted in India looking at the
co-morbidity of mental illnesses among patients with NCDs in the
elderly age group. The study findings suggest that one out of two elderly
people with existent NCDs, such as hypertension and diabetes, suffer
from depression and one in three have GAD. The majority (55%) of the
Table 1: Socio-demographic, behavioural and clinical
characteristics of elderly patients attending a chronic
disease clinic in Punjab, India, 2017
Characteristics Number (%) N=320
Age group
60–69 years 233 (72.8)
70–79 years 76 (23.8)
≥80 11 (3.4)
Gender
Male 143 (44.7)
Female 177 (55.3)
Type of family
Nuclear 79 (24.7)
Joint/extended 241 (75.3)
Marital status
Married 244 (76.3)
Single/divorced/separated/widowed 76 (23.8)
Per capita family income in INR*
≤1,875 109 (34.1)
1,876–6,253 134 (41.9)
≥6,254 77 (24.1)
Place of residence
Urban 36 (11.3)
Rural 284 (88.8)
Living alone
Yes 35 (10.9)
No 285 (89.1)
Current tobacco use
Yes 13 (4.1)
No 307 (95.9)
Current alcohol use
Yes 38 (11.9)
No 282 (88.1)
Co-morbid conditions
Diabetes 93 (29.1)
Hypertension 161 (50.3)
Both 66 (20.6)
Duration of disease (years)
1–5 54 (16.9)
6–10 95 (29.7)
>10 171 (53.4)
Body mass index (in kg/m2)
Underweight (<18.5) 12 (3.8)
Normal (<18.5–22.9) 106 (33.1)
Overweight (23.0–24.9) 54 (16.9)
Obese (>25.0) 148 (46.3)
Educational status
Illiterate 155 (48.4)
Up to middle school (>8 years of schooling) 80 (25.0)
High school & above (>12 years of schooling) 85 (26.6)
Occupational status
Unemployed/retired/homemaker 146 (45.6)
Unskilled worker 49 (15.3)
Semi-skilled/skilled worker 27 (8.4)
Clerical/shop owner/farmer 84 (26.3)
Professional 10 (3.1)
Not known 4 (1.3)
*Per capita monthly income as per BG Prasad Socioeconomic classification scale
(2017).
Figures represent numbers with percentages in parentheses. INR = Indian Rupee
Figure 1: Prevalence of depression (A) and generalised
anxiety disorder (B) among elderly in Punjab, India, 2018
A
B
59.4
27.7
41.8
25.2
23.2
24.1
15.4
49.2
34.1
0
10
20
30
40
50
60
70
80
90
100
Males (n=143) Females (n=177)
Proportion of patients (%)
Severe Minimal Normal
18.2 19.2 18.8
59.4
28.8
42.5
14
23.2
19.1
8.4
28.8 19.7
0
10
20
30
40
50
60
70
80
90
100
Males (n=143) Females (n=177)
Proportion of patients (%)
Minimal Mild Moderate Severe
Total (n=320)
Total (n=320)

Depression and Anxiety Among Elderly with Non-communicable Diseases
5
EUROPEAN ENDOCRINOLOGY
Table 2: Socio-economic, behavioural and clinical factors associated with depression among elderly patients attending a
chronic disease clinic in Punjab, India, 2017
Characteristics Total N Depression n (%) Crude OR (95% CI) p-value Adjusted OR (95% CI) p-value
Age group
60–69 years 233 134 (57.5) Reference value -
70–79 years 76 45 (59.2) 1.07 (0.6–1.8) -
≥80 11 7 (63.6) 1.29 (0.4–4.5) -
Gender <0.001
Male 143 58 (40.6) Reference value Reference value
Female 177 128 (72.3) 3.82 (2.4–6.1) 3.7 (2.1–6.5) <0.001
Living alone** 0.01
No 285 159 (55.8) Reference value -
Yes 35 27 (77.1) 2.67 (1.2–6.1) -
Type of family 0.004
Joint/extended 241 129 (53.5) Reference value Reference value
Nuclear 79 57 (72.2) 2.24 (1.3–3.9) 2.9 (1.5–5.4) 0.001
Per capita family income in INR 0.02
≤1,875 109 75 (68.8) 2.1 (1.2–3.5) 1.9 (1.1–3.4) 0.04
1,876–6,253 134 69 (51.5) Reference value Reference value
≥6,254 77 42 (54.5) 1.1 (0.6–2.0) 1.1 (0.6–2.0) 0.8
Marital status <0.001
Married 244 125 (51.2) Reference value Reference value
Single/separated/divorced/widowed 76 61 (80.3) 3.9 (2.1–7.2) 3.4 (1.7–6.7) <0.001
