Annals of African Medicine

ORIGINAL ARTICLE
Year
: 2015  |  Volume : 14  |  Issue : 1  |  Page : 39--45

Blood pressure indices, life-style factors and anthropometric correlates of casual blood glucose in a rural Nigerian community


Augustine N Odili1, Emmanuel O Abatta2,  
1 Department of Internal Medicine, Faculty of Clinical Sciences, College of Health Sciences, University of Abuja, Abuja, Nigeria; Department of Cardiovascular Diseases, Studies Coordinating Centre, Division of Hypertension and Cardiovascular Rehabilitation, University of Leuven, Leuven, Belgium
2 Department of Public Health, Federal Ministry of Health, Abuja, Nigeria

Correspondence Address:
Augustine N Odili
Department of Internal Medicine, College of Health Sciences, University of University of Abuja, Main Campus, Off Airport Road, PMB 117, Garki, Abuja, Nigeria

Abstract

Background: Disordered blood glucose metabolism is associated with poor cardiovascular disease outcomes. Relationship between casual blood glucose (CBG) and blood pressure indices among rural dwellers in Nigeria has been less studied. Methods: We measured CBG, anthropometry, systolic blood pressure (SBP) and diastolic blood pressure (DBP) pulse pressure (PP) and mean arterial pressure (MAP) and life-style cardiovascular risk factors. Results: The mean (standard deviation) of CBG was 6.2 (1.9) and values were similar in men and women. Age, SBP, DBP PP, MAP, body mass index (BMI) and waist circumference were positively correlated with CBG; r = 0.23, 0.30, 0.24, 0.28, 0.28, 0.24 and 0.22 respectively. In a multivariate analysis, only PP and BMI predicted CBG. A 5 mmHg increase in PP or a 2 kg/m 2 increase in BMI increased CBG by 0.15 or 0.18 mmol respectively. PP and BMI in combination explained 13% of the variation in CBG (P < 0.001). Conclusion: PP and BMI are associated with CBG among rural dwellers in South-East Nigeria.



How to cite this article:
Odili AN, Abatta EO. Blood pressure indices, life-style factors and anthropometric correlates of casual blood glucose in a rural Nigerian community.Ann Afr Med 2015;14:39-45


How to cite this URL:
Odili AN, Abatta EO. Blood pressure indices, life-style factors and anthropometric correlates of casual blood glucose in a rural Nigerian community. Ann Afr Med [serial online] 2015 [cited 2020 Jul 12 ];14:39-45
Available from: http://www.annalsafrmed.org/text.asp?2015/14/1/39/148735


Full Text

 Introduction



Nigeria and indeed many countries of sub-Saharan Africa faces an emerging epidemic of non-communicable diseases of which cardiovascular diseases (CVDs) are major contributors. It is currently estimated that 80% of global deaths due to non-communicable diseases occur in low and middle income countries and deaths due to CVDs account for 30% of this number. [1] Most of these deaths and disabilities occur in people at the most productive stage of their life resulting to a huge negative economic impact on society.

Disorders of glucose metabolism including undiagnosed Type 2 diabetes mellitus are recognized risk factors for CVDs. This synergistic relationship is strongly supported by the evidence from a collaborative DECODE study [2],[3] which analyzed both all-cause and cardiovascular mortality in 27,714 subjects who had baseline glucose estimation and were followed-up for at least 11 years. People with diabetes mellitus and impaired glucose tolerance identified by 2 h post-glucose load had increased mortality while high fasting plasma glucose alone was not predictive once 2 h post-glucose is taken into consideration. In addition, increasing level of hemoglobin A1c, a maker of glucose metabolism over a longer period of time is associated with increasing CVD risk in several observational and outcome studies. [4],[5]

Recent observational studies indicate that the burden of CVD is increasing in Nigeria. [6],[7],[8],[9] Most authors adduce this to increasing westernized lifestyle and urbanization as a rural to urban gradient exits as regards the cardiovascular risk factors. Less attention is therefore paid to the fact that despite the rural-urban difference in CVD burden, the prevalence of risk factors like obesity [6] is substantially high in the rural areas. Consequently, the synergistic relationship between disorders of glucose metabolism and CVDs are less studied in the rural areas. We therefore set out to evaluate the relationship between casual blood sugar and anthropometric characteristics and blood pressure indices in a group of rural dwellers in South-Eastern part of Nigeria.

