RESEARCH ARTICLE
Community-Based Screening for Cardiovascular Disease in the Capricorn District of Limpopo Province, South Africa
Rambelani N. Malema1, *, Peter M. Mphekgwana2, Mpsanyana Makgahlela1, Tebogo M. Mothiba3, Kotsedi D. Monyeki4, Nancy Kgatla5, Irene Makgatho1, Tholene Sodi1
Article Information
Identifiers and Pagination:
Year: 2021Volume: 14
First Page: 241
Last Page: 249
Publisher ID: TOPHJ-14-241
DOI: 10.2174/1874944502114010241
Article History:
Received Date: 20/10/2020Revision Received Date: 10/3/2021
Acceptance Date: 1/4/2021
Electronic publication date: 10/06/2021
Collection year: 2021
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background:
The number of people who suffer and die from Cardiovascular Disease (CVD) is increasing at an alarming rate in low-and middle-income countries.
Objective:
The objective of the study was to screen communities using the non-laboratory INTERHEART Risk Score tool (NLIRS) to determine their level of risk for developing CVD.
Methods:
A community-based quantitative study was conducted in the Capricorn District of Limpopo Province. A total of 3315 participants were screened by 63 community health workers (CHWs) using the NLIRS tool. The tool covers the following items which are allocated different scores: Gender:male ≥55 years or female ≥65years=2; being a smoker or having stopped ≤12 months ago = 2; smoking1-5 cigarettes =2; 6-10=4; 11-15=6;16-20 a day and ≥20=11; indirect smoking last 12 months =2; having diabetes=6 and high blood pressure=5; parental history of heart attack=4; having stress and depression=3 each; consumption of salty and fried food, no vegetables or fruits each scored a 1; eating meat twice a day =2; being inactive =2; waist-to-hip ratio ≥.874-0.963=2 and ≥0.964=4. The scores were added and those who scored 0-9 were classified to be at low risk, 10-15 moderate and 16-48 at high risk.
Results:
On average 58% and 33% were found to be at low and moderate risk, respectively for developing CVD and 9% at high risk. The majority consumed salty, fried foods and meat and were inactive. Being hypertensive constituted 67% of being at high risk of developing CVD.
Conclusion:
Envisaged intervention will focus on preventive strategies for risk factors such as diet, exercise and hypertension. More males should be recruited to participate in future research to determine if the same results will be obtained.
1. INTRODUCTION
The World Health Organisation estimated that CVD contributed to 17.5 million deaths worldwide in 2012 with a third of those attributed to CVD [1]. In 2016 the number of CVD deaths increased to 17.9 million, which represented 31% of all global deaths [2]. It is projected that worldwide 24 million people will die from CVD by 2030 [3]. Seventy-five percent (75%) of these people stay in low- and middle-income countries [2, 4]. These estimates suggest that developed countries are experiencing a decline in CVD despite an increase in ageing population which is prone of CVD [5-7]. Another reason for the decline of CVD in developed countries may be due to the improvement in the management of their healthcare systems [5]. On the other hand, the expected increase of CVD in low and middle-income countries is attributed to rapid urbanisation and industrialisation [5, 8].
A report released by the WHO in 2017 indicates that CVD is now the second common cause of death after infectious diseases in Africa [2]. In South Africa, CVD is the second leading cause of death after HIV/AIDS [9] with about 210 people estimated to be dying from CVD every day [10]. It is estimated that the rate of premature death as a result of CVD amongst South African adults is projected to increase by 41% between 2000 and 2030 [11].
It is of concern that people who die from CVD lack awareness regarding the risk factors associated with CVD. Empirical studies have found that major risk factors associated with CVD include high blood pressure (hypertension), smoking, poor eating habits, unhealthy diet, obesity and lack of physical activity [10, 1, 12].
Studies conducted in South Africa by Nojilana et al. and Schutte [13, 14] recommended the prioritisation of the management of CVD in the same way as the aggressive approaches that are needed for the management of Non-Communicable Diseases (NCDs). Amongst strategies recommended for CVD prevention are health promotion and a change of lifestyle [15-17]. Training of nurses on CVD management has also been recommended [13, 14]. Studies show that CVD is preventable through health promotion and a change of lifestyle [15-17]. Epidemiological profiling of communities regarding their level of risk for developing cardiovascular disease, followed by appropriate interventions, may assist in reducing CVD prevalence [18, 19]. In line with the above recommendations, this study aimed to screen semi-urban and rural communities using the non-laboratory INTERHEART Risk Score tool (NLIRS). The results of the study will be used to develop relevant and suitable intervention strategies. This study is part of the bigger intervention study titled: “Scaling-up packages of intervention for cardiovascular disease prevention in selected sites in Europe and Sub-Saharan Africa” (SPICES).