Current tobacco 0.8
Yes 13 8 (61.5) 1.2 (0.4–3.6) -
No 307 178 (58.0) Reference value -
Current alcohol use 0.7
No 282 165 (58.5) Reference value -
Yes 38 21 (55.3) 0.9 (0.4–1.7) -
Disease <0.001
Diabetes 93 38 (40.9) Ref Reference value
Hypertension 161 105 (65.2) 2.0 (1.2–3.4) 3.1 (1.7–5.6) <0.001
Both 66 43 (65.2) 2.3 (1.2–4.3) 2.7 (1.3–5.7) 0.009
Duration of disease 0.7
1–5 years 54 34 (63.0) Reference value -
6–10 years 95 53 (55.8) 0.6 (0.3–1.2) -
>10 years 171 99 (57.9) 0.6 (0.3–1.2) -
Body mass index (kg/m2)0.5
Underweight (<18.5) 12 9 (75.0) Reference value -
Normal (18.5–22.9) 106 64 (60.4) 0.5 (0.1–2.0) -
Overweight (23.0–24.9) 54 29 (53.7) 0.4 (0.1–1.6) -
Obese (>25.0) 148 84 (56.8) 0.4 (0.1–1.7) -
Death of spouse* <0.001
No 274 145 (52.9) Reference value -
Yes 46 41 (89.1) 7.3 (2.8–19.0) -
Financial loss 0.1
No 306 175 (57.2) Reference value Reference value
Yes 14 11 (78.6) 2.7 (0.8–10.0) 4.0 (1.1–15.1) 0.05
Problem with spouse 0.9
No 310 180 (58.1) Reference value -
Yes 10 6 (60.0) 1.1 (0.3–3.9) -
Life-threatening illness†0.3
No 298 171 (57.4) Reference value -
Yes 22 15 (68.2) 1.6 (0.6–4.0) -

ORIGINAL RESEARCH Diabetes
6EUROPEAN ENDOCRINOLOGY
respondents were female and mostly residing in rural areas and in
joint families, and about half of them were illiterate and unemployed.
Females outnumber males probably because the study population
(elderly with NCDs) is markedly different from the general population.
The following reasons could explain the high female:male ratio in the
study population: i) higher life expectancy of females in the elderly age
group; ii) better health-seeking behaviour among females, this being a
hospital-based sample. It is also well known that undiagnosed cases of
diabetes/hypertension are higher among males because of their poor
health seeking.16,17
We believe that the high burden of comorbid NCDs and mental illnesses
could be due to psychological co-morbidities leading to hypertension,
diabetes and other cardiovascular events; and chronic diseases leading
to psychological co-morbidities such as stress, anxiety, and depression.
This has important public-health implications. Major modifiable risk
factors for NCDs such as poor diet, physical inactivity, tobacco use and
harmful alcohol use, are exacerbated by poor mental health. Thus, mental
illness is a key risk factor for NCD. In addition, individuals with mental
health conditions are less likely to seek help for NCD and symptoms may
affect adherence to treatment as well as prognosis.18
There is considerable evidence showing that psychological factors
including depression and anxiety predict the onset and severity of
cardiovascular morbidities such as hypertension, metabolic syndrome
and diabetes, which contribute to higher morbidity and mortality.19 On
the other hand, chronic diseases such as diabetes and hypertension also
lead to depression, anxiety, and stress as reported in the present study.
Similar findings have been presented in the previous literature where
patients have reported poor psychological health due to the disease
itself and have expressed concerns about the chronic and potential long-
term complications of the disease.20,21
In diabetes, there is evidence of decreased quality of life and poor mental
well-being because of fear and distress associated with the disease that
is difficult to distinguish from other common mental disorders.22 Future
studies should focus on measuring these aspects related to diabetes.
