Role of Hypertension and Obesity as Risk Factors for IHD

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Ghaffari, Abdul Samad Ahmadi This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2466103/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 Background Hypertension and obesity are two major modifiable risk factors for CAD, most of the time there will be more than two risk factors in an IHD. Obesity itself cause insulin resistance to initiate type − 2 DM. is the most common and significant RFs for IHD, and proper BP management is the cornerstone of both direct and indirect prevention. Overweight and obesity account for more than 80% of CHD patients. Obesity is sometimes viewed as a "minor" CHD RF, however it is a widely effective risk-factor approach. A range of "major" risk factors have been proven to be significantly influenced by weight loss, including HTN, hyperlipidemia and insulin resistance/T2DM. Aim To assess arterial hypertension and obesity as risk factors of IHD. Methods This cross sectional study which was done retrospectively by collecting data from database of "Scientific Research Institute of Cardiology and Internal Diseases" Almaty city, Kazakhstan during 2020. IHD confirmed by history,physical exam, angiography and other lab findings. Result The research involved a total of 649 participants. The mean age of study population was 64.2 ± 9.24 (P = 0,000).Mean of SBP and DBP were 180.73 ± 34.9; 99.48 ± 14.28 mmHg respectively. Number of female with normal BMI 50(21.6%), overweight 93(40.10%), obesity class – 1, 59(25.4%), obesity class – 2, 23(9.90%) and obesity class – 3, 7(3%), (P = 0.486). Number of male with underweight BMI 1(0.20%), normal BMI 96(23%), overweight 190(45.6%), obesity class – 1, 89(21.3%), obesity class – 2, 29(7%) and obesity class – 3, 12(2.9%). (P = 0.486). Mean of BMI in both gender was (28.72 ± 11.79). Conclusion The burden of CVDs and their related risk factors is significant in Almaty, posing a major public health concern. For accurate management and implementation of preventive measures in this area, effective strategies in management, education, and healthcare centers are needed. Cardiac & Cardiovascular Systems Body Mass Index Hypertension Overweight Obesity IHD Introduction The most compelling evidence of causality, as well as a high prevalence of exposure, is related to high blood pressure. There is, however, considerable evidence that a physiologically normal blood pressure in humans is significantly lower than what is often used in clinical practice and science, leading in underreporting of blood pressure as a CVD risk factor (1). HTN and diabetes mellitus are two conditions that are intricately related and increase the risk of cardiovascular disease.(2). HTN was seen in 57.2 % of acute myocardial infarction (AMI) patients in South Korea, while diabetes was discovered in 32.3 percent (3).Hypertension is a substantial independent predictor of all-cause mortality and cardiac death (CD) in people who have had an AMI (4).In individuals with ST-segment elevation MI, DM is a significant independent prognostic factor of restenosis following percutaneous coronary intervention (PCI) and is linked to an increased risk of both early and late death (STEMI)(5Despite the fact that HTN and diabetes are well-known RFs for coronary heart disease, there have been few face investigations assessing their impact on long-term clinical outcomes in AMI patients following coronary artery stenting. Obesity is an independent risk factor for coronary artery disease (6).Obesity has also been associated to a faster deterioration of CHD after a diagnosis.Obesity and overweight people are more prone to insulin resistance and T2DM, which can lead to CHD and make the prognosis worse (7).As a result, CHD progresses more quickly, and the prognosis deteriorates.Furthermore, insulin resistance and T2DM are associated to renal, ophthalmic, neurologic, and cerebrovascular problems.Obesity is a widely successful intervention, even though it is often viewed as a "small" independent CHD risk factor. Weight loss may have a major impact on hypertension, dyslipidemia, and insulin resistance/T2DM, among other "big" risk factors (8).Unlike other CHD risk factor mitigation methods like exercise and, more broadly, cardiac rehabilitation, cardiac rehabilitation (CR) recommends at least 150 minutes of moderate activity each week to avoid numerous chronic diseases, according to the Physical Activity Guidelines for Americans.However, this quantity of exercise has not been demonstrated to be sufficient for weight loss in overweight/obese persons, and weight loss is assisted when physical activity is combined with calorie restriction in the diet. Despite some evidence of an inverse relationship between overweight/obesity and mortality, described as the "obesity paradox," weight loss recommendations are provided for almost all obese CHD patients.Obesity and health outcomes have a contradictory link, according to studies that looked at people with CAD, HF, hypertension, and peripheral artery disease (9).Even in the absence of comorbidities, as extra adipose tissue grows in excess amounts, a variety of adaptations/alterations in heart shape and function occur (10). Obesity and overweight are linked to both traditional and unconventional CVD risk factors, resulting in CVD in general and CHDin particular.Obesity is frequently considered a risk factor.The metabolic syndrome, of which central obesity is a prominent component, is associated to CVD, including heart disease, as an independent risk factor.There is a lot of epidemiologic evidence to suggest that being overweight and having heart disease are linked.Postmortem study and coronary artery imaging investigations provide less convincing evidence (11).Almaty, like other nations, experienced an epidemiological change. NCDs are the top causes of death in Almaty, Kazakhstan.The majority of the information comes from a hospital database.The purpose of this research is to establish a relationship between hyperlipidemia and hypertension with coronary heart