Prevalence of the Modifiable Risk Factors of Cardiovascular Diseases in Young Adults of District Hyderabad Sindh Pakistan

Prevalence of the Modifiable Risk Factors of Cardiovascular Diseases in Young Adults of District Hyderabad Sindh Pakistan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence of the Modifiable Risk Factors of Cardiovascular Diseases in Young Adults of District Hyderabad Sindh Pakistan Shakil Ahmed Shaikh, Salma Farukh Meomn, Keenjhar Rani Laghari, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4735932/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective: The main purpose of this study is to determine CVD risk factors in the healthy population of district Jamshoro, Sindh. Methodology: The cross-sectional study was conducted from July 2023 to December 2023, in this study, apparently healthy young adults of not more than 40 years of age were included. A self-designed questionnaire was set for the collection of data. Blood pressure was taken by the standard method through a digital apparatus, BMI was calculated by South Asian standards, and the blood sample was taken after 10 hours of fasting for lipid profile and fasting blood sugar. Collected data was analyzed by SPSS version 26.0. Results: In this study, one risk factor was found in 76% of the participants, and Obesity was found in 29% and 30% respectively in male and female participants. Central obesity was found higher in females 61% than in males 35%. Male participants had been found to have a higher systolic blood pressure than females 40% and 22% respectively. Cholesterol and blood sugar levels were found higher in 7%, triglyceride level was found higher in 35%, and HDL was less than the desired level in 26% of the population. LDL was prevalent in 6% of all the participants. Conclusion : This study concluded that 3 risk factors were found higher in females, and 4 risk factors were found higher in males, thus making the male population more prone for affected by CVD even at an early age. In addition, all risk factors were more prevalent in people over 30 years of age. Therefore results of the study were similar to most studies done. Cardiovascular Disease Risk Factors Young Adults Introduction Traditionally it is known that cardiovascular diseases affect the older aged population. Hence it is well documented nowadays that the higher frequency of the younger population is also affected by cardiovascular diseases. Early onset of these risk factors may lead to a longer duration of exposure thereby increasing the chances of developing cardiovascular diseases in the later half of life. Being aware of these trends in the young adult population is necessary of time to prevent cardiovascular diseases. The frequency of overweight and obesity in young adults has been a rising trend, that significantly contributes towards the development of increased blood pressure, dyslipidemia, and insulin resistance, these all are the risk factors for cardiovascular diseases 1 . Hypertension almost remained undiagnosed and untreated in the young population, and it is a major risk factor for cardiovascular diseases. Timely detection and treatment are essential to avoid the long-term development of cardiovascular diseases 2 . Abnormal lipid concentrations, including higher concentrations of LDL, TG, and decreased concentrations of HDL are increasingly detected in younger populations. Dyslipidemia is mainly caused by improper diet patterns, physical inactivity, and genetic traits 3 . Cigarette smoking and tobacco use are also one of the significant contributors for cardiovascular diseases. The new rising trend of vaping as an alternative to traditional smoking is also a bigger contributor, as the use of both causes endothelial dysfunction and the development of atherosclerosis 4 . Physical Inactivity: Sedentary lifestyles, prevalent among young adults, are linked to obesity, hypertension, and other cardiovascular risk factors. Promoting physical activity is crucial for cardiovascular health 5 Consumption of unhealthy diets, like diets with increased saturated fats, increased sodium, and higher levels of sugar is linked with increased cardiovascular diseases. On the other hand diet rich in fruits, vegetables, whole grains, and lean proteins has protective effects against cardiovascular disease 6 . Therefore, early diagnosis and treatment of risk factors can prevent the development and progression of any type of cardiovascular disease 7 . Limiting the risk factors in the young population can lead to significant long-term health benefits, reducing the overall burden of cardiovascular diseases on the healthcare system 8 . Understanding these risk factors benefits developing targeted health strategies among the young population, thus promoting healthier generations in the future 9 . Hence, the increasing frequency of cardiovascular disease risk factors among the young population is a public health concern that needs urgent consideration. These recent trends marked the necessity, therefore we aimed to find out the association of cardiovascular disease risk factors among the young healthy population. Methodology This study was designed as a cross-sectional comparative and conducted in the healthy population of different universities, college students, and employees of district Jamshoro from May 2022 to December 2022 after approval from the research ethical committee. Informed consent was taken from all participants before study. The sample size was collected by using the Epi info software calculator, with a 5% error margin and, a 95% confidence interval. About 300 healthy participants were approached and finally, 263 participants agreed with the response rate of 87.66% for this study. A random sampling technique was used to collect data. Participants below 40 years of age were recruited; participants with a history of any cardiovascular, diabetes, on medication, pregnant females, and those who are smokers were excluded. A self-prepared questionnaire was used to collect data from participants. The questionnaire included: sociodemographic characteristics, height, weight measurements to calculate BMI, and questions about physical activities, dietary habits, and questions to collect information about cardiovascular diseases. The BMI was calculated by standard method and South Asian scale was used for the measurement of BMI and blood pressure readings were taken by standard method. Blood pressure was measured by the digital apparatus MEDSIGN (Made in Shanghai, China). Fasting Blood sugar levels were obtained by glucometer (Easy max by Biotechnology Corp). Blood was collected in fasting for lipid profile and blood serums from samples were taken by centrifuging at Rpm of 2000 for five minutes. Then Serum was kept at -20 degrees Celsius until analyzed. The Microlab 300 (Merck) was used for sample analysis. Associations of all variables were analyzed: including BMI, all parameters of lipid profile, blood sugar levels, and physical activity. The differences in these variables were analyzed between both age groups. The average (Mean) and standard deviations (SD) of variables were obtained first by Microsoft Excel and then confirmed by SPSS (Statistical Package for Social Sciences) version 26.0 Statistical significance was set at p < 0.05 Results In this study, 300 participants were approached and 263 finally participated with a response rate of 87.66%. According to their age participants were divided into two groups. Group I include the participants aged from 20 to 29 and group II aged participants from 30–40. The mean ages of the participants were 29.05 ± 1.01. Out of 263, the male population was 168(64%) and females were 95 (36%), 171 (65.01%) were in group I and 91 (34.60%) were in group II. Table No.1 indicates the sociodemographic characteristics of participants. Table No.2, almost all risk factors were in age group II with central obesity being most prevalent with 72% of participants having increased waist circumference (P 0.0001). Dyslipidemia was almost twice more frequent in age group II and results were statistically significant for all but one parameter; LDL. The same goes for hyperglycemia with 12% sufferers in group II, in comparison to 4% in group I. However statistical significance failed to reach. Table No.3 that participants had one risk factor found in 76% of the study population. No risk factor was found in 24% of participants. Only 24% of the participants were found to have 2 risk factors, 11% of the participants were found to have 3 risk factors, and more than 3 risk factors were found in 18% of subjects. Table No. 4, below shows a comparison between the frequency of risk factors in male and female subjects. Both genders showed almost the same frequency of risk factors; however, the frequency was slightly increased in male subjects. 