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\def\RunningAuthor{Iniyan Selvamani et al.}
\firstPage{1819}
\articleType{Original Article}
\receivedDate{09 Nov 2020}
\acceptedDate{19 Dec 2020}
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\title{Prevalence of depression, anxiety and stress symptoms and their association with quality of sleep and loneliness in the general population during the COVID-19 pandemic in India}
\author{Lavanya~L,  
            Iniyan~Selvamani\textsuperscript{*},  
            Venkatraman~Natarajan, 
            Raman~K~\\[5pt]{Department of Psychiatry, Saveetha Medical College \& Hospital, Chennai-602105, Tamil Nadu, India}}

\begin{abstract}
The impact of mental health due to coronavirus infection caused by SARS -2 COVID -19 is severe. The spread of the virus has been reported not only in India but also in many countries worldwide. The lockdown amid the recent COVID-19 widespread has brought about a change in the way of life in most people. The self-isolation and social distancing measures may result in individuals becoming more anxious, angry, stressed, disturbed and depressed. The aim of our study is to assess the prevalence of depression, anxiety and stress and their association with quality of sleep and loneliness in the general population during the Covid 19 pandemic. The study design was a cross-sectional study, and information and data were collected through an online questionnaire using Google forms. A total of 726 participants had completed the online questionnaire from which socio-demographic details, Depression, Anxiety \& Stress (DASS 21), Insomnia (ISI) and Loneliness (UCLA) were assessed. The overall prevalence rate of depression, anxiety, stress, insomnia and loneliness was 27\%, 24.9\%, 12.1, 16.9\% and 8.8\%, respectively. Age, education, occupation and living status had a strong association with depression. Concerning anxiety, age, marital status, living status and past history of medical illness were positively correlated. Stress had a strong association with education. Insomnia was significantly associated with depression, anxiety, stress and loneliness. Anxiety, stress and insomnia had a strong association with loneliness. This study shows that the psychological impact of the COVID-19 pandemic in the general population is very high. Since loneliness and insomnia have been shown to be associated with psychological symptoms, screening for and addressing them can help in reducing the psychological impact of COVID-19. 
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}Depression,\newline Anxiety,\newline Stress,\newline Insomnia,\newline Loneliness,\newline Covid 19,\newline Indian Population
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Iniyan~Selvamani~\\ Phone:\ 9962133994~\\  Email:\ iniyanmbbs@gmail.com
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\section{Introduction}
The novel coronavirus SARS 2 (COVID-19) created a pandemic situation, wherein initially, a small number of atypical cases of pneumonia were reported in December 2019, and the causative virus CoV-2 were similar with SARS-CoV from the 2003 SARS outbreak. On February 12, 2020, the World Health Organization officially named the disease caused by the novel coronavirus as coronavirus disease 2019 (COVID-19). On March 11, 2020, the WHO announced the outbreak as a worldwide pandemic which has created a lot of threat to human lives both physically and mentally. 

India is the second most populated nation in the world, with a population of 1.3 billion individuals spread over different states having vast financial, social and health imbalances, which posed an extraordinary challenge in this period of the COVID-19 pandemic. India reported its first case on January 30, 2020 \unskip~\citep{1008931:21450073}. The common symptoms include fever, cough, and myalgia, with diarrhoea, with or without the subsequent development of dyspnea and transmission of Covid 19 infections occurred through infected secretions, droplets and direct contact. To reduce the spread of COVID-19, the Indian Government announced a complete lockdown for 21 days from March 25, 2020. The lockdown was further extended, and many other restrictions were put in place to curtail disease spread. Many aspects of this disease prevention, including social distancing, decreased means of travel, closure of workplace and educational institutions, resulting in individuals being separated from family, friends, colleagues or co-students. These have the potential to cause loneliness, anxiety, and depression. Many previous studies during outbreaks or epidemics have reported a high prevalence of psychiatric symptoms in the general population \unskip~\citep{1008931:21450088,1008931:21450082}. Even during the current pandemic, a few studies have reported the psychological impact of COVID-19 among the general population \unskip~\citep{1008931:21450085,1008931:21450080} and among healthcare workers \unskip~\citep{1008931:21450528,1008931:21450067,1008931:21450089}. 

Some studies have attempted to analyse the correlates of psychological symptoms like depression and anxiety during the COVID-19 pandemic. In a study by Smith et al., it was concluded that female sex, student status, chronic physical illness, and low socioeconomic status were altogether related to a significant psychological impact and higher levels of stress, anxiety, and loneliness \unskip~\citep{1008931:21450083}. Extensive utilisation of social media by youth and grown-ups between 18 and 35 years of age is connected with a raised tendency to create decreased interaction and disturbance of day to day activities. The COVID-19 situation and the lockdown also resulted in altered work pattern and the closure of educational institutions. In such a case, people are also likely to have varying sleep pattern. A few studies have looked for the quality of sleep and the prevalence of insomnia during the COVID-19 pandemic \unskip~\citep{1008931:21450079,1008931:21450066,1008931:21450071}. They have reported a high prevalence of sleep problems in the general population during the COVID-19 pandemic. Many factors were attributed to the increase in sleep problems, including increased screen time, altered work timings, altered working habits like working from home and closure of workplaces and educational institutions. Hence we conducted this study to find the prevalence of depression, anxiety and stress symptoms and their association with loneliness and insomnia in the general population during the COVID-19 pandemic.  
    
\section{Materials and Methods}
\textbf{Study design and procedure}

In this study, the design was a cross-sectional epidemiological study. We collected data through an online survey questionnaire, mainly targeting the general population in India. The survey was conducted by distributing forms through Google link to known friends and passing it on to their groups through snowball sampling technique within India. The study was done after getting approval from the ethical committee of the institution. The responses were collected for 3 months, from April to June 2020. Out of 740 participants, 726 had completed their forms; hence final sample size in this study was 726. All participants aged between 18 to 65years of age were included after obtaining informed consent. They were instructed to withdraw at any time if they felt any discomfort and we have informed the purpose of the study to all participants through the same form.

\textbf{Measures }

Socio-demographic measures included age, sex, address, education, occupation, marital status, family status, living status, student status, past history of medical illness and past history of psychiatric illness.