 Methods



Study population

Ihite Aforukwu is a small rural community located about 40 km from Owerri, the capital city of Imo State in South-Eastern Nigeria. Residents are either subsistence farmers or involved in small scale trading within the neighboring communities. Most of the residents have been living within the community since birth except for a few who retired to the village having worked in the cities.

Ihite Aforukwu sits in typical rainforest vegetation; precipitation and temperature ranges from 2 to 20 mm and 21-34°C respectively with the highest precipitation experienced between July and September.

Training of field workers

Under the framework of Nigerian Population Research on Environment Gene and Health a cardiovascular assessment was incorporated in a yearly health promotion campaign at Ihitteafoukwu in Ahiazu-Mbaise Local Government area of Imo state, Nigeria. Two months to the exercise, three registered nurses who were indigenes of the community were trained on blood pressure measurement according to the European Society of Hypertension (ESH)/European Society of Cardiology guidelines. Training also covered other aspects of the protocol including questionnaire administration, anthropometric examination and blood glucose estimation using Accu-Check glucometer.

Field work

The field work was carried out in December 2012. All adults aged 18 years and above living in the community were invited to participate in the 2 day health screening exercise. 122 adults who consented were included in this analysis. We used a structured investigator administered a questionnaire to inquire into the medical history, smoking habits, alcohol consumption and intake of medications The Health Research Ethical Committee of University of Abuja Teaching Hospital, gave ethical approval and the study complied with guidelines involving research with human subjects as outlined in the Helsinki declaration. [10]

Blood pressure measurement

Trained observers measured blood pressure with a standard mercury sphygmomanometer 3 times consecutively. The guidelines of the ESH/European Society of Cardiology [11] were applied. Standard cuffs had a 12-24 cm inflatable bladder, but, if upper arm circumference exceeded 31 cm, a larger cuff with 15-35 cm bladder was used. After at least 10 min rest, three consecutive blood pressure readings were obtained in the sitting position with an interval of 30-60 s between readings. The cuff was deflated at approximately 2 mmHg/s and systolic blood pressure (SBP) and phase V diastolic blood pressure (DBP) were recorded to the nearest 2 mmHg. Each subject's blood pressure was the mean of the 3 readings and pulse pressure (PP) determined as the difference between SBP and DBP; mean arterial pressure (MAP) as diastolic pressure +1/3 PP.

Blood glucose estimation

Irrespective of the time of last meal, capillary blood was obtained by pricking the index finger. Blood was allowed to drop freely on the test strip already inserted on an Accu-Check glucometer without squeezing the pricked finger. The reading was expressed in mmol/l as the casual blood sugar.

Anthropometry and lifestyle factors

With the shoes off and light clothing and no cap or head gear, height and weight were measured with a standard stadiometer; to the nearest 0.2 cm and 0.1 kg respectively. The waist circumference (WC) was measured with a non-expansible tape without clothing or light clothing in between the lower coastal margin and the iliac crest with the arm relax by the side.

Investigator administered questionnaire was used to collect information on alcohol consumption, past and present cigarette smoking perceived stress as modified from the Cohen et al. perceived stress scale [12] and physical activity as modified from the International Physical Activity Questionnaire. [13]

Statistical analysis

SAS software (SAS institute, Cary, NC, USA), version 9.3 was used for database management and statistical analysis. The central tendency and spread of the data were reported as mean and standard deviation (SD). Normality of continuously distributed variables was evaluated by the Kolmogorov-Smirnov. [14] Skewness and Kurtosis were computed as the third and fourth moments about the mean. We used Student's t-tests to evaluate differences between paired and unpaired samples. We used a Pearson correlation to determine correlation between blood pressure indices; life-style factors and casual blood glucose (CBG). A stepwise multiple linear regression was used to analyze the relationship in a model that included CBG as dependent variable and all the other factors studied as independent variable. A stepwise approach was used and the P value for any variable to remain in the model was set at 0.15. For a variable to be significantly associated with casual blood pressure, a P value of change in R2 must be 0.05 or less.

