Introduction:
Hypertension is one of the leading risk factors for morbidity and mortality worldwide. Aside this, it contributes significantly to the burden of heart disease, stroke, kidney failure, premature death and disability.(1) It is often referred to as a silent killer as a result of its asymptomatic nature which allows its diagnosis to be evaded among several individuals.(2) This potentially increase the chance of developing target organ damage and other life threatening conditions as early diagnosis affords opportunity for prompt intervention.(3)
Gone are the days when hypertension was considered a disease found only in the developed nations. Currently, hypertension has spread its tentacles across several countries, even to economically disadvantaged regions, including Sub-Saharan Africa.(4,5) Nigeria is not exempted from this growing menace. Studies have reported a high prevalence of hypertension in the country.(6-8)
A significant contributor to the rising hypertension burden is the increasing burden of obesity. While several individuals have a possibility of developing obesity, some are particularly at a greater risk. One of such is an important population group, the public civil servants, whose nature of job promotes sedentary behaviour coupled with unhealthy dietary practices and consequently, obesity.(9) Public civil servants constitute a large percentage of a nation’s workforce and they contribute significantly to the economic development of a nation. While the focus of hypertension has always been on the hospitalised patients, the assumption that asymptomatic individuals are healthy is doubtful. In the light of this, this study examined the prevalence, awareness and correlates of hypertension among apparently healthy individuals working in Ondo State Civil Service Commission. Information on the prevalence, awareness, and correlates of hypertension in specific population will play a crucial role in planning effective preventive measures tailored to the peculiarities of each population group. Particularly, among the public civil servants, such information might be useful in crafting an effective workplace policy on non-communicable diseases.
Methods
Study area and design
We undertook a workplace population study (cross-sectional study) of public service workers drawn across the 47 ministries, departments and agencies (MDAs) in Akure, the state capital of Ondo State, Nigeria. The majority of the State MDAs are located within the state secretariat at Alagbaka, Akure. About 30,000 workers are employed across the various MDAs, with the official working hours between 8:00am to 4:00pm, with variations in some departments.
Participants and Sample Size
We chose the public service workers to test the study hypotheses; (1) whether a workplace screening will lead to increase diagnosis of hypertension at the population level and (2) whether a significant proportion of men will access the hypertension screening in their workplace. All public civil service workers at the study settings who fulfilled the inclusion criteria and were on duty during the period of the study were eligible for recruitment into the study. Participants were included if they were 18 years and above, willing to participate and had fasted for eight hours prior to study. Pregnant and lactating women, and those with physical deformities which impacts on anthropometric assessments were considered ineligible. A convenient sample of workers (N = 4844), corresponding to about one-sixth of the workers in Akure, across the various MDAs was considered adequate to test the hypotheses of the study. A communique detailing the purpose, process and specific dates for each ministry was sent to the relevant authorities and all workers. Each MDA was allocated one to three days in which to gather adequate samples of workers for the study.
Data Collection
Trained research nurses took measurements and conducted the interviews. Participants were interviewed using standardized World Health Organization (WHO) STEPwise Methodology for the surveillance of non-communicable diseases (NCDs) risk factors at the country level.(10) The questionnaire was pre-tested in a pilot that included 25 workers in the ministry of health and finalized after necessary amendments. However, the pilot data was not included in the main study.
The questionnaire included items on gender, age, grade level of employment, marital status, smoking status, alcohol intake, diet, hours of sleep and physical activity. The level of education was determined according to the grade level attained in school and participants were categorized as having no formal education, primary (grade 1-6), secondary (7-12), tertiary (first degree in university or colleges of higher learning) or post-graduate (minimum of second degree). Public service workers were categorized based on their grade level into; senior management staff (13-17), middle level staff (8–12) and junior management staff (less than 8). Participants were questioned on daily consumption of red meat (Western-type diet), cigarette smoking status (considered as smoked if they have ever smoked cigarette or not), excessive consumption of alcohol (if they ever had three or more units of alcohol for men and two for women or not). Physical activity was based on self-reporting and participants were categorized as inactive (sedentary lifestyle) if they spent eight or more hours in sitting position per day. Participants were asked whether or not they have ever had their blood pressure measured by health workers.