One such instrument is the Problem Areas In Diabetes questionnaire
which covers a wide variety of emotional concerns that are associated
with depressive symptoms and undesirable coping styles.23 Female
gender, residing in a nuclear family, being separated/widowed/divorced
and the presence of other chronic diseases was significantly associated
with depression and anxiety in the present study population. Female
gender is a predominant risk factor for psychological morbidities
probably due to hormonal fluctuations and societal driven discriminatory
attitudes both within and outside the family.24–27 The present study found
that elderly people living in a nuclear family system were more likely to
suffer from depression and anxiety as supported by other studies.28–30
This could be due to the higher level of support that a joint family offers
to the elderly than a nuclear family system, especially physical, social
and emotional support. Mental illnesses are also common among
those who are separated/divorced/widowed.29,31–34 This could be due to
mental stress, loneliness and lack of support as a result of the loss of the
partner/spouse.
The findings or the present study have the following programmatic
implications: first, given the high burden of anxiety and depression among
elderly patients who attend the NCD clinics, all elderly patients should be
formally and regularly assessed for depression and anxiety disorders, at
least once a year, using simple validated tools. Second, considering the
co-existence of mental illness and NCDs, WHO has recommended an
integrated approach to manage mental illnesses among persons with
NCDs and reducing the risk of NCDs among people with mental illnesses.
This model of care will improve patient satisfaction, adherence to treatment
and health outcomes, and it is proven to be cost-effective as well.35
Third, primary healthcare physicians and physicians in charge of NCD clinics
need to be trained to identify common psychological morbidities such as
depression and anxiety, and take appropriate action. All the physicians at
the primary health centres need to be trained under the District Mental
Health Programme of the National Mental Health Programme (NMHP) of
the Government of India to manage them, and should also have access to
effective evidence-based interventions.36 Fourth, special counselling and
follow-up services should be offered to those with anxiety and depression.
Fifth, the burden of comorbid NCDs and mental illness among the elderly
presents a strong rationale for integration of the NMHP; the National
Program for Prevention and Control of Cancer, Diabetes, Cardiovascular
Diseases and Stroke; and the National Programme for Health Care of the
Elderly to provide mental-health care to this vulnerable population at
public health facilities. Sixth, it is prudent to include mental disorders in the
broad rubric of NCDs which is currently missing.
The study had some strengths. It was conducted at a rural government
health centre undertaking mental health screening among elderly with
comorbid chronic diseases in operational settings and thus, it reflects the
ground reality of the situation. This model of healthcare can be replicated
elsewhere across the country in similar settings. The tools used to screen
mental illness were standard validated tools and therefore there are least
chances of false diagnosis. The data were double entered and validated
using EpiData software to minimise data entry errors.
Characteristics Total N Depression n (%) Crude OR (95% CI) p-value Adjusted OR (95% CI) p-value
Living away 0.23
No 280 159 (56.8) Reference value
Yes 40 27 (67.5) 1.6 (0.8–3.2) -
Educational status 0.09 -
Illiterate 155 97 (62.6) Reference value Reference value
Up to middle school 80 48 (60.0) 0.9 (0.5–1.5) 1.2 (0.6–2.2) 0.6
High school and above 85 41 (48.2) 0.6 (0.3–0.9) 1.3 (0.7–2.6) 0.4
*living alone and death of spouse were not included in the model due to multicollinearity. †Life-threatening illnesses include history of severe infections, myocardial infarction,
stroke, chronic obstructive pulmonary disease, benign or malignant tumours. Backward conditional multivariable logistic regression was performed. CI = confidence interval;
INR = Indian Rupee; OR = odds ratio.
Table 2: Cont.