2. MATERIALS AND METHODS
2.1. Study Design
A quantitative research approach applying the household-based cross-sectional descriptive design was used to conduct this study. Once-off data collection was done from the participants, using the NLIRS tool at their homes.
2.2. Study Setting
The study was conducted in two study sites of the Polokwane Municipality in Limpopo province, Capricorn district namely, Seshego semi-urban township located in the west and Ga-Molepo villages located in the eastern part of Polokwane city. The semi-urban township was serviced by 4 public Primary Health Care (PHC) clinics whereas, the rural villages were serviced by 7 public PHC clinics. The two sites were selected based on the findings and recommendations of research studies that reported a high prevalence of chronic diseases and an increase in the risk factors associated with the development of CVD [20-25]. These previous studies also recommended the development and implementation of health interventions to control the risk factors associated with NCDs and CVD (Fig. 1) [15-24].
 |
Fig. (1). Map of Polokwane municipality showing selected villages for the study. |
2.3. Population and Sampling
The total number of households was 3,930 for Seshego semi-urban township and 11,854 for Ga-Molepo rural villages. Yamane’s mathematical formula with an error of 5% and a confidence coefficient of 95% [26] was used to obtain a sample size for the selected sites (Seshego and Ga-Molepo) of 1,111 and 2,082 households, respectively. Furthermore, to obtain the exact number of the sample as proposed by Yamane’s mathematical formula [26] per village, proportional sampling was used where the researchers divided the population sample size per site into sub-villages and then applied proportionalsampling techniques to each sub-population. The total number of participants screened on both sites was 3315 (1390 Seshego and 1925 Ga-Molepo)due to their availability and willingness to participate in the study at the time of data collection.
2.4. Ethical Considerations
In preparation for data collection, ethical clearance was obtained from the University of Limpopo Turfloop Research and Ethics Committee (TREC/381/2017). Permission to conduct the study was obtained from the Limpopo Department of Health Research Committee. All the screened participants were briefed by trained CHWs about the data collection procedure before consenting to participate. Participants were further informed that their participation in the study was voluntary and that they were free to withdraw from the study at any time. A consent form was signed by those who agreed to participate in the study. Anonymity was ensured and all data was kept secure. No animals or plants were used in this study.
2.5. Data Collection
Data were collected over 8 months from June 2018 to January 2019 by 63 trained CHWs attached to the 11 clinics, 14 CHWs were from Seshego semi-urban township, whereas 49 were from Ga-Moleporural villages. The 63 CHWs were selected from a total of 143 CHWs due to their level of education. On average, each CHW was allocated between 280 and 242 households, which are under his/her care at the clinic in Seshego and Ga-Molepo, respectively. The CHWs are also well known to the communities because they reside in those areas. Each community health worker screened all members of a household who were at home on the day the data were collected, from 18 years and above, using the non-laboratory INTERHEART Risk Score tool.
2.5.1. The Interheart Risk Score Tool
The NLIRS tool covered the following items and was each allocated a score: Being male ≥55 years and female ≥65years=2; being a smoker or having stopped 12 months ago orless= 2; smoking 1-5 cigarettes=2; 6-10=4; 11-15 cigarettes=6;16-20 and 20+ per day=11; inhaling smoke from other people in the last 12 months =2; having diabetes=6and high blood pressure=5; a parental history of heart attack=4; psychological factors: experience of several periods of permanent work or home life stress in the past year and feeling depressed for two weeks or more in a row in the past 12 months=3 each; diet: consumption of: salty food or snacks one or more times a day and deep fried foods, snacks or fast foods 3 or more times a week=1 each, no vegetables or fruits a day=1, eating chicken or red meat twice a day=2; inactive or performing mild physical exercise during leisure=2; and measurement of waist-to-hip ratio (WHR) ≥.874-0.963=2 and ≥0.964=4 [26, 27]. At the end, the scores were added and those who scored 0-9 were deemed to be at low risk, 10-15 were at moderate risk and 16-48 were at high risk. The English version of the NLIRS tool was translated by a language expert to Northern Sotho after conducting the pilot study. Northern Sotho is an indigenous language spoken by the majority of respondents in the Capricorn district of Limpopo Province [28]. The NLIRS tool was chosen because it can be used in settings with limited resources [19, 29].
