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\def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2020-01-15 (revised: 15 January 2020)} \def\TheID{\makeatother } \def\TheDate{2020-01-15} \title{Determinants of Hypertension in a Rural Area of Kancheepuram District, Tamilnadu} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@ \belowdisplayskip \abovedisplayskip \abovedisplayshortskip \z@ plus2\p@ \belowdisplayshortskip 4\p@ plus2\p@ minus2\p@ \def\@listi{\leftmargin\leftmargini \topsep 2\p@ plus1\p@ minus1\p@ \parsep 2\p@ plus\p@ minus\p@ \itemsep 1pt} } \makeatother \fvset{frame=single,numberblanklines=false,xleftmargin=5mm,xrightmargin=5mm} \fancyhf{} \setlength{\headheight}{14pt} \fancyhead[LE]{\bfseries\leftmark} \fancyhead[RO]{\bfseries\rightmark} \fancyfoot[RO]{} \fancyfoot[CO]{\thepage} \fancyfoot[LO]{\TheID} \fancyfoot[LE]{} \fancyfoot[CE]{\thepage} \fancyfoot[RE]{\TheID} \hypersetup{citebordercolor=0.75 0.75 0.75,linkbordercolor=0.75 0.75 0.75,urlbordercolor=0.75 0.75 0.75,bookmarksnumbered=true} \fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}} \date{} \usepackage{authblk} \providecommand{\keywords}[1] { \footnotesize \textbf{\textit{Index terms---}} #1 } \usepackage{graphicx,xcolor} \definecolor{GJBlue}{HTML}{273B81} \definecolor{GJLightBlue}{HTML}{0A9DD9} \definecolor{GJMediumGrey}{HTML}{6D6E70} \definecolor{GJLightGrey}{HTML}{929497} \renewenvironment{abstract}{% \setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Dr. M. Vijayakarthikeyan} \author[2]{Dr. Muthulakshmi Muthiah} \renewcommand\Authands{ and } \date{\small \em Received: 10 December 2019 Accepted: 1 January 2020 Published: 15 January 2020} \maketitle \begin{abstract} Background: Hypertension is one of the most important modifiable risk factors for cardiovascular diseases (CVDs). Hypertension is a risk factor that accounts for 12.3% of the deaths and disabilities combined in Tamilnadu during 2016. Objectives ? To assess the prevalence of risk factors of hypertension among the study population. ? To determine the association between sociodemographic factors and hypertension. ? To determine the association between various risk factors and hypertension. Materials and methods: It is a community-based crosssectional study. The sample size calculated was 1250 and a systematic random sampling method was used. A pre-tested structured questionnaire was used to collect data from the study population. Information regarding socio-demographic characteristics, risk factors, regarding hypertension and physical measurements were obtained. The data analysis was done using SPSS software (version 22). Results: Among the study population,23.6% were hypertensive, and. in this study,12.8% use tobacco in any form, 18.6% use alcohol, 66.2% of the participants are physically inactive, and 72.5% are consuming an unhealthy diet. In the Univariate analysis, the variables that are significantly associated with hypertension are age, marital status, education, occupation, socio-economic status, family type, positive family history, presence of associated comorbidities, knowledge about hypertension and BMI. In multivariate analysis are age, presence of associated comorbidities, knowledge about hypertension, family type, and BMI. Conclusion: The prevalence of hypertension and its determinants is high in this study are tumultuous. Lifestyle modification plays a pivotal role, and hypertension is a lifestyle disease change in that harmful lifestyle habits must be adopted. Objectives? To assess the prevalence of risk factors of hypertension among the study population.? To determine the association between socio-demographic factors and hypertension.? To determine the association between various risk factors and hypertension. \end{abstract} \keywords{blood pressure, risk factor, cardiovascular disease.