Low Prevalence of Ideal Cardiovascular Health Metrics in Nigerians: a cross sectional study

Low Prevalence of Ideal Cardiovascular Health Metrics in Nigerians: a cross sectional study | 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 Low Prevalence of Ideal Cardiovascular Health Metrics in Nigerians: a cross sectional study Casmir Amadi, Folasade Lawal, Clement Akinsola, Ifeoma Udenze, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3321566/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 01 Jan, 2023 Read the published version in Nigerian Journal of Cardiology → Version 1 posted You are reading this latest preprint version Abstract Background: Ideal cardiovascular health (ICH) is a metrics for primordial prevention of cardiovascular disease (CVD). Its prevalence in Nigerians is not known. Methods This cross-sectional study assessed the seven American Heart Association’s ICH metrics of 889 Nigerians. The metrics included non-smoking, healthy diet, physical activity, body mass index (<25 kg/m2), untreated blood pressure <120/<80 mmHg, untreated total cholesterol <200 mg/dL, and untreated fasting blood glucose <100 mg/dL). Logistic regressions were used to estimate associations between sociodemographic factors (age and sex) and meeting 5–7 CVH metrics. Results: No one met all 7 of ICH metrics while 70 (7.8%) had 5-7metrics. The most prevalent and least prevalent ideal biological factors were ideal fasting plasma cholesterol (62.8%) and ideal blood pressure (31.5%) respectively. The most prevalent and least prevalent behavioural factors were ideal smoking status (86.2%) and ideal diet (6.5%) respectively. Compared to males, females had better ideal BP, p=0.005; better ideal fasting plasma glucose, p=0.031; better ideal fasting plasma cholesterol, p<0.001 and ideal smoking status, p<0.001. Ages 45 to 64 had better ideal smoking status and ideal physical activity (p<0.001 and p=0.001 respectively). Conclusion: There is a low prevalence of ICHamong Nigerians. Concerted efforts should be made to improve healthy living among Nigerians. Ideal Cardiovascular Health Metrics CVD AHA Nigeria Figures Figure 1 Figure 2 Introduction With increasing urbanization and globalization of westernized lifestyles the burden of Non-Communicable Diseases (NCDs) particularly cardiovascular diseases (CVDs), continues to increase in Nigeria and Sub-Sahara Africa (SSA)[ 1 ]. This burden is driven by mainly the plethora of potentially addressable and often co-occurring CVD risk factors such as hypertension, type 2 diabetes, obesity, and dyslipidemia [ 2 , 3 ]. Not only are these risk factors in abundance in the general population their control to target levels is largely sub-optimal [ 4 , 5 ]. By extension the risk of prevalent and incident CVD continues to rise [ 6 , 7 ]. Despite prevention policies and growing therapeutic options, CVD remains the main cause of mortality globally, accounting for about 31% of global mortality [ 8 , 9 ]. Whereas primary and secondary prevention strategies continue to address those with one or more risk factors or who have already had a CV event, primordial prevention (health promotion) has been suggested as very key in promoting cardiovascular health in the general population. To better monitor and improve cardiovascular health, the American Heart Association in 2010 created the construct ‘ideal cardiovascular health metrics’ [ 10 ]. This construct is based on three biological factors (ideal levels of blood pressure, blood glucose and total cholesterol) and four health behaviours (non-smoking status, ideal body mass index (BMI), healthy diet and meeting physical activity recommendations). To have an ideal cardiovascular health (ICH) and individual should have ideal levels of the three biologic and four behavioural factors. These metrics are defined as follows: Untreated blood pressure < 120/80mmHg Untreated fasting blood glucose < 100mg/dl Untreated total cholesterol less than 200mg/dl Non-smoking status Body Mass Index < 25kg/m 2 Moderate intensity physical activity of at least 150 minutes per week Consumption of 4 of 5 five components of the DASH diet [ 11 ]. There is evidence of a strong inverse association between the number of cardiovascular health metrics at the ideal level with all-cause and cardiovascular mortality, as well as incident cardiovascular diseases, disability, and morbidity [ 12 , 13 ]. Despite this the prevalence of ICH metrics globally is low [ 14 – 16 ]. In Nigeria with its high prevalence of NCDs there is dearth of data on ICH metrics of Nigerians. We decided to study the prevalence of ICH metrics and its association with age and sex in Nigerians living in Lagos. Methods This cross-sectional study involved 1,004 Nigerians who participated in a Community-Pharmacist led opportunistic screening for CVD risk factors during the celebration of World’s Heart Day of 2018. Details of the study methodology have been published elsewhere [ 17 ]. In summary data collection followed the World Health Organization’s three STEPS methodology; step 1: structured questionnaire administration (socio-demographics data, medical history, medication use, and lifestyle choices); step 2: anthropometric measurementa and blood pressure and step 3: biochemical tests (blood glucose and blood lipid). Anthropometry The body weight of the participants in kilograms and their height in centimetres were measured with a digital weighing scale and a standard stadiometer respectively according to standard protocols. Their Body Mass Index (BMI) was calculated with a standard formula [ 18 ]. Blood Pressure Blood pressure (BP) was measured after 5 min of rest with the participant seated comfortably, feet on the floor, arm at the level of the heart and free of any constricting clothing. Appropriately sized cuffs connected to an Omron HEM7233 (Osaka, Japan) digital sphygmomanometer was used in measuring the BP. BP was taken initially on both arms and the arm with the higher value was used in subsequent measurements. Three BP readings were taken at 2–3 min intervals. The average of three readings was used for analysis. Biochemical tests Fasting capillary blood glucose and cholesterol measurements were done for each subject with Accucheck brand of glucometer and CardioChek point-of-care cholesterol meter respectively while observing aseptic technique. The reliability and accuracy of these point-of-care instruments for glucose and cholesterol estimations have been documented [ 19 , 20 ]. The questionnaires were administered by trained research assistants and pharmacist who underwent the investigator competency training. The whole screening lasted about 45 minutes. Definition of ICH Factors/Outcome measures Biological Factors Ideal blood pressure was defined as blood pressure < 120/<80 mm Hg and without any antihypertensive medication, intermediate was SBP 120–139 or DBP 80–89 mm Hg or treated to blood pressure < 120/<80 mm Hg, and poor was blood pressure ≥ 140/≥90 mm Hg. Ideal total cholesterol was TC < 200 mg/dL and without any cholesterol-lowering medication, intermediate was TC 200–239 mg/dL or treated to TC < 200 mg/dL and poor was TC ≥ 240 mg/dL. Ideal fasting blood glucose was < 100 mg/dL and without any glucose-lowering medication, intermediate was glucose 100–125 mg/dL or treated to < 100 mg/dL and poor was glucose ≥ 126 mg/dL. Behavioural Factors Ideal BMI was defined as 18.5–24.9 kg/m 2 and poor was BMI ≥ 30 kg/m 2 . Smoking was defined as ideal if self-report of never having smoked or a former smoker who quit > 12 months ago. Intermediate smoking included those who quit within the past 1–12 months, and poor included daily smoker (> 1 cigarette/day or if former but last cigarette was in the past 1 month). Healthy diet score used to define ICH included fruits and vegetables ≥ 4.5 cups/day, fish ≥ 2 3.5 oz. /week, whole grains ≥ 3 1 oz. servings/day, sodium < 1500 mg/day, added sugar in sugar-sweetened beverages < 450 kcal/week. Since these were difficult to measure in our cohort, we used intake of fruits and vegetables ≥ 4.5 times/day as a surrogate of ideal diet in the definition of ICH, as used in prior studies [ 21 , 22 ]. For this variable, discrimination between intermediate and poor nutrition status was not possible. Hence it was dichotomised to ideal (≥ 4 times/day) and poor (< 4 times/day). Physical activity was assessed with the validated International Physical Activity Questionnaire-Short Form (IPAQ-SF). Ideal physical activity was ≥ 150 min/week moderate or ≥ 75 min/week vigorous or ≥ 150 min/week moderate and vigorous activity. Poor physical activity was no physical activity reported with intermediate activity as any other amounts of activity. Statistics Continuous variables were expressed as mean ± standard deviation (SD) or median and interquartile range when skewed, while categorical variables expressed as percentages. Analysis of variance (ANOVA) and Kruskal Wallis were used to compare differences in the 4 phenotypes for the continuous variables while chi square test was used to compare differences between categorical variables. Logistic regression was used to test the association between sex and gender and ICH factors. All statistical analyses were performed using SPSS version 26.0 software (SPSS Inc, Chicago, IL), and a p < 0.05 was considered as statistically significant. Tables and charts were used for data presentation where appropriate. Results Of the 1004 subjects that took part in the study 889(88.5%) had complete data for analysis. Table 1 shows the general characteristics of the study population. Table 1 General Characteristics of the Study Population Parameter Mean ± SD n (%) Age (yrs.) 56.8 ± 12.1 Age Group (yrs.) < 45 139 (15.6) 45–64 537 (60.4) Gender Male 379 (42.6) Female 510 (57.4) Hypertension Previously known 290(32.9) On treatment Diabetes Previously known On treatment 254(87.6) 89(9.2) 66(80.5) Previous CVD Stroke 21 (2.4) Ischaemic Heart Disease 19 (20.0) Smoking Current Smoking 38 (4.3) Previous Smoking 108 (12.1) Current use of alcohol 237 (26.7) The mean age of the subjects was 56.8 ± 12.1 years with the majority (60.4%) being within the ages of 45 and 