Measurements
Participants gave consent to visit their family doctors or accept a referral to the state specialist hospital in event of an abnormal measurements.
Blood pressure: Blood pressure (systolic and diastolic) was measured in accordance with standard protocol (11) with a validated Microlife BP A100 Plus model (Omron HEM – 705 CP Device, Tokyo, Japan), which provided average of two readings for each participant. Hypertension was defined as average of two systolic blood pressure of > 140mmHg and diastolic of > 90mmHg or a history of hypertension.(12)
Blood Glucose: Glycaemia was measured using ACCUTRENDR test strips (2010 LifeScan, Inc. 021-606, Switzerland) for capillary blood glucose (fasting state). Pre-diabetes and diabetes were defined as fasting blood glucose 6.1-6.9mmol/l and greater than or equal to 7.0mmol/l, respectively.(13)
Weight and Height: Body weight was measured in light clothing to the nearest 0.5kg in the standing position using Soehnle Scale (Soenle-Waagen Gmbh Co., Muurhardt, Germany). The height was measured by stadiometer in standing position with closed feet (without shoes to the nearest 0.5cm), holding their breath in full inspiration and Frankfurt line of vision.(14) Body mass index (BMI) was calculated as weight divided by height in square metres. BMI was categorized in accordance with WHO criteria (15) as <18.5kg/m2, 18.5-24.9kg/m2, 25.5-29.9kg/m2 and ≥30.0kg/m2 as underweight, normal, overweight and obese, respectively.
Ethical Considerations
Ethical approval was granted by the Ondo State Health Research Ethics Committee (SHREC – AD4693/307). Prior to each day’s interview, a public lecture was delivered to the participants describing all information regarding the study. Information sheets and consent forms were provided to the participants. All participants provided written informed consent before they were enrolled for the study. Participants were interviewed in a secured room to ensure privacy and confidentially of each worker.
Data analysis
Data were analysed using Statistical Package for Social Science (SPSS) version 21 for windows (SPSS Inc., Chicago, IL, USA). Data were expressed as mean values ± standard deviations (SD) for continuous variables. Frequencies (n) and proportions (%) were reported for categorical variables. Counts (frequency = n) and proportions (%) were reported for categorical variables. Percentages were compared using chi-square test. A bivariate and multivariate analysis was done to determine the prevalence, awareness and correlates of hypertension among the participants. We calculated multivariate ORs and their 95% confidence intervals (95%CIs) using logistic regression to identify the predictors of hypertension in our sample. Our logistic regression model analysis adjusted for sex, age, level of education, hours of sleep, formal exercise programme, excessive alcohol intake, cigarette smoking and red meat consumption. A p-value of < 0.05 was considered statistically significant.
Results
Of the total participants (N=4844); 52.4% (n=2538) were females while 47.6% (n=2303) were males. The majority had at least a secondary education (86.5%), were married (76.6%), and middle level category (53.2%). Sedentary behaviour (spending up to 8 hours daily in sitting position) was reported by 24.5% of study participants with no significant difference between sexes. The majority (85.2%) sleep less than six hours daily. Only few smoke more than three cigarettes per day (2.9%) and consume alcohol daily (8.5%). One in three of the participants consume red meat daily and engage in physical exercise. About 25% of the participants spend up to eight hours daily sitting (Table 1).