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{Introduction}]{Introduction}\par igh blood pressure (BP) is one of the most important modifiable risk factors for cardiovascular diseases (CVDs). 1 Hypertension (HTN) is a chronic condition of concern because of its role in the causation of coronary heart disease (CHD), stroke, and other vascular complications. It is the most common CVD disorder which poses a significant public health challenge to a population undergoing socioeconomic evolution. It is one of the dominant risk factors for CVD mortality, accounting for 20-50\% of all deaths. \hyperref[b0]{2,}\hyperref[b1]{3} Hypertension (HTN) exerts a substantial public health burden on cardiovascular health status and healthcare systems in India. \hyperref[b2]{4,}\hyperref[b3]{5} The analysis showed that about 26\% of the population globally is suffering from hypertension, and the prevalence is higher among developed as compared to developing countries. \hyperref[b4]{6} It is predicted that the number of adults with hypertension would increase by about 60\% to a total of 1.56 billion by 2025. \hyperref[b5]{7,}\hyperref[b6]{8} HTN is directly responsible for 57\% of all stroke deaths and 24\% of all coronary heart disease (CHD) deaths in India. \hyperref[b7]{9,}\hyperref[b8]{10} Currently, the incidence of hypertension is 20 to 40\% in urban areas and 12 to 17\% in rural areas of India. One in three Indian adults has high blood pressure. According to the World Health Statistics 2012 report, India has low rates of hypertension compared to world figures. \hyperref[b9]{11} In India, 23.10\% of men and 22.60\% of women over 25 years suffer from hypertension. \hyperref[b10]{12,}\hyperref[b11]{13} As per the NFHS 4 report, prevalence of hypertension in males is 10.3\% and in females is 6.7\% . \hyperref[b12]{14} Community surveys have documented that in a period of three to six decades, prevalence of hypertension has increased by about 30 times among the urban dwellers and by about ten times among the rural inhabitants. \hyperref[b13]{15,}\hyperref[b14]{16} The technological and economic developments have reduced the physical activity of the people to a real large extent and increased the alcohol and tobacco use which are the vital causes for the rising burden of hypertension. \hyperref[b15]{17} The risk factors for non-communicable disease are grouped into three categories they are behavioral, metabolic and biochemical risk factors. Behavioral risk factors include tobacco use, alcohol use, unhealthy diet, and lack of physical activity. Metabolic risk factors include overweight, obesity, diabetes, and Abstract-Background: Hypertension is one of the most important modifiable risk factors for cardiovascular diseases (CVDs). Hypertension is a risk factor that accounts for 12.3\% of the deaths and disabilities combined in Tamilnadu during 2016. \section[{Objectives}]{Objectives} \section[{?}]{?}\par To assess the prevalence of risk factors of hypertension among the study population. \section[{?}]{?}\par To determine the association between sociodemographic factors and hypertension. \section[{?}]{?}\par To determine the association between various risk factors and hypertension. \section[{Conclusion: The prevalence of hypertension and its}]{Conclusion: The prevalence of hypertension and its}\par determinants is high in this study are tumultuous. Lifestyle modification plays a pivotal role, and hypertension is a lifestyle disease change in that harmful lifestyle habits must be adopted.\par hypertension (HTN). Biochemical risk factors include hypercholesteremia and hypertriglyceridemia. \hyperref[b16]{18} To contain the increasing burden of Non-Communicable Diseases, Ministry of Health and Family Welfare, Government of India, has launched the National Programme on Prevention and Control of Diabetes, Cardiovascular Diseases and Stroke (NPDCS). \hyperref[b17]{19} As fewer studies has been undertaken in rural India, this study was planned to assess the determinants of hypertension among the rural population of Kancheepuram district of Tamil Nadu. This study will shed some light on the existing problem. \section[{II.