disease, as well as to determine whether systolic or diastolic hypertension is linked to IHD, and to determine the function of overweight and obesity as a key modifiable risk factor for IHD. Justification of the choice of articles and goals and objectives Aim : To study the hypertension and obesity as risk factor of IHD. Objectives: Relationship of hypertension, obesity with gender in IHD patients. Relationship of hypertension, obesity with age category. Contribution of multiple risk factors in presence of IHD. Methodology This is a descriptive and retrospective cross sectional study of 649 IHD registered patients in "Scientific Research Institute of Cardiology and Internal Diseases" Almaty city, Kazakhstan during 2020.A consecutive non random sampling was adopted by combining all patients with IHD. Hypertension, obesity as major modifiable risk factors were compared with age, sex, DM, lipid profile and previous IHD. Patients were not included if they treated in emergency room, left hospital before optimal hospitalization date and without echocardiography report. For statistical analysis IBM SPSS statistics 22 and Excel were used. Chi squire test, is used to compare categorical variables and P < 0.05 was considered significant. Independent T test performed with 95% CI to compare scale variable with categorical variable. One sample T test with 95% CI used to compare mean of LVEF in our study with mean of LVEF in other literatures. Data are presented as the number of patients andmean ± SD( 11 ). Results The study enlisted the participation of 649 participants. The individuals' socio-demographic characteristics and the burden of cardiovascular risk factors are shown.Data was seen according to age group distribution and gender. The mean of age in study population is 64.2 years (63.15 in male and 66.09 in female), (P = 0,000). Systolic blood pressure 6(2.6%) of female and 17(4.1%) of male had normal arterial blood pressure, 5(2.2%) of female and 26(6.2%) of male had elevated arterial blood pressure, 2(0.9%) female and 12(2.9%) of male had stage – 1 HTN,44(19%) female and 140(33.6%) of male had stage – 2 HTN,175(75.4%) of female and 222(53.2%) of male had hypertensive crisis, (P = 0,000). Mean of SBP 180.73mmHg ± 34.956, number of participants with SBP equal to 180 mmHg were more (Mode).Maximum and minimum of SBP were 300mmHg, 90 mmHg respectively. Diastolic blood pressure 3(1.3%) of female and 2(0.5%) of male had normal arterial blood pressure, 4(1.7%) of female and 16(3.8%) of male had elevated arterial blood pressure, 23(9.9%) female and 62(14.9%) of male had stage – 1 HTN,189(81.5%) female and 333(79.9%) of male had stage – 2 HTN,13(5.6%) of female and 4(1%) of male had hypertensive crisis(P = 0.001).Mean of DBP 99.48 mmHg,100mmHg, number of participant with DBP equal to 100 mmHg were more(Mode).Maximum and minimum of DBP were 150mmHg,60 mmHg respectively. Note In this study I include maximum of peak of SBP and DBP . Table 1 - Comparison of SBP, DBP mean with sex Mean of SBP according to sex Sex N Mean Std. Deviation Std. Error Mean SBP Male 417 175.40 34.382 1.684 Female 232 190.33 33.987 2.231 DBP Male 417 97.52 13.184 .646 Female 232 103.02 15.471 1.016 Table 2 Comparison of SBP, DBP mean with sex Independent Samples Test Compare means of SBP,DBP with Sex Levene's T Test of differences F Sig. t df Sig. (2-tailed) Mean Difference Std. Error Difference 95% CI Lower Upper SBP Equal variances assumed .781 .377 -5.324 647 .000 -14.932 2.805 -20.439 -9.425 Equal variances not assumed -5.342 482.14 .000 -14.932 2.795 -20.424 -9.439 DBP Equal variances assumed 3.518 .061 -4.781 647 .000 -5.499 1.150 -7.758 -3.241 Equal variances not assumed -4.569 417.5 .000 -5.499 1.204 -7.865 -3.134 Number of female with normal BMI 50(21.6%), overweight 93(40.10%), obesity class – 1, 59(25.4%), obesity class – 2, 23(9.90%) and obesity class – 3, 7(3%). (P = 0.486). Number of male with underweight BMI 1(0.20%), normal BMI 96(23%), overweight 190(45.6%), obesity class – 1, 89(21.3%), obesity class – 2, 29(7%) and obesity class – 3, 12(2.9%). (P = 0.486). Mean of BMI in both gender was (28.72 ± 11.79).Lipid profile analysis in our study showed that mean of total cholesterol was 4.714 ± 2.09 mmol/l, HDLc1.1135 ± 0.3374mmol/l, LDLc 3.017 ± 1.046mmol/l, triglyceride 1.7589 ± 0.951mmol/l. 28.5% had abnormal total cholesterol (high, intermediate), 91.6% had low and intermediate level of HDLc, 34.5% with abnormal level of LDLc (high, intermediate), 60.4% had abnormal triglyceride level (high and intermediate). Table 3 Blood pressure stages, BMI category in IHD patients Variables Female Male Test of differences Number /Percent N % N % χ2 DF P value SBP category Normal 6 2.60 17 4.10% 32.159 4 0,000 Elevated BP 5 2.20 26 6.20% Stage − 1 2 0.90 12 2.90% Stage − 2 44 19.00 140 33.60% H - Crisis 175 75.40 222 53.20% DBP Category Normal 3 1.30 2 0.50% 18.556 4 0.001 Elevated BP 4 1.70 16 3.80% Stage − 1 23 9.90 62 14.90% Stage − 2 189 81.50 333 79.90% H - Crisis 13 5.60 4 1.00% BMI Category Underweight 0 0.00 1 0.20% 4.486 5 0.486 Discussion We considered the role of hypertension and obesity as risk factors of IHD among patients who visited "Scientific Research Institute of Cardiology and Internal Diseases" Almaty city, Kazakhstan during 2020.This is the first study after COVID − 19 pandemic in Almaty, Kazakhstan. Mean of SBP according to sex are[male(175.4 ± 34.382),female(190.987 ± 33.987)],and mean of DBP based on sex are[ male(97.52 ± 13.184),female(103.02 ± 15.471), but mean of SBP in general was 180 ± 34.956 and DBP mean was 99.48 ± 14.278 .Male vs female ratio was 1:79.In comparison with another study which was done byDhungana,et al in 2018 on 347 participant showed that 34.4% had high blood pressure,and mean of SBP was 122.6 ± 16.9 (P = 0.07), and mean of DBP was 81.1 ± 9.9(P = 0.017),( 13 ),which has significantly differences from our findings. The same as described study ,there were 39 840 participants (18–86 years, mean age 47.9 ± 16.2 years), 17964 (45.1%) men and 21 876 (54.9%) women. mean of SBP 123.3 ± 16( male125.1 ± 14.7 ; female 121.8 ± 16.8),DBP mean was 78.7 ± 9.6( male 80.1 ± 9.3 ;female 121.8 ± 16.8) ( 14 ).Reasons of high SBP and DBP in our study may be due to; In this study we selected peak of SBP and DBP during whole life of patients, beside that number of vegetarians in compare to non – vegetarians were low, level of knowledge regarding to hypertension prevention, benefit of daily physical activities was lower than aforementioned study, furthermore some of participant did not remember the correct value of their blood pressure. In our study mean of BMI was 28.72 ± 5.152 (male 28.52 ± 5.04; female 29.09 ± 5.33). 