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\begin{document}


\def\RunningAuthor{Bharath J et al.}
\firstPage{76}
\articleType{Original Article}
\receivedDate{30 Nov 2019}
\acceptedDate{15 Feb 2020}
\revisedDate{12 Feb 2020}
\journalVolume{2020, 11(SPL)}
\journalIssue{2}
\journalDoi{ijrps.v11iSPL2.2117}
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\title{Prevalence of overweight and obesity-associated risk factors amongst medical students in South India}
\author{Tina~J,  
            Yogesh~Mohan\textsuperscript{*},  
            Jayashri~D, 
            Timsi~Jain~\\[5pt]{Department of Community Medicine, Saveetha Medical College Hospital, Chennai -602105, Tamilnadu, India}}

\begin{abstract}
Obesity is defined as an excessive accumulation of body fat to an extent where health is impaired. Obesity among students is progressing towards an epidemic level. The change in lifestyle, lack of physical activity and exercise, improper eating habits and lack of awareness about obesity has become a major problem of college students, especially among medical students. This study was conducted with the objective to estimate the prevalence of overweight \& obesity and associated factors. A cross-sectional study was conducted among medical students of Saveetha Medical College and Hospital (SMCH) with a sample size of 230 and a purposive sampling technique was used. Data was collected using a semi-structured questionnaire. Data were entered in Microsoft Excel and analyzed using relevant statistical tests.  Prevalence of overweight and obesity was 20.4\% and 2.1\%, respectively and factors such as diet pattern and sleep duration are significantly associated with overweight and obesity. Measures such as motivating the students, organizing group exercise activities and making physical activity as part of the curriculum and importance of adequate sleep should be emphasized.
\end{abstract}\def\keywordstitle{Keywords}

\begin{keywords}Body Mass Index,\newline Exercise,\newline Diet,\newline Obesity,\newline Overweight
\end{keywords}
\twocolumn[ \maketitle {\printKwdAbsBox}]
\makeatletter{\raggedright\textsuperscript{*}Corresponding Author\par Name:\ Yogesh~Mohan~\\ Phone:\ +919551270101~\\  Email:\ dr.yogeshmohan@gmail.com
        \par}\vspace*{-11pt}\hrulefill\par{\fontsize{12}{14}\selectfont ISSN: 0975-7538}\par% 
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\section{Introduction}
Obesity is defined as an excessive accumulation of body fat to an extent where health is impaired. Obesity has a broad range of adverse health effects that are independent of adult weight \unskip~\citep{700953:16598926}. According to the Indian Council of Medical Research, the prevalence rate of obesity in India varies from 11.8\% to 31.3\% \unskip~\citep{700953:16598928}.

In Tamil Nadu, the prevalence rate of obesity among all the adults was 52.4\% and females it was ranging from 22.8\% to 34.8\% and in males, it was ranging from 23.4 to 22\% \unskip~\citep{700953:16598934}.

While the majority of the researches done highlight obesity and overweight as problems of the developed countries, recent studies also show that the third world countries are no exception \unskip~\citep{700953:16598936}. Obesity is a risk factor for metabolic syndrome. The other risk factors include increased blood pressure (greater than 130/85 mmHg), high blood sugar levels, excess fat around the waist, high triglyceride levels and low levels of good cholesterol or HDL. 

India is experiencing an epidemiological and nutritional transition with the increasing prevalence of non-communicable diseases (NCDs). The conspicuous transition includes increased consumption of animal protein and fat, decreased cereal intake, the proliferation of fast-food restaurants and reduced physical activity \unskip~\citep{700953:16598925}.  Body Mass Index (BMI) is an indicator of body obesity. 