Depression and Anxiety Among Elderly with Non-communicable Diseases
7
EUROPEAN ENDOCRINOLOGY
Table 3: Socio-economic, behavioural and clinical factors associated with generalised anxiety disorder among elderly
patients attending a chronic disease clinic in Punjab, India, 2017
Characteristics Total N GAD n (%) Crude OR (95% CI) p-value Adjusted OR (95% CI) p-value
Age group 0.5
60–69 years 233 87 (37.3) Reference value -
70–79 years 76 31 (40.8) 1.2 (0.7–1.9) -
≥80 11 6 (54.5) 2.0 (0.6–6.8) -
Gender <0.001
Male 143 32 (22.4) Reference value Reference value
Female 177 92 (52.0) 3.7 (2.3–6.1) 3.3 (1.9–5.9) <0.001
Living alone 0.02
No 285 104 (36.5) Reference value -
Yes 35 20 (57.1) 2.3 (1.1–4.7) -
Type of family 0.02
Joint/extended 241 85 (35.3) Reference value Reference value
Nuclear 79 39 (49.4) 1.8 (1.1–2.9) 2.2 (1.2–3.9) 0.009
Per capita family income in INR 0.004
≤1,875 109 53 (48.6) 2.4 (1.4–4.1) 2.1 (1.2–3.8) 0.01
1,876–6,253 134 38 (28.4) Reference value Reference value
≥6,254 77 33 (42.9) 1.9 (1.0–3.4) 1.9 (1.1–3.6) 0.05
Marital status 0.001
Married 244 82 (33.6) Reference value Reference value
Single/separated/divorced/widowed 76 42 (55.3) 2.4 (1.4–4.1) 1.9 (1.2–3.9) 0.03
Current tobacco 0.5
Yes 13 4 (30.8) 0.7 (0.2–2.3) -
No 307 120 (39.1) Reference value -
Current alcohol use 0.22
Yes 38 11 (28.9) 0.6 (0.3–1.3) -
No 282 113 (40.1) Reference value -
Disease 0.003
Diabetes 93 23 (24.7) Reference value Reference value
Hypertension 161 75 (46.6) 2.1 (1.2–3.6) 2.9 (1.5–5.3) 0.001
Both 66 26 (39.4) 2.1 (1.1–4.2) 1.7 (0.8–3.6) 0.1
Duration of disease 0.3
1–5 years 54 26 (48.1) Reference value -
6–10 years 95 35 (36.8) 0.6 (0.3–1.2) -
>10 years 171 63 (36.8) 0.6 (0.3–1.2) -
Body mass index (kg/m2)0.4
Underweight (<18.5) 12 5 (41.7) Reference value -
Normal (18.5–22.9) 106 47 (44.3) 1.1 (0.3–3.7) -
Overweight (23.0–24.9) 54 17 (31.5) 0.6 (0.2–2.3) -
Obese (>25.0) 148 55 (37.2) 0.8 (0.3–2.7) -
Death of spouse* <0.001
No 274 93 (33.9) Reference value -
Yes 46 31 (67.4) 4.0 (2.1–7.8) -
Financial loss 0.4
No 306 117 (38.2) Reference value -
Yes 14 7 (50.0) 1.6 (0.6–4.7) -
Problem with spouse 0.9
No 310 120 (38.7) Reference value -
Yes 10 4 (40.0) 1.1 (0.3–3.8) -
Life-threatening illness†0.01
No 298 110 (36.9) Reference value Reference value
Yes 22 14 (63.6) 3.0 (1.2–7.4) 2.7 (1.1–7.2) 0.05

ORIGINAL RESEARCH Diabetes
8EUROPEAN ENDOCRINOLOGY
Characteristics Total N GAD n (%) Crude OR (95% CI) p-value Adjusted OR (95% CI) p-value
Living away 0.6
No 280 107 (38.2) Reference value -
Yes 40 17 (42.5) 1.2 (0.6–2.3) -
Educational status 0.06
Illiterate 155 70 (45.2) Reference value Reference value
Up to middle school 80 28 (35.0) 0.7 (0.4–1.1) 0.8 (0.4–1.5) 0.5
High school and above 85 26 (30.6) 0.5 (0.3–0.9) 1.1 (0.6–2.2) 0.7
*living alone and death of spouse were not included in the model due to multicollinearity. †Life-threatening illnesses include history of severe infections, myocardial infarction,
stroke, chronic obstructive pulmonary disease, benign or malignant tumours. Backward conditional multivariable logistic regression was performed. CI = confidence interval;
GAD = generalised anxiety disorder; INR = Indian Rupee; OR = odds ratio.