Table 1: Demographic characteristics of the participants |
Variables |
Total (n=4828) |
Male (n=2299) |
Female (n=2529) |
p-value |
Age groups (Years) |
≤24 |
215(4.5) |
91(4.0) |
124(4.9) |
0.000 |
25-34 |
1185(24.5) |
541(23.5) |
644(25.5) |
|
35-44 |
1673(34.7) |
773(33.6) |
900(35.6) |
|
45-54 |
1408(29.2) |
681(29.6) |
727(28.7) |
|
55-64 |
333(6.9) |
200(8.7) |
133(5.3) |
|
≥65 |
14(0.3) |
13(0.6) |
1(0.0) |
|
Level of education |
No formal education |
59(1.3) |
49(2.2) |
10(0.4) |
0.000 |
Primary Education |
568(12.4) |
356(16.1) |
212(8.9) |
|
Secondary Education |
1258(27.7) |
556(25.2) |
702(29.6) |
|
Tertiary Education |
1783(38.9) |
779(35.3) |
1004(42.3) |
|
Post Graduate Education |
911(19.9) |
467(21.2) |
444(18.7) |
|
Marital Status |
Single |
934(19.8) |
442(19.9) |
492(19.8) |
0.000 |
Married |
3606(76.6) |
1766(79.3) |
1840(74.1) |
|
Widowed |
131(2.8) |
10(0.4) |
121(4.9) |
|
Separated |
38(0.8) |
8(0.4) |
30(1.2) |
|
Grade level |
Junior staff |
1162(29.1) |
555(28.8) |
607(29.5) |
0.000 |
Middle level |
2125(53.2) |
962(49.8) |
1163(56.4) |
|
Senior level |
704(17.6) |
413(21.4) |
291(14.1) |
|
Sleep less than six hours daily |
4125(85.2) |
1952 (84.8) |
2173 (85.6) |
0.701 |
Smoke more than three sticks of cigarette per day |
138(2.9) |
99(4.3) |
39(1.5) |
0.000 |
Consume lots of red meat daily |
1555(32.1) |
816(35.4) |
739(29.1) |
0.000 |
Consume alcohol daily |
411(8.5) |
353(15.3) |
58(2.3) |
0.000 |
Engage in physical exercise |
1906(39.4) |
937(40.7) |
969(38.2) |
0.13 |
Spend up to eight hours daily on sitting |
1187(24.5) |
560(24.3) |
627(24.7) |
0.005 |
Prevalence of hypertension
High prevalence of pre-hypertension 36.1% (n=1751) and hypertension 35% (n=1692) was found in the study sample. Of the hypertensive participants, only 28% (n=474) had a prior diagnosis of hypertension by history. As shown in Fig. 1, males have a slightly higher prevalence of hypertension (39.1%) than females (21.3%).
 |
Fig. 1: Hypertension Prevalence by Gender |
Determinants of hypertension
In the bivariate analysis, sex, educational level, age, marital status, obesity, physical activity, cigarette smoking, sedentary lifestyle, sleeping less than 6 hours, alcohol use, work cadre and diabetes were significantly associated with hypertension (Table 2).
However, after adjusting for confounding factors (educational level, physical activity, cigarette smoking, sedentary lifestyle, sleeping less than 6 hours per day and work cadre) in the multivariate (logistic regression model) analysis; only sex, age, educational level, marital status, obesity and diabetes were the independent and significant determinants of hypertension among the study participants (Table 3).