\textbf{DASS-21}

Psychological status was measured using the scale - DASS 21. The DASS-21 is a 21-item validated tool that has been extensively used to measure psychiatric symptoms of depression, anxiety and stress \unskip~\citep{1008931:21450075}. DASS-21 has also been used to assess the psychological impact of COVID-19 in previous studies \unskip~\citep{1008931:21450078}. It contains 3 scales, each containing 7 items which are further divided into subscales having the same content. The scale contains 4 options, namely 0,1,2,3. 0 meant that "it did not apply to me at all", whereas 3 meant "applied to me very much or most of the time ". Based on which option suited them over the past week, the participant had to choose one of the four options. The sum of the scores was calculated separately for depression, stress and anxiety and then multiplied by 2 to determine the final score. For depression, a score of 0-9 was considered normal, 10-13 mild, 14-20 moderate, 21-27 severe and 28+ was extremely severe. For anxiety, a score of 0-7 was taken to be normal,8-9 mild,10-14 moderate,15-19 severe, and 20+ was extremely severe. For stress, a score of 0-14 was considered normal,15-18 mild,19-25 moderate,26-33 severe and 34+ extremely severe. In line with previous studies, we took only moderate and above scoring to represent each of the evaluated symptoms of depression, anxiety and stress \unskip~\citep{1008931:21450070,1008931:21450087}. Mild scoring was ignored and was not taken to represent depression, anxiety or stress symptoms. 

\textbf{Insomnia Severity Index}

The quality of sleep was assessed using the Insomnia severity index scale. The Insomnia Severity Index (ISI) is a brief instrument that is designed to assess the severity of insomnia. It is used as a metric of treatment response in clinical research. Its psychometric properties and its validity has been previously established \unskip~\citep{1008931:21450072,1008931:21450064}. 

In the scale, 7 questions are asked, which are related to: difficulty falling asleep, difficulty staying asleep, problem waking up too early, satisfaction with sleep pattern, distress about sleep, noticeability of sleep problems by others and interference of sleep difficulties with daytime functioning. A 5-point Likert scale is used to rate each item (e.g., 0 = no problem; 4 = very severe problem), yielding a total score ranging from 0 to 28. The total score is interpreted as follows Categories,

0{\textendash}7 = No clinically significant insomnia

8{\textendash}14 = Sub-threshold insomnia

15{\textendash}21 = Clinical insomnia (moderate severity) 

22{\textendash}28 = Clinical insomnia (severe). (Charles M Martin). 

\textbf{UCLA Loneliness Scale}

For loneliness measurement, the UCLA loneliness scale was used. The validity and reliability of the scale and its application in the Indian context has been established in previous studies \unskip~\citep{1008931:21450076,1008931:21450069}. It is a 20-item scale designed to measure one's subjective feelings of loneliness as well as feelings of social isolation. Participants rate each item as either O~(``I often feel this way''), S (``I sometimes feel this way''), R (``I rarely feel this way''), N (``I never feel this way''). Scoring: Make all O's =3, all S's =2, all R's =1, and all N's =0. 

\textbf{Statistical analysis}

Data was analysed using SPSS statistics, and we ran descriptive analysis and frequency distribution for all information. The association between variables was measured using the Chi-square test. P value \textless\ 0.05 was considered as significant value.
    
\section{Results}
In the total sample of 726, 274 participants belonged to 18 -35 years, 286 were aged 36-50years, 166 were in the age group of 51-65 years. The majority of the participants were females (385). In educational status, most were school going students (424). 559 were unmarried, and more participants were from a semi-urban background (285). 515 had no past history of medical illness, and 681 were not affected by any previous psychiatric illness. This study showed the overall prevalence of depression 27\% (196), anxiety 24.9\% (181), stress 12.1 \% (88), Insomnia 16.9\% (123), and Loneliness 8.8\% (64) (Table~\ref{tw-d59df4ac83d4}) \& (Figure~\ref{f-3018cb4766d4}).