64 years. There were more females, 510 (57.4%). Two hundred and ninety (32.9%) of the subjects were previously known hypertensives while 82 (9.2%) were previously known diabetics. Thirty-eight (4.3%) and 237 (26.6%) were current smokers and alcohol users respectively. Eight hundred and thirty-one (93.5%) of the subjects consumed < 4 portions of fruits and vegetables per day while 644 (72.4%) did not meet the recommended daily dose of Physical activity. Prevalence of ICH factors No subject had all the 7 ideal cardiovascular health metrics. Seventy (7.8%) had ideal CV metrics (5–7 metrics) while 430 (48.8%) and 389 (43.8%) had intermediate CV metrics (3–4 metrics) and poor CV metrics (0–2 metrics) respectively. (Fig. 1 ). Figure 2 shows the prevalence of the individual components of cardiovascular health metrics of the study population. For the biological factors ideal fasting total cholesterol was the most prevalent (62.8%) followed by ideal fasting blood glucose (57.7%) while ideal blood pressure was the least prevalent (31.5%). For the behavioural factors non-smoking status was the most prevalent (86.2%) while ideal diet and ideal physical activity were the least prevalent, 6.5% and 27.6% respectively. Sex and Age prevalence of ICH factors Generally, females had better ideal biological cardiovascular health metrics compared to males. For fasting plasma total cholesterol 75.3% and 45.9% of females and males respectively had ideal levels; p < 0.001 while for fasting plasma glucose 60.8% and 53.6% of females and males respectively had ideal levels; p = 0.031. (Table 2 ). Table 2 Sex distribution of the ICH Factors Sex Distribution of ICH Factors ICH Factor Ideal Non-Ideal Total P-value Male Female Male Female Male Female Blood Pressure 100(26.4) 180(35.3) 279(73.6) 330(64.7) 379(100.0) 510(100.0) 0.005 FBG 203(53.6) 310(60.8) 176(64.4) 200(39.2) 379(100.0) 510(100.0) 0.031 Total Cholesterol 174(45.9) 384(75.3) 205(54.1) 126(24.7) 379(100.0) 510(100.0) < 0.001 BMI 133(35.1) 125(24.5) 246(64.9) 385(75.5) 379(100.0) 510(100.0) 0.001 Smoking 217(71.5) 496(97.3) 108(28.5) 14(2.7) 379(100.0) 510(100.0) < 0.001 Diet 26(6.9) 32(6.3) 353(93.1) 478(93.7) 379(100.0) 510(100.0) 0.73 Physical Activity 134(38.3) 100(19.6) 234(61.7) 410(80.4) 379(100.0) 510(100.0) < 0.001 Legend: FBG, Fasting Blood Glucose; BMI, Body Mass Index For the behavioural factors females had better non-smoking status than males, 97.3% vs 71.5%; p < 0.001. However, males compared to females had better ideal BMI and physical activity profile; p = 0.001 and p < 0.001 respectively. With respect to age ideal total cholesterol was most prevalent in the 65 age groups. Non-smoking and ideal physical activity profile were comparable across the age ranges. (Table 3 ). Table 3 Age-Group distribution of the ICH Factors Age Distribution of ICH Factors ICH Factor Ideal n(%) Non-Ideal n(%) Total P-value < 45 45–64 ≥ 65 < 45 45–64 ≥ 65 < 45 45–64 ≥ 65 Blood Pressure 44(31.7) 174(32.4) 62(29.1) 95(68.2) 363(67.6) 151(70.9) 139(100.0) 537(100.0) 213(100.0) 0.68 FBG 81(58.3) 299(55.7) 133(62.4) 58(41.7) 238(44.3) 80(37.6) 139(100.0) 537(100.0) 213(100.0) 0.24 Total Cholesterol 97(69.8) 314(58.5) 147(69.0) 42(30.2) 223(41.5) 66(31.0) 139(100.0) 537(100.0) 213(100.0) 0.05 BMI 34(24.5) 160(29.8) 64(30.0) 105(75.5) 277(70.2) 149(70.0) 139(100.0) 537(100.0) 213(100.0) 0.43 Smoking 131(94.2) 438(81.0) 201(94.4) 8(5.8) 102(19.0) 12(5.6) 139(100.0) 537(100.0) 213(100.0) < 0.001 Diet 7(5.0) 41(7.6) 10(4.7) 132(95.0) 496(92.4) 203(95.3) 139(100.0) 537(100.0) 213(100.0) 0.25 Physical Activity 32(23.0) 172(32.0) 41(19.2) 107(77.0) 365(68.0) 172(80.8) 139(100.0) 537(100.0) 213(100.0) 0.001 Legend: FGB, Fasting Blood Glucose; BMI; Body Mass Index Association between ideal and non-ideal CH metrics with age and gender Table 4 shows the association between ideal and non-ideal CV health metrics with age and gender and the odds ratios. Compared to males, females had lesser odds of having non-ideal blood pressure, fasting blood glucose, total cholesterol, BMI and smoking status but high odds of having non-ideal BMI and Physical activity. Age 45–64 had higher odds of having ideal total cholesterol and Physical activity. Table 4 Association between ideal cardiovascular health metrics with age and sex Variable Ideal Non-ideal (Intermediate/ Poor) Odd ratio (95% CI) p-value BP Age group (Years) 65 44(31.7) 174(32.4) 62(29.1) 95(68.3) 363(67.6) 151(70.9) 1 1.035(0.693–1.545) 1.128(0.709–1.794) 0.681 0.302 Sex Male Female 100(26.4) 180(35.3) 279(73.6) 330(64.7) 1 0.657(0.491–0.880) 0.005* FBG Age group (Years) 65 81(58.3) 299(55.7) 133(62.4) 58(41.7) 238(44.3) 80(37.6) 1 1.112(0.762–1.622) 0.840(0.543–1.299) 0.237 0.392 Sex Male Female 203(53.6) 310(60.8) 176(46.4) 200(39.2) 1 0.733(0.560–0.959) 0.031* TC Age group (Years) 65 97(69.8) 314(58.5) 147(69.0) 42(30.2) 223(41.5) 66(31.0) 1 1.640 (1.098–2.449) 1.037(0.652–1.649) 0.005* 0.321 Sex Male Female 174(45.9) 384(75.3) 205(54.1) 126(24.7) 1 0.279(0.209–0.370) < 0.001* BMI Age group (Years) 65 34(24.5) 160(29.8) 64(30.0) 105(75.5) 377(70.2) 149(70.0) 1 0.763(0.497 − 0.171) 0.754(0.464–1.225) 0.434 0.254 Sex Male Female 133(35.1) 125(24.5) 246(64.9) 385(75.5) 1 1.665(1.244–2.229) 0.001* Smoking Age group (Years) 65 131(94.2) 438(81.0) 201(94.4) 8(5.8) 102(19.0) 12(5.6) 1 3.813(1.809–8.038) 0.978(0.388–2.56) < 0.001* 0.961 Sex Male Female 217(71.5) 496(97.3) 108(28.5) 14(2.7) 1 0.056(0.032–0.101) < 0.001* Diet Age group (Years) 65 7(5.0) 41(7.6) 10(4.7) 132(95.0) 496(92.4) 203(95.3) 1 0.893(0.718–1.834) 0.988(0.835–1.393) 0.252 0.391 Sex Male Female 26(6.9) 32(6.3) 353(93.1) 478(93.7) 1 0.991(0.868–1.049) 0.727 Physical Activity Age group (Years) 65 32(23.0) 172(32.0) 41(19.2) 107(77.0) 365(68.0) 172(80.8) 1 0.635(0.411–0.980) 1.255(0.744–2.114) 0.001* 0.394 Sex Male Female 134(38.3) 100(19.6) 234(61.7) 410(80.4) 1 2.348(1.731–3.184) < 0.001* Legend: BP, Blood Pressure; FBG, Fasting Blood Glucose; TC, Total Cholesterol; BMI, Body Mass Index Discussion This is the first study in Nigeria (from the knowledge of the authors) to investigate the prevalence of the AHA-recommended ideal cardiovascular health metrics and its relationship with age and sex. In our study no subject met the seven ICH metrics. Globally the prevalence of meeting the seven ICH metrics is low, ranging between 0.1% and 15% depending on the geographical region, age, sex and educational status [ 14 , 23 – 26 ]. We found a prevalence of 7.9% of ICH (5–7 metrics) from our study, which perhaps is the lowest in the world comparable to 9.1% reported by Wu et al in China [ 27 ]. In Peru and in Chilean women the prevalence of ICH (5–7 metrics) was reported to be 12.7% and 14.3% respectively [ 28 , 29 ]. Other studies however have reported higher prevalence of ICH in recent times. In Nepal, Bangladesh, Malawi, Uganda, and South Africa the prevalence of ICH was 51.6%, 43.1%, 71.5%, 50% and 53% respectively [ 29 – 34 ]. The higher prevalence in these studies might reflect the impact of the increased global campaign on the importance of healthy lifestyle choices as the fulcrum for the primordial prevention of NCDs/CVD [ 35 , 36 ]. Low prevalence of ICH in the general population means that majority of the people live with these modifiable CVD risk factors and are at a heightened risk CVD [ 12 , 13 ]. Studies have documented graded and continuous inverse relationship between the components of ICH and risk of incident CVD, Type 2 DM, cognitive impairment, depression, and cancers [ 37 , 38 ]. The low prevalence of ICH from our study instructs that significant effort must be invested in the promotion of cardiovascular health through enforceable health policies. Our study also found differences in the prevalence in ideal biologic and behavioural ICH factors. For the biologic metrics ideal total cholesterol was the most (62.7%) prevalent, followed by ideal blood glucose (57.7%) while ideal blood pressure was the least (31.5%). For the ideal behavioural metrics non-smoking status was the most (86.3%) prevalent while prevalence of ideal diet was abysmally low (6.5%). Our findings corroborate reports in published literature where ideal total cholesterol, non-smoking and blood glucose had the best global prevalence [ 39 , 40 ]. According to AHA's 2018 heart disease and stroke statistics update, the prevalence of ICH among US adults, was 77.1% for smoking, 60.3% for TC, 53.2% for FBG, 49.7% for physical activity, 45.4% for BP, 29.6% for BMI, and 1.1% for dietary pattern [ 41 ]. These are somewhat comparable to our overall results. The prevalence of ideal blood pressure of 31.5% in our cohort is lower than figures from Peru (51%) Marshall Islands (46.7%) and Malawi (46.9%) [ 28 , 32 , 40 ], but comparable to prevalence rates from Bangladesh (29.3%), Nepal (26.3%), Uganda (37%), China (32.3%) and 29.9% (Urban male dwelling Ghanaians) [ 30 – 33 , 42 – 43 ]. The relatively low prevalence of ideal BP in our cohort might be an indirect reflection of the high burden of hypertension in Nigeria characterized by high prevalence of low awareness, high burden of undiagnosed and poor control [ 5 , 44 ]. The prevalence of ideal diet is globally low according to published literature and our finding of 6.1% aligns with this global trend [ 28 – 33 , 40 – 42 ]. This global trend might be attributable to the twin problems of availability and affordability of fruits and vegetables remotely due to urbanization where arable farmlands have been converted for physical urban development [ 34 , 45 ]. We also found a low prevalence of ideal physical activity profile of 27.6% in our cohort, implying that 72.4% did not met the ideal physical activity requirements. In Nigeria the prevalence of physical inactivity in adults varies between studies. A recent meta-analysis reported a cruse prevalence of physical inactivity to be between 25% and 57% [ 46 ]. The high prevalence of physical inactivity in our cohort may reflect the effects of globalization, westernization of lifestyles, and poor town planning due to teeming population [ 47 , 48 ]. Unhealthy diets and physical inactivity drive the global burden of obesity (all