79% of male subjects had at least 1 risk factor, in comparison to 70% of females having at least 1 risk factor. More female subjects (30%) were clear of risk factors as compared to 21% of male subjects. Table No.5 the difference was much higher in the frequency of risk factors when age group I was compared with age group II. Increasing age showed the increasing frequency of CVD risk factors. Subjects in the older age group (II) had risk factors more. 33% of subjects of age group I were free from CVD risk factors, while only 8% of subjects of age group II had no risk factor. A whopping percentage (92%) of subjects belonging to age group II had at least one risk factor. Table No.6 the results for awareness of CVD risk factors were almost equal in both groups. Only 24% were aware of CVD risk factors; the rest of the 76% of subjects did not know CVD risk factors and their effects. Discussion At present, limited studies have been conducted to find out the frequency of diseases associated with cardiovascular and their risk factors in the young healthy population of Pakistan. The studies that were conducted were associated with the population aged more than 40 years of age which is also very limited to almost non-existent. Furthermore, studies conducted with the difference in frequency of cardiovascular risk factors between the young population and older population are also limited. Hence, it was a very difficult task to compare this study with the studies done in the past. In this study, we assessed the overall prevalence of risk factors in young adults (<40 years of age). The increase in the prevalence of risk factors with increasing age was also examined. The results achieved with this study are mostly in agreement with the majority of the literature available. More risk factors were available in male subjects; a fact widely accepted is that the male population is higher at risk for cardiovascular disease. A similar trend was found by Tran D-MT et al 10 . Another vital finding was the increase in the prevalence of risk factors with increasing age; which has been consistent time and again in other investigations, similarly RS Vasan 11 conducted a Framingham study with a sample size of 317849. Thus, concluding that males are more at risk for developing CVDs and this risk becomes higher with increasing age. Obesity is one of the major CVD risk factors. Pakistan was ranked as the 9 th most obese country in the world. In this study also obesity was found as one of the most prevalent CVD risk factors. 30% of all subjects were found to be overweight or obese according to BMI. The prevalence of obesity was less in males (29%) as compared to females (30%). The finding of this study is inconsistent with different Tran D-MT et al 10 conducted cross-sectional population-based research from 2011 and 2017 found increased BMI major cause of CVD risk factor. Pigi Dikaiou et al 12 conducted a prospective study in Sweden and documented a slightly J-shaped association of BMI with CVD risk factor. Studies were done in Pakistan that have found the prevalence of obesity in young adult Pakistanis in between 25 -35% by Z UA Sabhia et al 13 and obesity as being more prevalent in females as compared to males with only a small margin of difference. Later findings also match several studies which show a higher prevalence of obesity in females in comparison to males by S Khan et al 14 . M Asif et al 15 , S Ibrahim et al 16 . We found waist circumference as being more prevalent in females than in male subjects and there was an increase in waist circumference with increasing age. These results highly matched the investigation done by Gadekar et al 17 , who also observed higher waist circumferences in females which were found to increase with increasing age. Hypertension is a distinguished, highly studied, and established risk factor for the development of CVDs. The Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure in their seventh report has emphasized that systolic more than diastolic Blood Pressure is strongly related to CVDs. Thus, our study has mostly emphasized systolic blood pressure. The combined overall frequency of pre-hypertension and hypertension combined was 34%. These results were similar to a study done by Tran D-MT et al 10 , who found the prevalence of hypertension in people above 40 years of age to be 38%. The difference in age group is sufficient to address this slight difference in prevalence. Incidence of hypertension was found higher in males as compared to female subjects at 22%; these results were in agreement with studies done by Mills et al 18 and M Riaz et al 19 , (who showed HTN as being more prevalent in males than in females). Another important risk factor, Dyslipidemia (the presence of an elevated concentration of as a minimum one category of cholesterol/lipid) was prevalent in 35% of participants with increased triglycerides as the most prevalent of all cholesterol types. Similar results were achieved by EK Duran et al 20 , and Abdul Basit et al 21 who diagnosed 31% of subjects with dyslipidemia and found impaired triglyceride levels as most prevalent. Diabetes not only directly affects the integrity of the vascular system, but also impacts other cardiovascular risk factors. A satisfying number of studies have revealed higher levels of Dyslipidemia in diabetics as compared to non-diabetics. The prevalence of hyperglycemia was 7% in total subjects with being higher prevalent in male subjects. No diabetics were found in this study, a possible explanation for this might be the limited sample size. MHS study by Barbar Dennis et al and Kalim Uddin Aziz et al 22 showed hyperglycemia in 8-10% of subjects. A sedentary or less active lifestyle leads to increased deposits of fat in the body causing obesity and subsequent risk factors. This risk factor was found to be prevalent in 74% of total subjects. Louise Hayes et.al 23 . compared activity levels among the Indian and Pakistani populations with that of Europe and found that Europeans were more physically active than Indians, Pakistanis, or Bangladeshis. Their study showed that 52 percent of European men did not meet the required levels of physical activity, compared to 71 percent of Indians, 88 percent of Pakistanis, and 87 percent of Bangladeshis. Similar findings were documented for women. In conclusion, European men and women participated more frequently in moderate to intense sports and exercise activities as compared to Pakistani and Indians. Thus lack of exercise combined with inappropriate diet (high fat, high car, high calorie) are responsible for the growing epidemic of obesity (and subsequent risk factors) in Pakistan. Females were less active as compared to male subjects. A possible reason for this might be that women mostly believe domestic responsibilities as working out and consider that working at home keeps them physically active and thus they don’t need exercise, which is not true on biological grounds. Household chores are time-consuming but are not energy-consuming and thus less energy is consumed during 1 hour of household chores as compared to half an hour of intense walking or 15 minutes of jogging. This might also be the reason behind the findings that women are more obese, both generally and physically. In addition, cultural inhibitions combined with a lack of awareness don’t allow women to go out on jogging tracks or gyms. But men are allowed to go out and therefore nowadays the number of men engaging in jogging, swimming, sports gyming, and other activities is increasing. Furthermore, awareness about cardiovascular risk factors was less in the majority of subjects. Only 24% of subjects were moderate to high level aware of cardiovascular risk factors. The remaining did not know whatsoever about cardiovascular risk factors and their destructive effects on health. The lack of awareness co-relates with the increased incidence of cardiovascular risk factors. The less a person is aware of risk factors, the more he will succumb. Conclusion The majority of participants analyzed in this study (76%) had at least one risk factor. Such a high prevalence of cardiovascular risk factors in young adults is an alarming finding. Young adults with a lack of exercise, poor quality, high-fat diet, and lack of awareness about cardiovascular diseases and cardiovascular risk factors are moving towards the development of an unhealthy generation. These risk factors not only lead to cardiovascular diseases but also compromise the quality of life Inactive lifestyle, Central obesity, Dyslipidemia, hypertension, and obesity were the most prevalent cardiovascular risk factors. Furthermore, 4 risk factors were more prevalent in male subjects; increased Triglycerides, Hypertension, Hyperglycemia, less than desired HDL, and increased LDL, as compared to female subjects. These results indicate male population is slightly more at risk for developing CVDs. Declarations Ethical Approval: The study was approved by the ethical and research committee of the University of Sindh Jamshoro (No. DRGS/1601-01-21). Consent for publication: Not applicable. Competing Interests: The authors declare that they have no competing interests. Conflict of Interest: The authors declare no conflict of interest. Funding No funding Author Contribution 1. Shakil Ahmed Shaikh, concept/ Design Study, initial write-up of manuscript2. Salma Farukh Memon, critical analysis, correction of manuscript3. Keenjhar Rani Laghari, Data Collection and data interpretation4. Naila Hajira Rahu, data collection, critical analysis5. Hanozia Shah, data collection and data interpretation 6. Zulfiqar Ali Laghari. Final Approval and Supervision Data Availability The data will be available when required References Ren J, Wu NN, Wang S, Sowers JR, Zhang Y. Obesity cardiomyopathy: evidence, mechanisms, and therapeutic implications. Physiol Rev. 2021;101(4):1745–807. Parati G, Stergiou GS, Bilo G, Kollias A, Pengo M, Ochoa JE, et al. 