There were some limitations to the study. The study was carried out
in a single rural health clinic raising questions on the generalisability
of the findings in other settings. The study is a cross-sectional design,
causal pathways underlying the reported associations cannot be
ascertained. This was a clinic-based study, so referral bias could
have affected the results. There was no control group, so we do not
know whether the prevalence of psychological morbidities, such as
anxiety and depression, is similar in the general population. Finally,
the patients were evaluated on questionnaires and not assessed by a
specialist psychiatrist, which is considered as gold standard for making
a psychiatric diagnosis.
Conclusion
To conclude, there is a huge burden of comorbid NCDs with mental
illness among the elderly population in India. There is a need to develop
an integrated care model to manage this comorbidity to this vulnerable
population at all levels of health care facilities.
Table 3: Cont.
1. World Health Organization. NCD mortality and morbidity WHO.
2017. Available at: www.who.int/gho/ncd/mortality_morbidity/en/
(accessed 6 April 2019).
2. Whiteford HA, Degenhardt L, Rehm J, et al. Global burden of
disease attributable to mental and substance use disorders:
findings from the Global Burden of Disease Study 2010. Lancet.
2013;382:1575–86.
3. World Health Organization. Depression and Other
Common Mental Disorders: Global Health Estimates. 2017.
Available at: http://apps.who.int/iris/bitstream/
handle/10665/254610/WHO-MSD-MER-2017.2-eng.
pdf?sequence=1 (accessed 6 April 2019).
4. Baxter AJ, Scott KM, Vos T, Whiteford HA. Global prevalence of
anxiety disorders: a systematic review and meta-regression.
Psychol Med. 2013;43:897–910.
5. Yeates K, Lohfeld L, Sleeth J, et al. A global perspective on
cardiovascular disease in vulnerable populations. Can J Cardiol.
2015;31:1081–93.
6. Lustman PJ, Anderson RJ, Freedland KE, et al. Depression and
poor glycemic control: a meta-analytic review of the literature.
Diabetes Care. 2000;23:934–42.
7. Moussavi S, Chatterji S. Depression, chronic diseases, and
decrements in health: results from the World Health Surveys.
Lancet. 2007;370:851–8.
8. World Health Organization. Noncommunicable diseases. 2018.
Available at: www.who.int/news-room/fact-sheets/detail/
noncommunicable-diseases (accessed 6 April 2019).
9. Rajput R, Gehlawat P, Gehlan D, et al. Prevalence and
predictors of depression and anxiety in patients of diabetes
mellitus in a tertiary care center. Indian J Endocrinol Metab.
2016;20:746–51.
10. World Health Organization. The WHO STEPwise approach to
chronic disease risk factor surveillance WHO STEPS Surveillance
Manual. WHO Global Report, Geneva. 2008. Available at: http://
apps.who.int/iris/bitstream/10665/43376/1/9241593830_eng.
pdf (accessed 6 April 2019).
11. Yesavage JA, Brink TL, Rose TL, e t al. Development and
validation of a geriatric depression screening scale:
A preliminary report. J Psychiatr Res. 1982;17:37–49.
12. Spitzer RL, Kroenke K, Williams JBW, Löwe B. A brief measure for
assessing generalized anxiety disorder the GAD-7. Arch Intern
Med. 2006;166:1092–7.
13. Ganguli M, Dube S, Johnston JM, et al. Depressive symptoms,
cognitive impairment and functional impairment in a
rural elderly population in India: a Hindi version of the
geriatric depression scale (GDS-H). Int J Geriatr Psychiatry.
1999;14:807–20.
14. Avasthi A, Grover S, Bhansali A, et al. Presence of common
mental disorders in patients with diabetes mellitus using
a two-stage evaluation method. Indian J Med Res Suppl.
2015;141:364–7.
15. Grover S, Avasthi A, Sahoo S, et al. Indian Association for
Geriatric Mental Health’s multicentric study on depression in
elderly: Symptom profile and influence of gender, age of onset,
age at presentation, and number of episodes on symptom
profile. J Geriatr Ment Heal. 2018;5:35.