Table 2: Determinants of hypertension |
| Variables |
Hypertensive |
Not hypertensive |
p-value |
Sex |
Male |
974(42.3) |
1326(57.7) |
<0.001 |
Female |
895(35.3) |
1638(64.7) |
|
Educational level |
Primary or no education |
323(51.7) |
302(48.3) |
<0.001 |
Post-primary education |
1457(36.9) |
2492(63.1) |
|
Obesity |
Yes |
510(52.4) |
464(47.6) |
<0.001 |
No |
1291(34.9) |
2410(65.1) |
|
Age |
41 and above |
1263(52.9) |
1125(47.1) |
<0.001 |
40 and below |
603(24.8) |
1833(75.2) |
|
Diabetes |
Yes |
159(62.6) |
95(37.4) |
<0.001 |
No |
1702(37.3) |
2855(62.7) |
|
Marital status |
Married |
1669(42.8) |
2235(57.2) |
<0.001 |
Never married |
202(21.7) |
730(78.3) |
|
Engage in physical activity |
Yes |
801(36.9) |
1371(63.1) |
0.011 |
No |
1070(40.2) |
1594(59.8) |
|
Cigarette smoking of more than 3 sticks per day |
Yes |
70(50.7) |
68(49.3) |
0.002 |
No |
1801(38.3) |
2897(61.7) |
|
More than 8 hours in sitting position |
Yes |
509(42.9) |
678(57.1) |
<0.001 |
No |
1362(37.3) |
2287(62.7) |
|
Sleep less than 6 hours per day |
Yes |
661(40.5) |
970(59.5) |
0.033 |
No |
1210(37.8) |
1995(62.2) |
|
Drink alcohol daily |
Yes |
178(43.3) |
233(56.7) |
0.026 |
No |
1693(38.3) |
2732(61.7) |
|
Cadre |
Junior staff |
477(41.2) |
681(58.8) |
<0.000 |
Middle level |
819(38.6) |
1305(61.4) |
|
Senior level |
348(49.6) |
354(50.4) |
|
Table 3: Binary logistic regression showing correlates of hypertension |
| Variable |
Beta |
S.E |
Wald |
OR (95%CI) |
p-value |
Age |
41 and above |
1.02 |
0.07 |
202.35 |
2.8(2.4-3.2) |
<0.001 |
40 and below (Reference) |
|
|
|
|
|
Educational level |
Primary or no education |
0.39 |
0.09 |
16.93 |
1.5(1.2-1.8) |
<0.001 |
Post-primary education (reference) |
|
|
|
|
|
Obesity |
Yes |
0.75 |
0.08 |
77.97 |
2.1(1.8-2.5) |
<0.001 |
No(reference) |
|
|
|
|
|
Sex |
Male |
0.43 |
0.07 |
37.22 |
1.5(1.3-1.8) |
<0.001 |
Female (reference) |
|
|
|
|
|
Marital status |
Married |
0.38 |
0.10 |
14.54 |
1.5(1.2-1.8) |
<0.001 |
Never married (reference) |
|
|
|
|
|
Diabetic |
Yes |
0.65 |
0.15 |
19.93 |
1.9(1.4-2.6) |
<0.001 |
No(reference) |
|
|
|
|
|
Hypertension awareness
Of all the study participants, about half (48.1%) check their blood pressure regularly. More females reported that they regularly check their blood pressure (50.5%) than males (45.4%). Females had a higher prevalence of ever been diagnosed of hypertension (10.8%) than males (8.7%). Prior admission for severe hypertension occurred more in females (4.3%) than in males (2.6) (Table 4). Of all the hypertensive participants (n= 1692), only 28% (n=474) were aware of their hypertension status.
Table 4: Hypertension screening history |
| Variables |
Total (n=4841) |
Male (n=2303) |
Female (n=2538) |
p-value |
Measure BP regularly |
2327(48.1) |
1045(45.4) |
1282(50.5) |
0.001 |
Ever been diagnosed of Hypertension |
474(9.8) |
200(8.7) |
274(10.8) |
0.016 |
Ever been admitted for severe hypertension |
171(3.5) |
61(2.6) |
110(4.3) |
0.000 |
Discussion
Hypertension is one of the leading causes of morbidity and mortality with an increasing prevalence in the developing nations. This study sought to determine the prevalence, awareness and correlates of hypertension among urban public civil servants in Ondo State. The overall prevalence of pre-hypertension and hypertension was 71.4%. This connotes a high burden of hypertension among this sect. The prevalence of hypertension was 35%. This finding is slightly higher than the reported prevalence among civil servants in a northern area of Nigeria, Nigeria (29%),(16) civil servants in Ethiopia, 27.3% (1) and Ghana, 27.4%.(3) The prevalence in this study is higher than the overall prevalence (28.9%) of hypertension in Nigeria as reported in a systematic review.(6) The higher prevalence found among this study population could be linked to their work characteristics which entails long period of sitting coupled with physical inactivity and unhealthy dietary practices which predispose them to obesity. This is evidenced by the significant association between physical inactivity and hypertension as well as high prevalence of obesity already documented among this study population.(9) Also, the settings of this study, being an urban area might have informed the higher rate reported as urban dwellers have been shown to have a higher burden of hypertension compared to their rural counterparts.(7) In addition to this, 36.4% of the participants were diagnosed as pre-hypertensive. Given that pre-hypertension is a precursor to the development of hypertension, this shows that this group of workers could further increase the present burden of hypertension in the nearest future if prompt actions are not taken.