77.7% had obesity and overweight .Number of female with normal BMI 50(21.6%), overweight 93(40.10%), obesity class – 1, 59(25.4%), obesity class – 2, 23(9.90%) and obesity class – 3, 7(3%). Number of male with underweight BMI 1(0.20%), normal BMI 96(23%), overweight 190(45.6%), obesity class – 1, 89(21.3%), obesity class – 2, 29(7%) and obesity class – 3, 12(2.9%). (P = 0.486).In 2016, the global burden of disease (GBD) for risk profiles in the Middle East and North Africa (MENA) showed that 80.7% of participant had obesity and over weight( P < 0.001), ( 15 ).Dhungana,et al in 2018 performed on 347 participant .15.3% were obese and.mean of BMI in this study was 26.2 ± 5.1.mean of BMI was more in female than male (26 ± 5.1, 25.4 ± 5.3) respectively (P = 0.03),( 13 ). In one another performed study mean of BMI was 23.4 ± 3.2 ( male 23.6 ± 3 ; female 23.2 ± 3.3) ,( 14 ).Strenuous daily physical activities, being vegetarian will be the reasons for decline BMI in this study.Finding of lipid profile in our study showed that mean of total cholesterol was 4.714 ± 2.09 mmol/l, HDLc1.1135 ± 0.3374 mmol/l, LDLc 3.017 ± 1.046 mmol/l, triglyceride 1.7589 ± 0.951 mmol/l. 28.5% had abnormal total cholesterol (high, intermediate), 91.6% had low and intermediate level of HDLc, 34.5% with abnormal level of LDLc (high, intermediate), 60.4% had abnormal triglyceride level (high and intermediate).In a study which was done in Palastine showed ; 8.8% had total cholesterol level ≥ 6.2mmol/l( P < 0.001), 8.45% LDLc ≥ 4.137mmol/l (P = 0.001) ,70% low HDLc ( P = 0.847) and 40.2% TG ≥ 1.693mmol/l ( P = 0.006)( 15 ).Other study on 296 participants showed; total cholesterol mean 4.34 ± 0.814; HDLc 1.09 ± 0.168; HDL 2.534 ± 0.68 and TG was1.535 ± 0.759 mg/dl ( 14 ). Conclusion This single center based study exhibited significant differences in arterial blood pressure for both gender. There was an ascending link between increasing age and elevation of systolic blood pressure in IHD patients. In Almaty, the burden of IHD and their associated risk factors were high and included; arterial hypertension, diabetes mellitus, obesity, previous IHD, and hyperlipidemia that made a major public health concerns. Effective strategies in administration, education, and healthcare centers are needed for accurate management and implementation of preventive measures in this field. References Fuchs FD, Whelton PK. High Blood Pressure and Cardiovascular Disease. Hypertension. 2020;(Cvd):285–92. Mancia G. The association of hypertension and diabetes: Prevalence, cardiovascular risk and protection by blood pressure reduction. Acta Diabetol. 2005;42(SUPPL. 1):17–25. Kim Y, Ahn Y, Cho MC, Kim CJ, Kim YJ, Jeong MH. Current status of acute myocardial infarction in Korea. Korean J Intern Med. 2019;34(1):1–10. Rosendorff C, Lackland DT, Allison M, Aronow WS, Black HR, Blumenthal RS, et al. Treatment of hypertension in patients with coronary artery disease: A scientific statement from the american heart association, american college of cardiology, and american society of hypertension. Vol. 131, Circulation. 2015. 435–470 p. Teven S, Affner MH, Eppo S, Ehto L, Apani T, Önnemaa R, et al. MOR TALITY FROM CORONARY HEAR T DISEASE IN SUB JEC TS WITH AND WITHOUT TYPE 2 DIABETES MORTALITY FROM CORONARY HEART DISEASE IN SUBJECTS WITH TYPE 2 DIABETES AND IN NONDIABETIC SUBJECTS WITH AND WITHOUT PRIOR MYOCARDIAL INFARCTION A BSTRACT Background Typ. N Engl J Med. 1998;339:229–34. Turpie AGG, Bauer KA, Eriksson BI, Lassen MR. Overweight and obesity as determinants of cardiovascular risk: The Framingham experience. Arch Intern Med. 2002;162(16):1867–72. Grundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Curr Opin Cardiol. 2006;21(1):1–6. Ades PA, Savage PD, Toth MJ, Harvey-Berino J, Schneider DJ, Bunn JY, et al. High-calorie-expenditure exercise: A new approach to cardiac rehabilitation for overweight coronary patients. Circulation. 2009;119(20):2671–8. Sierra-Johnson J, Wright SR, Lopez-Jimenez F, Allison TG. Relation of body mass index to fatal and nonfatal cardiovascular events after cardiac rehabilitation. Am J Cardiol. 2005;96(2):211–4. Lavie CJ, Milani R V., Ventura HO. Obesity and Cardiovascular Disease. Risk Factor, Paradox, and Impact of Weight Loss. J Am Coll Cardiol [Internet]. 2009;53(21):1925–32. Available from: http://dx.doi.org/10.1016/j.jacc.2008.12.068 Katta N, Loethen T, Lavie CJ, Alpert MA. Obesity and Coronary Heart Disease: Epidemiology, Pathology, and Coronary Artery Imaging. Curr Probl Cardiol [Internet]. 2021;46(3):100655. Available from: https://doi.org/10.1016/j.cpcardiol.2020.100655 Casey DE, Thomas RJ, Bhalla V, Commodore-Mensah Y, Heidenreich PA, Kolte D, et al. 2019 AHA/ACC clinical performance and quality measures for adults with high blood pressure: A report of the american college of cardiology/american heart association task force on performance measures. Vol. 12, Circulation: Cardiovascular Quality and Outcomes. 2019. 