behavioural factors) and buttresses the inter-relatedness of the CVD risk factors [ 49 , 50 ]. The high prevalence of ideal smoking status (86.2%) from our study aligns with published literature [ 28 – 32 ] and mirrors the low prevalence of smoking in the general Nigerian population (10.4% current smokers and 17.7% ever smokers vs 4.3% current smokers and 12.1% previous smokers from our study) [ 51 ]. Sex and age are non-modifiable risk factors for CVD and have been shown to determine the prevalence of ICH. From our study there were sex and age differences in the prevalence of both the ideal biologic and behavioural factors. Females in our cohort had higher prevalence of ideal cholesterol, blood pressure and blood glucose compared to the males. They also had higher prevalence of non-smoking status. Similar studies have reported better ICH metrics (both behavioural and biologic) in females than males [ 28 , 29 , 40 – 43 ]. This might be due better self-care practices in women compared with men [ 52 , 53 , 54 ]. Higher prevalence of ideal BP in females can also be partly explained by women’s stronger anti-inflammatory immune profile, which might as a compensatory mechanism to limit increases in blood pressure [ 55 – 59 ]. We also found lower prevalence of ICH with increasing age. Those below age 45 years irrespective of sex had higher prevalence of ICH compared to those above 45 years of age. This trend has been reported by other similar studies [ 28 , 29 , 40 – 43 ]. The risk of CVD increases linearly with age. With advancing age, the risk of hypertension, diabetes, obesity, and physical inactivity also increases [ 60 , 61 ]. The corollary is that the odd for ICH decreases as age increases. Both the behavioural and biological ICH factors are interwoven with respect to incident CVD. The heart and soul of preventive cardiology is primordial prevention which entails a life-course approach to the prevention of the development of the intermediate/biologic/metabolic risk factors for CVD (obesity, hypertension, dyslipidemia and diabetes) in the general population [ 62 ]. This is ensured through the promotion of healthy living via consumption of heart-healthy diets (DASH and Mediterranean diets), abstinence from tobacco use, healthy use of alcohol (if necessary), intentional physical activity and healthy management of psycho-social stress. Promotion of these behaviours ideally should start in childhood as it has been shown that non-ideal lifestyles in childhood is associated with increased risk of CVD in later adult life as evidenced by PDAY and the Bogalusa Heart studies [ 63 – 65 ]. This is further supported by the results of the the Cardiovascular Risk in Young Finns Study and Special Turku Coronary Risk Factor Intervention Project for Children [STRIP] studies [ 66 , 67 ]. Appropriate dietary intake, including reduction in sodium and saturated fat consumption, can reduce the risk of developing hypertension and dyslipidaemia. Regular physical activity is associated with lower blood pressure, healthier lipid profiles and ideal body weight. Diet and exercise are critical to maintaining ideal weight that engenders cardiovascular health. Behavioural factors such as stress management, sleep duration, portion control, and meal timing may play a role in weight management and offer additional routes of intervention [ 68 ]. Smoking, in addition to being an independent risk factor for CVD, is also associated with increased BP and heart rate, poorer lipid profile and high BMI [ 69 ]. In the same vein unhealthy use of alcohol leads to raised BP, unhealthy lipid profile and increased BMI [ 70 ]. Unrelenting public health campaign on the importance and benefits of healthy lifestyles is a sine qua non in the promotion of primordial prevention of CVD/NCDs. Structured lifestyle modification programs population via National policies will go a long way in promoting primordial prevention of CVD. Opportunistic screening especially of individuals aged 40 years and above will not only identify individuals with latent risk factors for CVD but also those in whom intense lifestyle modification will become a major intervention. The burden of CVD/NCDs is driven by urbanization. National governments should enunciate and implement policies that will mitigate the adverse impacts of urbanization on public health. Conclusions Our study demonstrated low prevalence of ICH factors among Nigerians and its association with age. Efforts should be spared in the campaign against unhealthy lifestyles such as physical inactivity and unhealthy diets as these two in particular are drivers of metabolic risks like hypertension, obesity, dyslipidemia and Type 2 diabetes. Our study has some limitations. First there is the issue of recall bias as some of the data was via self-report. Secondly our study was cross-sectional in design and was unable to show any association with incident CVD or establish causality. However, we have proved information which we believe should inspire further research in this area. Abbreviations AHA American Heart Association ANOVA Analysis of Variance BMI Body Mass Index BP Blood Pressure CVD Cardiovascular Disease DASH Dietary Approach to Stopping Hypertension FBG Fasting Blood Glucose ICH Ideal Cardiovascular Health IPAQ-SF International Physical Activity Questionnaire-Short Form NCDs Non-Communicable Diseases PDAY Pathobiological Determinants of Atherosclerosis in the Young SSA Sub-Saharan Africa STRIP Special Turku Coronary Risk Factor Intervention Project for Children TC Total cholesterol Declarations Ethics Approval and consent to participate Ethics approval was obtained from the Health Research Ethics Committee of the Amuwo Odofin Municipality, overseeing the political administration of the study area. The study participants were informed about the purpose and nature of the study and that the data generated from the study would be anonymized and de-identified when published. No data was collected before detailed information was provided to the study participants, and a signed, informed consent was obtained. Participants who had elevated CVD risk factors were duly referred to their primary care physicians/Public hospitals for definitive management. The study complied with the Declaration of Helsinki. Consent for publication Study participants gave their consent for their de-identified data to be published. Availability of data and material The raw data of this study is available on reasonable request. Competing interests The authors declare no competing interests. Funding Raid Checks Diagnostics and Wellness, Roche Diabetic Care and Omron Healthcare provided the equipment (cholesterol meter, glucometer, and BP monitors) for the training and for the research. There were no branded promotional information/materials from these companies around the vicinity of the screening exercises nor were there financial rewards to the participants for taking part in the study. Authors’ contributions: CEA and FOL conceptualized the research topic, coordinated the investigators’ training and data curation. CMA analysed the data. ICU and ACM drafted the manuscript while CEA, JNA and DAO reviewed the draft of the manuscript. All authors read and approved the final draft of the manuscript. Acknowledgements : The authors wish to acknowledge the management of Rapid Check Diagnostic and Wellness Ltd, Roche Diabetes Care, Omron Healthcare, Victory Drugs and Meridian Cardiac Clinic for providing the equipment and training for the research. References Hamid S, Groot W, Pavlova M. Trends in cardiovascular diseases and associated risks in sub-Saharan Africa: a review of the evidence for Ghana, Nigeria, South Africa, Sudan and Tanzania. 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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-3321566","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":232573523,"identity":"c9937fa8-f628-4886-a3bf-2d67268e5e30","order_by":0,"name":"Casmir Amadi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAw0lEQVRIiWNgGAWjYNCCAgY5BgYe4tUzNjAYMBiTriWxgWgt/O2Hjz/4YXA4fcPxswcffGCwk9NtIKBF4kxaYmOPQVruhjN5yYYzGJKNzQ4QsuYGj2EDj4FN7oYDOWbSPAwHErcR0iJ/g/9j4x8DiXSD82+I1GJwg4exGWhLgsENYm0xPJNmOFvGIM1w5o03xoYzDIjwi9zxww8+vqk4LM93PsfwwYcKOznC3ocBBbBKA2KVg4B8AymqR8EoGAWjYEQBAMoiQoOn1O1lAAAAAElFTkSuQmCC","orcid":"","institution":"University of Lagos","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Casmir","middleName":"","lastName":"Amadi","suffix":""},{"id":232573524,"identity":"e373c5c2-26c1-415a-9f7f-7296de30c2bf","order_by":1,"name":"Folasade Lawal","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Folasade","middleName":"","lastName":"Lawal","suffix":""},{"id":232573525,"identity":"bae25e5e-b75d-4a62-9beb-97d3cb42cc30","order_by":2,"name":"Clement Akinsola","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Clement","middleName":"","lastName":"Akinsola","suffix":""},{"id":232573526,"identity":"a9dda116-c0ac-4cd3-b764-7e3b09194a8c","order_by":3,"name":"Ifeoma Udenze","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ifeoma","middleName":"","lastName":"Udenze","suffix":""},{"id":232573527,"identity":"ab60ce13-c022-4077-b3d2-d27ffcaf5624","order_by":4,"name":"Amam Mbakwem","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Amam","middleName":"","lastName":"Mbakwem","suffix":""},{"id":232573530,"identity":"a467d126-f870-45fb-bc7a-af371a32d80a","order_by":5,"name":"Jayne Ajuluchukwu","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jayne","middleName":"","lastName":"Ajuluchukwu","suffix":""},{"id":232573534,"identity":"f5bf76df-3667-4522-8356-3a80e6e34038","order_by":6,"name":"David Oke","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Oke","suffix":""}],"badges":[],"createdAt":"2023-09-03 11:44:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3321566/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3321566/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.4103/njc.njc_15_23","type":"published","date":"2023-01-01T15:03:38+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":43313949,"identity":"4f81117e-bb08-4259-aec9-f6f7b2ffd8bd","added_by":"auto","created_at":"2023-09-18 16:46:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":87003,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Ideal Cardiovascular Health Metrics\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-3321566/v1/08c64ccf6baf269b5e71414f.png"},{"id":43313951,"identity":"04a72792-188f-43d8-a66f-7c0fbb99f6d7","added_by":"auto","created_at":"2023-09-18 16:46:32","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":27079,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of the components of the ICH metrics\u003c/p\u003e\n\u003cp\u003eLegend: BP, Blood Pressure; FBG, Fasting Blood Glucose; TC, Total cholesterol; BMI, Body Mass Index.