16. Tripathy JP, Singh Thakur J, Jeet G, et al. Alarmingly high
prevalence of hypertension and pre-hypertension in North
India-results from a large cross-sectional STEPS survey.
PLoS One. 2017;12:e0188619.
17. Tripathy JP, Thakur JS, Jeet G, et al. Prevalence and risk factors
of diabetes in a large community-based study in North India:
results from a STEPS survey in Punjab, India. Diabetol Metab
Syndr. 2017;9:8.
18. Ngo VK, Rubinstein A, Ganju V, et al. Grand challenges:
integrating mental health care into the non-communicable
disease agenda. PLoS Med. 2013;10:1–5.
19. Penninx BWJH. Depression and cardiovascular disease:
Epidemiological evidence on their linking mechanisms.
Neurosci Biobehav Rev. 2017;74:277–86.
20. Peyrot M, Rubin RR, Lauritzen T, et al. Psychosocial problems
and barriers to improved diabetes management: results of the
Cross-National Diabetes Attitudes, Wishes and Needs (DAWN)
Study. Diabet Med. 2005;22:1379–85.
21. Sendhilkumar M, Tripathy JP, Harries AD, et al. Factors
associated with high stress levels in adults with diabetes
mellitus attending a tertiary diabetes care center, Chennai,
Tamil Nadu, India. Indian J Endocrinol Metab. 2017;21:56–63.
22. Kalra S, Bathla M, Khandelwal D. The GlucoCoper—a
salutogenic approach to diabetes distress. US Endocrinolology.
2018;14:30–1.
23. Welch GW, Jacobson AM, Polonsky WH.The Problem Areas in
Diabetes Scale. An evaluation of its clinical utility.Diabetes care.
1997;20:760–6.
24. Sivertsen H, Bjørkløf GH, Engedal K, et al. Depression and
quality of life in older persons: a review. Dement Geriatr Cogn
Disord. 2015;40:311–39.
25. Luppa M, Sikorski C, Luck T, et al. Age- and gender-specific
prevalence of depression in latest-life – Systematic review and
meta-analysis. J Affect Disord. 2012;136:212–21.
26. Cole MG, Dendukuri N. Risk factors for depression among
elderly community subjects: a systematic review and
meta-analysis. Am J Psychiatry. 2003;160:1147–56.
27. Albert PR. Why is depression more prevalent in women?
J Psychiatry Neurosci. 2015;40:219–21.
28. Tu Y-Y, Lai Y-L, Shin S-C, et al. Factors associated with
depressive mood in the elderly residing at the long-term care
facilities. Int J Gerontol. 2012;6:5–10.
29. Taqui AM, Itrat A, Qidwai W, Qadri Z. Depression in the elderly:
does family system play a role? A cross-sectional study.
BMC Psychiatry. 200725;7:57.
30. Jhingan HP, Sagar R, Pandey RM. Prognosis of late-
onset depression in the elderly: a study from India.
Int psychogeriatrics. 2001;13:51–61.
31. Turvey CL, Carney C, Arndt S, et al. Conjugal Loss and
Syndromal Depression in a Sample of Elders Aged 70 Years or
Older. Am J Psychiatry. 1999;156:1596–601.
32. Zisook S, Shuchter SR, Sledge PA, et al. The spectrum
of depressive phenomena after spousal bereavement.
J Clin Psychiatry. 1994;55 Suppl:29–36.
33. Infurna FJ, Luthar SS. The multidimensional nature of resilience
to spousal loss. J Pers Soc Psychol. 2017;112:926–47.
34. Fried EI, Bockting C, Arjadi R, et al. From loss to loneliness: The
relationship between bereavement and depressive symptoms.
J Abnorm Psychol. 2015;124:256–65.
35. Cohen A. Addressing comorbidity between mental disorders
and major noncommunicable diseases. World Health
Organization. 2017. Availabe at: www.euro.who.int/en/
publications/abstracts/addressing-comorbidity-between-
mental-disorders-and-major-noncommunicable-diseases-2017
(accessed 6 April 2019).
36. National Institute of Health and Family Welfare.
National Mental health Programme. 2014. Available
at: www.nihfw.org/NationalHealthProgramme/
NATIONALMENTALHEALTHPROGRAMME.html
(accessed 6 April 2019).