Pertaining to hypertension awareness, only 28% of those diagnosed of hypertension were aware of their hypertension status. This finding is lower than the reported rate among university workers, 62.9% (17) and bank workers (79.1%) in Nigeria.(18) The awareness rate in this study population is even lower compared to the reported rate among informal workers such as commercial bus drivers (28.8%) and traders (29.4%) in Nigeria. The wide disparity in the reports suggest that workplace screening should be mandatory and periodic practice among civil service workers in the state and the country. This finding affirms our postulation that asymptomatic individuals are not necessarily healthy. This is quite disheartening, considering that this is a group that is supposedly exposed to workplace health assessment, and their level of education is also expected to influence their health behaviour.(17) There is a need to further enlighten this group about cardiovascular diseases especially undiagnosed hypertension and the consequent complications. Therefore, regular NCD screening at the workplace will benefit this population and might further prevent cardiovascular morbidities. Females were found to have better awareness about their hypertension status than males. This can be associated with better health seeking behaviour of females.(19) Also, females have several reasons to visit the healthcare system and thus, afford them opportunities to screen for hypertension, which is a routine screening at all clinic visits.
Male sex, older age, educational level, marital status, obesity and diabetes were the independent determinants of hypertension among the study population. The higher prevalence found among male workers could be ascribed to lifestyle factors such as work stress, high alcohol and salt intake which are more common among men than women.(20) Also, to some extent, females are offered some protective effect by the female hormones, especially before menopausal age.(21) Since the majority of the study participants were below the age of 45 years, this could also be a plausible reason for the lower prevalence of hypertension found among the females.
Participants who were older than 40 years were found to have a higher odds of developing hypertension. This finding is consistent with studies conducted in Nigeria(6,8) and other countries.(22,23) High burden of hypertension is inevitable among the elderly. Ageing is often accompanied by changes in body system and the cardiovascular system is not exempted from such changes. Changes in cardiovascular system such as arterial stiffness, inflammation and endothelial dysfunction account for the greater burden of hypertension among the elderly.(24,25)
Also, those with primary or no educational qualification had higher odds of being hypertensive. This corroborates the findings among civil servants in Northern Nigeria and among South African adults.(16,22) Although, there exist a complex relationship between educational level and hypertension, however, it is presumed that the more educated an individual is, the more knowledgeable they are about their health.(26) Higher level of knowledge might foster better health practices and prevent the development of hypertension and its associated predisposing factors such as obesity.(27) Married workers had higher odds of developing hypertension than the unmarried ones. This could be linked to the higher prevalence of obesity usually found among married adults.(28) The higher prevalence of hypertension found among the obese participants in this study confirms this assumption. Obesity is a leading predisposing factor for hypertension and often stimulate mechanisms such as inflammation and endothelial dysfunction which promotes hypertension development.(29) The impact of genetics in the development of hypertension however cannot be overruled and this might have also contributed to the higher prevalence of hypertension found among the married participants.
Finally, we found a significant association between diabetes and hypertension. This is not surprising. There is always an intersection between both conditions as a result of shared metabolic pathway and risk factors.(30,31) Individuals with diabetes have been reported to have two-fold risk of developing hypertension compared to those who do not have diabetes.(32)
Strengths and Limitations
The cross-sectional design and the convenience sampling are obvious limitations of the study. Notwithstanding the limitations, the use of standard measures and the large sample size gives credence to the findings of this study.