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\caption{\boldmath {Prevalence of Depression, Anxiety, Stress, Insomnia and Loneliness}}
\label{f-3018cb4766d4}
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\begin{table*}[!htbp]
\caption{\boldmath {Prevalence of Depression, Anxiety, Stress, Insomnia and Loneliness} }
\label{tw-d59df4ac83d4}
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\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Parameter & \cAlignHack Present (N) & \cAlignHack Percentage & \cAlignHack Absent (N) & \cAlignHack Percentage\\
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\cAlignHack Depression (Mod+Severe+Ext) &
  \cAlignHack 196 &
  \cAlignHack 27 &
  \cAlignHack 530 &
  \cAlignHack 73\\
 &
   &
   &
   &
  \\
\cAlignHack Anxiety (Mod+Severe+Ext) &
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 &
   &
   &
   &
  \\
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  \cAlignHack 87.9\\
 &
   &
   &
   &
  \\
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 &
   &
   &
   &
  \\
\cAlignHack Loneliness (O \& S) &
  \cAlignHack 64 &
  \cAlignHack 8.8 &
  \cAlignHack 662 &
  \cAlignHack 91.2\\
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\begin{table*}[!htbp]
\caption{\boldmath {Severity of Depression, Anxiety, Stress, Insomnia and Loneliness} }
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\textbf{Depression} &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Normal  &
  \cAlignHack 336 &
  \cAlignHack 46.3\\
\cAlignHack Mild  &
  \cAlignHack 194 &
  \cAlignHack 26.7\\
\cAlignHack Moderate  &
  \cAlignHack 104 &
  \cAlignHack 14.3\\
\cAlignHack Severe  &
  \cAlignHack 69 &
  \cAlignHack 9.5\\
\cAlignHack Extreme &
  \cAlignHack 23 &
  \cAlignHack 3.1\\
\textbf{Anxiety } &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Normal  &
  \cAlignHack 402 &
  \cAlignHack 55.4\\
\cAlignHack Mild  &
  \cAlignHack 143 &
  \cAlignHack 19.7\\
\cAlignHack Moderate  &
  \cAlignHack 86 &
  \cAlignHack 11.9\\
\cAlignHack Severe  &
  \cAlignHack 63 &
  \cAlignHack 8.3\\
\cAlignHack Extreme &
  \cAlignHack 32 &
  \cAlignHack 4.4\\
\textbf{Stress} &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Normal  &
  \cAlignHack 471 &
  \cAlignHack 64.9\\
\cAlignHack Mild  &
  \cAlignHack 167 &
  \cAlignHack 23.0\\
\cAlignHack Moderate  &
  \cAlignHack 42 &
  \cAlignHack 5.8\\
\cAlignHack Severe  &
  \cAlignHack 35 &
  \cAlignHack 4.8\\
\cAlignHack Extreme &
  \cAlignHack 11 &
  \cAlignHack 1.5\\
\textbf{Insomnia} &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack  No  &
  \cAlignHack 603 &
  \cAlignHack 83.1\\
\cAlignHack Subthreshold &
  \cAlignHack 61 &
  \cAlignHack 8.4\\
\cAlignHack Clinical MOD &
  \cAlignHack 49 &
  \cAlignHack 6.7\\
\cAlignHack Severe &
  \cAlignHack 13 &
  \cAlignHack 1.8\\
\textbf{Loneliness} &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack O~&
  \cAlignHack 9 &
  \cAlignHack 1.2\\
\cAlignHack S &
  \cAlignHack 55 &
  \cAlignHack 7.6\\
\cAlignHack R &
  \cAlignHack 86 &
  \cAlignHack 11.8\\
\cAlignHack N &
  \cAlignHack 576 &
  \cAlignHack 79.3\\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Socio-demographic variables and their association with depression} }
\label{tw-db85eba50ed0}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.14285714285714285\linewidth-2\tabcolsep}p{\dimexpr.15115714285714285\linewidth-2\tabcolsep}p{\dimexpr.1345571428571429\linewidth-2\tabcolsep}p{\dimexpr.15942857142857148\linewidth-2\tabcolsep}p{\dimexpr.15355714285714292\linewidth-2\tabcolsep}p{\dimexpr.12380000000000008\linewidth-2\tabcolsep}p{\dimexpr.13464285714285719\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Variable & \multicolumn{4}{p{\dimexpr(.5987000000000002\linewidth-2\tabcolsep)}}{\cAlignHack Depression} & \cAlignHack  & \cAlignHack P-value\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack Present N=196 & \cAlignHack \% & \cAlignHack Absent N=530 & \cAlignHack \% & \cAlignHack Total N=726 & \\
\tblmidrule 
\textbf{Age group} &
  \cAlignHack  &
  \cAlignHack  &
   &
   &
   &
  \\
\cAlignHack 18-35 years &
  \cAlignHack 104 &
  \cAlignHack 37.96 &
  \cAlignHack 170 &
  \cAlignHack 62.04 &
  \cAlignHack 274 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack 36-50 years &
  \cAlignHack 52 &
  \cAlignHack 18.18 &
  \cAlignHack 234 &
  \cAlignHack 81.82 &
  \cAlignHack 286 &
  \cAlignHack \\
\cAlignHack 51-65 years &
  \cAlignHack 40 &
  \cAlignHack 24.10 &
  \cAlignHack 126 &
  \cAlignHack 75.90 &
  \cAlignHack 166 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Sex} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack  Male &
  \cAlignHack 77 &
  \cAlignHack 22.58 &
  \cAlignHack 264 &
  \cAlignHack 77.42 &
  \cAlignHack 341 &
  \cAlignHack 0.0116\\
\cAlignHack  Female  &
  \cAlignHack 119 &
  \cAlignHack 30.91 &
  \cAlignHack 266 &
  \cAlignHack 69.09 &
  \cAlignHack 385 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Address } &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Rural  &