 Results



Characteristics of participants

The 122 participants included 67 (54.9%) women; their age averaged 54.7 and ranged between 19 and 80 years. 23 (18.9%) had greater than 6 years of formal education and 90 (73.8) reported experiencing moderate to severe level of stress. Both cigarette smoking and alcohol consumption were significantly higher among men when compared with women. 66 (54.1%) and 10 (8.2%) of all participants had hypertension and diabetes mellitus respectively; with no significant gender difference. The men were significantly older (59.8 vs. 50.5 years) and had higher body mass index (BMI) (25.9 vs. 27.8 kg/m 2 ) than women; P < 0.001 and 0.05 respectively. The mean (SD) SBP, DBP, PP and MAPs were 133.2 (26.8), 78.8 (12.9), 54.4 (17.4) and 96.9 (16.8) mmHg respectively and all the blood pressure indices showed a trend toward higher values in men than women. The mean (SD) of CBG was 6.2 (1.9) and there was no significant gender difference. Other characteristics are as shown in [Table 1].{Table 1}

Correlates of CBG

As it has shown in [Table 2], CBG has a positive correlation with age, BMI, WC and systolic, diastolic, PP and MAP. The Pearson correlation coefficients, r (P value) were 0.23 (0.02); 0.24 (0.02); 0.22 (0.03); 0.30 (0.002); 0.24 (0.01); 0.28 (0.004) and 0.28 (0.004) respectively. None of the life-style factors correlated with CBG [Table 2].{Table 2}

In the multivariate analysis, only PP (β = 0.030, P < 0.001) and BMI (β =0.088, P < 0.05) were found to be significantly associated with CBG. Increasing PP by 5 mmHg or BMI by 2 kg/m 2 was associated with a 0.15 and 0.18 mmol/l increase in CBG respectively. PP and BMI together explained 13% of the variation in CBG; 9% of which is attributed to PP alone [Table 3].{Table 3}

The relationship between PP and CBG appear to be J shaped with the rise in PP becoming steep and apparent at the blood glucose level of about 6.0; in both younger (<50 years) and older (>50 years) participants [Figure 1] and [Figure 2]. The rise in PP with increasing BMI showed a continuous relationship in all participants [Figure 3]. This relationship was maintained when subjects were separated into younger (<50 years) and older(>50 years) age groups [Figure 4]. The rise in casual blood sugar [Figure 5] is continuous across all ranges of BMI classes (overweight; 26 30 kg/m 2 through to obese; >30 kg/m 2 ).{Figure 1}{Figure 2}{Figure 3}{Figure 4}{Figure 5}

 Discussion



In our present study, CBG was significantly associated with PP and BMI. Both variables explained about 13% of the variation in CBG. The association of PP or BMI was independent of the other confounding variables such as age, sex, alcohol consumption, educational qualification and psychosocial stress.

Both earlier [15],[16],[17] and more recent [18],[19],[20] studies indicated that prevalence of hypertension in diabetic individuals is about two fold that in the non-diabetic population. Population data from Nigeria evaluating the prevalence of hypertension in diabetes patients are lacking but a clinic based observational study [21] in Lagos, South West Nigeria indicated that 10% of patients visiting the medical out-patient department had concomitant hypertension and diabetes. Diabetes and hypertension acts synergistically to cause many CVDs. Hypertension causes a fourfold increase in cardiovascular risk in people with diabetes and presence of diabetes on the other hand doubles the CVD risk in hypertensive men and more than triples the risk in women. [22]