}]{II.} \section[{Materials and Methods}]{Materials and Methods} \section[{a) Study design}]{a) Study design}\par This study is a community-based crosssectional study conducted in a rural area of Kancheepuram district, Tamil Nadu. \section[{b) Study area}]{b) Study area}\par The study was conducted in Serappanachery Padappai (S. Padappai), which is the rural field practice area of the Rural Health and Training Centre (RHTC) attached to our Institution (Sree Balaji medical college and hospital). \section[{c) Study population}]{c) Study population}\par The study population included are those permanently residing in Serappana-chery Padappai and belonging to the adult age group of 20-60 years. \section[{d) Study period}]{d) Study period}\par The study was conducted during December 1 st 2018 -May 31 st , 2019. \section[{e) Sample size}]{e) Sample size}\par The sample size was calculated from a previous study conducted by Kishore J et al, in a rural area in 2016, the prevalence of hypertension recorded in this study was 14.1\%. \hyperref[b18]{20} The sample size was calculated using the formula N = Z?²pq/ [L] 2 where Z = 1.96, p = 14.1\%, q =85.9 (100-14.1), L = 2. 115. Accounting 15\% for non-response, the final sample size was calculated as 1245 (rounded off to 1250). [N = 1250] \section[{f) Inclusion criteria}]{f) Inclusion criteria}\par The inclusion criteria for the study were the adult population of age group (20-60 years) residing in Serappanachery Padappaiand willing to participate in the study. \section[{g) Exclusion criteria}]{g) Exclusion criteria}\par The exclusion criteria for the study were females who were pregnant, psychiatric patients, who are severely ill, and those who didn't give consent to participate in the study was excluded. \section[{h) Sampling method}]{h) Sampling method}\par A systematic random sampling technique was used to identify the study subjects. Sampling Interval (N/n) is calculated as follows: [N= Total number of households in Padappai=1851, n = sample size = 1250. N/n=1851/1250= 2]. Thus alternate household is selected for identifying the adult population between 20-60 years of age. \section[{i) Study tool}]{i) Study tool}\par A structured questionnaire based on the WHO STEPS approach is used as a study stool for data collection, Details included in it are socio demographic profiles, details regarding risk factors for hypertension, and physical measurements (height, weight, waist circumference, and BP). \section[{j) Informed consent}]{j) Informed consent}\par Informed Consent was obtained from each participant before the administration of the interview schedule. \section[{k) Ethical approval}]{k) Ethical approval}\par The study proposal was presented and was approved by the Institutional Ethics Committee. l) Operational definitions 1. Tobacco user: \hyperref[b19]{21} Tobacco user was defined as individuals who had used any form of tobacco in the last 30 days. 2. Alcohol user: \hyperref[b19]{21} Alcohol users were those who had consumed at least one standard drink of alcohol (30 ml of spirits, 285 ml of beer, or 120 ml of wine) in the last 12 months. 3. Unhealthy diet: \hyperref[b16]{18} A unhealthy diet is Low consumption of fruits and vegetables at less than five servings per day (one cup of raw leafy vegetables or a half cup of other vegetables (cooked) was considered one serving. One medium-sized piece of fruit or half cup of chopped fruit was measured as one serving). 4. Physical activity: \hyperref[b16]{18} Physical activity low physical activity was defined as <150 minutes of moderate physical activity per week. 5. Overweight: \hyperref[b20]{22} Overweight was defined as BMI 23-24.9 kg /m2. 