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Status of Cardiovascular Health in US Adults: Prevalence Estimates from the National Health and Nutrition Examination Surveys (NHANES) 2003–2008. Stone NJ, Smith SC Jr, Orringer CE, Rigotti NA, Navar AM, Khan SS, et al. Managing atherosclerotic cardiovascular risk in young adults: JACC state-of-the-art review. J Am Coll Cardiol. 2022;79(8):819–36. Coronado F, Melvin SC, Bell RA, Zhao G. Peer Reviewed: Global Responses to Prevent, Manage, and Control Cardiovascular Diseases. Prev Chronic Dis. 2022;19. Tran D-MT, Lekhak N, Gutierrez K, Moonie S. Risk factors associated with cardiovascular disease among adult Nevadans. PLoS ONE. 2021;16(2):e0247105. Vasan RS, Enserro DM, Xanthakis V, Beiser AS, Seshadri S. Temporal trends in the remaining lifetime risk of cardiovascular disease among middle-aged adults across 6 decades: the Framingham study. Circulation. 2022;145(17):1324–38. Dikaiou P, Björck L, Adiels M, Lundberg CE, Mandalenakis Z, Manhem K, et al. Obesity, overweight and risk for cardiovascular disease and mortality in young women. Eur J Prev Cardiol. 2021;28(12):1351–9. Sabiha ZUA, Rasool G, Zia T. Investigating Knowledge, Attitude and Practices of Under Graduate Students Regarding Obesity, in Peshawar, Pakistan. Pakistan J Med Health Sci. 2022;16(07):495. Khan S, Nauman H, Saher S, Imtiaz HA, Bibi A, Sajid H, et al. Gender difference in obesity prevalence among general population of Lahore, Pakistan. Eur J Med Health Sci. 2021;3(3):55–8. Asif M, Aslam M, Altaf S, Atif S, Majid A. Prevalence and sociodemographic factors of overweight and obesity among Pakistani adults. J Obes metabolic syndrome. 2020;29(1):58. Ibrahim S, Akram Z, Noreen A, Baig MT, Sheikh S, Huma A, et al. Overweight and obesity prevalence and predictors in people living in Karachi. J Pharm Res Int. 2021;33:194–202. Gadekar T, Dudeja P, Basu I, Vashisht S, Mukherji S. Correlation of visceral body fat with waist–hip ratio, waist circumference and body mass index in healthy adults: A cross sectional study. Med J Armed Forces India. 2020;76(1):41–6. Mills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223–37. Riaz M, Shah G, Asif M, Shah A, Adhikari K, Abu-Shaheen A. Factors associated with hypertension in Pakistan: A systematic review and meta-analysis. PLoS ONE. 2021;16(1):e0246085. Duran EK, Aday AW, Cook NR, Buring JE, Ridker PM, Pradhan AD. Triglyceride-rich lipoprotein cholesterol, small dense LDL cholesterol, and incident cardiovascular disease. J Am Coll Cardiol. 2020;75(17):2122–35. Basit A, Sabir S, Riaz M, Fawwad A. NDSP 05: Prevalence and pattern of dyslipidemia in urban and rural areas of Pakistan; a sub analysis from second National Diabetes Survey of Pakistan (NDSP) 2016–2017. J Diabetes Metabolic Disorders. 2020;19:1215–25. Dennis B, Aziz K, She L, Faruqui A, Davis C, Manolio TA, et al. High rates of obesity and cardiovascular disease risk factors in lower middle class community in Pakistan: the Metroville Health Study. J Pak Med Assoc. 2006;56(6):267–72. Hayes L, White M, Unwin N, Bhopal R, Fischbacher C, Harland J, et al. Patterns of physical activity and relationship with risk markers for cardiovascular disease and diabetes in Indian, Pakistani, Bangladeshi and European adults in a UK population. J Public Health. 2002;24(3):170–8. Tables Table. No.1, Sociodemographic Characteristics of the Participants VARIABLES FREQUENCY TOTAL (363) PERCENTAGE GENDER Male 236 65 Female 127 35 AGE Age group I (20-29Y) 236 65 Male 139 59 Female 97 41 Age group II (30-39Y) 127 35 Male 93 73.22 Female 34 26.77 EDUCATION Low 103 28.37 High 260 71.62 SOCIAL STATUS Low 98 27 Middle 200 55 High 65 18 Table. No.2, MEAN AND STANDARD DEVIATION OF VARIABLES IN AGE GROUPS: I AND II PARAMETERS GROUP I (n=236) GROUP II (n=127) Total (n=363) Age 25.7 ± 2.3 33.24 ± 3.3 29.05 ± 1.01 Height 1.63 ± 0.1 1.6 ± 0.1 1.6 ± 0.1 Weight 63.2 ± 10.5 71.9 ± 16.3 66.2 ± 13.4 BMI 23.8 ± 3.1 26.5 ± 5.2 24.7 ± 4.2 WC 82.7 ± 10.3 92.3 ± 11.7 86.0 ± 11.7 SBP 120.4 ± 10.9 126 ± 10.4 122.4 ± 11.0 DBP 81.3 ± 9.1 87.2 ± 8.9 83.4 ± 9.4 TC 135.9 ± 30.7 150.2 ± 40.1 140.9 ± 34.7 LDL 91.2 ± 20.2 92.4 ± 25.2 91.6 ± 21.9 TG 131.5 ± 54.3 157.96 ± 51.7 140.8 ± 54.5 HDL 48.1 ± 7.7 54.8 ± 26.9 50.5 ± 17.2 Glucose 98.6 ± 26.4 101.2 ± 28.1 99.5 ± 26.8 Table. No.3, COMPARISON OF INDIVIDUAL RISK FACTORS BETWEEN AGE GROUPS AGE GROUP I Total (n236) II Total (n127) P value INDIVIDUAL RISK FACTORS Obesity 40 (17%) 66 (52%) ˂0.05 Central obesity 69 (29%) 92 (72%) ˂0.05 Hypertension 61 (26%) 61 (48%) ˂0.05 Increased TC 09 (4%) 17 (13%) ˂0.05 Increased LDL 10 (2%) 15 (12%) >0.05 Increased TG 66 (28%) 61 (48%) ˂0.05 Hyperglycemia 09 (4%) 14(12%) >0.05 Less than required HDL 50 (21%) 47 (37%) ˂0.05 Inactive Lifestyle 186 (79%) 83 (65%) ˂0.05 Table.No4, CLUSTERING OF RISK FACTORS IN TOTAL SUBJECTS Frequency of Risk Factors Prevalence (n) Prevalence (%) 0 factors 87 24% At least 1 factor 276 76% 1 factor 83 23% 2 factors 88 24% 3 factors 40 11% 4 factors 36 10% 5 factors 22 6% 6 factors 04 1% 7 factors 04 1% Table No.5, COMPARISON OF CLUSTERING OF RISK FACTORS BETWEEN AGE GROUPS AGE GROUP I (20-29 yrs) II (30-40 yrs) Frequency of RF n % n % 0 factors 78 33 10 8 At least 1 factor 158 67 117 92 1 factor 66 28 15 12 2 factors 57 24 31 24 3 factors 26 11 15 12 4 factors 00 0 36 28 5 factors 05 2 15 12 6 factors 00 0 05 4 7 factors 05 2 00 0 Table No:06, AWARENESS OF CVD RISK FACTORS IN MALE AND FEMALE SUBJECTS GENDER Male Female Total AWARENESS ABOUT CVD RISK FACTORS Yes 39 24 63 No 129 71 200 Total 168 95 263 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4735932","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":338860391,"identity":"8d3c69a4-d991-460a-8e57-a5f01561d540","order_by":0,"name":"Shakil Ahmed Shaikh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIie3PMQuCQBTA8XccaMNF60VgX+GBYAl9k6Zo1QhahBYhqCVwdaqvYEtz4tBitBYtQp8gWgoaOoVwMh2D7j8dx/vBewAy2U/GgLjYBVCBXLMPSt0qhItJoDoAigepQiAjSisjUELa3iG8+WOudSgzpmPn1W8sBHk420KCp9GwGSDXzRkzLn6Mth8RlyzjSzHhDJsJ8kEQCVKfo+0KQsm8mLS9WH9+yCQl6zICO8tIF8sITUlQRvBkGaYvbsFImbRYrNsbQcJvt6SLnZevnob72ebOHM1eHaMweThfFsurYb5tlXmRmlQclMlksn/rDT1qU+n8ARkFAAAAAElFTkSuQmCC","orcid":"","institution":"Suleman Roshan Medical College","correspondingAuthor":true,"prefix":"","firstName":"Shakil","middleName":"Ahmed","lastName":"Shaikh","suffix":""},{"id":338860392,"identity":"377ac4e4-f017-4334-853a-0597cdc29f05","order_by":1,"name":"Salma Farukh Meomn","email":"","orcid":"","institution":"Liaquat University of Medical \u0026 Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Salma","middleName":"Farukh","lastName":"Meomn","suffix":""},{"id":338860393,"identity":"116e19a3-c1d7-45c0-a45e-b4f6822ffac2","order_by":2,"name":"Keenjhar Rani Laghari","email":"","orcid":"","institution":"Liaquat University of Medical \u0026 Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Keenjhar","middleName":"Rani","lastName":"Laghari","suffix":""},{"id":338860394,"identity":"babd60ec-e76e-4211-afe1-ac3376254976","order_by":3,"name":"Naila Hajira Rahu","email":"","orcid":"","institution":"Peoples University of Medical and Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Naila","middleName":"Hajira","lastName":"Rahu","suffix":""},{"id":338860395,"identity":"e45bd6c8-c531-4aec-b782-066f356fcefe","order_by":4,"name":"Hanozia Shah","email":"","orcid":"","institution":"Bilawal Medical College","correspondingAuthor":false,"prefix":"","firstName":"Hanozia","middleName":"","lastName":"Shah","suffix":""},{"id":338860396,"identity":"7ab722cb-b5bb-4b64-a5f0-bd47ff04a8d7","order_by":5,"name":"Zulfiqar Ali Laghari","email":"","orcid":"","institution":"University of Sindh","correspondingAuthor":false,"prefix":"","firstName":"Zulfiqar","middleName":"Ali","lastName":"Laghari","suffix":""}],"badges":[],"createdAt":"2024-07-13 16:38:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4735932/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4735932/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65165827,"identity":"fe07534e-f7d1-4f94-b53f-966e1299eb3c","added_by":"auto","created_at":"2024-09-24 09:54:36","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":511483,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4735932/v1/b981d287-7628-4bd8-a163-56dac4a0f063.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence of the Modifiable Risk Factors of Cardiovascular Diseases in Young Adults of District Hyderabad Sindh Pakistan","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTraditionally it is known that cardiovascular diseases affect the older aged population. Hence it is well documented nowadays that the higher frequency of the younger population is also affected by cardiovascular diseases. Early onset of these risk factors may lead to a longer duration of exposure thereby increasing the chances of developing cardiovascular diseases in the later half of life. Being aware of these trends in the young adult population is necessary of time to prevent cardiovascular diseases.