2.5.2. Measurements
The waist-to-height ratio circumference was measured using a tape measure. The waist circumference was measured at the approximate midpoint between the lower margin of the last palpable rib and the top of the iliac crest and the hip circumference was measured around the widest portion of the buttocks [30]. The blood pressure (BP) of those who did not know if they were hypertensive, was measured on the left arm using the MEDIC Pharmacists Choice Devices Blood Pressure Monitor Classic (MPCDBPMC). TheBP Monitor used has been clinically validated according to the European Society of Hypertension (ESH) protocol [31]. Being hypertensive included those who answered yes when asked if they had high blood pressure and those who did not know that they are hypertensive, but were found to have a systolic BP score of
2.5.3. Validity and Reliability
To ensure validity and reliability, the CHWs were first trained by the research team on risk factors associated with CVD, prevention of CVD and how to screen the participants using the NLIRS tool for a week followed by a one-day refresher course before commencing with the pilot study. Training of the CHWs at their respective clinics continued after the pilot study. The NLIRS tool has been validated by 52 countries [25-27]. The CHWs were supervised by registered nurses and the research team during data collection.
2.6. Statistical Analysis
The participants who scored
3. RESULTS
The risk levels of developing CVD per residential site are presented in Table 1 below. Of the 3 315 participants who were screened, 1 390 were from Seshego and 1 925 from Ga-Molepo. On average 58% were at low and 9% at high risk.Whereas 33% were at moderate risk of developing CVD for both sites. Using a t-test it was found that there were no statistical differences between the risk score mean of the two sites. The number of female participants was almost triple that of males (females 75% vs 25%).
The mean NLIRS for the males was higher as compared to that of the females (10.59 vs 9.10, p< 0.001) (Table 2). Eighty-nine percent (89%) of the participants were non-smokers, with the majority (75%) consuming salty food/snacks (
The differences between gender with behavioural, biological, dietary and physical factors are also presented. The mean age of men and women was 49.34 and 48.79 years, respectively, with no major gender differences. There is a statistical difference between the numbers of the inactive participants/ those who performed mild exercises in the women sample as compared to the men sample (p < 0.001) with a higher number of women being inactive or performing mild exercises. There was no statistical difference in gender (p>0.05) regarding other factors, such as being diabetic and stressed, low fruit and vegetable intake, consumption of salty/deep-fried foods and red /poultry meat twice per day. Males exhibited an elevated ≥0.964 WHR as compared to females [64 males vs. 36, p < 0.001].
| - | Total | Low | Moderate | High | P-value |
|---|---|---|---|---|---|
| Seshego | n (%) | n (%) | n (%) | n (%) | 0.077 |
| Female | 1035 (75) | 646 (78,30) | 317 (69,82) | 72 (64,86) | |
| Male | 355 (25) | 179 (21,70) | 137 (30,18) | 39 (35,14) | |
| Total | - | 825 (59) | 454 (33) | 111 (8) | |
| Ga-Molepo | - | - | - | - | |
| Female | 1440 (75) | 872 (79,34) | 448 (71,34) | 120 (60,61) | |
| Male | 485 (25) | 227 (20,66) | 180 (28,66) | 78 (39,39) | |
| Total | - | 1099 (57) | 628 (33) | 198 (10) | - |
Fig. (2) illustrates the percentage distribution by diabetes, hypertension, number of cigarettes and parental history of heart attack among all the categories of risk levels. It can be seen from the plot that participants who reported being hypertensive hold a high proportion (67.9%) of being at a high-risk level of developing CVD. The proportion of being diabetic, having a parent who has a history of heart disease, smoking more than 6 cigarettes per day increases as you move from low to moderate, to high risk. Only the high-risk level had participants that smoked more than 20 cigarettes per day. The mean age for both genders increased as you moved from low to high risk (Fig. 3) suggesting that the level of risk for developing CVD increases with age for both males and females. More females were at moderate and high risk for developing CVD than males.
 |
Fig. (2). INTERHEART risk scores in diabetes, hypertension, number of cigarettes and parental history of heart attack, by risk level. |
 |
Fig. (3). The mean age of females and males by risk level. |
4. DISCUSSION
The study aimed to screen communities for their level of risk for developing CVD using the NLIRS tool. The results from the study showed that ageing for both males and females could increase a person's risk of developing CVD. This was not surprising, because age is a well-known independent risk factor for developing CVD [33]. However, the lowering of blood pressure, cholesterol, blood glucose, smoking abstinence, being female and having a higher education increased the survival rate up to the age of 85 years [34].