6. Pre obese: \hyperref[b20]{22} Pre obese was defined as BMI equal to or more than 25 kg /m2. 7. Obese: \hyperref[b20]{22} Obese was defined as BMI equal to as or more than 30 kg /m2. 8. Central obesity: \hyperref[b20]{22} Central obesity is assessed based on the waist-hip ratio. As per WHO guideline, males with a waist-hip ratio above 0.9 and females with a waist-hip ratio above 0.85 have central obesity.\par III. \section[{Results}]{Results} \section[{a) Socio-demographic characteristics of the study population}]{a) Socio-demographic characteristics of the study population}\par Socio-demographic characteristics of the study population are shown in Table \hyperref[tab_1]{1}. Among the study participants, 44.2\% belonged to 50-60 years of age, 24.2\% belonged to 20-30 years of age, and 20.8\% belonged to 30-40 years of age. About 57.4\% of the study participants were females, and 42.6\% were males. Nearly 82.4\% are married, and 5.44\% were unmarried. Almost 18.7\% of the study samples had no formal education, 30.2\% had middle school education, and 21.3\% had a high school education. Among the participants, around 43.7\% were unemployed, 32.2\% are engaged in unskilled occupation, and 17.8\% are involved in semiskilled occupation.49.6\% belonged to lower-middle socio-economic category, and 21.8\% belonged to the upper lower socio-economic group. In this study, 56.8\% of them belong to the nuclear family,30\% belonged to the joint family, and the rest were belonging to three-generation family. \section[{f) Knowledge regarding hypertension among the study population}]{f) Knowledge regarding hypertension among the study population}\par Among the study participants, when asked whether they know the normal blood pressure value, 24.8\% said they know the normal blood pressure value., and among them, only 60\% said the correct blood pressure value and 40\% said incorrect value. In this study, 47.5\% of the participants have adequate knowledge about hypertension, as shown in FIGURE {\ref 4}. \section[{g) Univariate analysis findings among the study population}]{g) Univariate analysis findings among the study population}\par In the Univariate analysis the variables that are significantly associated with hypertension are age (pvalue-<0.0001), marital status (p-value-<0.0001), education (p-value-0.015), occupation (p-value-0.003), socio-economic status (p-value-<0.015), family type (pvalue-<0.0001), positive family history (p-value-0.009), presence of associated comorbidity (p-value-<0.0001), knowledge about hypertension (p-value-<0.0001) and BMI (p-value-<0.0001). There was no association found between other variables and hypertension. \hyperref[b21]{23} 25.5\% of the ever used tobacco in a study by Maroof KA In Uttar Pradesh. \hyperref[b22]{24} In Peter Lloyd-Sherlock study 64.6\% had never smoked and 24.1\% are smoking daily. \hyperref[b23]{25} 15.9 \% are smoking daily, and 73.2\% are using smokeless tobacco in a study by Aroor Bhagyalaxmi which was conducted in a rural area of Gujarat, India. \hyperref[b24]{26} Sathish Kumar conducted a study in Salem in which 24.7\% had never used tobacco, and 25\% are past users. \hyperref[b19]{21} ii. Alcohol use In this stud, 18.6\% are current alcohol users, and 1.1\% were past users of alcohol. Sathish Kumar , s study showed that 58.3\% are using alcohol daily or a few days a week, and 28.6\% had used alcohol in the past. \hyperref[b19]{21} 40.9\% are consuming alcohol in a study by Chataut J. \hyperref[b21]{23} In a study by K. A. Maroof,35.5\% had ever used alcohol,, and the remaining 64.5\% had never used alcohol. \hyperref[b22]{24} 76.8\% had never consumed alcohol in their lifetime in a study conducted by Peter Lloyd-Sherlock. \hyperref[b23]{25} iii. Physical activity In this study, 66.2\% were physically inactive, and only 33.8\% were physically active as per the operational definition, and this showed that the majority of the