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-3321566/v1/6f58147d86783c247240fc9a.png"},{"id":56545400,"identity":"792eb8be-8126-4a10-9122-40a7b1a0028a","added_by":"auto","created_at":"2024-05-15 15:03:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1033305,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3321566/v1/a39d9fef-1692-4f56-b3c6-030413786c29.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Low Prevalence of Ideal Cardiovascular Health Metrics in Nigerians: a cross sectional study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWith increasing urbanization and globalization of westernized lifestyles the burden of Non-Communicable Diseases (NCDs) particularly cardiovascular diseases (CVDs), continues to increase in Nigeria and Sub-Sahara Africa (SSA)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This burden is driven by mainly the plethora of potentially addressable and often co-occurring CVD risk factors such as hypertension, type 2 diabetes, obesity, and dyslipidemia [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Not only are these risk factors in abundance in the general population their control to target levels is largely sub-optimal [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. By extension the risk of prevalent and incident CVD continues to rise [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Despite prevention policies and growing therapeutic options, CVD remains the main cause of mortality globally, accounting for about 31% of global mortality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Whereas primary and secondary prevention strategies continue to address those with one or more risk factors or who have already had a CV event, primordial prevention (health promotion) has been suggested as very key in promoting cardiovascular health in the general population.\u003c/p\u003e \u003cp\u003eTo better monitor and improve cardiovascular health, the American Heart Association in 2010 created the construct \u003cem\u003e\u0026lsquo;ideal cardiovascular health metrics\u0026rsquo;\u003c/em\u003e [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This construct is based on three biological factors (ideal levels of blood pressure, blood glucose and total cholesterol) and four health behaviours (non-smoking status, ideal body mass index (BMI), healthy diet and meeting physical activity recommendations). To have an ideal cardiovascular health (ICH) and individual should have ideal levels of the three biologic and four behavioural factors.\u003c/p\u003e \u003cp\u003eThese metrics are defined as follows:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUntreated blood pressure\u0026thinsp;\u0026lt;\u0026thinsp;120/80mmHg\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUntreated fasting blood glucose\u0026thinsp;\u0026lt;\u0026thinsp;100mg/dl\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eUntreated total cholesterol less than 200mg/dl\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNon-smoking status\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eBody Mass Index\u0026thinsp;\u0026lt;\u0026thinsp;25kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eModerate intensity physical activity of at least 150 minutes per week\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eConsumption of 4 of 5 five components of the DASH diet [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eThere is evidence of a strong inverse association between the number of cardiovascular health metrics at the ideal level with all-cause and cardiovascular mortality, as well as incident cardiovascular diseases, disability, and morbidity [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Despite this the prevalence of ICH metrics globally is low [\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In Nigeria with its high prevalence of NCDs there is dearth of data on ICH metrics of Nigerians. We decided to study the prevalence of ICH metrics and its association with age and sex in Nigerians living in Lagos.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e This cross-sectional study involved 1,004 Nigerians who participated in a Community-Pharmacist led opportunistic screening for CVD risk factors during the celebration of World\u0026rsquo;s Heart Day of 2018. Details of the study methodology have been published elsewhere [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In summary data collection followed the World Health Organization\u0026rsquo;s three STEPS methodology; step 1: structured questionnaire administration (socio-demographics data, medical history, medication use, and lifestyle choices); step 2: anthropometric measurementa and blood pressure and step 3: biochemical tests (blood glucose and blood lipid).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eAnthropometry\u003c/h2\u003e \u003cp\u003eThe body weight of the participants in kilograms and their height in centimetres were measured with a digital weighing scale and a standard stadiometer respectively according to standard protocols. Their Body Mass Index (BMI) was calculated with a standard formula [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eBlood Pressure\u003c/h2\u003e \u003cp\u003eBlood pressure (BP) was measured after 5 min of rest with the participant seated comfortably, feet on the floor, arm at the level of the heart and free of any constricting clothing. Appropriately sized cuffs connected to an Omron HEM7233 (Osaka, Japan) digital sphygmomanometer was used in measuring the BP. BP was taken initially on both arms and the arm with the higher value was used in subsequent measurements. Three BP readings were taken at 2\u0026ndash;3 min intervals. The average of three readings was used for analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eBiochemical tests\u003c/h2\u003e \u003cp\u003eFasting capillary blood glucose and cholesterol measurements were done for each subject with \u003cem\u003eAccucheck brand\u003c/em\u003e of glucometer and \u003cem\u003eCardioChek\u003c/em\u003e point-of-care cholesterol meter respectively while observing aseptic technique. The reliability and accuracy of these point-of-care instruments for glucose and cholesterol estimations have been documented [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe questionnaires were administered by trained research assistants and pharmacist who underwent the investigator competency training. The whole screening lasted about 45 minutes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eDefinition of ICH Factors/Outcome measures\u003c/h2\u003e \u003cp\u003e \u003cem\u003eBiological Factors\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIdeal blood pressure was defined as blood pressure\u0026thinsp;\u0026lt;\u0026thinsp;120/\u0026lt;80 mm Hg and without any antihypertensive medication, intermediate was SBP 120\u0026ndash;139 or DBP 80\u0026ndash;89 mm Hg or treated to blood pressure\u0026thinsp;\u0026lt;\u0026thinsp;120/\u0026lt;80 mm Hg, and poor was blood pressure\u0026thinsp;\u0026ge;\u0026thinsp;140/\u0026ge;90 mm Hg.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIdeal total cholesterol was TC\u0026thinsp;\u0026lt;\u0026thinsp;200 mg/dL and without any cholesterol-lowering medication, intermediate was TC 200\u0026ndash;239 mg/dL or treated to TC\u0026thinsp;\u0026lt;\u0026thinsp;200 mg/dL and poor was TC\u0026thinsp;\u0026ge;\u0026thinsp;240 mg/dL.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIdeal fasting blood glucose was \u0026lt;\u0026thinsp;100 mg/dL and without any glucose-lowering medication, intermediate was glucose 100\u0026ndash;125 mg/dL or treated to \u0026lt;\u0026thinsp;100 mg/dL and poor was glucose\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003e \u003cem\u003eBehavioural Factors\u003c/em\u003e \u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIdeal BMI was defined as 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e and poor was BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eSmoking was defined as ideal if self-report of never having smoked or a former smoker who quit\u0026thinsp;\u0026gt;\u0026thinsp;12 months ago. Intermediate smoking included those who quit within the past 1\u0026ndash;12 months, and poor included daily smoker (\u0026gt;\u0026thinsp;1 cigarette/day or if former but last cigarette was in the past 1 month).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHealthy diet score used to define ICH included fruits and vegetables\u0026thinsp;\u0026ge;\u0026thinsp;4.5 cups/day, fish\u0026thinsp;\u0026ge;\u0026thinsp;2 3.5 oz. /week, whole grains\u0026thinsp;\u0026ge;\u0026thinsp;3 1 oz. servings/day, sodium\u0026thinsp;\u0026lt;\u0026thinsp;1500 mg/day, added sugar in sugar-sweetened beverages\u0026thinsp;\u0026lt;\u0026thinsp;450 kcal/week. Since these were difficult to measure in our cohort, we used intake of fruits and vegetables\u0026thinsp;\u0026ge;\u0026thinsp;4.5 times/day as a surrogate of ideal diet in the definition of ICH, as used in prior studies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. For this variable, discrimination between intermediate and poor nutrition status was not possible. Hence it was dichotomised to ideal (\u0026ge;\u0026thinsp;4 times/day) and poor (\u0026lt;\u0026thinsp;4 times/day).