1–48 p. Dhungana RR, Thapa P, Devkota S, Banik PC, Gurung Y, Mumu SJ, et al. Prevalence of cardiovascular disease risk factors: A community-based cross-sectional study in a peri-urban community of Kathmandu, Nepal. Indian Heart J. 2018;70:S20–7. Hong X, Ye Q, He J, Wang Z, Yang H, Qi S, et al. Prevalence and clustering of cardiovascular risk factors: A cross-sectional survey among Nanjing adults in China. BMJ Open. 2018;8(6):1–13. Shahwan AJ, Abed Y, Desormais I, Magne J, Preux PM, Aboyans V, et al. Epidemiology of coronary artery disease and stroke and associated risk factors in Gaza community -Palestine. PLoS One. 2019;14(1):1–11. Declarations Ethical Approval All of the authors have given consent for the article's publication. Competing Interests The authors have no interest in financial aspects; they just need the journal's cooperation for next article publication. Authors’ contribution Mohammad Mujtaba Ghaffari Abdul Samad Ahmadi 2 Aida Akhenbaeva Kyat Biandivich Abzaliev Natalya Glushkova Funding We wrote this article with our own financial support. Availability of data and materials The row data was compiled from the Almaty-based National Research Institute of Cardiology and Internal Medicine's database.( [email protected] ). Additional Declarations Ethical Approval: This article was approved by the Ethical Committee of Al-Farabi Kazakh National University and the administration of the Scientific Research Institute of Cardiology and Internal Diseases and Professor Kuat Abzaliev is the Dean of this hospital ( [email protected] ). DECLARATION OF COMPETING INTERESTS: None is declared under financial, general, and institutional competing interests. We had full access to all study data, take full responsibility for the accuracy of the data analysis, and have authority over manuscript preparation and decisions to submit the manuscript for publication. Supplementary Files DATAOFGHAFFARIMOHAMMADMUJTABA.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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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-2466103","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":166796835,"identity":"066feec7-93a7-43dd-9474-ab6587368b3e","order_by":0,"name":"Mohammad Mujtaba. 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There is, however, considerable evidence that a physiologically normal blood pressure in humans is significantly lower than what is often used in clinical practice and science, leading in underreporting of blood pressure as a CVD risk factor (1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHTN and diabetes mellitus are two conditions that are intricately related and increase the risk of cardiovascular disease.(2). HTN was seen in 57.2 % of acute myocardial infarction (AMI) patients in South Korea, while diabetes was discovered in 32.3 percent (3).Hypertension is a substantial independent predictor of all-cause mortality and cardiac death (CD) in people who have had an AMI (4).In individuals with ST-segment elevation MI, DM is a significant independent prognostic factor of restenosis following percutaneous coronary intervention (PCI) and is linked to an increased risk of both early and late death (STEMI)(5Despite the fact that HTN and diabetes are well-known RFs for coronary heart disease, there have been few face investigations assessing their impact on long-term clinical outcomes in AMI patients following coronary artery stenting.\u003c/p\u003e\n\u003cp\u003eObesity is an independent risk factor for coronary artery disease (6).Obesity has also been associated to a faster deterioration of CHD after a diagnosis.Obesity and overweight people are more prone to insulin resistance and T2DM, which can lead to CHD and make the prognosis worse (7).As a result, CHD progresses more quickly, and the prognosis deteriorates.Furthermore, insulin resistance and T2DM are associated to renal, ophthalmic, neurologic, and cerebrovascular problems.Obesity is a widely successful intervention, even though it is often viewed as a \u0026quot;small\u0026quot; independent CHD risk factor.\u003c/p\u003e\n\u003cp\u003eWeight loss may have a major impact on hypertension, dyslipidemia, and insulin resistance/T2DM, among other \u0026quot;big\u0026quot; risk factors (8).Unlike other CHD risk factor mitigation methods like exercise and, more broadly, cardiac rehabilitation, cardiac rehabilitation (CR) recommends at least 150 minutes of moderate activity each week to avoid numerous chronic diseases, according to the Physical Activity Guidelines for Americans.However, this quantity of exercise has not been demonstrated to be sufficient for weight loss in overweight/obese persons, and weight loss is assisted when physical activity is combined with calorie restriction in the diet. Despite some evidence of an inverse relationship between overweight/obesity and mortality, described as the \u0026quot;obesity paradox,\u0026quot; weight loss recommendations are provided for almost all obese CHD patients.Obesity and health outcomes have a contradictory link, according to studies that looked at people with CAD, HF, hypertension, and peripheral artery disease (9).Even in the absence of comorbidities, as extra adipose tissue grows in excess amounts, a variety of adaptations/alterations in heart shape and function occur (10).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eObesity and overweight are linked to both traditional and unconventional CVD risk factors, resulting in CVD in general and CHDin particular.Obesity is frequently considered a risk factor.The metabolic syndrome, of which central obesity is a prominent component, is associated to CVD, including heart disease, as an independent risk factor.There is a lot of epidemiologic evidence to suggest that being overweight and having heart disease are linked.Postmortem study and coronary artery imaging investigations provide less convincing evidence (11).Almaty, like other nations, experienced an epidemiological change. NCDs are the top causes of death in Almaty, Kazakhstan.The majority of the information comes from a hospital database.The purpose of this research is to establish a relationship between hyperlipidemia and hypertension with coronary heart disease, as well as to determine whether systolic or diastolic hypertension is linked to IHD, and to determine the function of overweight and obesity as a key modifiable risk factor for IHD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eJustification of the choice of articles and goals and objectives\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAim\u003c/strong\u003e: To study the hypertension and obesity as risk factor of IHD.