The number of females screened was almost triple that of males in this study. The reason for the high number of females as compared to males in this study could be attributed to the fact that most men were not at home at the time of screening, as they could probably have been at work [35].
There was a higher number of hypertensive females compared to males in this study. This differs from other findings, where there were more males with hypertension as compared to females [36-39]. Studies that have investigated gender differences in hypertension reported that the reason why there were more men than women with hypertension is that women are protected by biological factors such as the sex hormones oestrogen and progesterone before they reach menopause [40, 41] and chromosomes [42-44]. These biological factors become evident during adolescence and persist through adulthood and disappear when women reach menopause and at that point, the differences in hypertension become smaller or non-existent [40, 41, 45-47].
More males in this study had a WHR of
In this study, more females were consuming more red meat/poultry ≥2 times/day than males. A study conducted amongst college students found that males consumed more red meat than females [58]. Consumption of red meat is a risk factor for developing CVD, type 2 diabetes and colon cancer [59-63]. But consumption of more than one portion per day and regular consumption of processed meat rather than fresh red meat put people at greater risk of developing type 2 diabetes, coronary heart diseases and CVD [64].
More females perform mild exercises than males, who tend to lead a sedentary life. In most cases, women do not have the time to exercise because of the housework, taking care of children, care for the elderly or disabled family members [65]. In some places, there are no sidewalks and women are an easy target for criminals so they are afraid to go to parks.
The majority, 89%, of the participants in this study were non-smokers. The prevalence of smoking in South Africa based on the national survey conducted in 2012 was 17.6% [66]. However, the participants who smoked 20 and more cigarette per day in this study were all found to be at high risk of developing CVD. Cigarette smoking is a major risk factor for the development of CVD [67, 68]. Many researchers reported that cigarette smoking poses a double risk of developing CVD, including cerebrovascular diseases and heart failure, irrespective of the number of cigarettes smoked a day [69-74].
Most participants who were hypertensive were classified to be at high risk of developing CVD. Hypertension has been reported by many researchers as the strongest risk factor for developing almost all different cardiovascular heart diseases, cardiac arrhythmias, including arterial fibrillation, cerebral stroke and renal failure [75-80].
CONCLUSION
Communities were successfully screened to determine their level of risk for developing CVD by trained CHWs. Those at high risk for developing CVD were referred for further management to their respective Primary Health Care clinics. Those who were found to be at moderate risk will be enrolled in an intervention programme focusing on the prevention of hypertension, reduction in the consumption of salty foods/snacks, deep-fried foods/fast foods and red meat/poultry applying self-management strategies. More than half of the participants who reported being mainly inactive, or performing mild exercises, will be advised/taught individual exercises at their homes or group exercises at their respective Primary Health Care clinics and those who can afford to will be advised to enrol at the available Gyms in their communities. Ageing was also found to be a contributing risk factor for developing CVD. Rolling-out of intervention programmes at schools will be beneficial. Very few males participated in the study as compared to females. More males should be recruited to participate in future research studies to determine if the same results will be obtained.
ETHICS APPROVAL AND CONSENT TO PARTICIPATE
Ethical clearance was obtained from the University of Limpopo Turfloop Research and Ethics Committee, South Africa (TREC/381/2017).
HUMAN AND ANIMAL RIGHTS
No Animals were used in this research. All human research procedures were followed in accordance with the ethical standards of the committee responsible for human experimentation (institutional and national), and with the Helsinki Declaration of 1975, as revised in 2013.
CONSENT FOR PUBLICATION
Written informed consent was obtained from all the participants.
AVAILABILITY OF DATA AND MATERIALS
Derived data supporting the findings of this study are available from the corresponding author [R.N] on request.
FUNDING
This research is funded by the European Commission through the Horizon 2020 Research and Innovation Action Grant Agreement No. 733356.