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePhysical activity was assessed with the validated International Physical Activity Questionnaire-Short Form (IPAQ-SF). Ideal physical activity was \u0026ge;\u0026thinsp;150 min/week moderate or \u0026ge;\u0026thinsp;75 min/week vigorous or \u0026ge;\u0026thinsp;150 min/week moderate and vigorous activity. Poor physical activity was no physical activity reported with intermediate activity as any other amounts of activity.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistics\u003c/h2\u003e \u003cp\u003eContinuous variables were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) or median and interquartile range when skewed, while categorical variables expressed as percentages. Analysis of variance (ANOVA) and Kruskal Wallis were used to compare differences in the 4 phenotypes for the continuous variables while chi square test was used to compare differences between categorical variables. Logistic regression was used to test the association between sex and gender and ICH factors. All statistical analyses were performed using SPSS version 26.0 software (SPSS Inc, Chicago, IL), and a p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered as statistically significant. Tables and charts were used for data presentation where appropriate.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eOf the 1004 subjects that took part in the study 889(88.5%) had complete data for analysis. Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e shows the general characteristics of the study population.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eGeneral Characteristics of the Study Population\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eParameter\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eMean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAge (yrs.)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\"\u0026plusmn;\"\u003e\n\u003cp\u003e56.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eAge Group (yrs.)\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e139 (15.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e537 (60.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eGender\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e379 (42.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e510 (57.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eHypertension\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePreviously known\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e290(32.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eOn treatment\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eDiabetes\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003ePreviously known\u003c/p\u003e\n\u003cp\u003eOn treatment\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e254(87.6)\u003c/p\u003e\n\u003cp\u003e89(9.2)\u003c/p\u003e\n\u003cp\u003e66(80.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003ePrevious CVD\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eStroke\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e21 (2.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eIschaemic Heart Disease\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e19 (20.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cem\u003eSmoking\u003c/em\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCurrent Smoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e38 (4.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePrevious Smoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e108 (12.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eCurrent use of alcohol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e237 (26.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe mean age of the subjects was 56.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1 years with the majority (60.4%) being within the ages of 45 and 64 years. There were more females, 510 (57.4%). Two hundred and ninety (32.9%) of the subjects were previously known hypertensives while 82 (9.2%) were previously known diabetics. Thirty-eight (4.3%) and 237 (26.6%) were current smokers and alcohol users respectively. Eight hundred and thirty-one (93.5%) of the subjects consumed\u0026thinsp;\u0026lt;\u0026thinsp;4 portions of fruits and vegetables per day while 644 (72.4%) did not meet the recommended daily dose of Physical activity.\u003c/p\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n\u003ch2\u003ePrevalence of ICH factors\u003c/h2\u003e\n\u003cp\u003eNo subject had all the 7 ideal cardiovascular health metrics. Seventy (7.8%) had ideal CV metrics (5\u0026ndash;7 metrics) while 430 (48.8%) and 389 (43.8%) had intermediate CV metrics (3\u0026ndash;4 metrics) and poor CV metrics (0\u0026ndash;2 metrics) respectively. (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e shows the prevalence of the individual components of cardiovascular health metrics of the study population. For the biological factors ideal fasting total cholesterol was the most prevalent (62.8%) followed by ideal fasting blood glucose (57.7%) while ideal blood pressure was the least prevalent (31.5%). For the behavioural factors non-smoking status was the most prevalent (86.2%) while ideal diet and ideal physical activity were the least prevalent, 6.5% and 27.6% respectively.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n\u003ch2\u003eSex and Age prevalence of ICH factors\u003c/h2\u003e\n\u003cp\u003eGenerally, females had better ideal biological cardiovascular health metrics compared to males. For fasting plasma total cholesterol 75.3% and 45.9% of females and males respectively had ideal levels; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 while for fasting plasma glucose 60.8% and 53.6% of females and males respectively had ideal levels; p\u0026thinsp;=\u0026thinsp;0.031. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab2\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eSex distribution of the ICH Factors\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"8\" align=\"left\"\u003e\n\u003cp\u003eSex Distribution of ICH Factors\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eICH Factor\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eIdeal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eNon-Ideal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlood Pressure\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100(26.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e180(35.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e279(73.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e330(64.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFBG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e203(53.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e310(60.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e176(64.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e200(39.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.031\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal Cholesterol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e174(45.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e384(75.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e205(54.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e126(24.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133(35.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e125(24.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e246(64.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e385(75.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e217(71.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e496(97.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e108(28.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e14(2.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiet\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26(6.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e353(93.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e478(93.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.73\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePhysical Activity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e134(38.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e100(19.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e234(61.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e410(80.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e379(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e510(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n\u003cp\u003eLegend: FBG, Fasting Blood Glucose; BMI, Body Mass Index\u003c/p\u003e\n\u003cp\u003eFor the behavioural factors females had better non-smoking status than males, 97.3% vs 71.5%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001. However, males compared to females had better ideal BMI and physical activity profile; p\u0026thinsp;=\u0026thinsp;0.001 and p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 respectively. With respect to age ideal total cholesterol was most prevalent in the \u0026lt;\u0026thinsp;45 and \u0026gt;\u0026thinsp;65 age groups. Non-smoking and ideal physical activity profile were comparable across the age ranges. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab3\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAge-Group distribution of the ICH Factors\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003cth colspan=\"11\" align=\"left\"\u003e\n\u003cp\u003eAge Distribution of ICH Factors\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eICH Factor\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eIdeal n(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eNon-Ideal n(%)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth colspan=\"3\" align=\"left\"\u003e\n\u003cp\u003eTotal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eP-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u0026ge;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBlood Pressure\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e44(31.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e174(32.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e62(29.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e95(68.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e363(67.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e151(70.