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eRelationship of hypertension, obesity with gender in IHD patients.\u003c/li\u003e\n \u003cli\u003eRelationship of hypertension, obesity with age category.\u003c/li\u003e\n \u003cli\u003eContribution of multiple risk factors in presence of IHD.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Methodology","content":"\u003cp\u003eThis is a descriptive and retrospective cross sectional study of 649 IHD registered patients in \"Scientific Research Institute of Cardiology and Internal Diseases\" Almaty city, Kazakhstan during 2020.A consecutive non random sampling was adopted by combining all patients with IHD. Hypertension, obesity as major modifiable risk factors were compared with age, sex, DM, lipid profile and previous IHD. Patients were not included if they treated in emergency room, left hospital before optimal hospitalization date and without echocardiography report. For statistical analysis IBM SPSS statistics 22 and Excel were used. Chi squire test, is used to compare categorical variables and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered significant. Independent T test performed with 95% CI to compare scale variable with categorical variable. One sample T test with 95% CI used to compare mean of LVEF in our study with mean of LVEF in other literatures. Data are presented as the number of patients andmean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study enlisted the participation of 649 participants. The individuals' socio-demographic characteristics and the burden of cardiovascular risk factors are shown.Data was seen according to age group distribution and gender. The mean of age in study population is 64.2 years (63.15 in male and 66.09 in female), (P\u0026thinsp;=\u0026thinsp;0,000).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSystolic blood pressure\u003c/strong\u003e \u003cp\u003e6(2.6%) of female and 17(4.1%) of male had normal arterial blood pressure, 5(2.2%) of female and 26(6.2%) of male had elevated arterial blood pressure, 2(0.9%) female and 12(2.9%) of male had stage \u0026ndash; 1 HTN,44(19%) female and 140(33.6%) of male had stage \u0026ndash; 2 HTN,175(75.4%) of female and 222(53.2%) of male had hypertensive crisis, (P\u0026thinsp;=\u0026thinsp;0,000). Mean of SBP 180.73mmHg\u0026thinsp;\u0026plusmn;\u0026thinsp;34.956, number of participants with SBP equal to 180 mmHg were more (Mode).Maximum and minimum of SBP were 300mmHg, 90 mmHg respectively.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eDiastolic blood pressure\u003c/strong\u003e \u003cp\u003e3(1.3%) of female and 2(0.5%) of male had normal arterial blood pressure, 4(1.7%) of female and 16(3.8%) of male had elevated arterial blood pressure, 23(9.9%) female and 62(14.9%) of male had stage \u0026ndash; 1 HTN,189(81.5%) female and 333(79.9%) of male had stage \u0026ndash; 2 HTN,13(5.6%) of female and 4(1%) of male had hypertensive crisis(P\u0026thinsp;=\u0026thinsp;0.001).Mean of DBP 99.48 mmHg,100mmHg, number of participant with DBP equal to 100 mmHg were more(Mode).Maximum and minimum of DBP were 150mmHg,60 mmHg respectively.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eNote\u003c/strong\u003e \u003cp\u003e \u003cem\u003eIn this study I include maximum of peak of SBP and DBP\u003c/em\u003e.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003eComparison of SBP, DBP mean with sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eMean of SBP according to sex\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStd. Deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eStd. Error Mean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e175.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34.382\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.684\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.987\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.231\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.184\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e.646\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e232\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of SBP, DBP mean with sex\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"11\" nameend=\"c11\" namest=\"c1\"\u003e \u003cp\u003eIndependent Samples Test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" morerows=\"2\" nameend=\"c2\" namest=\"c1\" rowspan=\"3\"\u003e \u003cp\u003eCompare means of SBP,DBP with Sex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eLevene's T\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c11\" namest=\"c5\"\u003e \u003cp\u003eTest of differences\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003edf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMean Difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStd. Error Difference\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eLower\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eUpper\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEqual variances assumed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-5.324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-14.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-20.439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-9.425\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEqual variances not assumed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-5.342\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e482.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-14.932\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.795\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-20.424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-9.439\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eDBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEqual variances assumed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.061\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.781\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e647\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-7.