CONFLICT OF INTEREST
The authors declare no conflict of interest, financial or otherwise.
ACKNOWLEDGMENTS
The authors would like to thank all the participants, CHWs, professional nurses at the clinics, members of the SPICES research, the University of Limpopo and the Limpopo Provincial Department of Health. Lastly, to thank the European Commission for funding this project.
REFERENCES
| [1] | World Health Organization. Cardiovascular Disease Facts Sheets 2016. Available at: http://www.who.int/mediacentre/factsheets/fs317/en/ |
| [2] | WHO. Cardiovascular diseases, (CVDs) 2017. Available at: http://www.who.int/ |
| [3] | Fuster V, Kelly BB, Vedanthan R. Promoting global cardiovascular health: Moving forward. Circulation 2011; 123(15): 1671-8. |
| [4] | Naghavi M, Wang H, Lozano R. Global, regional, and national age-sex specific all-cause and cause-specific mortality for 240 causes of death, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. Lancet 2014; 385(9963): 117-71. |
| [5] | Peeters A, Nusselder WJ, Stevenson C, Boyko EJ, Moon L, Tonkin A. Age-specific trends in cardiovascular mortality rates in the Netherlands between 1980 and 2009. Eur J Epidemiol 2011; 26(5): 369-73. |
| [6] | Stringhini S, Viswanathan B, Gédéon J, Paccaud F, Bovet P. The social transition of risk factors for cardiovascular disease in the African region: Evidence from three cross-sectional surveys in the Seychelles. Int J Cardiol 2013; 168(2): 1201-6. |
| [7] | Krishnamurthi RV, Feigin VL, Forouzanfar MH, et al. Global and regional burden of first-ever ischaemic and haemorrhagic stroke during 1990-2010: Findings from the Global Burden of Disease Study 2010. Lancet Glob Health 2013; 1(5): e259-81. |
| [8] | O’Flaherty M, Buchan I, Capewell S. Contributions of treatment and lifestyle to declining CVD mortality: Why have CVD mortality rates declined so much since the 1960s? Heart 2013; 99(3): 159-62. |
| [9] | Msemburi W, Pillay-van Wyk V, Dorrington RE, et al. Second national burden of disease study for South Africa 1997-2010 2014; 1-23. |
| [10] | Zűhlke L. Why heart disease is on the rise in South Africa 2016. Available at: conversation.com/why-heart-disease-is-on-the |
| [11] | Gaziano TA. Reducing the growing burden of cardiovascular disease in the developing world. Health Aff (Millwood) 2007; 26(1): 13-24. |
| [12] | Mbewu AD. Burden of cardiovascular disease in sub-saharan africa. SAHeart 2009; 6(1): 4-10. |
| [13] | Nojilana B, Bradshaw D, Pillay-van Wyk V, et al. Persistent burden from non-communicable diseases in South Africa needs strong action. S Afr Med J 2016; 106(5): 23-4. |
| [14] | Schutte AE. Urgency for South Africa to prioritize cardiovascular disease management 2019. Available at: www.thelancet.com/lancetgh |
| [15] | Yu E, Malik VS, Hu FB. Cardiovascular disease prevention by diet modification. J Am Coll Cardiol 2018; 72(8): 914-26. |
| [16] | Leening MJG, Ikram MA. Primary prevention of cardiovascular disease: The past, present, and future of blood pressure- and cholesterol-lowering treatments. PLoS Med 2018; 15(3)e1002539 |
| [17] | Stewart J, Manmanthan G, Wilkinson P. Primary prevention of cardiovascular disease: A review of contemporary guidance and literature. JRSM Cardiovasc Dis 2017; 6: 2048004016687211. |
| [18] | Niiranen TJ, Vasan RS. Epidemiology of cardiovascular disease: Recent novel outlooks on risk factors and clinical approaches. Expert Rev Cardiovasc Ther 2016; 14(7): 855-69. |
| [19] | Ofori SN, Odia OJ. Risk assessment in the prevention of cardiovascular disease in low-resource settings. Indian Heart J 2016; 68(3): 391-8. |
| [20] | Alberts M, Urdal P, Steyn K, Stensvold I, Tverdal A, Nel JH, et al. Prevalence of cardiovascular diseases and associated risk factors in a rural black population of South Africa. Eur J Prev Cardiol 2005; 12(4): 347-54.http://cpr.sagepub.com/content/12/4/347 |