The present study established that workplace screening for hypertension and other NCDs will indeed lead to increased diagnosis in a population with poor health seeking behaviour. This strategy could potentially be a game changer in reducing the burden of undiagnosed hypertension similar population, and especially among men who tend to utilise healthcare facilities less frequently.
Conclusions
High burden of hypertension and pre-hypertension prevalence as well as high level of hypertension unawareness warrant attention of the state government. Findings from this study suggest that a carefully crafted workplace policy with focus on periodic cardiovascular health screening might mitigate the burden of undiagnosed hypertension among the civil service workers. Future studies should seek to explore the effectiveness of this strategy on the broader population of workers across all sectors of the economy.
Declarations
Consent for publication
All authors approved the submission of the final draft towards publication in a peer review journal.
Availability of data and materials
Data from this study will be made available on request.
Competing interests
The authors declare no conflict of interest.
Funding
This project was partly funded by the Ondo State ministry of health which has no influence in the conceptualization, design, implementation of the study and the outcomes.
Authors’ Contributions
IA1, OF4, MA5: conceptualised, designed the protocol and collected data. OVA2, DTG5, EOO3: provided intellectual input to the design of the protocol and drafted the manuscript. AIA7: conducted the statistical analysis. All authors read the manuscript and approved the final version.
Acknowledgements
The authors are grateful to the heads of the various ministries, departments and agencies for the unflinching support towards the successful implementation of the project.
References
- Angaw I, Dadi AF, Alene KA. Prevalence of hypertension among federal ministry civil servants in Addis Ababa, Ethiopia: a call for a workplace-screening program. BMC Cardiovasc Disord 2015;15:76.
- American Heart Association. What is high blood pressure? Available from: https://www.heart.org/HEARTORG/Conditions/HighBloodPressure/GettheFactsAboutHighBloodPressure/The-Facts-About-High-Blood-Pressure_UCM_002050_Article.jsp. Accessed 15th July, 2017.
- Addo J, Smeeth L, Leon DA. Prevalence, detection, management, and control of hypertension in Ghanaian civil servants. Ethn Dis. 2008 Autumn;18(4):505-11.
- Guwatudde D, Nankya-Mutyoba J, Kalyesubula R, et al. The burden of hypertension in sub-Saharan Africa: a four-country cross sectional study. BMC Public Health 2015;15:1211.
- Díaz A, Ferrante D. Trends in prevalence of hypertension in Argentina in the last 25 years: a systematic review of observational studies. Rev Panam Salud Publica 2015;38:496–503.
- Adeloye D, Basquill C, Aderemi AV, et al. An estimate of the prevalence of hypertension in Nigeria: a systematic review and meta-analysis. J Hypertens 2014;33(2): 230–42.
- Akinlua JT, Meakin R, Umar AM, et al. Current Prevalence Pattern of Hypertension in Nigeria: A Systematic Review. PLoS One 2015;10(10):e0140021. https://doi.org/10.1371/journal.pone.0140021.
- Ajayi IO, Sowemimo IO, Akpa OM, et al. Prevalence of hypertension and associated factors among residents of Ibadan-North Local Government Area of Nigeria. Nig J Cardiol [serial online] 2016;13:67-75.
- Aladeniyi I, Adeniyi OV, Fawole O, et al. Pattern and correlates of obesity among public service workers in Ondo State, Nigeria: a cross-sectional study. S Afr Fam Pract. 2017;1(1):1-6.
- World Health Organization. The WHO STEPwise approach to Surveillance of noncommunicable diseases (STEPS). Geneva. 2003. Available from: http://www.who.int/ncd_surveillance/en/steps_framework_dec03.pdf
- Seedat Y, Rayner B, Veriana Y. South African hypertension practice guideline. Cardiovas J Africa. 2014;2014(6):288–94. Available from: https://doi.org/10.5830/CVJA-2014-062.