\begin{table*}[!htbp]
\caption{\boldmath {Socio-demographic details of the study participants (n=230)} }
\label{tw-87d2159c51e3}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.6449\linewidth-2\tabcolsep}p{\dimexpr.18639999999999997\linewidth-2\tabcolsep}p{\dimexpr.1687\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor}Age group of the study participants years & \cAlignHack n & \cAlignHack \%\\
\tblmidrule 
17-20  &
  \cAlignHack 126  &
  \cAlignHack 54.7\% \\
21-24  &
  \cAlignHack 104  &
  \cAlignHack 45.2\% \\
Gender of the study participants &
  \cAlignHack  &
  \cAlignHack \\
Male  &
  \cAlignHack 104  &
  \cAlignHack 45.2\% \\
Female  &
  \cAlignHack 126  &
  \cAlignHack 54.7\% \\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Present place of residence of the study participants }\\
Day scholar/Home  &
  \cAlignHack 139  &
  \cAlignHack 60.4\% \\
Hostel  &
  \cAlignHack 91  &
  \cAlignHack 39.5\% \\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Adequacy of Exercise (WHO recommendation)}\\
Adequate  &
  \cAlignHack 108  &
  \cAlignHack 46.9\% \\
Inadequate  &
  \cAlignHack 122  &
  \cAlignHack 53\% \\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Diet pattern of study participants  }\\
Veg &
  \cAlignHack 80 &
  \cAlignHack 34.7\%\\
Mixed &
  \cAlignHack 150 &
  \cAlignHack 65.2\%\\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Consumption of junk food among study participants  }\\
Yes &
  \cAlignHack 211 &
  \cAlignHack 91.7\%\\
No &
  \cAlignHack 19 &
  \cAlignHack 8.2\%\\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{BMI categories of the study participants  }\\
Underweight(below 18.5) &
  \cAlignHack 9 &
  \cAlignHack 3.9\%\\
Normal(18.5-24.9) &
  \cAlignHack 169 &
  \cAlignHack 73.4\%\\
Overweight(25-29.9) &
  \cAlignHack 47 &
  \cAlignHack 20.4\%\\
Obese(above 30.0) &
  \cAlignHack 5 &
  \cAlignHack 2.1\%\\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{History of smoking among study participants  }\\
Yes &
  \cAlignHack 9 &
  \cAlignHack 3.9\%\\
No &
  \cAlignHack 221 &
  \cAlignHack 96\%\\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Consumption of alcohol among study participants  }\\
Yes &
  \cAlignHack 15 &
  \cAlignHack 6.5\%\\
No &
  \cAlignHack 215 &
  \cAlignHack 93.4\%\\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Approximate duration of sleep among study participants  }\\
{\textless}8 hrs &
  \cAlignHack 164 &
  \cAlignHack 71.3\%\\
{\textgreater}8 hrs &
  \cAlignHack 66 &
  \cAlignHack 28.6\%\\
\multicolumn{3}{p{\dimexpr(1\linewidth-2\tabcolsep)}}{Family history of DM, HTN among study participants  }\\
Yes &
  \cAlignHack 28 &
  \cAlignHack 12.1\%\\
No &
  \cAlignHack 202 &
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\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Univariate Logistic Regression Analysis (n=230)} }
\label{tw-f1847522efe4}
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\tbltoprule \rowcolor{kwdboxcolor} &  & \multicolumn{2}{p{\dimexpr(.26950000000000003\linewidth-2\tabcolsep)}}{\cAlignHack Obesity and Overweight} &  &  & \\
\rowcolor{kwdboxcolor}\cAlignHack Variables & \cAlignHack Category & \cAlignHack No & \cAlignHack Yes & \cAlignHack p-value & \cAlignHack OR & \multicolumn{2}{p{\dimexpr(.17790000000000003\linewidth-2\tabcolsep)}}{\cAlignHack 95\% CI}\\
\tblmidrule 
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  Hostilities &