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-3.241\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEqual variances not assumed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-4.569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e417.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-5.499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.204\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-7.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e-3.134\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNumber of female with normal BMI 50(21.6%), overweight 93(40.10%), obesity class \u0026ndash; 1, 59(25.4%), obesity class \u0026ndash; 2, 23(9.90%) and obesity class \u0026ndash; 3, 7(3%). (P\u0026thinsp;=\u0026thinsp;0.486). Number of male with underweight BMI 1(0.20%), normal BMI 96(23%), overweight 190(45.6%), obesity class \u0026ndash; 1, 89(21.3%), obesity class \u0026ndash; 2, 29(7%) and obesity class \u0026ndash; 3, 12(2.9%). (P\u0026thinsp;=\u0026thinsp;0.486). Mean of BMI in both gender was (28.72\u0026thinsp;\u0026plusmn;\u0026thinsp;11.79).Lipid profile analysis in our study showed that mean of total cholesterol was 4.714\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09 mmol/l, HDLc1.1135\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3374mmol/l, LDLc 3.017\u0026thinsp;\u0026plusmn;\u0026thinsp;1.046mmol/l, triglyceride 1.7589\u0026thinsp;\u0026plusmn;\u0026thinsp;0.951mmol/l. 28.5% had abnormal total cholesterol (high, intermediate), 91.6% had low and intermediate level of HDLc, 34.5% with abnormal level of LDLc (high, intermediate), 60.4% had abnormal triglyceride level (high and intermediate).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBlood pressure stages, BMI category in IHD patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eTest of differences\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber /Percent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eχ2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eDF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSBP category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e32.159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0,000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage \u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage \u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e33.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH - Crisis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDBP Category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.50%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e18.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eElevated BP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.80%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage \u0026minus;\u0026thinsp;1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStage \u0026minus;\u0026thinsp;2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e333\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79.90%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eH - Crisis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI Category\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnderweight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.486\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.486\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe considered the role of hypertension and obesity as risk factors of IHD among patients who visited \"Scientific Research Institute of Cardiology and Internal Diseases\" Almaty city, Kazakhstan during 2020.This is the first study after COVID \u0026minus;\u0026thinsp;19 pandemic in Almaty, Kazakhstan.\u003c/p\u003e \u003cp\u003eMean of SBP according to sex are[male(175.4\u0026thinsp;\u0026plusmn;\u0026thinsp;34.382),female(190.987\u0026thinsp;\u0026plusmn;\u0026thinsp;33.987)],and mean of DBP based on sex are[ male(97.52\u0026thinsp;\u0026plusmn;\u0026thinsp;13.184),female(103.02\u0026thinsp;\u0026plusmn;\u0026thinsp;15.471), but mean of SBP in general was 180\u0026thinsp;\u0026plusmn;\u0026thinsp;34.956 and DBP mean was 99.48\u0026thinsp;\u0026plusmn;\u0026thinsp;14.278 .Male vs female ratio was 1:79.In comparison with another study which was done byDhungana,et al in 2018 on 347 participant showed that 34.4% had high blood pressure,and mean of SBP was 122.6\u0026thinsp;\u0026plusmn;\u0026thinsp;16.9 (P\u0026thinsp;=\u0026thinsp;0.07), and mean of DBP was 81.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9(P\u0026thinsp;=\u0026thinsp;0.017),(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e),which has significantly differences from our findings.\u003c/p\u003e \u003cp\u003eThe same as described study ,there were 39 840 participants (18\u0026ndash;86 years, mean age 47.9\u0026thinsp;\u0026plusmn;\u0026thinsp;16.2 years), 17964 (45.1%) men and 21 876 (54.9%) women. mean of SBP 123.3\u0026thinsp;\u0026plusmn;\u0026thinsp;16( male125.1\u0026thinsp;\u0026plusmn;\u0026thinsp;14.7 ; female 121.8\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8),DBP mean was 78.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6( male 80.1\u0026thinsp;\u0026plusmn;\u0026thinsp;9.3 ;female 121.8\u0026thinsp;\u0026plusmn;\u0026thinsp;16.8) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).Reasons of high SBP and DBP in our study may be due to; In this study we selected peak of SBP and DBP during whole life of patients, beside that number of vegetarians in compare to non \u0026ndash; vegetarians were low, level of knowledge regarding to hypertension prevention, benefit of daily physical activities was lower than aforementioned study, furthermore some of participant did not remember the correct value of their blood pressure.\u003c/p\u003e \u003cp\u003eIn our study mean of BMI was 28.72\u0026thinsp;\u0026plusmn;\u0026thinsp;5.152 (male 28.52\u0026thinsp;\u0026plusmn;\u0026thinsp;5.04; female 29.09\u0026thinsp;\u0026plusmn;\u0026thinsp;5.33). 