- James P, Oparil S, Carter B, et al. Evidence-based guideline for the management of high blood pressure in adults report from the panel members appointed to the EIGHTH Joint National Committee (JNC 8). J Am Med Assoc. 2014;311(5):507–20. Available from: https://doi.org/10.1001/jama.2013.284427.
- SEMDSA: The 2012 SEMDSA guideline for the management of type 2 diabetes. Journal of Endocrinology, Metabolism and Diabetes of South Africa. In: Health Do, editor. Pretoria: Medpharm; 2012: p. S1–S94, vol. 17.
- Committee WE. Physical status: the use and interpretation of anthropometry. World Health Organ Tech Rep Ser. 1995;854:55.
- World Health Organization. Obesity and overweight. Factsheet. Available from: http://www.who.int/mediacentre/factsheets/fs311/en/. Accessed 8th July, 2017.
- Oladimeji AO, Fawole O, Nguku P, et al. Prevalence and factors associated with hypertension and obesity among civil servants in Kaduna, Kaduna State, June 2012. Pan Afr Med J. 2014;18(Supp 1):13.
- Vincent-Onabajo G, Mohammad HS, Umeonwuka C. Prevalence of undiagnosed hypertension among a cohort of university workers in Nigeria. Int J Community Med Public Health 2016;3:1963-7.
- Diwe KC, Enwere OO, Uwakwe KA, et al. Prevalence and awareness of hypertension and associated factors among bank workers in Owerri, Nigeria. IJBMR. 2015;4:1-7.
- Adeniyi OV, Longo-Mbenza B, Goon DT. Female sex, poverty and globalization as determinants of obesity among rural South African type 2 diabetics: a cross-sectional study. BMC Public Health 2015;15:298.
- Health Exchange. High blood pressure: how do men and women Differ? Managing Chronic Illnesses. Available from: https://in.news.yahoo.com/blogs/fit-to-post-health/high-blood-pressure-men-women-differ-051832336.html Accessed 15th July 2017.
- Reckelhoff JF. Gender differences in the regulation of blood pressure. Hypertension 2001;37:1199–208.
- Owolabi EO, Goon DT, Adeniyi OV, et al. Social epidemiology of hypertension in Buffalo City Metropolitan Municipality (BCMM): crosssectional study of determinants of prevalence, awareness, treatment and control among South African adults. BMJ Open 2017;7:e014349. doi:10.1136/bmjopen-2016-014349.
- Pires JE, Sebastião YV, Langa AJ, et al. Hypertension in Northern Angola : prevalence, associated factors, awareness, treatment and control. BMC Public Health 2013;13:90.
- Burford TW. Hypertension and Aging. Ageing Res Rev. 2016;26:96–111. doi:10.1016/j.arr.2016.01.007.
- Sun Z. Aging, Arterial Stiffness, and Hypertension. Hypertension. 2014;65:252-256. DOI: 10.1161/HYPERTENSIONAHA.114.03617.
- Cutler DM, Lleras-Muney A. Understanding differences in health behaviors by education. J Health Econ 2010;29:1–28.
- Sardinha LB, Santos DA, Silva AM, et al. Prevalence of Overweight, Obesity, and Abdominal Obesity in a representative sample of Portuguese Adults. PLoS ONE 2012;7(10): e47882.
- Janghorbani M, Amini M, Willett WC, et al. First Nationwide Survey of Prevalence of Overweight, Underweight, and Abdominal Obesity in Iranian Adults. Obesity 2007;15(11): 2797.
- Guh DP, Zhang W, Bansback N, et al. The incidence of co-morbidities related to obesity and overweight: a systematic review and meta-analysis. BMC Public Health 2009;9:88.
- Cheung BMY, Li C. Diabetes and hypertension: is there a common metabolic pathway? Curr Atheroscler Rep 2012;14:160–6.
- Cheung BMY. The hypertension–diabetes continuum. J Cardiovasc Pharmacol 2010;55:333–9.
- Landsberg L, Molitch M. Diabetes and hypertension: pathogenesis, prevention and treatment. Clin Exp Hypertens 2004;26(7-8):621–8.
|