study participants are following unhealthy lifestyle habits. In Chataut J study, 51.8\% are involved in moderate physical activity, and 8\% are engaged in sedentary activities. \hyperref[b21]{23} 28.5\% are physically inactive in a study done by Peter Lloyd-Sherlock. \hyperref[b23]{25} Aroor Bhagyalaxmi study showed that 14.1\% of the study samples were physically inactive. \hyperref[b24]{26} 34.9\% were doing sedentary physical activity and 33.8\% are involved in vigorous physical activities in a study done by Sathish Kumar. \hyperref[b19]{21} iv. Unhealthy diet 72.5\% of the respondents in this study were following an unhealthy diet. In a study conducted by Aroor Bhagyalaxmi most of the study participants i.e. 96.4\% were following unhealthy diet. \hyperref[b24]{26} 94.5\% were taking low fruit, and vegetables in a study by Garg A. \hyperref[b25]{27} Bhattacherjee S conducted a study in West Bengal in which 60.4\% were consuming an unhealthy diet. \hyperref[b26]{28} \section[{86}]{86} \section[{v. Overweight and obesity}]{v. Overweight and obesity}\par In this study, as per the Asian Adults BMI criteria, 26.2\% were overweight, 22 \% were pre-obese, and 12.6\% belonged to obese category. In V Mohan study 22.5\% were overweight and 28.5\% of the respondents are obese. \hyperref[b27]{29} 12\% of the respondents were overweight in a study by Aroor Bhagyalaxmi. \hyperref[b24]{26} In a study done by Prabhakaran D 35\% of them were overweight, and 3.3\% of the study participants belonged to theobese category. \hyperref[b28]{30} 20.5\% were overweight, and 4.2\% were the obese in Midha T. \hyperref[b29]{31} \section[{vi. Central obesity}]{vi. Central obesity}\par In this study, central obesity was assessed based on the waist-hip ratio. About 83.4\% of the study participants have central obesity. In a study by Isezuo SA. 13\% of the study participants had central obesity. \hyperref[b30]{32} Aroor Bhagyalaxmi showed that central obesity was present in 38\% of the samples. \hyperref[b24]{26} 15.7\% of the study participants have central obesity in AK Agarwal study. \hyperref[b31]{33} In a study by K. A. Maroof 30.5\% were centrally obese. \hyperref[b22]{24} 49.1\% have central obesity in a study by V Mohan. \hyperref[b27]{29} \section[{vii. Food habits}]{vii. Food habits}\par In this study, nearly 89.9\% of the study participants were nonvegetarian and 10.1\% were vegetarian. Among the non vegetarians, 54.1\% had non vegetarian food once a week, and 35.1 had non vegetarian food twice a week. In Chataut J study, 91.3\% of them are were nonvegetarian and 8.7\% were vegetarian and 71.4\% were nonvegetarian in a study by Sathish Kumar. \hyperref[b19]{21} \section[{viii. Family history of hypertension}]{viii. Family history of hypertension}\par In this study, among the study participants, 21.4 \% had a positive family history of hypertension. Rajeev Bhardwaj conducted a study in which only 4\% of the study participants have a positive family history of hypertension. \hyperref[b32]{34} In a study by Shyamal Kumar Das, 2.4\% of the study participants had a positive family history of hypertension. \hyperref[b33]{35} 53.8\% of the families have hypertension in a study by Haresh Chandwani. \hyperref[b35]{37} \section[{b) Association between sociodemographic variables, risk factors and hypertension}]{b) Association between sociodemographic variables, risk factors and hypertension}\par In this study in the Univariate analysis, the variables that are significantly associated with hypertension are age, marital status, education, occupation, socio-economic status, family type, positive family history, presence of associated comorbidity, knowledge about hypertension, and BMI. The variables that are significant in multivariate analysis are age, presence of associated comorbidity, knowledge about hypertension, family type, and BMI. In a study by Sathish Kumar, increasing