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.68\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eFBG\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81(58.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e299(55.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133(62.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e58(41.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e238(44.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e80(37.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.24\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eTotal Cholesterol\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97(69.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e314(58.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e147(69.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42(30.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e223(41.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e66(31.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34(24.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e160(29.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e64(30.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105(75.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e277(70.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e149(70.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.43\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eSmoking\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131(94.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e438(81.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e201(94.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(5.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e102(19.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e12(5.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003eDiet\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7(5.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41(7.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e10(4.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132(95.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e496(92.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e203(95.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.25\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003ePhysical Activity\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(23.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e172(32.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e41(19.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e107(77.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e365(68.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e172(80.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e139(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e537(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e213(100.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"char\" char=\".\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n\u003cp\u003eLegend: FGB, Fasting Blood Glucose; BMI; Body Mass Index\u003c/p\u003e\n\u003cdiv id=\"Sec13\" class=\"Section3\"\u003e\n\u003ch2\u003eAssociation between ideal and non-ideal CH metrics with age and gender\u003c/h2\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e shows the association between ideal and non-ideal CV health metrics with age and gender and the odds ratios. Compared to males, females had lesser odds of having non-ideal blood pressure, fasting blood glucose, total cholesterol, BMI and smoking status but high odds of having non-ideal BMI and Physical activity. Age 45\u0026ndash;64 had higher odds of having ideal total cholesterol and Physical activity.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n\u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003ctable id=\"Tab4\" border=\"1\"\u003e\u003ccaption\u003e\n\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n\u003cdiv class=\"CaptionContent\"\u003e\n\u003cp\u003eAssociation between ideal cardiovascular health metrics with age and sex\u003c/p\u003e\n\u003c/div\u003e\n\u003c/caption\u003e\n\u003cthead\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eVariable\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eIdeal\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eNon-ideal (Intermediate/ Poor)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eOdd ratio (95% CI)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003ep-value\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003eBP\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eAge group (Years)\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e44(31.7)\u003c/p\u003e\n\u003cp\u003e174(32.4)\u003c/p\u003e\n\u003cp\u003e62(29.1)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e95(68.3)\u003c/p\u003e\n\u003cp\u003e363(67.6)\u003c/p\u003e\n\u003cp\u003e151(70.9)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e1.035(0.693\u0026ndash;1.545)\u003c/p\u003e\n\u003cp\u003e1.128(0.709\u0026ndash;1.794)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e0.681\u003c/p\u003e\n\u003cp\u003e0.302\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003eSex\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e100(26.4)\u003c/p\u003e\n\u003cp\u003e180(35.3)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e279(73.6)\u003c/p\u003e\n\u003cp\u003e330(64.7)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.657(0.491\u0026ndash;0.880)\u003c/p\u003e\n\u003c/th\u003e\n\u003cth align=\"left\"\u003e\n\u003cp\u003e0.005*\u003c/p\u003e\n\u003c/th\u003e\n\u003c/tr\u003e\n\u003c/thead\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eFBG\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge group (Years)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e81(58.3)\u003c/p\u003e\n\u003cp\u003e299(55.7)\u003c/p\u003e\n\u003cp\u003e133(62.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e58(41.7)\u003c/p\u003e\n\u003cp\u003e238(44.3)\u003c/p\u003e\n\u003cp\u003e80(37.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e1.112(0.762\u0026ndash;1.622)\u003c/p\u003e\n\u003cp\u003e0.840(0.543\u0026ndash;1.299)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.237\u003c/p\u003e\n\u003cp\u003e0.392\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e203(53.6)\u003c/p\u003e\n\u003cp\u003e310(60.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e176(46.4)\u003c/p\u003e\n\u003cp\u003e200(39.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.733(0.560\u0026ndash;0.959)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.031*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eTC\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge group (Years)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e97(69.8)\u003c/p\u003e\n\u003cp\u003e314(58.5)\u003c/p\u003e\n\u003cp\u003e147(69.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e42(30.2)\u003c/p\u003e\n\u003cp\u003e223(41.5)\u003c/p\u003e\n\u003cp\u003e66(31.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e1.640 (1.098\u0026ndash;2.449)\u003c/p\u003e\n\u003cp\u003e1.037(0.652\u0026ndash;1.649)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.005*\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e0.321\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e174(45.9)\u003c/p\u003e\n\u003cp\u003e384(75.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e205(54.1)\u003c/p\u003e\n\u003cp\u003e126(24.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.279(0.209\u0026ndash;0.370)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd rowspan=\"2\" align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge group (Years)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e34(24.5)\u003c/p\u003e\n\u003cp\u003e160(29.8)\u003c/p\u003e\n\u003cp\u003e64(30.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e105(75.5)\u003c/p\u003e\n\u003cp\u003e377(70.2)\u003c/p\u003e\n\u003cp\u003e149(70.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.763(0.497\u0026thinsp;\u0026minus;\u0026thinsp;0.171)\u003c/p\u003e\n\u003cp\u003e0.754(0.464\u0026ndash;1.225)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.434\u003c/p\u003e\n\u003cp\u003e0.254\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e133(35.1)\u003c/p\u003e\n\u003cp\u003e125(24.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e246(64.9)\u003c/p\u003e\n\u003cp\u003e385(75.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e1.665(1.244\u0026ndash;2.229)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge group (Years)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e131(94.2)\u003c/p\u003e\n\u003cp\u003e438(81.0)\u003c/p\u003e\n\u003cp\u003e201(94.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e8(5.8)\u003c/p\u003e\n\u003cp\u003e102(19.0)\u003c/p\u003e\n\u003cp\u003e12(5.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e3.813(1.809\u0026ndash;8.038)\u003c/p\u003e\n\u003cp\u003e0.978(0.388\u0026ndash;2.56)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001*\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e0.961\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e217(71.5)\u003c/p\u003e\n\u003cp\u003e496(97.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e108(28.5)\u003c/p\u003e\n\u003cp\u003e14(2.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.056(0.032\u0026ndash;0.101)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eDiet\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge group (Years)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e7(5.0)\u003c/p\u003e\n\u003cp\u003e41(7.6)\u003c/p\u003e\n\u003cp\u003e10(4.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e132(95.0)\u003c/p\u003e\n\u003cp\u003e496(92.4)\u003c/p\u003e\n\u003cp\u003e203(95.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.893(0.718\u0026ndash;1.834)\u003c/p\u003e\n\u003cp\u003e0.988(0.835\u0026ndash;1.393)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.252\u003c/p\u003e\n\u003cp\u003e0.391\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e26(6.9)\u003c/p\u003e\n\u003cp\u003e32(6.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e353(93.1)\u003c/p\u003e\n\u003cp\u003e478(93.