  \cAlignHack 65 &
  \cAlignHack 27.43 &
  \cAlignHack 172 &
  \cAlignHack 72.57 &
  \cAlignHack 237 &
  \cAlignHack 0.5341\\
\cAlignHack Semiurban  &
  \cAlignHack 71 &
  \cAlignHack 24.91 &
  \cAlignHack 214 &
  \cAlignHack 75.09 &
  \cAlignHack 285 &
  \cAlignHack \\
\cAlignHack Urban  &
  \cAlignHack 60 &
  \cAlignHack 29.41 &
  \cAlignHack 144 &
  \cAlignHack 70.59 &
  \cAlignHack 204 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Education} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack School  &
  \cAlignHack 162 &
  \cAlignHack 38.21 &
  \cAlignHack 262 &
  \cAlignHack 61.79 &
  \cAlignHack 424  &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Diploma  &
  \cAlignHack 15 &
  \cAlignHack 16.48 &
  \cAlignHack 76 &
  \cAlignHack 83.52 &
  \cAlignHack 91 &
  \cAlignHack \\
\cAlignHack UG &
  \cAlignHack 16 &
  \cAlignHack 11.85 &
  \cAlignHack 119 &
  \cAlignHack 88.15 &
  \cAlignHack 135 &
  \cAlignHack \\
\cAlignHack PG &
  \cAlignHack 3 &
  \cAlignHack 3.95 &
  \cAlignHack 73 &
  \cAlignHack 96.05 &
  \cAlignHack 76 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Occupation} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Employed &
  \cAlignHack 75 &
  \cAlignHack 21.13 &
  \cAlignHack 280 &
  \cAlignHack 78.87 &
  \cAlignHack 355 &
  \cAlignHack 0.0005\\
\cAlignHack Unemployed  &
  \cAlignHack 121 &
  \cAlignHack 32.61 &
  \cAlignHack 250 &
  \cAlignHack 67.39 &
  \cAlignHack 371 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Marital} &
  \cAlignHack  &
  \cAlignHack  &
   &
   &
   &
  \\
\cAlignHack Unmarried &
  \cAlignHack 31 &
  \cAlignHack 20.53 &
  \cAlignHack 120 &
  \cAlignHack 79.47 &
  \cAlignHack 559 &
  \cAlignHack 0.0442\\
\cAlignHack Married  &
  \cAlignHack 163 &
  \cAlignHack 29.16 &
  \cAlignHack 396 &
  \cAlignHack 70.84 &
  \cAlignHack 151 &
  \cAlignHack \\
\cAlignHack Divorced  &
  \cAlignHack 2 &
  \cAlignHack 12.50 &
  \cAlignHack 14 &
  \cAlignHack 87.50 &
  \cAlignHack 16 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Family type} &
  \cAlignHack  &
  \cAlignHack  &
   &
   &
   &
  \\
\cAlignHack Nuclear  &
  \cAlignHack 159 &
  \cAlignHack 25.60 &
  \cAlignHack 462 &
  \cAlignHack 74.40 &
  \cAlignHack 621 &
  \cAlignHack 0.0397\\
\cAlignHack Joint  &
  \cAlignHack 37 &
  \cAlignHack 35.24 &
  \cAlignHack 68 &
  \cAlignHack 64.76 &
  \cAlignHack 105 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{2}{p{\dimexpr(.29401428571428568\linewidth-2\tabcolsep)}}{\textbf{Living alone}} &
  \cAlignHack  &
   &
   &
   &
  \\
\cAlignHack Yes &
  \cAlignHack 66 &
  \cAlignHack 58.93 &
  \cAlignHack 46 &
  \cAlignHack 41.07 &
  \cAlignHack 112 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack No &
  \cAlignHack 130 &
  \cAlignHack 21.17 &
  \cAlignHack 484 &
  \cAlignHack 78.83 &
  \cAlignHack 614 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{3}{p{\dimexpr(.4285714285714286\linewidth-2\tabcolsep)}}{\textbf{Past history of medical illness}} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Yes &
  \cAlignHack 72 &
  \cAlignHack 34.12 &
  \cAlignHack 139 &
  \cAlignHack 65.88 &
  \cAlignHack 211 &
  \cAlignHack 0.0056\\
\cAlignHack No &
  \cAlignHack 124 &
  \cAlignHack 24.08 &
  \cAlignHack 391 &
  \cAlignHack 75.92 &
  \cAlignHack 515 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{2}{p{\dimexpr(.29401428571428568\linewidth-2\tabcolsep)}}{\textbf{Past history of psy illness}} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Yes &
  \cAlignHack 17 &
  \cAlignHack 37.78 &
  \cAlignHack 28 &
  \cAlignHack 62.22 &
  \cAlignHack 45 &
  \cAlignHack 0.0925\\
\cAlignHack No &
  \cAlignHack 179 &
  \cAlignHack 26.28 &
  \cAlignHack 502 &
  \cAlignHack 73.72 &
  \cAlignHack 681 &
  \cAlignHack \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Socio-demographic variables and their association with anxiety} }
\label{tw-7001d037e6d9}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.204\linewidth-2\tabcolsep}p{\dimexpr.14599999999999998\linewidth-2\tabcolsep}p{\dimexpr.1495\linewidth-2\tabcolsep}p{\dimexpr.11270000000000003\linewidth-2\tabcolsep}p{\dimexpr.12459999999999999\linewidth-2\tabcolsep}p{\dimexpr.14\linewidth-2\tabcolsep}p{\dimexpr.1232\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Variable & \multicolumn{4}{p{\dimexpr(.5328\linewidth-2\tabcolsep)}}{\cAlignHack Anxiety} & \cAlignHack  & \cAlignHack P-value\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack Present N=181 & \cAlignHack \% & \cAlignHack Absent N=545 & \cAlignHack \% & \cAlignHack Total & \cAlignHack \\
\tblmidrule 
\textbf{Age group} &
   &
   &
   &
   &
   &
  \\
\cAlignHack 18-35 years &
  \cAlignHack 98 &
  \cAlignHack 35.77 &
  \cAlignHack 176 &
  \cAlignHack 64.23 &
  \cAlignHack 274 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack 36-50 years &
  \cAlignHack 51 &
  \cAlignHack 17.83 &
  \cAlignHack 235 &
  \cAlignHack 82.17 &
  \cAlignHack 286 &