\u003c/p\u003e\n\u003cp\u003eThe frequency of overweight and obesity in young adults has been a rising trend, that significantly contributes towards the development of increased blood pressure, dyslipidemia, and insulin resistance, these all are the risk factors for cardiovascular diseases \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Hypertension almost remained undiagnosed and untreated in the young population, and it is a major risk factor for cardiovascular diseases. Timely detection and treatment are essential to avoid the long-term development of cardiovascular diseases \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Abnormal lipid concentrations, including higher concentrations of LDL, TG, and decreased concentrations of HDL are increasingly detected in younger populations. Dyslipidemia is mainly caused by improper diet patterns, physical inactivity, and genetic traits \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Cigarette smoking and tobacco use are also one of the significant contributors for cardiovascular diseases. The new rising trend of vaping as an alternative to traditional smoking is also a bigger contributor, as the use of both causes endothelial dysfunction and the development of atherosclerosis \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Physical Inactivity: Sedentary lifestyles, prevalent among young adults, are linked to obesity, hypertension, and other cardiovascular risk factors. Promoting physical activity is crucial for cardiovascular health \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eConsumption of unhealthy diets, like diets with increased saturated fats, increased sodium, and higher levels of sugar is linked with increased cardiovascular diseases. On the other hand diet rich in fruits, vegetables, whole grains, and lean proteins has protective effects against cardiovascular disease \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eTherefore, early diagnosis and treatment of risk factors can prevent the development and progression of any type of cardiovascular disease \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Limiting the risk factors in the young population can lead to significant long-term health benefits, reducing the overall burden of cardiovascular diseases on the healthcare system \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. Understanding these risk factors benefits developing targeted health strategies among the young population, thus promoting healthier generations in the future \u003csup\u003e\u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eHence, the increasing frequency of cardiovascular disease risk factors among the young population is a public health concern that needs urgent consideration. These recent trends marked the necessity, therefore we aimed to find out the association of cardiovascular disease risk factors among the young healthy population.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003eThis study was designed as a cross-sectional comparative and conducted in the healthy population of different universities, college students, and employees of district Jamshoro from May 2022 to December 2022 after approval from the research ethical committee. Informed consent was taken from all participants before study. The sample size was collected by using the Epi info software calculator, with a 5% error margin and, a 95% confidence interval. About 300 healthy participants were approached and finally, 263 participants agreed with the response rate of 87.66% for this study. A random sampling technique was used to collect data. Participants below 40 years of age were recruited; participants with a history of any cardiovascular, diabetes, on medication, pregnant females, and those who are smokers were excluded. A self-prepared questionnaire was used to collect data from participants. The questionnaire included: sociodemographic characteristics, height, weight measurements to calculate BMI, and questions about physical activities, dietary habits, and questions to collect information about cardiovascular diseases. The BMI was calculated by standard method and South Asian scale was used for the measurement of BMI and blood pressure readings were taken by standard method. Blood pressure was measured by the digital apparatus MEDSIGN (Made in Shanghai, China). Fasting Blood sugar levels were obtained by glucometer (Easy max by Biotechnology Corp). Blood was collected in fasting for lipid profile and blood serums from samples were taken by centrifuging at Rpm of 2000 for five minutes. Then Serum was kept at -20 degrees Celsius until analyzed. The Microlab 300 (Merck) was used for sample analysis.\u003c/p\u003e\n\u003cp\u003eAssociations of all variables were analyzed: including BMI, all parameters of lipid profile, blood sugar levels, and physical activity. The differences in these variables were analyzed between both age groups. The average (Mean) and standard deviations (SD) of variables were obtained first by Microsoft Excel and then confirmed by SPSS (Statistical Package for Social Sciences) version 26.0 Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn this study, 300 participants were approached and 263 finally participated with a response rate of 87.66%. According to their age participants were divided into two groups. Group I include the participants aged from 20 to 29 and group II aged participants from 30\u0026ndash;40. The mean ages of the participants were 29.05\u0026thinsp;\u0026plusmn;\u0026thinsp;1.01. Out of 263, the male population was 168(64%) and females were 95 (36%), 171 (65.01%) were in group I and 91 (34.60%) were in group II. Table No.1 indicates the sociodemographic characteristics of participants. Table No.2, almost all risk factors were in age group II with central obesity being most prevalent with 72% of participants having increased waist circumference (P 0.0001). Dyslipidemia was almost twice more frequent in age group II and results were statistically significant for all but one parameter; LDL. The same goes for hyperglycemia with 12% sufferers in group II, in comparison to 4% in group I. However statistical significance failed to reach. Table No.3 that participants had one risk factor found in 76% of the study population. No risk factor was found in 24% of participants. Only 24% of the participants were found to have 2 risk factors, 11% of the participants were found to have 3 risk factors, and more than 3 risk factors were found in 18% of subjects. Table No. 4, below shows a comparison between the frequency of risk factors in male and female subjects. Both genders showed almost the same frequency of risk factors; however, the frequency was slightly increased in male subjects. 79% of male subjects had at least 1 risk factor, in comparison to 70% of females having at least 1 risk factor. More female subjects (30%) were clear of risk factors as compared to 21% of male subjects. Table No.5 the difference was much higher in the frequency of risk factors when age group I was compared with age group II. Increasing age showed the increasing frequency of CVD risk factors. Subjects in the older age group (II) had risk factors more. 33% of subjects of age group I were free from CVD risk factors, while only 8% of subjects of age group II had no risk factor. A whopping percentage (92%) of subjects belonging to age group II had at least one risk factor. Table No.6 the results for awareness of CVD risk factors were almost equal in both groups. Only 24% were aware of CVD risk factors; the rest of the 76% of subjects did not know CVD risk factors and their effects.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAt present,\u0026nbsp;limited studies have been conducted\u0026nbsp;to find out the frequency\u0026nbsp;of\u0026nbsp;diseases associated with cardiovascular and their risk factors in the young healthy population of Pakistan. The studies that were conducted were associated with the population aged more than 40 years of age which is also very\u0026nbsp;limited\u0026nbsp;to\u0026nbsp;almost\u0026nbsp;non-existent.\u0026nbsp;Furthermore,\u0026nbsp;studies\u0026nbsp;conducted with the difference in frequency of cardiovascular risk factors between the young population and\u0026nbsp;older population are also limited. Hence, it was a very difficult task to compare this\u0026nbsp;study\u0026nbsp;with the studies done in the past.\u003c/p\u003e\n\u003cp\u003eIn this study, we assessed the overall prevalence of risk factors in young adults (\u0026lt;40 years of\u0026nbsp;age). The increase in the\u0026nbsp;prevalence\u0026nbsp;of\u0026nbsp;risk factors with increasing\u0026nbsp;age\u0026nbsp;was\u0026nbsp;also examined. The results achieved with this study are mostly in agreement with the majority of the literature\u0026nbsp;available. More risk factors were available in male subjects; a fact widely accepted is that\u0026nbsp;the\u0026nbsp;male population is higher at risk for cardiovascular disease. A similar trend was found by\u0026nbsp;Tran D-MT et al\u0026nbsp;\u003ca href=\"#_ENREF_10\" title=\"Tran, 2021 #49\"\u003e\u003csup\u003e10\u003c/sup\u003e\u003c/a\u003e.