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e0.991(0.868\u0026ndash;1.049)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e0.727\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003ePhysical\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eActivity\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eAge group (Years)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026lt;\u0026thinsp;45\u003c/p\u003e\n\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\n\u003cp\u003e\u0026gt;\u0026thinsp;65\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e32(23.0)\u003c/p\u003e\n\u003cp\u003e172(32.0)\u003c/p\u003e\n\u003cp\u003e41(19.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e107(77.0)\u003c/p\u003e\n\u003cp\u003e365(68.0)\u003c/p\u003e\n\u003cp\u003e172(80.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e0.635(0.411\u0026ndash;0.980)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1.255(0.744\u0026ndash;2.114)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e0.001*\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e0.394\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMale\u003c/p\u003e\n\u003cp\u003eFemale\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e134(38.3)\u003c/p\u003e\n\u003cp\u003e100(19.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e234(61.7)\u003c/p\u003e\n\u003cp\u003e410(80.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e1\u003c/p\u003e\n\u003cp\u003e2.348(1.731\u0026ndash;3.184)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd align=\"left\"\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001*\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n\u003cp\u003eLegend: BP, Blood Pressure; FBG, Fasting Blood Glucose; TC, Total Cholesterol; BMI, Body Mass Index\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis is the first study in Nigeria (from the knowledge of the authors) to investigate the prevalence of the AHA-recommended ideal cardiovascular health metrics and its relationship with age and sex. In our study no subject met the seven ICH metrics. Globally the prevalence of meeting the seven ICH metrics is low, ranging between 0.1% and 15% depending on the geographical region, age, sex and educational status [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. We found a prevalence of 7.9% of ICH (5\u0026ndash;7 metrics) from our study, which perhaps is the lowest in the world comparable to 9.1% reported by Wu et al in China [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In Peru and in Chilean women the prevalence of ICH (5\u0026ndash;7 metrics) was reported to be 12.7% and 14.3% respectively [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Other studies however have reported higher prevalence of ICH in recent times. In Nepal, Bangladesh, Malawi, Uganda, and South Africa the prevalence of ICH was 51.6%, 43.1%, 71.5%, 50% and 53% respectively [\u003cspan additionalcitationids=\"CR30 CR31 CR32 CR33\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. The higher prevalence in these studies might reflect the impact of the increased global campaign on the importance of healthy lifestyle choices as the fulcrum for the primordial prevention of NCDs/CVD [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Low prevalence of ICH in the general population means that majority of the people live with these modifiable CVD risk factors and are at a heightened risk CVD [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Studies have documented graded and continuous inverse relationship between the components of ICH and risk of incident CVD, Type 2 DM, cognitive impairment, depression, and cancers [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. The low prevalence of ICH from our study instructs that significant effort must be invested in the promotion of cardiovascular health through enforceable health policies.\u003c/p\u003e \u003cp\u003eOur study also found differences in the prevalence in ideal biologic and behavioural ICH factors. For the biologic metrics ideal total cholesterol was the most (62.7%) prevalent, followed by ideal blood glucose (57.7%) while ideal blood pressure was the least (31.5%). For the ideal behavioural metrics non-smoking status was the most (86.3%) prevalent while prevalence of ideal diet was abysmally low (6.5%). Our findings corroborate reports in published literature where ideal total cholesterol, non-smoking and blood glucose had the best global prevalence [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. According to AHA's 2018 heart disease and stroke statistics update, the prevalence of ICH among US adults, was 77.1% for smoking, 60.3% for TC, 53.2% for FBG, 49.7% for physical activity, 45.4% for BP, 29.6% for BMI, and 1.1% for dietary pattern [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These are somewhat comparable to our overall results. The prevalence of ideal blood pressure of 31.5% in our cohort is lower than figures from Peru (51%) Marshall Islands (46.7%) and Malawi (46.9%) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], but comparable to prevalence rates from Bangladesh (29.3%), Nepal (26.3%), Uganda (37%), China (32.3%) and 29.9% (Urban male dwelling Ghanaians) [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The relatively low prevalence of ideal BP in our cohort might be an indirect reflection of the high burden of hypertension in Nigeria characterized by high prevalence of low awareness, high burden of undiagnosed and poor control [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. The prevalence of ideal diet is globally low according to published literature and our finding of 6.1% aligns with this global trend [\u003cspan additionalcitationids=\"CR29 CR30 CR31 CR32\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan additionalcitationids=\"CR41\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. This global trend might be attributable to the twin problems of availability and affordability of fruits and vegetables remotely due to urbanization where arable farmlands have been converted for physical urban development [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWe also found a low prevalence of ideal physical activity profile of 27.6% in our cohort, implying that 72.4% did not met the ideal physical activity requirements. In Nigeria the prevalence of physical inactivity in adults varies between studies. A recent meta-analysis reported a cruse prevalence of physical inactivity to be between 25% and 57% [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. The high prevalence of physical inactivity in our cohort may reflect the effects of globalization, westernization of lifestyles, and poor town planning due to teeming population [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. Unhealthy diets and physical inactivity drive the global burden of obesity (all behavioural factors) and buttresses the inter-relatedness of the CVD risk factors [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The high prevalence of ideal smoking status (86.2%) from our study aligns with published literature [\u003cspan additionalcitationids=\"CR29 CR30 CR31\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and mirrors the low prevalence of smoking in the general Nigerian population (10.4% current smokers and 17.7% ever smokers vs 4.3% current smokers and 12.1% previous smokers from our study) [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSex and age are non-modifiable risk factors for CVD and have been shown to determine the prevalence of ICH. From our study there were sex and age differences in the prevalence of both the ideal biologic and behavioural factors. Females in our cohort had higher prevalence of ideal cholesterol, blood pressure and blood glucose compared to the males. They also had higher prevalence of non-smoking status. Similar studies have reported better ICH metrics (both behavioural and biologic) in females than males [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. This might be due better self-care practices in women compared with men [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Higher prevalence of ideal BP in females can also be partly explained by women\u0026rsquo;s stronger anti-inflammatory immune profile, which might as a compensatory mechanism to limit increases in blood pressure [\u003cspan additionalcitationids=\"CR56 CR57 CR58\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. We also found lower prevalence of ICH with increasing age. Those below age 45 years irrespective of sex had higher prevalence of ICH compared to those above 45 years of age. This trend has been reported by other similar studies [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan additionalcitationids=\"CR41 CR42\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The risk of CVD increases linearly with age. With advancing age, the risk of hypertension, diabetes, obesity, and physical inactivity also increases [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]. The corollary is that the odd for ICH decreases as age increases.