  \cAlignHack 68 &
  \cAlignHack 24 &
  \cAlignHack 0.304 &
  \cAlignHack 1.387 &
  \cAlignHack 0.743 &
  \cAlignHack 2.586\\
 &
  Day Scholars &
  \cAlignHack 110 &
  \cAlignHack 28 &
  \cAlignHack -- &
  \cAlignHack Ref &
  \cAlignHack  &
  \cAlignHack \\
\multicolumn{1}{p{\dimexpr(.1849\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Sleep}} &
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  \cAlignHack 121 &
  \cAlignHack 43 &
  \cAlignHack 0.043 &
  \cAlignHack 2.251 &
  \multicolumn{1}{p{\dimexpr(.09150000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 1.027}} &
  \multicolumn{1}{p{\dimexpr(.0864\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 4.932}}\\
 &
  {\textgreater} 8 hours &
  \cAlignHack 57 &
  \cAlignHack 9 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\multicolumn{1}{p{\dimexpr(.1849\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Recommended Exercise \mbox{}\protect\newline }} &
  Yes &
  \cAlignHack 86 &
  \cAlignHack 21 &
  \cAlignHack -- &
  \cAlignHack Ref &
  \multicolumn{1}{p{\dimexpr(.09150000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.737}} &
  \multicolumn{1}{p{\dimexpr(.0864\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 2.583}}\\
 &
  No &
  \cAlignHack 92 &
  \cAlignHack 31 &
  \cAlignHack 0.314 &
  \cAlignHack 1.380 &
   &
  \\
\multicolumn{1}{p{\dimexpr(.1849\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Diet}} &
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  \cAlignHack 71 &
  \cAlignHack 10 &
  \cAlignHack -- &
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  \multicolumn{1}{p{\dimexpr(.09150000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 1.314}} &
  \multicolumn{1}{p{\dimexpr(.0864\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 5.912}}\\
 &
  Mixed &
  \cAlignHack 107 &
  \cAlignHack 42 &
  \cAlignHack 0.008 &
  \cAlignHack 2.787 &
   &
  \\
\multicolumn{1}{p{\dimexpr(.1849\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Smoking}} &
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  \cAlignHack 3 &
  \cAlignHack 0.438 &
  \cAlignHack 1.755 &
  \multicolumn{1}{p{\dimexpr(.09150000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.423}} &
  \multicolumn{1}{p{\dimexpr(.0864\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 7.274}}\\
 &
  No &
  \cAlignHack 172 &
  \cAlignHack 49 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\multicolumn{1}{p{\dimexpr(.1849\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Junk food consumption}} &
  Yes &
  \cAlignHack 162 &
  \cAlignHack 48 &
  \cAlignHack 0.771 &
  \cAlignHack 1.185 &
  \multicolumn{1}{p{\dimexpr(.09150000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.378}} &
  \multicolumn{1}{p{\dimexpr(.0864\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 3.713}}\\
 &
  No &
  \cAlignHack 16 &
  \cAlignHack 4 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\multicolumn{1}{p{\dimexpr(.1849\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Family history of obesity }} &
  Present &
  \cAlignHack 18 &
  \cAlignHack 9 &
  \cAlignHack 0.161 &
  \cAlignHack 1.860 &
  \multicolumn{1}{p{\dimexpr(.09150000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.781}} &
  \multicolumn{1}{p{\dimexpr(.0864\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 4.432}}\\
 &
  Absent &
  \cAlignHack 160 &
  \cAlignHack 43 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}