  \cAlignHack \\
\cAlignHack 51-65 years &
  \cAlignHack 32 &
  \cAlignHack 19.28 &
  \cAlignHack 134 &
  \cAlignHack 80.72 &
  \cAlignHack 166 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Sex} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack  Male &
  \cAlignHack 83 &
  \cAlignHack 24.34 &
  \cAlignHack 258 &
  \cAlignHack 75.66 &
  \cAlignHack 341 &
  \cAlignHack 0.7290\\
\cAlignHack  Female  &
  \cAlignHack 98 &
  \cAlignHack 25.45 &
  \cAlignHack 287 &
  \cAlignHack 74.55 &
  \cAlignHack 385 &
  \cAlignHack \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Address } &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Rural  &
  \cAlignHack 59 &
  \cAlignHack 24.89 &
  \cAlignHack 178 &
  \cAlignHack 75.11 &
  \cAlignHack 237 &
  \cAlignHack 0.9728\\
\cAlignHack Semiurban  &
  \cAlignHack 70 &
  \cAlignHack 24.56 &
  \cAlignHack 215 &
  \cAlignHack 75.44 &
  \cAlignHack 285 &
  \\
\cAlignHack Urban  &
  \cAlignHack 52 &
  \cAlignHack 25.49 &
  \cAlignHack 152 &
  \cAlignHack 74.51 &
  \cAlignHack 204 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Education} &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack  &
   &
  \\
\cAlignHack School  &
  \cAlignHack 119 &
  \cAlignHack 28.07 &
  \cAlignHack 305 &
  \cAlignHack 71.93 &
  \cAlignHack 424 &
  \cAlignHack 0.0821\\
\cAlignHack Diploma  &
  \cAlignHack 19 &
  \cAlignHack 20.88 &
  \cAlignHack 72 &
  \cAlignHack 79.12 &
  \cAlignHack 91 &
  \\
\cAlignHack UG &
  \cAlignHack 31 &
  \cAlignHack 22.96 &
  \cAlignHack 104 &
  \cAlignHack 77.04 &
  \cAlignHack 135 &
  \\
\cAlignHack PG &
  \cAlignHack 12 &
  \cAlignHack 15.79 &
  \cAlignHack 64 &
  \cAlignHack 84.21 &
  \cAlignHack 76 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Occupation } &
   &
   &
   &
   &
  \cAlignHack  &
  \\
\cAlignHack Employed &
  \cAlignHack 85 &
  \cAlignHack 23.94 &
  \cAlignHack 270 &
  \cAlignHack 76.06 &
  \cAlignHack 355 &
  \cAlignHack 0.5474\\
\cAlignHack Unemployed  &
  \cAlignHack 96 &
  \cAlignHack 25.88 &
  \cAlignHack 275 &
  \cAlignHack 74.12 &
  \cAlignHack 371 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Marital} &
   &
   &
   &
   &
   &
  \\
\cAlignHack Unmarried &
  \cAlignHack 82 &
  \cAlignHack 54.30 &
  \cAlignHack 69 &
  \cAlignHack 45.70 &
  \cAlignHack 559  &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Married  &
  \cAlignHack 96 &
  \cAlignHack 17.17 &
  \cAlignHack 463 &
  \cAlignHack 82.83 &
  \cAlignHack 151 &
  \\
\cAlignHack Divorced  &
  \cAlignHack 3 &
  \cAlignHack 18.75 &
  \cAlignHack 13 &
  \cAlignHack 81.25 &
  \cAlignHack 16 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Family type} &
   &
   &
   &
   &
   &
  \\
\cAlignHack Nuclear  &
  \cAlignHack 160 &
  \cAlignHack 25.76 &
  \cAlignHack 461 &
  \cAlignHack 74.24 &
  \cAlignHack 621 &
  \cAlignHack 0.2066\\
\cAlignHack Joint  &
  \cAlignHack 21 &
  \cAlignHack 20.00 &
  \cAlignHack 84 &
  \cAlignHack 80.00 &
  \cAlignHack 105 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Living alone} &
   &
   &
   &
   &
   &
  \\
\cAlignHack Yes  &
  \cAlignHack 51 &
  \cAlignHack 45.54 &
  \cAlignHack 61 &
  \cAlignHack 54.46 &
  \cAlignHack 112 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack No &
  \cAlignHack 130 &
  \cAlignHack 21.17 &
  \cAlignHack 484 &
  \cAlignHack 78.83 &
  \cAlignHack 614 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{2}{p{\dimexpr(.35\linewidth-2\tabcolsep)}}{\textbf{Past history of medical illness}} &
   &
   &
   &
   &
  \\
\cAlignHack Yes  &
  \cAlignHack 79 &
  \cAlignHack 37.44 &
  \cAlignHack 132 &
  \cAlignHack 62.56 &
  \cAlignHack 211 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack No  &
  \cAlignHack 102 &
  \cAlignHack 19.81 &
  \cAlignHack 413 &
  \cAlignHack 80.19 &
  \cAlignHack 515 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{2}{p{\dimexpr(.35\linewidth-2\tabcolsep)}}{\textbf{Past history of psy illness}} &
   &
   &
   &
   &
  \\
\cAlignHack Yes  &
  \cAlignHack 13 &
  \cAlignHack 28.89 &
  \cAlignHack 32 &
  \cAlignHack 71.11 &
  \cAlignHack 45 &
  \cAlignHack 0.5263\\
\cAlignHack No  &
  \cAlignHack 168 &
  \cAlignHack 24.67 &
  \cAlignHack 513 &
  \cAlignHack 75.33 &
  \cAlignHack 681 &
  \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Sociodemographic details and their association with stress} }
\label{tw-3b9779594c66}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.17450000000000003\linewidth-2\tabcolsep}p{\dimexpr.14700000000000001\linewidth-2\tabcolsep}p{\dimexpr.12219999999999997\linewidth-2\tabcolsep}p{\dimexpr.1542\linewidth-2\tabcolsep}p{\dimexpr.1306\linewidth-2\tabcolsep}p{\dimexpr.1435\linewidth-2\tabcolsep}p{\dimexpr.128\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Variable & \multicolumn{4}{p{\dimexpr(.554\linewidth-2\tabcolsep)}}{\cAlignHack Stress} & \cAlignHack  & \cAlignHack P-value\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack Present N=88 & \cAlignHack \% & \cAlignHack Absent N=638 & \cAlignHack \%  & \cAlignHack Total & \cAlignHack \\