age, male gender, increasing BMI levels, tobacco, alcohol, WHR were found to be significant independent predictors of hypertension and on multivariate analysis of these significant variables age, male gender, increasing BMI levels, were found to be significant after adjusting for other variables. \hyperref[b19]{21} In hypertension study group multicentric study multiple logistic regression analyses identified a higher body mass index, higher education status, and prevalent diabetes mellitus as important correlates of the prevalence of hypertension. \hyperref[b35]{37} Jonas JB conducted a study, in which hypertension was associated with higher age, higher body mass index, body height, Higher blood hemoglobin levels, and elevated blood urea concentration. \hyperref[b36]{38} V. \section[{Conclusion}]{Conclusion}\par The prevalence of hypertension and its determinants is high in this study are tumultuous. Lifestyle modification plays a pivotal role, and hypertension is a lifestyle disease change in that harmful lifestyle habits must be adopted. The target population for this strategy will be adolescents, and early adults, as the prevention of risk factors will curb the rates of hypertension and its risk factors.\par This study will initiate an internalization process of the government sector to make it more attractive, viable, and reliable, thereby giving scope proper screening, early diagnosis and treatment, and to provide accessible quality tertiary care.\begin{figure}[htbp] \noindent\textbf{2}\includegraphics[]{image-2.png} \caption{\label{fig_1}Figure 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{1} \par \begin{longtable}{P{0.11091877496671104\textwidth}P{0.34294274300932087\textwidth}P{0.1403462050599201\textwidth}P{0.03055925432756325\textwidth}P{0.13129161118508653\textwidth}P{0.09394141145139813\textwidth}} \multicolumn{5}{l}{Determinants of Hypertension in a Rural Area of Kancheepuram District, Tamilnadu}\tabcellsep \\ Sl. No.\tabcellsep Socio-Demographic Variable\tabcellsep \multicolumn{3}{l}{Frequency (N=1250) Percentage (\%)}\tabcellsep Year 2020\\ 1.\tabcellsep 20-30 Years\tabcellsep Age\tabcellsep 136\tabcellsep 10.9\tabcellsep 49\\ 2. 3.\tabcellsep 30-40 Years 40-50 Years 50-60 Years Male Female Unmarried\tabcellsep \multicolumn{2}{l}{302 260 552 Sex 532 718 Marital Status 68}\tabcellsep 24.2 20.8 44.2 42.6 57.4 5.4\tabcellsep Volume XX Issue I Version I\\ \tabcellsep Married\tabcellsep \tabcellsep 1030\tabcellsep 82.4\tabcellsep D D D D ) B\\ \tabcellsep Widower\tabcellsep \tabcellsep 142\tabcellsep 11.4\tabcellsep (\\ 4.\tabcellsep Divorcee Illetereate Primary School Middle School\tabcellsep \multicolumn{2}{l}{10 Education 234 282 378}\tabcellsep .8 18.7 22.6 30.2\tabcellsep Medical Research\\ 5.\tabcellsep High School Post High School Diploma Ug/Pg Professional\tabcellsep \multicolumn{2}{l}{266 12 72 6 Occupation}\tabcellsep 21.3 1.0 5.8 .5\tabcellsep Global Journal of\\ \tabcellsep Unemployed\tabcellsep \tabcellsep 546\tabcellsep 43.7\tabcellsep \\ \tabcellsep Unskilled\tabcellsep \tabcellsep 402\tabcellsep 32.2\tabcellsep \\ \tabcellsep Semiskilled\tabcellsep \tabcellsep 222\tabcellsep 17.8\tabcellsep \\ \tabcellsep Skilled\tabcellsep \tabcellsep 46\tabcellsep 3.7\tabcellsep \\ \tabcellsep \multicolumn{2}{l}{Farmers/Clerks/Shop Owners}\tabcellsep 10\tabcellsep .8\tabcellsep \\ \tabcellsep Semiprofessional\tabcellsep \tabcellsep 14\tabcellsep 1.1\tabcellsep \\ \tabcellsep Professional\tabcellsep \tabcellsep 10\tabcellsep .8\tabcellsep \\ \tabcellsep \tabcellsep \tabcellsep \tabcellsep © 2020 Global Journals\tabcellsep \end{longtable} \par \caption{\label{tab_1}Table 1 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{2} \par \begin{longtable}{P{0.37895833333333334\textwidth}P{0.16645833333333332\textwidth}P{0.16291666666666668\textwidth}P{0.14166666666666666\textwidth}} Sl. No.