| [21] | Goedecke JH, Jennings CL, Lambert EV. Obesity in South Africa. Chronic diseases of lifestyle in South Africa since 1995-2005. |
| [22] | Bradshaw D, Steyn K, Levitt N, Nojilana B. Non-Communicable Diseases–A race against time. Medical Research Council 2011. Available at: http://www.mrc.ac.za/policybriefs/raceagainst.pdf |
| [23] | Puoane TR, Tsolekile LP, Caldbick S, Igumbor EU, Meghnath K, Sanders D. Chronic non-communicable diseases in South Africa: Progress and challenges. S Afr Health Rev 2012; 2012(1): 115-26. |
| [24] | Ntuli TS, Maimela E, Alberts M, Choma S, Dikotope S. Prevalence and associated risk factors of hypertension amongst adults in a rural community of Limpopo Province of South Africa. Afr J Prim Health Care Fam Med 2015; 7(1): 847. |
| [25] | Maimela E, Alberts M, Modjadji SEP, et al. Theprevalence and determinants of chronic non-communicable disease risk factors amongst adults in the Dikgale Health Demographic and Surveillance System (HDSS) 2016; 11(2): e0147926.. |
| [26] | Yamane T. An introductory analysis 3rd. 1973. |
| [27] | McGorrian C, Yusuf S, Islam S, et al. Estimating modifiable coronary heart disease risk in multiple regions of the world: The INTERHEART Modifiable Risk Score. Eur Heart J 2011; 32(5): 581-9. |
| [28] | Cordero A, López-Palop R, Carrillo P, Miralles B, Masiá MD, Bertomeu-Martínez V. Prognostic value of the INTERHEART-cholesterol risk score in patients hospitalized for chest pain. Rev Esp Cardiol (Engl Ed) 2014; 67(7): 578-80. |
| [29] | Joseph P, Yusuf S, Lee SF, Ibrahim O. Prognostic validation of a non-laboratory and laboratory base cardiovascular disease risk score in multiple regions. Heart 2018; (104): 581-7. |
| [30] | Statistics South Africa. Census 2011 provincial profile: Limpopo report 03-01-78 2014, Statistics South Africa: Pretoria 2014. Available at: http://www.statsaa.gov.za/publications//Report -03-01-78/R-03-10-782011.pdf |
| [31] | Gerstein HC, Yusuf S, Holman R, Bosch J, Pogue J. Rationale, design and recruitment characteristics of a large, simple international trial of diabetes prevention: The DREAM trial. Diabetologia 2004; 47(9): 1519-27. |
| [32] | WHO. WHO STEPwise approach to surveillance (STEPS) Geneva, World Health Organization (WHO) 2008. |
| [33] | Chalmers JOHN, MacMahon S, Mancia G, et al. 1999 World Health Organization-International Society of Hypertension Guidelines for the management of hypertension. Guidelines sub-committee of the World Health Organization. Clinical and Experimental Hypertension (New York, NY: 1993) 1999; 21(5-6): 1009-60. |
| [34] | O’Brien E, Atkins N, Stergiou G, et al. Working Group on Blood Pressure Monitoring of the European Society of Hypertension. European Society of Hypertension International Protocol revision 2010 for the validation of blood pressure measuring devices in adults. Blood Press Monit 2010; 15(1): 23-38. |
| [35] | Dhingra R, Vasan RS. Age as a risk factor. Med Clin North Am 2012; 96(1): 87-91. |
| [36] | Seals DR, Jablonski KL, Donato AJ. Aging and vascular endothelial function in humans. Clin Sci (Lond) 2011; 120(9): 357-75.https://doi.org |
| [37] | South African Government News Agency. Males continue to dominate labour market 2018.https://www. sanews.gov.za/south-africa/males-continue-dominate-labour-market |
| [38] | Everett B, Zajacova A. Gender differences in hypertension and hypertension awareness among young adults. Biodemogr Soc Biol 2015; 61(1): 1-17. |
| [39] | Yoon SS, Gu Q, Nwankwo T, Wright JD, Hong Y, Burt V. Trends in blood pressure among adults with hypertension: United States, 2003 to 2012. Hypertension 2015; 65(1): 54-61. |