\begin{table*}[!htbp]
\caption{\boldmath {Multivariate Logistic Regression Analysis (n=230)} }
\label{tw-949a1c4e4c4c}
\def\arraystretch{1.1}
\ignorespaces 
\centering 
\begin{tabulary}{\linewidth}{p{\dimexpr.19349999999999998\linewidth-2\tabcolsep}p{\dimexpr.1158\linewidth-2\tabcolsep}p{\dimexpr.1529\linewidth-2\tabcolsep}p{\dimexpr.1347\linewidth-2\tabcolsep}p{\dimexpr.11129999999999999\linewidth-2\tabcolsep}p{\dimexpr.1036\linewidth-2\tabcolsep}p{\dimexpr.10090000000000002\linewidth-2\tabcolsep}p{\dimexpr.08729999999999999\linewidth-2\tabcolsep}}
\tbltoprule \rowcolor{kwdboxcolor} &  & \multicolumn{2}{p{\dimexpr(.28759999999999998\linewidth-2\tabcolsep)}}{\cAlignHack Obesity and Overweight} &  &  &  & \\
\rowcolor{kwdboxcolor}\cAlignHack Variables & \cAlignHack Category & \cAlignHack No & \cAlignHack Yes & \cAlignHack p-value & \cAlignHack OR & \multicolumn{2}{p{\dimexpr(.1882\linewidth-2\tabcolsep)}}{\cAlignHack 95\% CI}\\
\tblmidrule 
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Residence}} &
  Hostilities &
  \cAlignHack 68 &
  \cAlignHack 24 &
  \cAlignHack 0.067  &
  \cAlignHack 1.906  &
  \cAlignHack 0.955  &
  \cAlignHack 3.803 \\
 &
  Day Scholars &
  \cAlignHack 110 &
  \cAlignHack 28 &
  \cAlignHack -- &
  \cAlignHack Ref &
  \cAlignHack  &
  \cAlignHack \\
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Sleep }} &
  \textless\ 8 hours &
  \cAlignHack 121 &
  \cAlignHack 43 &
  \cAlignHack 0.021  &
  \cAlignHack 2.665  &
  \multicolumn{1}{p{\dimexpr(.10090000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 1.163 }} &
  \multicolumn{1}{p{\dimexpr(.08729999999999999\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 6.108 }}\\
 &
  {\textgreater} 8 hours &
  \cAlignHack 57 &
  \cAlignHack 9 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Recommended Exercise }} &
   Yes &
  \cAlignHack 86 &
  \cAlignHack 21 &
  \cAlignHack -- &
  \cAlignHack Ref &
  \multicolumn{1}{p{\dimexpr(.10090000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.617 }} &
  \multicolumn{1}{p{\dimexpr(.08729999999999999\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 2.306 }}\\
 &
  No &
  \cAlignHack 92 &
  \cAlignHack 31 &
  \cAlignHack 0.599  &
  \cAlignHack 1.193  &
   &
  \\
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Diet}} &
  Vegetarian &
  \cAlignHack 71 &
  \cAlignHack 10 &
  \cAlignHack -- &
  \cAlignHack Ref &
  \multicolumn{1}{p{\dimexpr(.10090000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 1.371 }} &
  \multicolumn{1}{p{\dimexpr(.08729999999999999\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 6.962 }}\\
 &
  Mixed &
  \cAlignHack 107 &
  \cAlignHack 42 &
  \cAlignHack 0.007  &
  \cAlignHack 3.089  &
   &
  \\
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Smoking}} &
  Yes &
  \cAlignHack 6 &
  \cAlignHack 3 &
  \cAlignHack 0.363  &
  \cAlignHack 2.031  &
  \multicolumn{1}{p{\dimexpr(.10090000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.441 }} &
  \multicolumn{1}{p{\dimexpr(.08729999999999999\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 9.359 }}\\
 &
  No &
  \cAlignHack 172 &
  \cAlignHack 49 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Junk food consumption}} &
  Yes &
  \cAlignHack 162 &
  \cAlignHack 48 &
  \cAlignHack 0.957  &
  \cAlignHack 1.036  &
  \multicolumn{1}{p{\dimexpr(.10090000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.288 }} &
  \multicolumn{1}{p{\dimexpr(.08729999999999999\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 3.726 }}\\
 &
  No &
  \cAlignHack 16 &
  \cAlignHack 4 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\multicolumn{1}{p{\dimexpr(.19349999999999998\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{Family history of obesity }} &
  Present &
  \cAlignHack 18 &
  \cAlignHack 9 &
  \cAlignHack 0.135  &
  \cAlignHack 2.016  &
  \multicolumn{1}{p{\dimexpr(.10090000000000002\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 0.804 }} &
  \multicolumn{1}{p{\dimexpr(.08729999999999999\linewidth-2\tabcolsep)}}{\multirow{2}{\linewidth}{\cAlignHack 5.053 }}\\
 &
  Absent &
  \cAlignHack 160 &
  \cAlignHack 43 &
  \cAlignHack -- &
  \cAlignHack Ref &
   &
  \\
\tblbottomrule 
\end{tabulary}\par 
\end{table*}
If BMI is 25.0 to 30, it falls within the overweight range. If BMI is 30.0 or higher, it falls within the obese category. Obesity among students is progressing towards an epidemic level. The change in lifestyle, lack of physical activity and exercise, improper eating habits and lack of awareness about obesity which has become a major problem of college students, especially among medical students who have a stressful schedule and are more prone to NCDs. So the present study was undertaken in Saveetha Medical College and Hospital to estimate the prevalence of overweight and obesity and associated risk factors.
    