\u0026nbsp; Another vital finding was the\u0026nbsp;increase in the prevalence of risk factors with increasing age; which has been consistent\u0026nbsp;time\u0026nbsp;and\u0026nbsp;again\u0026nbsp;in\u0026nbsp;other\u0026nbsp;investigations, similarly RS Vasan\u0026nbsp;\u003ca href=\"#_ENREF_11\" title=\"Vasan, 2022 #50\"\u003e\u003csup\u003e11\u003c/sup\u003e\u003c/a\u003e conducted a Framingham study with a sample size of 317849. Thus, concluding that males are\u0026nbsp;more\u0026nbsp;at risk for\u0026nbsp;developing\u0026nbsp;CVDs and\u0026nbsp;this risk becomes higher with increasing age.\u003c/p\u003e\n\u003cp\u003eObesity is one of the major CVD risk factors. Pakistan was ranked as the 9\u003csup\u003eth\u003c/sup\u003e most obese\u0026nbsp;country in the world. In this study also obesity was found as one of the most prevalent\u0026nbsp;CVD risk factors. 30% of all subjects were found to be overweight or obese according to\u0026nbsp;BMI. The prevalence of obesity was less in males (29%) as compared to females (30%).\u0026nbsp;The finding of this study is inconsistent with different Tran D-MT et al\u0026nbsp;\u003ca href=\"#_ENREF_10\" title=\"Tran, 2021 #49\"\u003e\u003csup\u003e10\u003c/sup\u003e\u003c/a\u003e conducted cross-sectional population-based research from 2011 and 2017 found increased BMI major cause of \u0026nbsp;CVD risk factor. Pigi Dikaiou et al\u0026nbsp;\u003ca href=\"#_ENREF_12\" title=\"Dikaiou, 2021 #51\"\u003e\u003csup\u003e12\u003c/sup\u003e\u003c/a\u003e conducted a prospective study in Sweden and documented a slightly J-shaped association of BMI with CVD risk factor.\u0026nbsp;Studies were done in Pakistan that have found\u0026nbsp;the\u0026nbsp;prevalence\u0026nbsp;of\u0026nbsp;obesity\u0026nbsp;in\u0026nbsp;young\u0026nbsp;adult\u0026nbsp;Pakistanis\u0026nbsp;in\u0026nbsp;between\u0026nbsp;25\u0026nbsp;-35%\u0026nbsp;by Z UA Sabhia et al\u0026nbsp;\u003ca href=\"#_ENREF_13\" title=\"Sabiha, 2022 #52\"\u003e\u003csup\u003e13\u003c/sup\u003e\u003c/a\u003e and\u0026nbsp;obesity\u0026nbsp;as\u0026nbsp;being\u0026nbsp;more\u0026nbsp;prevalent\u0026nbsp;in\u0026nbsp;females\u0026nbsp;as\u0026nbsp;compared\u0026nbsp;to\u0026nbsp;males\u0026nbsp;with\u0026nbsp;only a small margin of difference. Later findings also match several studies which\u0026nbsp;show\u0026nbsp;a\u0026nbsp;higher\u0026nbsp;prevalence\u0026nbsp;of\u0026nbsp;obesity in\u0026nbsp;females\u0026nbsp;in\u0026nbsp;comparison\u0026nbsp;to\u0026nbsp;males\u0026nbsp;by S Khan\u0026nbsp;et al\u0026nbsp;\u003ca href=\"#_ENREF_14\" title=\"Khan, 2021 #53\"\u003e\u003csup\u003e14\u003c/sup\u003e\u003c/a\u003e. M Asif et\u0026nbsp;al\u0026nbsp;\u003ca href=\"#_ENREF_15\" title=\"Asif, 2020 #54\"\u003e\u003csup\u003e15\u003c/sup\u003e\u003c/a\u003e, \u0026nbsp;S Ibrahim et\u0026nbsp;al\u0026nbsp;\u003ca href=\"#_ENREF_16\" title=\"Ibrahim, 2021 #55\"\u003e\u003csup\u003e16\u003c/sup\u003e\u003c/a\u003e. We found waist circumference as being more prevalent in females than in male subjects\u0026nbsp;and there was an increase in waist circumference with increasing age. These results highly\u0026nbsp;matched the investigation done by Gadekar et al\u0026nbsp;\u003ca href=\"#_ENREF_17\" title=\"Gadekar, 2020 #56\"\u003e\u003csup\u003e17\u003c/sup\u003e\u003c/a\u003e, who also observed\u0026nbsp;higher\u0026nbsp;waist\u0026nbsp;circumferences\u0026nbsp;in\u0026nbsp;females\u0026nbsp;which\u0026nbsp;were\u0026nbsp;found\u0026nbsp;to\u0026nbsp;increase\u0026nbsp;with\u0026nbsp;increasing\u0026nbsp;age.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHypertension\u0026nbsp;is\u0026nbsp;a\u0026nbsp;distinguished,\u0026nbsp;highly studied,\u0026nbsp;and\u0026nbsp;established\u0026nbsp;risk\u0026nbsp;factor\u0026nbsp;for\u0026nbsp;the\u0026nbsp;development of CVDs. The \u003cstrong\u003eJoint National Committee on Prevention, Detection, Evaluation,\u0026nbsp;and Treatment of High Blood Pressure\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003ein their seventh report has emphasized that\u0026nbsp;systolic more than diastolic Blood Pressure is strongly related to CVDs. Thus, our study\u0026nbsp;has\u0026nbsp;mostly\u0026nbsp;emphasized systolic blood pressure. The combined overall frequency of pre-hypertension and hypertension combined was\u0026nbsp;34%. These results were similar to a study done by Tran D-MT et al\u0026nbsp;\u003ca href=\"#_ENREF_10\" title=\"Tran, 2021 #49\"\u003e\u003csup\u003e10\u003c/sup\u003e\u003c/a\u003e, who found\u0026nbsp;the prevalence of hypertension in people above 40 years of age to be 38%. The\u0026nbsp;difference\u0026nbsp;in\u0026nbsp;age group\u0026nbsp;is\u0026nbsp;sufficient\u0026nbsp;to address\u0026nbsp;this\u0026nbsp;slight difference\u0026nbsp;in\u0026nbsp;prevalence. Incidence of hypertension was found higher in males as compared to female subjects at 22%; these results were in\u0026nbsp;agreement with studies done by \u0026nbsp;Mills et al\u0026nbsp;\u003ca href=\"#_ENREF_18\" title=\"Mills, 2020 #57\"\u003e\u003csup\u003e18\u003c/sup\u003e\u003c/a\u003e and M Riaz et al\u0026nbsp;\u003ca href=\"#_ENREF_19\" title=\"Riaz, 2021 #58\"\u003e\u003csup\u003e19\u003c/sup\u003e\u003c/a\u003e, (who showed HTN as being more\u0026nbsp;prevalent\u0026nbsp;in males than in\u0026nbsp;females).\u003c/p\u003e\n\u003cp\u003eAnother important risk factor, Dyslipidemia (the presence of an elevated concentration of as a minimum one\u0026nbsp;category of cholesterol/lipid) was prevalent in 35% of participants with increased triglycerides as\u0026nbsp;the\u0026nbsp;most prevalent of all cholesterol types. Similar results were achieved by EK Duran et al\u0026nbsp;\u003ca href=\"#_ENREF_20\" title=\"Duran, 2020 #59\"\u003e\u003csup\u003e20\u003c/sup\u003e\u003c/a\u003e, and Abdul Basit et al\u0026nbsp;\u003ca href=\"#_ENREF_21\" title=\"Basit, 2020 #61\"\u003e\u003csup\u003e21\u003c/sup\u003e\u003c/a\u003e who diagnosed 31% of subjects with dyslipidemia\u0026nbsp;and\u0026nbsp;found impaired triglyceride\u0026nbsp;levels as most prevalent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDiabetes\u0026nbsp;not\u0026nbsp;only\u0026nbsp;directly\u0026nbsp;affects\u0026nbsp;the\u0026nbsp;integrity\u0026nbsp;of\u0026nbsp;the\u0026nbsp;vascular\u0026nbsp;system, but\u0026nbsp;also\u0026nbsp;impacts\u0026nbsp;other\u0026nbsp;cardiovascular risk factors. A\u0026nbsp;satisfying number\u0026nbsp;of studies\u0026nbsp;have revealed higher levels\u0026nbsp;of Dyslipidemia in diabetics as compared to non-diabetics. The\u0026nbsp;prevalence of hyperglycemia was 7% in total subjects with being higher prevalent in male\u0026nbsp;subjects.\u0026nbsp;No\u0026nbsp;diabetics\u0026nbsp;were\u0026nbsp;found\u0026nbsp;in\u0026nbsp;this\u0026nbsp;study,\u0026nbsp;a\u0026nbsp;possible\u0026nbsp;explanation\u0026nbsp;for\u0026nbsp;this\u0026nbsp;might\u0026nbsp;be\u0026nbsp;the limited sample size. MHS study by Barbar Dennis et al and Kalim Uddin Aziz et al\u0026nbsp;\u003ca href=\"#_ENREF_22\" title=\"Dennis, 2006 #63\"\u003e\u003csup\u003e22\u003c/sup\u003e\u003c/a\u003e showed hyperglycemia in 8-10% of subjects.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA sedentary or less active lifestyle leads to increased deposits of fat in the body causing obesity\u0026nbsp;and subsequent risk factors. This risk factor was found to be prevalent in 74% of total\u0026nbsp;subjects. Louise Hayes et.al\u0026nbsp;\u003ca href=\"#_ENREF_23\" title=\"Hayes, 2002 #64\"\u003e\u003csup\u003e23\u003c/sup\u003e\u003c/a\u003e. compared activity levels among the Indian and Pakistani populations with that of Europe and found that Europeans were more physically active than Indians, Pakistanis, or Bangladeshis. Their study showed that 52 percent of European men did not meet the required levels of physical activity, compared to 71 percent of Indians, 88 percent of Pakistanis, and 87 percent of Bangladeshis. Similar findings were documented for women. In conclusion, European men and women participated more frequently in moderate to intense sports and exercise activities as compared to Pakistani and Indians. Thus lack of exercise combined with inappropriate diet (high fat, high car, high calorie) are responsible for the growing epidemic of obesity (and subsequent risk factors) in Pakistan. Females were less active as compared to male subjects. A possible reason for this might be that women mostly believe domestic responsibilities as working out and consider that working at home keeps them physically active and thus they don\u0026rsquo;t need exercise, which is not true on biological grounds. Household chores are time-consuming but are not energy-consuming and thus less energy is consumed during 1 hour of household chores as compared to half an hour of intense walking or 15 minutes of jogging. This might also be the reason behind the findings that women are more obese, both generally and physically. In addition, cultural inhibitions combined with a lack of awareness don\u0026rsquo;t allow women to go out on jogging tracks or gyms. But men are allowed to go out and therefore nowadays the number of men engaging in jogging, swimming, sports gyming, and other activities is increasing. Furthermore, awareness about cardiovascular risk factors was less in the majority of subjects. Only 24% of subjects were moderate to high level aware of cardiovascular risk factors. The remaining did not know whatsoever about cardiovascular risk factors and their destructive effects on health. The lack of awareness co-relates with the increased incidence of cardiovascular risk factors. The less a person is aware of risk factors, the more he will succumb.