\tabcellsep Food Habits\tabcellsep FREQUENCY\tabcellsep PERCENTAGE (\%)\\ 1.\tabcellsep \tabcellsep Food Type (N-1250)\tabcellsep \\ Vegetarian\tabcellsep \tabcellsep 126\tabcellsep 10.1\\ \multicolumn{2}{l}{Non Vegetarian}\tabcellsep 1124\tabcellsep 89.9\\ 2.\tabcellsep \multicolumn{3}{l}{Frequency of Non-Veg Intake (N-1124)}\\ \multicolumn{2}{l}{Once A Week}\tabcellsep 608\tabcellsep 54.1\\ \multicolumn{2}{l}{Twice A Week}\tabcellsep 394\tabcellsep 35.1\\ \multicolumn{2}{l}{Thrice A Week}\tabcellsep 104\tabcellsep 9.2\\ \multicolumn{2}{l}{Four Times A Week}\tabcellsep 12\tabcellsep 1.1\\ \multicolumn{2}{l}{> Four Times A Week}\tabcellsep 6\tabcellsep 0.5\end{longtable} \par {\small\itshape [Note: c)]} \caption{\label{tab_2}Table 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.04154135338345864\textwidth}P{0.4409774436090226\textwidth}P{0.21090225563909773\textwidth}P{0.15657894736842104\textwidth}} Sl. No.\tabcellsep Lifestyle\tabcellsep FREQUENCY\tabcellsep PERCENTAGE (\%)\\ 1.\tabcellsep \tabcellsep Job Type (N-1250)\tabcellsep \\ \tabcellsep Sedentary Work\tabcellsep 752\tabcellsep 60.2\\ \tabcellsep Moderate Work\tabcellsep 444\tabcellsep 35.5\\ \tabcellsep Heavy Work\tabcellsep 54\tabcellsep 4.3\\ 2.\tabcellsep \tabcellsep Exercise (N-1250)\tabcellsep \\ \tabcellsep Yes\tabcellsep 268\tabcellsep 21.4\\ \tabcellsep No\tabcellsep 982\tabcellsep 78.6\\ 3.\tabcellsep \multicolumn{2}{l}{Duration of Exercise (N-268)}\tabcellsep \\ \tabcellsep < 1 Hour/Week\tabcellsep 20\tabcellsep 7.4\\ \tabcellsep 1-2 Hours/ Week\tabcellsep 106\tabcellsep 39.6\\ \tabcellsep 2--5 Hours/ Week\tabcellsep 74\tabcellsep 27.7\\ \tabcellsep > 5 Hours/ Week\tabcellsep 68\tabcellsep 25.3\end{longtable} \par \caption{\label{tab_3}Table 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{4} \par \begin{longtable}{P{0.3466266866566717\textwidth}P{0.03950524737631184\textwidth}P{0.07901049475262369\textwidth}P{0.3249625187406297\textwidth}P{0.059895052473763116\textwidth}} Sl. No.\tabcellsep Risk Factor\tabcellsep \multicolumn{2}{l}{Frequency (N-1250)}\tabcellsep Percentage (\%)\\ 1.\tabcellsep \tabcellsep \multicolumn{2}{l}{Tobacco Use}\\ \tabcellsep Yes\tabcellsep \tabcellsep 160\tabcellsep 12.8\\ \tabcellsep No\tabcellsep \tabcellsep 1090\tabcellsep 87.2\\ 2.\tabcellsep \tabcellsep \tabcellsep Alcohol Use\\ \tabcellsep Yes\tabcellsep \tabcellsep 232\tabcellsep 18.6\\ \tabcellsep No\tabcellsep \tabcellsep 1018\tabcellsep 81.4\\ 3.\tabcellsep \tabcellsep \multicolumn{2}{l}{Physical Inactivity}\\ \tabcellsep Yes\tabcellsep \tabcellsep 828\tabcellsep 66.2\\ \tabcellsep No\tabcellsep \tabcellsep 422\tabcellsep 33.8\\ 4.\tabcellsep \tabcellsep \multicolumn{2}{l}{Unhealthy Diet}\\ \tabcellsep Yes\tabcellsep \tabcellsep 906\tabcellsep 72.5\\ \tabcellsep No\tabcellsep \tabcellsep 344\tabcellsep 27.5\\ \multicolumn{3}{l}{d) Prevalence of risk factors among the study}\tabcellsep \multicolumn{2}{l}{consuming an unhealthy diet. Among the study}\\ population\tabcellsep \tabcellsep \tabcellsep \multicolumn{2}{l}{participants, 21.4 \% had a positive family history of}\\ \multicolumn{3}{l}{Prevalence of risk factors for hypertension is}\tabcellsep \multicolumn{2}{l}{hypertension,3\% of them are under oral contraceptive}\\ \multicolumn{3}{l}{depicted in TABLE 4 and 5.in this study 12.8\% use}\tabcellsep \multicolumn{2}{l}{pills, and 24.8\% are suffering from various comorbidties}\\ \multicolumn{3}{l}{tobacco in any form, 18.6\% use alcohol, 66.2\% of the}\tabcellsep (TABLE 5).\\ \multicolumn{3}{l}{participants are physically inactive, and 72.5\% are}\tabcellsep \end{longtable} \par \caption{\label{tab_4}Table 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{5} \par \begin{longtable}{P{0.05261904761904762\textwidth}P{0.4169047619047619\textwidth}P{0.22666666666666666\textwidth}P{0.1538095238095238\textwidth}} Sl. No.\tabcellsep Risk Factors\tabcellsep Frequency (N-1250)\tabcellsep Percentage (\%)\\ 1.