| [40] | Roger VL, Go AS, Lloyd-Jones DM, et al. Heart disease and stroke statistics--2011 update: A report from the American Heart Association. Circulation 2011; 123(4): e18-e209. |
| [41] | Wenner MM, Stachenfeld NS. Blood pressure and water regulation: Understanding sex hormone effects within and between men and women. J Physiol 2012; 590(23): 5949-61. |
| [42] | Mozaffarian D, Benjamin EJ, Go AS, et al. Heart disease and stroke statistics-2016 update: A report from the American Heart Association. Circulation 2016; 133(4): e38-e360. |
| [43] | Choi HM, Kim HC, Kang DR. Sex differences in hypertension prevalence and control: Analysis of the 2010-2014 Korea National Health and Nutrition Examination Survey. Plos 2017. |
| [44] | Sandberg K, Ji H. Sex differences in primary hypertension. Biol Sex Differ 2012; 3(1): 7. |
| [45] | Rodgers JL, Jones J, Bolleddu SI, et al. Cardiovascular risks associated with gender and aging. J Cardiovasc Dev Dis 2019; 6(2): 19. |
| [46] | Vitale C, Fini M, Speziale G, Chierchia S. Gender differences in the cardiovascular effects of sex hormones. Fundam Clin Pharmacol 2010; 24(6): 675-85. |
| [47] | Vitale C, Mendelsohn ME, Rosano GMC. Gender differences in the cardiovascular effect of sex hormones. Nat Rev Cardiol 2009; 6(8): 532-42. |
| [48] | WHO. Global burden of disease update 2004 2008. |
| [49] | Medical News Today. Why is the waist-hip-ratio important? 2017.https://www.medicalnewstoday.com/articles/319439 |
| [50] | Huxley R, Mendis S, Zheleznyakov E, Reddy S, Chan J. Body mass index, waist circumference and waist:hip ratio as predictors of cardiovascular risk--a review of the literature. Eur J Clin Nutr 2010; 64(1): 16-22. |
| [51] | Ul-Haq Z, Smith DJ, Nicholl BI, et al. Gender differences in the association between adiposity and probable major depression: A cross-sectional study of 140,564 UK Biobank participants. BMC Psychiatry 2014; 14: 153. |
| [52] | CzernichowS, Kengne A-P, Huxley RR, Batty GD, de Galan B, Grobbee D, Pillai A,Zoungas S, Marre M, Woodward M, Neal B, Chalmers J et al. . Comparison of waist-to-hip ratio and other obesity indices as predictors of cardiovascular disease risk in people with type 2 diabetes: A prospective cohort study from ADVANCE. Euro J CardiovascPrevRehabil 2011; 18(2): 312-9. |
| [53] | Lapidus L, Bengtsson C, Larsson B, Pennert K, Rybo E, Sjöström L. Distribution of adipose tissue and risk of cardiovascular disease and death: A 12 year follow up of participants in the population study of women in Gothenburg, Sweden. Br Med J (Clin Res Ed) 1984; 289(6454): 1257-61. [OpenUrl]. |
| [54] | Qiao Q, Nyamdorj R. Is the association of type II diabetes with waist circumference or waist-to-hip ratio stronger than that with body mass index? Eur J Clin Nutr 2010; 64(1): 30-4. a |
| [55] | Qiao Q, Nyamdorj R. The optimal cutoff values and their performance of waist circumference and waist-to-hip ratio for diagnosing type II diabetes. Eur J Clin Nutr 2010; 64(1): 23-9. b |
| [56] | Seidell JC. Waist circumference and waist/hip ratio in relation to all-cause mortality, cancer and sleep apnea. Eur J Clin Nutr 2010; 64(1): 35-41. |
| [57] | Srikanthan P, Seeman TE, Karlamangla AS. Waist-hip-ratio as a predictor of all-cause mortality in high-functioning older adults. Ann Epidemiol 2009; 19(10): 724-31. |
| [58] | Forestell CA, Spaeth AM, Kane SA. To eat or not to eat red meat. A closer look at the relationship between restrained eating and vegetarianism in college females. Appetite 2012; 58(1): 319-25. |
| [59] | Bernstein AM, Sun Q, Hu FB, Stampfer MJ, Manson JE, Willett WC. Major dietary protein sources and risk of coronary heart disease in women. Circulation 2010; 122(9): 876-83. |
| [60] | Pan A, Sun Q, Bernstein AM, et al. Red meat consumption and mortality: Results from 2 prospective cohort studies. Arch Intern Med 2012; 172(7): 555-63. |