77.7% had obesity and overweight .Number of female with normal BMI 50(21.6%), overweight 93(40.10%), obesity class \u0026ndash; 1, 59(25.4%), obesity class \u0026ndash; 2, 23(9.90%) and obesity class \u0026ndash; 3, 7(3%). Number of male with underweight BMI 1(0.20%), normal BMI 96(23%), overweight 190(45.6%), obesity class \u0026ndash; 1, 89(21.3%), obesity class \u0026ndash; 2, 29(7%) and obesity class \u0026ndash; 3, 12(2.9%). (P\u0026thinsp;=\u0026thinsp;0.486).In 2016, the global burden of disease (GBD) for risk profiles in the Middle East and North Africa (MENA) showed that 80.7% of participant had obesity and over weight( P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).Dhungana,et al in 2018 performed on 347 participant .15.3% were obese and.mean of BMI in this study was 26.2\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1.mean of BMI was more in female than male (26\u0026thinsp;\u0026plusmn;\u0026thinsp;5.1, 25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.3) respectively (P\u0026thinsp;=\u0026thinsp;0.03),(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). In one another performed study mean of BMI was 23.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.2 ( male 23.6\u0026thinsp;\u0026plusmn;\u0026thinsp;3 ; female 23.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3) ,(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).Strenuous daily physical activities, being vegetarian will be the reasons for decline BMI in this study.Finding of lipid profile in our study showed that mean of total cholesterol was 4.714\u0026thinsp;\u0026plusmn;\u0026thinsp;2.09 mmol/l, HDLc1.1135\u0026thinsp;\u0026plusmn;\u0026thinsp;0.3374 mmol/l, LDLc 3.017\u0026thinsp;\u0026plusmn;\u0026thinsp;1.046 mmol/l, triglyceride 1.7589\u0026thinsp;\u0026plusmn;\u0026thinsp;0.951 mmol/l. 28.5% had abnormal total cholesterol (high, intermediate), 91.6% had low and intermediate level of HDLc, 34.5% with abnormal level of LDLc (high, intermediate), 60.4% had abnormal triglyceride level (high and intermediate).In a study which was done in Palastine showed ; 8.8% had total cholesterol level\u0026thinsp;\u0026ge;\u0026thinsp;6.2mmol/l( P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), 8.45% LDLc\u0026thinsp;\u0026ge;\u0026thinsp;4.137mmol/l (P\u0026thinsp;=\u0026thinsp;0.001) ,70% low HDLc ( P\u0026thinsp;=\u0026thinsp;0.847) and 40.2% TG\u0026thinsp;\u0026ge;\u0026thinsp;1.693mmol/l ( P\u0026thinsp;=\u0026thinsp;0.006)(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).Other study on 296 participants showed; total cholesterol mean 4.34\u0026thinsp;\u0026plusmn;\u0026thinsp;0.814; HDLc 1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.168; HDL 2.534\u0026thinsp;\u0026plusmn;\u0026thinsp;0.68 and TG was1.535\u0026thinsp;\u0026plusmn;\u0026thinsp;0.759 mg/dl (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis single center based study exhibited significant differences in arterial blood pressure for both gender. There was an ascending link between increasing age and elevation of systolic blood pressure in IHD patients.\u003c/p\u003e \u003cp\u003eIn Almaty, the burden of IHD and their associated risk factors were high and included; arterial hypertension, diabetes mellitus, obesity, previous IHD, and hyperlipidemia that made a major public health concerns. Effective strategies in administration, education, and healthcare centers are needed for accurate management and implementation of preventive measures in this field.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFuchs FD, Whelton PK. High Blood Pressure and Cardiovascular Disease. Hypertension. 2020;(Cvd):285\u0026ndash;92.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMancia G. The association of hypertension and diabetes: Prevalence, cardiovascular risk and protection by blood pressure reduction. Acta Diabetol. 2005;42(SUPPL. 1):17\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim Y, Ahn Y, Cho MC, Kim CJ, Kim YJ, Jeong MH. Current status of acute myocardial infarction in Korea. Korean J Intern Med. 2019;34(1):1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRosendorff C, Lackland DT, Allison M, Aronow WS, Black HR, Blumenthal RS, et al. Treatment of hypertension in patients with coronary artery disease: A scientific statement from the american heart association, american college of cardiology, and american society of hypertension. Vol.\u0026nbsp;131, Circulation. 2015. 435\u0026ndash;470 p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTeven S, Affner MH, Eppo S, Ehto L, Apani T, \u0026Ouml;nnemaa R, et al. MOR TALITY FROM CORONARY HEAR T DISEASE IN SUB JEC TS WITH AND WITHOUT TYPE 2 DIABETES MORTALITY FROM CORONARY HEART DISEASE IN SUBJECTS WITH TYPE 2 DIABETES AND IN NONDIABETIC SUBJECTS WITH AND WITHOUT PRIOR MYOCARDIAL INFARCTION A BSTRACT Background Typ. N Engl J Med. 1998;339:229\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTurpie AGG, Bauer KA, Eriksson BI, Lassen MR. Overweight and obesity as determinants of cardiovascular risk: The Framingham experience. Arch Intern Med. 2002;162(16):1867\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGrundy SM, Cleeman JI, Daniels SR, Donato KA, Eckel RH, Franklin BA, et al. Diagnosis and management of the metabolic syndrome An American Heart Association/National Heart, Lung, and Blood Institute scientific statement. Curr Opin Cardiol. 2006;21(1):1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdes PA, Savage PD, Toth MJ, Harvey-Berino J, Schneider DJ, Bunn JY, et al. High-calorie-expenditure exercise: A new approach to cardiac rehabilitation for overweight coronary patients. Circulation. 2009;119(20):2671\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSierra-Johnson J, Wright SR, Lopez-Jimenez F, Allison TG. Relation of body mass index to fatal and nonfatal cardiovascular events after cardiac rehabilitation. Am J Cardiol. 2005;96(2):211\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLavie CJ, Milani R V., Ventura HO. Obesity and Cardiovascular Disease. Risk Factor, Paradox, and Impact of Weight Loss. J Am Coll Cardiol [Internet]. 2009;53(21):1925\u0026ndash;32. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.1016/j.jacc.2008.12.068\u003c/span\u003e\u003cspan address=\"10.1016/j.jacc.2008.12.068\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatta N, Loethen T, Lavie CJ, Alpert MA. Obesity and Coronary Heart Disease: Epidemiology, Pathology, and Coronary Artery Imaging. Curr Probl Cardiol [Internet]. 2021;46(3):100655. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.cpcardiol.2020.100655\u003c/span\u003e\u003cspan address=\"10.1016/j.cpcardiol.2020.100655\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCasey DE, Thomas RJ, Bhalla V, Commodore-Mensah Y, Heidenreich PA, Kolte D, et al. 2019 AHA/ACC clinical performance and quality measures for adults with high blood pressure: A report of the american college of cardiology/american heart association task force on performance measures. Vol.\u0026nbsp;12, Circulation: Cardiovascular Quality and Outcomes. 2019. 1\u0026ndash;48 p.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDhungana RR, Thapa P, Devkota S, Banik PC, Gurung Y, Mumu SJ, et al. Prevalence of cardiovascular disease risk factors: A community-based cross-sectional study in a peri-urban community of Kathmandu, Nepal. Indian Heart J. 2018;70:S20\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHong X, Ye Q, He J, Wang Z, Yang H, Qi S, et al. Prevalence and clustering of cardiovascular risk factors: A cross-sectional survey among Nanjing adults in China. BMJ Open. 2018;8(6):1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShahwan AJ, Abed Y, Desormais I, Magne J, Preux PM, Aboyans V, et al. Epidemiology of coronary artery disease and stroke and associated risk factors in Gaza community -Palestine. PLoS One. 2019;14(1):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll of the authors have given consent for the article\u0026apos;s publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no interest in financial aspects; they just need the journal\u0026apos;s cooperation for next article publication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMohammad Mujtaba Ghaffari\u003c/p\u003e\n\u003cp\u003eAbdul Samad Ahmadi\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eAida Akhenbaeva \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eKyat Biandivich Abzaliev\u003c/p\u003e\n\u003cp\u003eNatalya Glushkova\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe wrote this article with our own financial support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe row data was compiled from the Almaty-based National Research Institute of Cardiology and Internal Medicine\u0026apos;s database.(\u003ca href=\"mailto:[email protected]\" target=\"_blank\"\[email protected]\u003c/a\u003e).\u0026nbsp;\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Al-Farabi Kazakh National University","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":"Body Mass Index, Hypertension, Overweight, Obesity, IHD","lastPublishedDoi":"10.21203/rs.3.rs-2466103/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2466103/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHypertension and obesity are two major modifiable risk factors for CAD, most of the time there will be more than two risk factors in an IHD. Obesity itself cause insulin resistance to initiate type \u0026minus;\u0026thinsp;2 DM. is the most common and significant RFs for IHD, and proper BP management is the cornerstone of both direct and indirect prevention. Overweight and obesity account for more than 80% of CHD patients. Obesity is sometimes viewed as a \"minor\" CHD RF, however it is a widely effective risk-factor approach. A range of \"major\" risk factors have been proven to be significantly influenced by weight loss, including HTN, hyperlipidemia and insulin resistance/T2DM.\u003c/p\u003e\u003ch2\u003eAim\u003c/h2\u003e \u003cp\u003eTo assess arterial hypertension and obesity as risk factors of IHD.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross sectional study which was done retrospectively by collecting data from database of \"Scientific Research Institute of Cardiology and Internal Diseases\" Almaty city, Kazakhstan during 2020. IHD confirmed by history,physical exam, angiography and other lab findings.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe research involved a total of 649 participants. The mean age of study population was 64.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.24 (P\u0026thinsp;=\u0026thinsp;0,000).Mean of SBP and DBP were 180.73\u0026thinsp;\u0026plusmn;\u0026thinsp;34.9; 99.48\u0026thinsp;\u0026plusmn;\u0026thinsp;14.28 mmHg respectively. Number of female with normal BMI 50(21.6%), overweight 93(40.10%), obesity class \u0026ndash; 1, 59(25.4%), obesity class \u0026ndash; 2, 23(9.90%) and obesity class \u0026ndash; 3, 7(3%), (P\u0026thinsp;=\u0026thinsp;0.486). Number of male with underweight BMI 1(0.20%), normal BMI 96(23%), overweight 190(45.6%), obesity class \u0026ndash; 1, 89(21.3%), obesity class \u0026ndash; 2, 29(7%) and obesity class \u0026ndash; 3, 12(2.9%). (P\u0026thinsp;=\u0026thinsp;0.486). Mean of BMI in both gender was (28.72\u0026thinsp;\u0026plusmn;\u0026thinsp;11.79).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe burden of CVDs and their related risk factors is significant in Almaty, posing a major public health concern. For accurate management and implementation of preventive measures in this area, effective strategies in management, education, and healthcare centers are needed.\u003c/p\u003e","manuscriptTitle":"Role of Hypertension and Obesity as Risk Factors for IHD","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-01-12 17:40:53","doi":"10.21203/rs.3.rs-2466103/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":"fd13dc6d-0c69-48b4-88e0-afd5ed5d8dcc","owner":[],"postedDate":"January 12th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":18366861,"name":"Cardiac \u0026 Cardiovascular Systems"}],"tags":[],"updatedAt":"2023-01-12T17:40:53+00:00","versionOfRecord":[],"versionCreatedAt":"2023-01-12 17:40:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2466103","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2466103","identity":"rs-2466103","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}