\tabcellsep \multicolumn{3}{l}{Family History of Hypertension (N-1250)}\\ \tabcellsep YES\tabcellsep 268\tabcellsep 21.4\\ \tabcellsep NO\tabcellsep 982\tabcellsep 78.6\\ 2.\tabcellsep \multicolumn{3}{l}{OCP Pill Intake Among Females (N-718)}\\ \tabcellsep YES\tabcellsep 38\tabcellsep 3.0\\ \tabcellsep NO\tabcellsep 680\tabcellsep 97.0\\ 3.\tabcellsep \tabcellsep Co-Morbidity (N-1250)\tabcellsep \\ \tabcellsep YES\tabcellsep 310\tabcellsep 24.8\\ \tabcellsep NO\tabcellsep 940\tabcellsep 75.2\end{longtable} \par {\small\itshape [Note: e) Prevalence of obesity among the study populationAs per the Asian Adults BMI criteria (FIGURE2), 26.2\% were overweight, 22.\% were pre-obese and 12.B © 2020 Global JournalsDeterminants of Hypertension in a Rural Area of Kancheepuram District, Tamilnadu]} \caption{\label{tab_5}Table 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{8} \par \begin{longtable}{P{0.85\textwidth}} .5\%\end{longtable} \par \caption{\label{tab_6}TABLE 8 .}\end{figure} \begin{figure}[htbp] \noindent\textbf{7} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_7}Table 7 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{8} \par \begin{longtable}{P{0.4737704918032786\textwidth}P{0.005359394703656999\textwidth}P{0.026796973518284993\textwidth}P{0.07074401008827239\textwidth}P{0.06538461538461539\textwidth}P{0.14577553593947037\textwidth}P{0.06216897856242118\textwidth}} \multicolumn{3}{l}{Variable}\tabcellsep P Value\tabcellsep Adjusted Or\tabcellsep Hypertension 95\% Ci\tabcellsep Nagelkerke R Square Value\\ Age\tabcellsep \tabcellsep \tabcellsep <0.0001\tabcellsep 0.417\tabcellsep 0.341-0.510\\ \multicolumn{2}{l}{Marital Status}\tabcellsep \tabcellsep 0.235\tabcellsep 0.807\tabcellsep 0.567-1.149\\ Education\tabcellsep \tabcellsep \tabcellsep 0.266\tabcellsep 0.925\tabcellsep 0.806-1.061\tabcellsep 0.360\\ Occupation\tabcellsep \tabcellsep \tabcellsep 0.397\tabcellsep 0.935\tabcellsep 0.393-1.093\\ \multicolumn{3}{l}{Socio Economic Status}\tabcellsep 0.556\tabcellsep 1.058\tabcellsep 0.877-1.276\\ \multicolumn{3}{l}{Positive Family History}\tabcellsep 0.117\tabcellsep 1.343\tabcellsep 0.929-01.944\tabcellsep Cox And Snell R Square Value\\ Presence\tabcellsep of\tabcellsep Associated\tabcellsep \tabcellsep \\ Comorbidity\tabcellsep \tabcellsep \tabcellsep <0.0001\tabcellsep 2.516\tabcellsep 1.806-3.505\\ Knowledge\tabcellsep \tabcellsep About\tabcellsep \tabcellsep \tabcellsep 0.240\\ \multicolumn{2}{l}{Hypertension}\tabcellsep \tabcellsep <0.0001\tabcellsep 2.712\tabcellsep 1.958-3.756\\ Bmi\tabcellsep \tabcellsep \tabcellsep <0.0001\tabcellsep 0.530\tabcellsep 0.459-0.611\\ Family Type\tabcellsep \tabcellsep \tabcellsep 0.0001\tabcellsep 0.656\tabcellsep 0.517-0.832\\ \multicolumn{6}{l}{** P value < 0.05 is significant and *** P value < 0.01 is highly significant}\\ \tabcellsep IV.\tabcellsep \multicolumn{2}{l}{Discussion}\tabcellsep \\ \multicolumn{3}{l}{a) Risk factors for hypertension}\tabcellsep \tabcellsep \\ \multicolumn{2}{l}{i. Tobacco use}\tabcellsep \tabcellsep \tabcellsep \\ \multicolumn{5}{l}{In this study among the study participants,}\\ \multicolumn{5}{l}{12.8\% use tobacco and of which 3.5\% use smokeless}\\ \multicolumn{5}{l}{tobacco. In a study, by Chataut J, 40.2\% of the study}\\ \multicolumn{3}{l}{population has smoking habit.}\tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_8}Table 8 :}\end{figure} \footnote{B © 2020 Global JournalsDeterminants of Hypertension in a Rural Area of Kancheepuram District, Tamilnadu} \backmatter \begin{bibitemlist}{1} \bibitem[ World Health Organization. World health statistics report ()]{b9}\label{b9} \textit{}, \textit{World Health Organization. World health statistics report} 2012. \bibitem[Agarwal et al. (1994)]{b31}\label{b31} ‘A clinicalepidemiological study of hypertension in rural population of Jawan Block’. 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