| [61] | Battaglia Richi E, Baumer B, Conrad B, Darioli R, Schmid A, Keller U. Health risks associated withmeatconsumption: A review of epidemiological studies. Int J Vitam Nutr Res 2015; 85(1-2): 70-8. |
| [62] | Abete I, Romaguera D, Vieira AR, Lopez de Munaina A, Norat T. Association between total, processed, red and white meat consumption and all-cause, CVD and IHD mortality: A meta-analysis of cohort studies. British Journal Nutrition 2014; 112(5): 762-75. |
| [63] | Wolk A. Potential health hazards of eating red meat. J Intern Med 2017; 281(2): 106-22. |
| [64] | Salter AM. Impact of consumption of animal products on cardiovascular disease, diabetes, and cancer in developed countries. Anim Front 2013; 3(1): 20-7. |
| [65] | Sergeant DJ. Why Women Don’t Exercise Enough 2019. Available at: http://www.bfohealth.com/features/why- |
| [66] | Reddy P, Zuma K, Shisana O, Kim J, Sewpaul R. Prevalence of tobacco use among adults in South Africa: Results from the first South African National Health and Nutrition Examination Survey. S Afr Med J 2015; 105(8): 648-55. |
| [67] | Mannan H, Stevenson C, Peeters A, Walls H, McNeil J. Framingham risk prediction equations for incidence of cardiovascular disease using detailed measures for smoking. Heart Int 2010; 5(2)e11 |
| [68] | Keto J, Ventola H, Jokelainen J, et al. Cardiovascular disease risk factors in relation to smoking behaviour and history: A population-based cohort study. Open Heart 2016; 3(2)e000358 |
| [69] | Lubin JH, Coupper D, Lutsey PL, Woodward M, Yatsuya H, Huxley RR. Risk of cardiovascular disease from cumulative cigarette use and the impact of smoking intensity. Epidemiology 2016; 27(3): 395-27. |
| [70] | GBD 2016 Risk Factors Collaborators. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2016: A systematic analysis for the Global Burden of Disease Study. Lancet 2017; 390(10100): 1345-422. |
| [71] | Thun MJ, Carter BD, Feskanich D, et al. 50-year trends in smoking-related mortality in the United States. N Engl J Med 2013; 368(4): 351-64. |
| [72] | Pirie K, Peto R, Reeves GK, Green J, Beral V. Million Women Study Collaborators. The 21st century hazards of smoking and benefits of stopping: A prospective study of one million women in the UK 2013; 381: 133-41. |
| [73] | Carter BD, Abnet CC, Feskanich D, et al. Smoking and mortality--beyond established causes. N Engl J Med 2015; 372(7): 631-40. |
| [74] | Banks E, Joshy G, Korda RJ, et al. Tobacco smoking and risk of 36 cardiovascular disease subtypes: Fatal and non-fatal outcomes in a large prospective Australian study. BMC Med 2019; 17(1): 128. |
| [75] | Kjeldsen SE. Hypertension and cardiovascular risk: General aspects. Pharmacol Res 2018; 129: 95-9. |
| [76] | Kokubo Y, Iwashima Y. Higher blood pressure as a risk factor for diseases other than stroke and Ischemic Heart Disease. American Heart Association 2018; 66(2): 254-9.Http://doi.ng/10.1161/HYPER TENSIONAHA.115.03480 |
| [77] | Rosendorff C, Lackland DT, Allison M, et al. Treatment of hypertension in patients with coronary artery disease: A scientific statement from the American Heart Association, American College of Cardiology, and American Society of Hypertension. Circulation 2015; 131(19): e435-70. |
| [78] | Risk Factors Collaborators GBD. Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2016: A systematic analysis for the Global Burden of Disease Study 2016. Lancet 2017; 390(10100): 1345-422. |
| [79] | Lamprea-Montealegre JA, Zelnick LR, Hall YN, Bansal N, de Boer IH. Prevalence of hypertension and cardiovascular risk according to blood pressure thresholds used for diagnosis. Hypertension 2018; 72(3): 602-9. |
| [80] | Fuchs FD, Whelton PK. High blood pressure and cardiovascular disease. Hypertension 2020; 75(2): 285-92. |