\u003c/p\u003e \u003cp\u003eBoth the behavioural and biological ICH factors are interwoven with respect to incident CVD. The heart and soul of preventive cardiology is primordial prevention which entails a life-course approach to the prevention of the development of the intermediate/biologic/metabolic risk factors for CVD (obesity, hypertension, dyslipidemia and diabetes) in the general population [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. This is ensured through the promotion of healthy living via consumption of heart-healthy diets (DASH and Mediterranean diets), abstinence from tobacco use, healthy use of alcohol (if necessary), intentional physical activity and healthy management of psycho-social stress. Promotion of these behaviours ideally should start in childhood as it has been shown that non-ideal lifestyles in childhood is associated with increased risk of CVD in later adult life as evidenced by PDAY and the Bogalusa Heart studies [\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]. This is further supported by the results of the the Cardiovascular Risk in Young Finns Study and Special Turku Coronary Risk Factor Intervention Project for Children [STRIP] studies [\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Appropriate dietary intake, including reduction in sodium and saturated fat consumption, can reduce the risk of developing hypertension and dyslipidaemia. Regular physical activity is associated with lower blood pressure, healthier lipid profiles and ideal body weight. Diet and exercise are critical to maintaining ideal weight that engenders cardiovascular health. Behavioural factors such as stress management, sleep duration, portion control, and meal timing may play a role in weight management and offer additional routes of intervention [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]. Smoking, in addition to being an independent risk factor for CVD, is also associated with increased BP and heart rate, poorer lipid profile and high BMI [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. In the same vein unhealthy use of alcohol leads to raised BP, unhealthy lipid profile and increased BMI [\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUnrelenting public health campaign on the importance and benefits of healthy lifestyles is a sine qua non in the promotion of primordial prevention of CVD/NCDs. Structured lifestyle modification programs population via National policies will go a long way in promoting primordial prevention of CVD. Opportunistic screening especially of individuals aged 40 years and above will not only identify individuals with latent risk factors for CVD but also those in whom intense lifestyle modification will become a major intervention. The burden of CVD/NCDs is driven by urbanization. National governments should enunciate and implement policies that will mitigate the adverse impacts of urbanization on public health.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study demonstrated low prevalence of ICH factors among Nigerians and its association with age. Efforts should be spared in the campaign against unhealthy lifestyles such as physical inactivity and unhealthy diets as these two in particular are drivers of metabolic risks like hypertension, obesity, dyslipidemia and Type 2 diabetes.\u003c/p\u003e \u003cp\u003eOur study has some limitations. First there is the issue of recall bias as some of the data was via self-report. Secondly our study was cross-sectional in design and was unable to show any association with incident CVD or establish causality. However, we have proved information which we believe should inspire further research in this area.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAHA\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;American Heart Association\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eANOVA\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Analysis of Variance\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;BMI\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Body Mass Index\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eBP\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Blood Pressure\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCVD\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Cardiovascular Disease\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDASH\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Dietary Approach to Stopping Hypertension \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFBG\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Fasting Blood Glucose\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;ICH\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Ideal Cardiovascular Health \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIPAQ-SF\u0026nbsp;\u0026nbsp; \u0026nbsp;\u0026nbsp;International Physical Activity Questionnaire-Short Form\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNCDs\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Non-Communicable Diseases\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePDAY\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Pathobiological Determinants of Atherosclerosis in the Young\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSSA\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sub-Saharan Africa\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSTRIP\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Special Turku Coronary Risk Factor Intervention Project for Children\u003c/p\u003e\n\u003cp\u003eTC \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Total cholesterol\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval was obtained from the Health Research Ethics Committee of the Amuwo Odofin Municipality, overseeing the political administration of the study area.\u0026nbsp;The study participants were informed about the purpose and nature of the study and that the data generated from the study would be anonymized and de-identified when published.\u0026nbsp;No data was collected before detailed information was provided to the\u0026nbsp;study participants, and a signed, informed consent was obtained.\u0026nbsp;Participants who had elevated CVD risk factors were duly referred to their primary care physicians/Public hospitals for definitive management.\u0026nbsp;The study complied with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eStudy participants gave their consent for their de-identified data to be published.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and material\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data of this study is available on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaid Checks Diagnostics and Wellness, Roche Diabetic Care and Omron Healthcare\u0026nbsp;provided the equipment\u0026nbsp;(cholesterol meter, glucometer, and BP monitors) for the\u0026nbsp;training\u0026nbsp;and\u0026nbsp;for the research.\u0026nbsp;There were no branded promotional information/materials from these companies\u0026nbsp;around the vicinity of the screening exercises\u0026nbsp;nor were there financial rewards to the participants for taking part in the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions:\u003c/strong\u003e CEA and FOL conceptualized the research topic, coordinated the investigators’ training and data curation. CMA analysed the data. ICU and ACM drafted the manuscript while CEA, JNA and DAO reviewed the draft of the manuscript. All authors read and approved the final draft of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003cstrong\u003e:\u003c/strong\u003e The authors wish to acknowledge the management of Rapid Check Diagnostic and Wellness Ltd, Roche Diabetes Care, Omron Healthcare, Victory Drugs and Meridian Cardiac Clinic for providing the equipment and training for the research.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHamid S, Groot W, Pavlova M. Trends in cardiovascular diseases and associated risks in sub-Saharan Africa: a review of the evidence for Ghana, Nigeria, South Africa, Sudan and Tanzania. Aging Male. 2019;22(3):169\u0026ndash;176. doi: 10.1080/13685538.2019.1582621. Epub 2019 Mar 16. 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PMID: 32326404; PMCID: PMC7231110.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"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":"Ideal Cardiovascular Health, Metrics, CVD, AHA, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-3321566/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3321566/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/em\u003e Ideal cardiovascular health (ICH) is a metrics for primordial prevention of cardiovascular disease (CVD). Its prevalence in Nigerians is not known.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study assessed the seven American Heart Association’s ICH metrics of 889 Nigerians. The metrics included non-smoking, healthy diet, physical activity, body mass index (\u0026lt;25 kg/m2), untreated blood pressure \u0026lt;120/\u0026lt;80 mmHg, untreated total cholesterol \u0026lt;200 mg/dL, and untreated fasting blood glucose \u0026lt;100 mg/dL). Logistic regressions were used to estimate associations between sociodemographic factors (age and sex) and meeting 5–7 CVH metrics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e No one met all 7 of ICH metrics while 70 (7.8%) had 5-7metrics. The most prevalent and least prevalent ideal biological factors were ideal fasting plasma cholesterol (62.8%) and ideal blood pressure (31.5%) respectively. The most prevalent and least prevalent behavioural factors were ideal smoking status (86.2%) and ideal diet (6.5%) respectively. Compared to males, females had better ideal BP, p=0.005; better ideal fasting plasma glucose, p=0.031; better ideal fasting plasma cholesterol, p\u0026lt;0.001 and ideal smoking status, p\u0026lt;0.001. Ages 45 to 64 had better ideal smoking status and ideal physical activity (p\u0026lt;0.001 and p=0.001 respectively).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/em\u003e There is a low prevalence of ICHamong Nigerians. Concerted efforts should be made to improve healthy living among Nigerians.\u003c/p\u003e","manuscriptTitle":"Low Prevalence of Ideal Cardiovascular Health Metrics in Nigerians: a cross sectional study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-09-18 16:46:27","doi":"10.21203/rs.3.rs-3321566/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":"cafc8fa7-6fd9-417e-bbe4-ca6f32c7996c","owner":[],"postedDate":"September 18th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-05-15T15:03:38+00:00","versionOfRecord":{"articleIdentity":"rs-3321566","link":"https://doi.org/10.4103/njc.njc_15_23","journal":{"identity":"nigerian-journal-of-cardiology","isVorOnly":true,"title":"Nigerian Journal of Cardiology"},"publishedOn":"2023-01-01 15:03:38","publishedOnDateReadable":"January 1st, 2023"},"versionCreatedAt":"2023-09-18 16:46:27","video":"","vorDoi":"10.4103/njc.njc_15_23","vorDoiUrl":"https://doi.org/10.4103/njc.njc_15_23","workflowStages":[]},"version":"v1","identity":"rs-3321566","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3321566","identity":"rs-3321566","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}