\tblmidrule 
\textbf{Age group} &
   &
   &
   &
   &
   &
  \\
\cAlignHack 18-35 years &
  \cAlignHack 30 &
  \cAlignHack 10.95 &
  \cAlignHack 244 &
  \cAlignHack 89.05 &
  \cAlignHack 274 &
  \cAlignHack 0.7498\\
\cAlignHack 36-50 years &
  \cAlignHack 37 &
  \cAlignHack 12.94 &
  \cAlignHack 249 &
  \cAlignHack 87.06 &
  \cAlignHack 286 &
  \\
\cAlignHack 51-65 years &
  \cAlignHack 21 &
  \cAlignHack 12.65 &
  \cAlignHack 145 &
  \cAlignHack 87.35 &
  \cAlignHack 166 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Sex} &
   &
   &
   &
  \cAlignHack  &
  \cAlignHack  &
  \\
\cAlignHack  Male &
  \cAlignHack 39 &
  \cAlignHack 11.44 &
  \cAlignHack 302 &
  \cAlignHack 88.56 &
  \cAlignHack 341 &
  \cAlignHack 0.5949\\
\cAlignHack  Female  &
  \cAlignHack 49 &
  \cAlignHack 12.73 &
  \cAlignHack 336 &
  \cAlignHack 87.27 &
  \cAlignHack 385 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Address } &
   &
   &
   &
  \cAlignHack  &
  \cAlignHack  &
  \\
\cAlignHack Rural  &
  \cAlignHack 31 &
  \cAlignHack 13.08 &
  \cAlignHack 206 &
  \cAlignHack 86.92 &
  \cAlignHack 237 &
  \cAlignHack 0.8387\\
\cAlignHack Semiurban  &
  \cAlignHack 34 &
  \cAlignHack 11.93 &
  \cAlignHack 251 &
  \cAlignHack 88.07 &
  \cAlignHack 285 &
  \\
\cAlignHack Urban  &
  \cAlignHack 23 &
  \cAlignHack 11.27 &
  \cAlignHack 181 &
  \cAlignHack 88.73 &
  \cAlignHack 204 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Education} &
   &
   &
   &
   &
   &
  \\
\cAlignHack School  &
  \cAlignHack 79 &
  \cAlignHack 18.63 &
  \cAlignHack 345 &
  \cAlignHack 81.37 &
  \cAlignHack 424 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Diploma  &
  \cAlignHack 2 &
  \cAlignHack 2.20 &
  \cAlignHack 89 &
  \cAlignHack 97.80 &
  \cAlignHack 91 &
  \\
\cAlignHack UG &
  \cAlignHack 5 &
  \cAlignHack 3.70 &
  \cAlignHack 130 &
  \cAlignHack 96.30 &
  \cAlignHack 135 &
  \\
\cAlignHack PG &
  \cAlignHack 2 &
  \cAlignHack 2.63 &
  \cAlignHack 74 &
  \cAlignHack 97.37 &
  \cAlignHack 76 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Occupation } &
   &
   &
   &
   &
   &
  \\
\cAlignHack Employed &
  \cAlignHack 37 &
  \cAlignHack 10.42 &
  \cAlignHack 318 &
  \cAlignHack 89.58 &
  \cAlignHack 355 &
  \cAlignHack 0.1701\\
\cAlignHack Unemployed  &
  \cAlignHack 51 &
  \cAlignHack 13.75 &
  \cAlignHack 320 &
  \cAlignHack 86.25 &
  \cAlignHack 371 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Marital} &
   &
   &
   &
   &
   &
  \\
\cAlignHack Unmarried &
  \cAlignHack 27 &
  \cAlignHack 17.88 &
  \cAlignHack 124 &
  \cAlignHack 82.12 &
  \cAlignHack 559 &
  \cAlignHack 0.4435\\
\cAlignHack Married  &
  \cAlignHack 60 &
  \cAlignHack 10.73 &
  \cAlignHack 499 &
  \cAlignHack 89.27 &
  \cAlignHack 151 &
  \\
\cAlignHack Divorced  &
  \cAlignHack 1 &
  \cAlignHack 6.25 &
  \cAlignHack 15 &
  \cAlignHack 93.75 &
  \cAlignHack 16 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Family type} &
   &
   &
   &
   &
   &
  \\
\cAlignHack Nuclear  &
  \cAlignHack 72 &
  \cAlignHack 11.59 &
  \cAlignHack 549 &
  \cAlignHack 88.41 &
  \cAlignHack 621 &
  \cAlignHack 0.2900\\
\cAlignHack Joint  &
  \cAlignHack 16 &
  \cAlignHack 15.24 &
  \cAlignHack 89 &
  \cAlignHack 84.76 &
  \cAlignHack 105 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\textbf{Living alone} &
   &
   &
   &
   &
   &
  \\
\cAlignHack Yes  &
  \cAlignHack 15 &
  \cAlignHack 13.39 &
  \cAlignHack 97 &
  \cAlignHack 86.61 &
  \cAlignHack 112 &
  \cAlignHack 0.6538\\
\cAlignHack No &
  \cAlignHack 73 &
  \cAlignHack 11.89 &
  \cAlignHack 541 &
  \cAlignHack 88.11 &
  \cAlignHack 614 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{3}{p{\dimexpr(.44370000000000005\linewidth-2\tabcolsep)}}{\textbf{Past history of medical illness}} &
   &
   &
   &
  \\
\cAlignHack Yes  &
  \cAlignHack 21 &
  \cAlignHack 9.95 &
  \cAlignHack 190 &
  \cAlignHack 90.05 &
  \cAlignHack 211 &
  \cAlignHack 0.2518\\
\cAlignHack No  &
  \cAlignHack 67 &
  \cAlignHack 13.01 &
  \cAlignHack 448 &
  \cAlignHack 86.99 &
  \cAlignHack 515 &
  \\
 &
   &
   &
   &
   &
   &
  \\
\multicolumn{2}{p{\dimexpr(.32150000000000006\linewidth-2\tabcolsep)}}{\textbf{Past history of psy illness}} &
   &
   &
   &
   &
  \\
\cAlignHack Yes  &
  \cAlignHack 3 &
  \cAlignHack 6.67 &
  \cAlignHack 42 &
  \cAlignHack 93.33 &
  \cAlignHack 45 &
  \cAlignHack 0.2470\\
\cAlignHack No  &
  \cAlignHack 85 &
  \cAlignHack 12.48 &
  \cAlignHack 596 &
  \cAlignHack 87.52 &
  \cAlignHack 681 &
  \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Association of insomnia with Depression, Anxiety and Stress} }