\section{Materials and Methods}
A cross-sectional study was carried out among the medical students of Saveetha Medical College and Hospital for the study duration of 3 months. A sample size of 230 was calculated using the formula 4pq/r\ensuremath{^{2}}. Where p = 29.5 \unskip~\citep{700953:16598930}, r = 20\% of p. The study participants were selected using a purposeful sampling technique. All the students who gave informed consent to participate in the study were included. A semi-structured questionnaire was used for data collection using interview techniques.

The data was collected using a semi-structured questionnaire during May-June 2018 and was entered into the Microsoft Excel sheet. The analysis was done using Epi-Info software and relevant statistics such as proportions and chi-square; logistic regression was used for data analysis. A p-value of less than 0.05 was considered statistically significant. Institutional Ethical Committee approval was taken before starting the study.

\textbf{Operational definitions}

\textbf{Adequate exercise}

According to Global strategy on a diet, physical activity and Health, Adults aged 18{\textendash}64 should do at least 150 minutes of moderate-intensity aerobic physical activity throughout the week or do at least 75 minutes of vigorous-intensity aerobic physical activity throughout the week or an equivalent combination of moderate- and vigorous-intensity activity \unskip~\citep{700953:16598925}.

\textbf{Junk food}

Junk food is energy-dense food with a high amount of refined sugar, white flour, trans-fat, polyunsaturated fat, salt, numerous additives and low nutrient value in terms of protein, fibre, vitamin, and mineral content. Foods like chips, chocolate, soft drink, etc. are generally taken as junk food \unskip~\citep{700953:16598929}.

\textbf{Current tobacco users}

According to (GATS) Global Adult Tobacco Survey 2010, the constituents of smoking will include using smoked cigarettes, smoked water pipes, smoked water pipes \unskip~\citep{700953:16598931}.

Anthropometric measurements like height (in meters) and weight (in kilograms) of the subjects were undertaken by means of stadiometer and weighing machine, respectively.

BMI is calculated by the formula;
\begin{eqnarray*}BMI=\frac{Weight\;\left(kg\right)}{Height\;\left(m\right)^{2}} \end{eqnarray*}

    
\section{Results and Discussion}
The prevalence of overweight was 20.4\% (Table~\ref{tw-87d2159c51e3}) and obesity was 2.1\% in the current study was lower compared to the study done by Mohan V et al. \unskip~\citep{700953:16598932} the difference may be due that fact that our study focuses only on medical students and time duration between the two studies.

It was observed that the prevalence of obesity was less among those study participants who consumed vegetarian food (Table~\ref{tw-87d2159c51e3}), which is similar to the study conducted by Newby P \unskip~\citep{700953:16598927}.

Although study participants who did inadequate exercise were more overweight as compared to those who did adequate exercise (Table~\ref{tw-87d2159c51e3}), the differences were not statistically significant. This is contrary to the results observed by Miles J L \unskip~\citep{700953:16598933}, the differences may be due to the fact that study participants may have exaggerated their exercise duration. 

 Sleep was a significant contributor of overweight and obesity in our study (Table~\ref{tw-87d2159c51e3}) which is similar to the study conducted by Gangwisch J E \unskip~\citep{700953:16598935}  in the year 2005 observed an increase in the prevalence of obesity with day time sleep and inadequate sleep during the night.

Table~\ref{tw-f1847522efe4}  shows that upon univariate analysis of the various factors which are assumed to be contributing to overweight and obesity, factors such as sleep and diet were independently associated with overweight and obesity. However, factors such as residence, smoking habit, junk food consumption, and family history of obesity were not independently associated with overweight and obesity.

Multivariate logistic regression was performed (Table~\ref{tw-949a1c4e4c4c}) to ascertain the effects of place of residence, sleep duration, recommended exercise, diet, smoking, junk food consumption, family history of obesity, on the likelihood that participants become overweight and obesity. The logistic regression model was statistically significant i.e. chi-square value = 19.154, df =9, p=0.008. The model explained 12.2\% (Nagelkerke R2) of the variance in becoming overweight and obese and correctly classified 77.10\% of overweight and obese individuals. Individuals who sleep less than 8 hours a day were 2.6 times more likely to become obese and individuals on a mixed diet were 3 times more likely to become overweight and obese than individuals who are on a vegetarian diet.
    
\section{Conclusion}
In the present study, the prevalence of overweight and obesity was 20.4\% and 2.1\%, respectively and factors such as diet pattern and sleep duration are significantly associated with overweight and obesity. Measures such as motivating the students, organizing group exercise activities and making physical activity as part of the curriculum and importance of adequate sleep should be emphasized.
    

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