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe majority of participants analyzed in this study (76%) had at least one risk factor. Such a high\u0026nbsp;prevalence of cardiovascular risk factors in young adults is an alarming finding. Young\u0026nbsp;adults with a lack of exercise, poor quality, high-fat diet, and lack of awareness about\u0026nbsp;cardiovascular diseases and cardiovascular risk factors are moving towards the development\u0026nbsp;of\u0026nbsp;an\u0026nbsp;unhealthy\u0026nbsp;generation.\u0026nbsp;These\u0026nbsp;risk\u0026nbsp;factors\u0026nbsp;not\u0026nbsp;only lead\u0026nbsp;to\u0026nbsp;cardiovascular\u0026nbsp;diseases\u0026nbsp;but also compromise\u0026nbsp;the\u0026nbsp;quality\u0026nbsp;of life\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInactive lifestyle, Central obesity, Dyslipidemia, hypertension, and obesity were the most prevalent cardiovascular risk factors. Furthermore, 4 risk factors were more prevalent in male subjects; increased Triglycerides, Hypertension, Hyperglycemia, less than desired HDL, and increased LDL, as compared to female subjects. These results indicate male population is slightly more at risk for developing CVDs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical Approval:\u003c/h2\u003e\n\u003cp\u003eThe study was approved by the ethical and research committee of the University of Sindh Jamshoro (No. DRGS/1601-01-21).\u003c/p\u003e\n\u003ch2\u003eConsent for publication:\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eCompeting Interests:\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eNo funding\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003e1. Shakil Ahmed Shaikh, concept/ Design Study, initial write-up of manuscript2. Salma Farukh Memon, critical analysis, correction of manuscript3. Keenjhar Rani Laghari, Data Collection and data interpretation4. Naila Hajira Rahu, data collection, critical analysis5. Hanozia Shah, data collection and data interpretation 6. Zulfiqar Ali Laghari. Final Approval and Supervision\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data will be available when required\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRen J, Wu NN, Wang S, Sowers JR, Zhang Y. Obesity cardiomyopathy: evidence, mechanisms, and therapeutic implications. Physiol Rev. 2021;101(4):1745\u0026ndash;807.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eParati G, Stergiou GS, Bilo G, Kollias A, Pengo M, Ochoa JE, et al. Home blood pressure monitoring: methodology, clinical relevance and practical application: a 2021 position paper by the Working Group on Blood Pressure Monitoring and Cardiovascular Variability of the European Society of Hypertension. 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Risk factors associated with cardiovascular disease among adult Nevadans. PLoS ONE. 2021;16(2):e0247105.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVasan RS, Enserro DM, Xanthakis V, Beiser AS, Seshadri S. Temporal trends in the remaining lifetime risk of cardiovascular disease among middle-aged adults across 6 decades: the Framingham study. Circulation. 2022;145(17):1324\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDikaiou P, Bj\u0026ouml;rck L, Adiels M, Lundberg CE, Mandalenakis Z, Manhem K, et al. Obesity, overweight and risk for cardiovascular disease and mortality in young women. Eur J Prev Cardiol. 2021;28(12):1351\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSabiha ZUA, Rasool G, Zia T. Investigating Knowledge, Attitude and Practices of Under Graduate Students Regarding Obesity, in Peshawar, Pakistan. Pakistan J Med Health Sci. 2022;16(07):495.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhan S, Nauman H, Saher S, Imtiaz HA, Bibi A, Sajid H, et al. Gender difference in obesity prevalence among general population of Lahore, Pakistan. Eur J Med Health Sci. 2021;3(3):55\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsif M, Aslam M, Altaf S, Atif S, Majid A. Prevalence and sociodemographic factors of overweight and obesity among Pakistani adults. J Obes metabolic syndrome. 2020;29(1):58.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIbrahim S, Akram Z, Noreen A, Baig MT, Sheikh S, Huma A, et al. Overweight and obesity prevalence and predictors in people living in Karachi. J Pharm Res Int. 2021;33:194\u0026ndash;202.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGadekar T, Dudeja P, Basu I, Vashisht S, Mukherji S. Correlation of visceral body fat with waist\u0026ndash;hip ratio, waist circumference and body mass index in healthy adults: A cross sectional study. Med J Armed Forces India. 2020;76(1):41\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMills KT, Stefanescu A, He J. The global epidemiology of hypertension. Nat Rev Nephrol. 2020;16(4):223\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRiaz M, Shah G, Asif M, Shah A, Adhikari K, Abu-Shaheen A. Factors associated with hypertension in Pakistan: A systematic review and meta-analysis. PLoS ONE. 2021;16(1):e0246085.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuran EK, Aday AW, Cook NR, Buring JE, Ridker PM, Pradhan AD. Triglyceride-rich lipoprotein cholesterol, small dense LDL cholesterol, and incident cardiovascular disease. J Am Coll Cardiol. 2020;75(17):2122\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBasit A, Sabir S, Riaz M, Fawwad A. NDSP 05: Prevalence and pattern of dyslipidemia in urban and rural areas of Pakistan; a sub analysis from second National Diabetes Survey of Pakistan (NDSP) 2016\u0026ndash;2017. J Diabetes Metabolic Disorders. 2020;19:1215\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDennis B, Aziz K, She L, Faruqui A, Davis C, Manolio TA, et al. High rates of obesity and cardiovascular disease risk factors in lower middle class community in Pakistan: the Metroville Health Study. J Pak Med Assoc. 2006;56(6):267\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHayes L, White M, Unwin N, Bhopal R, Fischbacher C, Harland J, et al. Patterns of physical activity and relationship with risk markers for cardiovascular disease and diabetes in Indian, Pakistani, Bangladeshi and European adults in a UK population. J Public Health. 2002;24(3):170\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable. No.1, Sociodemographic Characteristics of the Participants\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003e\u003cstrong\u003eVARIABLES\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u003cstrong\u003eFREQUENCY\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eTOTAL\u0026nbsp;(363)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e\u003cstrong\u003ePERCENTAGE\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\u003cstrong\u003eGENDER\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eMale\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;236\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e65\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eFemale\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 127\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e35\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\u003cstrong\u003eAGE\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eAge\u0026nbsp;group I\u0026nbsp;(20-29Y)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 236\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e65\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eMale\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 139\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e59\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eFemale\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;97\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e41\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eAge\u0026nbsp;group II\u0026nbsp;(30-39Y)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;127\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e35\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eMale\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;93\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e73.22\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eFemale\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;34\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e26.77\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\u003cstrong\u003eEDUCATION\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eLow\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 103\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e28.37\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eHigh\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 260\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e71.62\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"3\" valign=\"top\"\u003e\u003cstrong\u003eSOCIAL STATUS\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eLow\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;98\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e27\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eMiddle\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 200\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e55\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.05084745762712%\" valign=\"top\"\u003eHigh\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.389830508474574%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 65\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e18\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eTable. No.2, MEAN AND STANDARD DEVIATION OF VARIABLES IN AGE GROUPS: I AND II\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u003cstrong\u003ePARAMETERS\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u003cstrong\u003eGROUP\u0026nbsp;I\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n=236)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u003cstrong\u003eGROUP\u0026nbsp;II\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n=127)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(n=363)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eAge\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e25.7\u0026nbsp;\u0026plusmn;\u0026nbsp;2.