\label{tw-12ee23bf50ee}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.1304\linewidth-2\tabcolsep}p{\dimexpr.13030000000000001\linewidth-2\tabcolsep}p{\dimexpr.1107\linewidth-2\tabcolsep}p{\dimexpr.1552\linewidth-2\tabcolsep}p{\dimexpr.1232\linewidth-2\tabcolsep}p{\dimexpr.1242\linewidth-2\tabcolsep}p{\dimexpr.10959999999999999\linewidth-2\tabcolsep}p{\dimexpr.1164\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Variable & \multicolumn{4}{p{\dimexpr(.51940000000000005\linewidth-2\tabcolsep)}}{\cAlignHack Insomnia} & \cAlignHack  & \cAlignHack  & \cAlignHack P-value\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack Present N=123 & \cAlignHack \% & \cAlignHack Absent N=603 & \cAlignHack \%  & \cAlignHack Total & \cAlignHack \% & \cAlignHack \\
\tblmidrule 
\textbf{Depression} &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Present  &
  \cAlignHack 77 &
  \cAlignHack 62.6 &
  \cAlignHack 119 &
  \cAlignHack 19.7 &
  \cAlignHack 196 &
  \cAlignHack 27.0 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 46 &
  \cAlignHack 37.4 &
  \cAlignHack 484 &
  \cAlignHack 80.3 &
  \cAlignHack 530 &
  \cAlignHack 73.0 &
  \cAlignHack \\
\textbf{Anxiety} &
   &
   &
   &
   &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Present  &
  \cAlignHack 80 &
  \cAlignHack 65.0 &
  \cAlignHack 101 &
  \cAlignHack 16.7 &
  \cAlignHack 181 &
  \cAlignHack 24.9 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 43 &
  \cAlignHack 35.0 &
  \cAlignHack 502 &
  \cAlignHack 83.3 &
  \cAlignHack 545 &
  \cAlignHack 75.1 &
  \cAlignHack \\
\textbf{Stress} &
   &
   &
   &
   &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Present  &
  \cAlignHack 35 &
  \cAlignHack 28.5 &
  \cAlignHack 53 &
  \cAlignHack 8.8 &
  \cAlignHack 88 &
  \cAlignHack 12.1 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 88 &
  \cAlignHack 71.5 &
  \cAlignHack 550 &
  \cAlignHack 91.2 &
  \cAlignHack 638 &
  \cAlignHack 87.9 &
  \cAlignHack \\
\textbf{Loneliness } &
   &
   &
   &
   &
  \cAlignHack  &
  \cAlignHack  &
  \cAlignHack \\
\cAlignHack Present  &
  \cAlignHack 31 &
  \cAlignHack 25.2 &
  \cAlignHack 33 &
  \cAlignHack 5.5 &
  \cAlignHack 64 &
  \cAlignHack 8.8 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 92 &
  \cAlignHack 74.8 &
  \cAlignHack 570 &
  \cAlignHack 94.5 &
  \cAlignHack 662 &
  \cAlignHack 91.2 &
  \cAlignHack \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Association of Loneliness with Depression, Anxiety, Stress and Insmonia} }
\label{tw-e181ac2809b3}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.1583\linewidth-2\tabcolsep}p{\dimexpr.13459999999999997\linewidth-2\tabcolsep}p{\dimexpr.1179\linewidth-2\tabcolsep}p{\dimexpr.1304\linewidth-2\tabcolsep}p{\dimexpr.1179\linewidth-2\tabcolsep}p{\dimexpr.1241\linewidth-2\tabcolsep}p{\dimexpr.10349999999999998\linewidth-2\tabcolsep}p{\dimexpr.1133\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}\cAlignHack Variable & \multicolumn{4}{p{\dimexpr(.5007999999999999\linewidth-2\tabcolsep)}}{\cAlignHack Loneliness} & \cAlignHack  & \cAlignHack  & \cAlignHack P-value\\
\rowcolor{kwdboxcolor}\cAlignHack  & \cAlignHack Present N=64 & \cAlignHack \% & \cAlignHack Absent N=662 & \cAlignHack \%  & \cAlignHack Total & \cAlignHack \% & \cAlignHack \\
\tblmidrule 
\textbf{Depression} &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Present  &
  \cAlignHack 19 &
  \cAlignHack 29.7 &
  \cAlignHack 177 &
  \cAlignHack 26.7 &
  \cAlignHack 196 &
  \cAlignHack 27.0 &
  \cAlignHack 0.6116\\
\cAlignHack Absent  &
  \cAlignHack 45 &
  \cAlignHack 70.3 &
  \cAlignHack 485 &
  \cAlignHack 73.3 &
  \cAlignHack 530 &
  \cAlignHack 73.0 &
  \\
\textbf{Anxiety } &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Present  &
  \cAlignHack 35 &
  \cAlignHack 54.7 &
  \cAlignHack 146 &
  \cAlignHack 22.1 &
  \cAlignHack 181 &
  \cAlignHack 24.9 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 29 &
  \cAlignHack 45.3 &
  \cAlignHack 516 &
  \cAlignHack 77.9 &
  \cAlignHack 545 &
  \cAlignHack 75.1 &
  \\
\textbf{Stress } &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Present  &
  \cAlignHack 25 &
  \cAlignHack 39.1 &
  \cAlignHack 63 &
  \cAlignHack 9.5 &
  \cAlignHack 88 &
  \cAlignHack 12.1 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 39 &
  \cAlignHack 60.9 &
  \cAlignHack 599 &
  \cAlignHack 90.5 &
  \cAlignHack 638 &
  \cAlignHack 87.9 &
  \\
\textbf{Insomnia} &
   &
   &
   &
   &
   &
   &
  \\
\cAlignHack Present  &
  \cAlignHack 28 &
  \cAlignHack 43.8 &
  \cAlignHack 95 &
  \cAlignHack 14.4 &
  \cAlignHack 123 &
  \cAlignHack 16.9 &
  \cAlignHack {\textless}0.0001\\
\cAlignHack Absent  &
  \cAlignHack 36 &
  \cAlignHack 56.3 &
  \cAlignHack 567 &
  \cAlignHack 85.6 &
  \cAlignHack 603 &
  \cAlignHack 83.1 &
  \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
Using DASS 21, in depression, 14.3\% (104) of participants had moderate, 9.5\% (69) Severe and 3.1\% (23) extreme severe depression. In anxiety, 11.3\% (86), 8.3\% (63), and 4.4\% (32) were found to have moderate, severe and extreme severe anxiety, respectively. Similarly, 5.8\% (42), 4.8\% and 1.5\% (11) of participants had the moderate, severe and extreme type of stress (Table~\ref{tw-8029ceae1cbf}).

\textbf{Socio-demographic variables and their association with depression}

Pearson's chi-square test was used to determine the socio-demographic variables with depression, anxiety, stress, insomnia and loneliness. Younger age group, school going, being unemployed and living alone were associated with more prevalence of depression (Table~\ref{tw-db85eba50ed0}).

\textbf{Socio-demographic variables and their association with anxiety }

Younger age, being unmarried, living alone and a past history of medical illness had a strong association with more prevalence of anxiety (Table~\ref{tw-7001d037e6d9}).

\textbf{Socio-demographic details and their association with stress}

In contrast to depression and anxiety, stress had a strong significant association only with education with more stress found in school-going children (Table~\ref{tw-3b9779594c66}).

\textbf{Association of insomnia with Depression, Anxiety and Stress }

Insomnia had a statistically significant association with depression, anxiety, stress and loneliness (Table~\ref{tw-12ee23bf50ee}).

\textbf{Association of Loneliness with Depression, Anxiety, Stress and Insmonia}

Anxiety, stress and insomnia had a statistically significant association with loneliness. But there was no significant association between depression and loneliness (Table~\ref{tw-e181ac2809b3}).
    
\section{\textbf{DISCUSSION}}
This study was conducted in the Indian adult population during the lockdown period due to the Covid-19 pandemic. The main aim of this study was to determine the prevalence of depression, anxiety and stress and their association with insomnia and loneliness among the study population. 

\textbf{Prevalence of Depression, Anxiety and Stress during the pandemic}

Our study showed a high prevalence of depression, anxiety and stress among the general population during the COVID-19 pandemic. To account for various factors and in line with previous studies, we omitted milder forms of depression, anxiety and stress and took only moderate and above severity to represent the presence of a psychological symptom. Despite that, we found a high prevalence of depression, anxiety and stress. Our study showed that 27\%, 24.9\% 12.1 \% were depressed, anxious and stressed, respectively. Increased prevalence of psychiatric symptoms has been observed during previous epidemics. Taylor et al., in H1N1 SARS outbreak in Australia reported 34\% high psychological distress compared to levels of around 12\% in the general Australian population \unskip~\citep{1008931:21450062}. A study on the Middle East respiratory syndrome (MERS) epidemic by Jeong and colleagues (2016) reported that 7.6\% of 1,656 patients in Korea had anxiety symptoms, and 16.6\% of them were distressed \unskip~\citep{1008931:21450081}. Studies done during the COVID-19 pandemic have also reported a high prevalence of psychiatric morbidity in the general population. In a study by Wang and associates, out of the 1211 members, 53.8\% evaluated the mental effect of the outbreak as direct or serious; 28.8\% reported moderate to severe anxiety symptoms; 16.5\% showed moderate to severe depressive symptoms; 8.1\% reported moderate to severe stress levels \unskip~\citep{1008931:21450063}. Another study in India showed similar results using DASS 21, where 28.8\% reported moderate to severe anxiety symptoms; 16.5\% showed moderate to severe depressive symptoms; 8.1\% reported moderate to severe stress levels \unskip~\citep{1008931:21450074}. A study conducted in China appeared that those who are at the greatest chance for mental health impact are youths, health care professionals, and individuals who spend a part of their time around patients in the pandemics \unskip~\citep{1008931:21450077}. Some previous research found that the prevalence of overall stress was between 8.1\% to over 81.9\%. \unskip~\citep{1008931:21450068,1008931:21450063}.

\textbf{Sleep and Loneliness} \textbf{\space }

In our study, the prevalence of overall insomnia was 16.9\%, in that sub-threshold was 8.4\%, 6.7\% of participants had moderate insomnia, and 1.8\% study group had a severe form of insomnia. In a study by Gupta et al., it was found that compared to the pre lockdown period, there was a shift to a later bedtime and waking time, with a reduction in nighttime sleep and an increase in daytime napping \unskip~\citep{1008931:21450066}. In the study, 23.4\% reported that sleep quality had worsened. In 8.4\%, it had improved, and in others, it had remained similar to the pre lockdown state. In a study, Voitsidis et al. reported that sleep problems were detected in 37.6\% of the participants \unskip~\citep{1008931:21450065}. He also concluded that sleep deprivation inside the Greek people was a function of loneliness, instability, depression, and COVID 19 related stresses with a genuine commitment from two components which were depression and uncertainty. Other components that were said to impact sleep patterns were screen time, which increased after lockdown. Longer time on screen is related to shorter sleep and lesser quality of sleep.  

\textbf{Association with Socio-Demographics}

In this study population, younger age group, school going, being unemployed and living alone were associated with more prevalence of depression. This result was similar to previous research, which showed that people less than 40 years old displayed more psychological impact during the pandemic \unskip~\citep{1008931:21450077}. The study by Smith et al. had also reported younger age group were associated with higher levels of poor mental health \unskip~\citep{1008931:21450083}. Age, marital status, living status and past history of medical illness had a strong association with anxiety. Stress was associated only with education. In a study by {\"{O}}zdin et al., it was found that individuals with previous psychiatric illness, individuals living in urban areas and those with an accompanying chronic disease have more psychological distress \unskip~\citep{1008931:21450086}. 

\textbf{Association of psychological symptoms with Insomnia and Loneliness}

In our study, we found that all the psychological symptoms, including depression, anxiety and stress, had a strong positive association with insomnia. This association can reflect either a causative role of insomnia producing psychological symptoms, or insomnia can also be an easily observable symptom of the psychological impact of COVID-19. Though we cannot establish causation, we can say that evaluation or screening for insomnia would help to identify those with psychiatric disturbances. Also, people may be more forthcoming answering questions related to insomnia as a screening tool rather than answering a screening questionnaire related to psychological symptoms because of the associated stigma. Our study found a positive association between loneliness and the psychological symptoms of anxiety and stress, but there was no statistically significant association between loneliness and depression. This was in contrast to a previous study that showed that loneliness was the leading risk factor for depression \unskip~\citep{1008931:21450084}. 

\textbf{Strengths}

This study offers information on the mental health issues of the Indian population during the ongoing COVID-19 pandemic lockdown. The data suggest that there is an increased prevalence of anxiety and depressive symptoms and psychological distress in the Indian population related to the continuing pandemic.

\textbf{Limitations}

There are a few limitations to this study that should be considered. The study is of cross-sectional design, which has its own set of constraints. Also, selection bias is possible in this study, as an online survey was used to collect the information. Thus the section of the population without access to internet facility has not been included in this study. Therefore the inferences cannot be extrapolated to the entire population. 
    
\section{Conclusion}
In conclusion, our study revealed a high prevalence of psychological symptoms of depression, anxiety and stress in the general population during the COVID-19 pandemic. Also, a high prevalence of insomnia and loneliness was observed. Younger age, being unmarried, school going, being unemployed and living alone were some of the factors associated with more psychological symptoms. Psychological symptoms were also associated with loneliness and insomnia. This study brings out the significant psychological impact of COVID-19 into the light. Developing screening methods with a focus on the established associations in this study can help for early detection and management of psychological symptoms.

\textbf{Funding Support}

The authors declare that they have no funding support for this study.

\textbf{Conflict of Interest}

The authors declare that they have no conflict of interest for this study.
    

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