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e33.24\u0026nbsp;\u0026plusmn; 3.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u0026nbsp;29.05 \u0026plusmn; 1.01\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eHeight\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e1.63\u0026nbsp;\u0026plusmn;\u0026nbsp;0.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e1.6\u0026nbsp;\u0026plusmn;\u0026nbsp;0.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e1.6\u0026nbsp;\u0026plusmn;\u0026nbsp;0.1\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eWeight\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e63.2\u0026nbsp;\u0026plusmn;\u0026nbsp;10.5\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e71.9\u0026nbsp;\u0026plusmn;\u0026nbsp;16.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e66.2\u0026nbsp;\u0026plusmn;\u0026nbsp;13.4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eBMI\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e23.8\u0026nbsp;\u0026plusmn;\u0026nbsp;3.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e26.5\u0026nbsp;\u0026plusmn;\u0026nbsp;5.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e24.7\u0026nbsp;\u0026plusmn;\u0026nbsp;4.2\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eWC\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e82.7\u0026nbsp;\u0026plusmn;\u0026nbsp;10.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e92.3\u0026nbsp;\u0026plusmn;\u0026nbsp;11.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e86.0\u0026nbsp;\u0026plusmn;\u0026nbsp;11.7\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eSBP\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e120.4\u0026nbsp;\u0026plusmn; 10.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e126\u0026nbsp;\u0026plusmn;\u0026nbsp;10.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e122.4\u0026nbsp;\u0026plusmn; 11.0\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eDBP\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e81.3\u0026nbsp;\u0026plusmn;\u0026nbsp;9.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e87.2\u0026nbsp;\u0026plusmn;\u0026nbsp;8.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e83.4\u0026nbsp;\u0026plusmn;\u0026nbsp;9.4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eTC\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e135.9\u0026nbsp;\u0026plusmn; 30.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;150.2 \u0026plusmn; 40.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e140.9\u0026nbsp;\u0026plusmn; 34.7\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eLDL\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e91.2\u0026nbsp;\u0026plusmn;\u0026nbsp;20.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e92.4\u0026nbsp;\u0026plusmn;\u0026nbsp;25.2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e91.6\u0026nbsp;\u0026plusmn;\u0026nbsp;21.9\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eTG\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e131.5\u0026nbsp;\u0026plusmn; 54.3\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp;157.96 \u0026plusmn; 51.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e140.8\u0026nbsp;\u0026plusmn; 54.5\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eHDL\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e48.1\u0026nbsp;\u0026plusmn;\u0026nbsp;7.7\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e54.8\u0026nbsp;\u0026plusmn;\u0026nbsp;26.9\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e50.5\u0026nbsp;\u0026plusmn;\u0026nbsp;17.2\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003eGlucose\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e98.6\u0026nbsp;\u0026plusmn;\u0026nbsp;26.4\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;101.2 \u0026plusmn; 28.1\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e99.5\u0026nbsp;\u0026plusmn;\u0026nbsp;26.8\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable. No.3, COMPARISON OF INDIVIDUAL RISK FACTORS BETWEEN AGE GROUPS\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003e\u003cstrong\u003eAGE\u0026nbsp;GROUP\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; I\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003eTotal\u0026nbsp;(n236)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eII\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003eTotal\u0026nbsp;(n127)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u003cstrong\u003e\u003cem\u003eP\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003evalue\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"85.59322033898304%\" colspan=\"3\" valign=\"top\"\u003e\u003cstrong\u003eINDIVIDUAL\u0026nbsp;RISK\u0026nbsp;FACTORS\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eObesity\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e40\u0026nbsp;(17%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e66\u0026nbsp;(52%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026nbsp; ˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eCentral\u0026nbsp;obesity\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e69\u0026nbsp;(29%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e92\u0026nbsp;(72%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026nbsp; ˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eHypertension\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e61\u0026nbsp;(26%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e61\u0026nbsp;(48%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026nbsp; ˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eIncreased\u0026nbsp;TC\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e09\u0026nbsp;(4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e17\u0026nbsp;(13%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eIncreased\u0026nbsp;LDL\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e10\u0026nbsp;(2%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e15\u0026nbsp;(12%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026gt;0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eIncreased\u0026nbsp;TG\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e66\u0026nbsp;(28%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e61\u0026nbsp;(48%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp;˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eHyperglycemia\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e09\u0026nbsp;(4%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e14(12%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e\u0026gt;0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eLess\u0026nbsp;than required\u003cbr\u003eHDL\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e50\u0026nbsp;(21%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e47\u0026nbsp;(37%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.627118644067796%\" valign=\"top\"\u003eInactive\u0026nbsp;Lifestyle\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.47457627118644%\" valign=\"top\"\u003e186\u0026nbsp;(79%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"29.491525423728813%\" valign=\"top\"\u003e83\u0026nbsp;(65%)\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"14.40677966101695%\" valign=\"top\"\u003e˂0.05\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable.No4, CLUSTERING OF RISK FACTORS IN TOTAL SUBJECTS\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e\u003cstrong\u003eFrequency\u0026nbsp;of\u0026nbsp;Risk\u0026nbsp;Factors\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e\u003cstrong\u003ePrevalence\u0026nbsp;(n)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e\u003cstrong\u003ePrevalence\u0026nbsp;(%)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e0\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e87\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e24%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003eAt\u0026nbsp;least\u0026nbsp;1\u0026nbsp;factor\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e276\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e76%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e1\u0026nbsp;factor\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e83\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e23%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e2\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e88\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e24%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e3\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e40\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e11%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e4\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e36\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e10%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e5\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e22\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e6%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e6\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e04\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e1%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.76271186440678%\" valign=\"top\"\u003e7\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"30.677966101694917%\" valign=\"top\"\u003e04\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"33.559322033898304%\" valign=\"top\"\u003e1%\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable No.5, COMPARISON OF CLUSTERING OF RISK FACTORS BETWEEN AGE GROUPS\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e\u003cstrong\u003eAGE\u0026nbsp;GROUP\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"37.6271186440678%\" colspan=\"2\" valign=\"top\"\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; I\u0026nbsp;\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(20-29\u0026nbsp;yrs)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"38.813559322033896%\" colspan=\"2\" valign=\"top\"\u003e\u003cstrong\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; II\u003c/strong\u003e\u003cbr\u003e\u003cstrong\u003e(30-40\u0026nbsp;yrs)\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e\u003cstrong\u003eFrequency\u0026nbsp;of\u0026nbsp;RF\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; n\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; %\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003en\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; %\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e0\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e78\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;33\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e10\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e8\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003eAt\u0026nbsp;least\u0026nbsp;1\u0026nbsp;factor\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e158\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;67\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e117\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e92\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e1\u0026nbsp;factor\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e66\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 28\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e12\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e2\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e57\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; 24\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e31\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e24\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e3\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e26\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;11\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e12\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e4\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e00\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e36\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e28\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e5\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e05\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e15\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e12\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e6\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e00\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;0\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e05\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e4\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"23.559322033898304%\" valign=\"top\"\u003e7\u0026nbsp;factors\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.305084745762713%\" valign=\"top\"\u003e05\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.322033898305083%\" valign=\"top\"\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;2\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"18.8135593220339%\" valign=\"top\"\u003e00\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e0\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Table No:06, AWARENESS OF CVD RISK FACTORS IN MALE AND FEMALE SUBJECTS\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.304568527918782%\" valign=\"top\"\u003e\u003cstrong\u003eGENDER\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"31.810490693739425%\" valign=\"top\"\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.426395939086294%\" valign=\"top\"\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.4585448392555%\" valign=\"top\"\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"80.50847457627118%\" colspan=\"3\" valign=\"top\"\u003e\u003cstrong\u003eAWARENESS\u0026nbsp;ABOUT\u0026nbsp;CVD\u0026nbsp;RISK\u0026nbsp;FACTORS\u003c/strong\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.491525423728813%\" valign=\"top\"\u003e\u0026nbsp;\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.304568527918782%\" valign=\"top\"\u003eYes\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"31.810490693739425%\" valign=\"top\"\u003e39\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.426395939086294%\" valign=\"top\"\u003e24\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.4585448392555%\" valign=\"top\"\u003e63\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.304568527918782%\" valign=\"top\"\u003eNo\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"31.810490693739425%\" valign=\"top\"\u003e129\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.426395939086294%\" valign=\"top\"\u003e71\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.4585448392555%\" valign=\"top\"\u003e200\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.304568527918782%\" valign=\"top\"\u003eTotal\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"31.810490693739425%\" valign=\"top\"\u003e168\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"28.426395939086294%\" valign=\"top\"\u003e95\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"19.4585448392555%\" valign=\"top\"\u003e263\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Cardiovascular Disease, Risk Factors, Young Adults","lastPublishedDoi":"10.21203/rs.3.rs-4735932/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4735932/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003eThe main purpose of this study is to determine CVD risk factors in the healthy population of district Jamshoro, Sindh.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology:\u003c/strong\u003eThe cross-sectional study was conducted from July 2023 to December 2023, in this study, apparently healthy young adults of not more than 40 years of age were included. A self-designed questionnaire was set for the collection of data. Blood pressure was taken by the standard method through a digital apparatus, BMI was calculated by South Asian standards, and the blood sample was taken after 10 hours of fasting for lipid profile and fasting blood sugar. Collected data was analyzed by SPSS version 26.0.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eIn this study, one risk factor was found in 76% of the participants, and Obesity was found in 29% and 30% respectively in male and female participants. Central obesity was found higher in females 61% than in males 35%. Male participants had been found to have a higher systolic blood pressure than females 40% and 22% respectively. Cholesterol and blood sugar levels were found higher in 7%, triglyceride level was found higher in 35%, and HDL was less than the desired level in 26% of the population. LDL was prevalent in 6% of all the participants.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This study concluded that 3 risk factors were found higher in females, and 4 risk factors were found higher in males, thus making the male population more prone for affected by CVD even at an early age. In addition, all risk factors were more prevalent in people over 30 years of age. Therefore results of the study were similar to most studies done.\u003c/p\u003e","manuscriptTitle":"Prevalence of the Modifiable Risk Factors of Cardiovascular Diseases in Young Adults of District Hyderabad Sindh Pakistan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-20 09:00:05","doi":"10.21203/rs.3.rs-4735932/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"389f1b6d-35ca-4bd2-9b89-d60a18d01574","owner":[],"postedDate":"August 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-10-29T05:53:35+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-20 09:00:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4735932","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4735932","identity":"rs-4735932","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}