The pathophysiological mechanisms explaining the relationship between disorders of glucose metabolism and increasing blood pressure and other CVDs has been linked to insulin resistance and hyperinsulinemia in a wide range of experimental [23],[24],[25],[26],[27] and clinic studies. [28],[29],[30],[31],[32] Hyperinsulinemia has been associated with increased renal reabsorption of sodium, [25] sympathetic nervous system over activity, [28],[29] increased activation of renin-angiotensin system, [26] endothelial dysfunction; [27],[33] and small [34] and large [30],[31],[32] artery remodeling. Aortic, carotid and coronary blood vessels are all involved in the remodeling process. Aortic stiffening increases the pulse wave velocity and thus augments the second systolic peak, resulting in an elevation of SBP and an increase in PP. [35] In our present study, PP was independently associated with casual blood sugar and thus supports the notion that the dysglycemia is also an important CVD risk even among rural dwellers in Nigeria.

Abnormalities in the structure and function of adipose tissue have been identified as early events that prelude the development of insulin resistance and hyperinsulinemia hence obesity is the key driver in the cardiovascular continuum of disordered glucose metabolism. The mean BMI, 27 kg/m 2 obtained in this present study was higher than reported in cross-sectional population studies in rural communities in Western [36] and Northern [37] regions of the country. The reason for this discrepancy is not clear but the possibility of increasing urbanization of rural areas of the South-Eastern region of Nigeria as documented in the reports of the National Bureau of Statistics [38] offers a possible explanation. In the 2010 report of the harmonized standard of living in Nigeria, the South-East region has the highest number of people who are self-employed in non-agricultural activities. The implication is that involvement in agrarian activities, a hallmark of a rural residency may be dwindling in that region.

Our current results must be interpreted within the context of its potential limitations. First, our present report is based on relatively small sample size since it is an on-going project. This study however is meant to open up research interest into the study of cardio-metabolic diseases in rural areas of Nigeria which were presumed hitherto to be free of CVDs. Furthermore, we applied a validated protocol of blood pressure measurement and maintained a strict quality control program. [39]

We measured casual blood sugar as against the diagnostic gold standard of oral glucose tolerance test. Measurement of casual blood sugar is cheap and convenient and thus could easily be translated to everyday clinical practice in such resource poor setting. In addition, it has been reported that casual blood sugar measurement could identify undiscovered diabetic patients in a general Nigerian urban population. [40]

Our study raises some important public health issues. The common CVDs seen in the urban areas of Nigeria may equally be rising in the rural communities especially in the South-Eastern Nigeria. Primary prevention strategies being advocated for the urban communities should thus be extended to the rural ones. Prevention of CVD should include screening for disordered glucose metabolism. Glucometers for capillary blood glucose estimation are cheap and do not require high technical know-how to operate. We therefore advocate a paradigm shift in the cardiovascular primary prevention strategies in Nigeria to include blood glucose estimation as the cost of screening the entire population by measurement of CBG far outweighs the cost of managing cardiovascular complications of diabetes.

 Acknowledgments



The authors gratefully acknowledge the support of Chioma Onuoha, Faith Nwachukwu, Ozioma Egbujor, Adaeze Ike, Ikechukwu Duru and Dimeke Onyebuchi in mobilizing the community.

References

1World Health Organization. 2008-2013 Action Plan for the Global Strategy for the Prevention and Control of Noncommunicable Diseases. Geneva, Switzerland: World Health Organization; 2008.
2Ning F, Tuomilehto J, Pyörälä K, Onat A, Söderberg S, Qiao Q, et al. Cardiovascular disease mortality in Europeans in relation to fasting and 2-h plasma glucose levels within a normoglycemic range. Diabetes Care 2010;33:2211-6.
3Glucose tolerance and mortality: Comparison of WHO and American Diabetes Association diagnostic criteria. The DECODE study group. European Diabetes Epidemiology Group. Diabetes Epidemiology: Collaborative analysis Of Diagnostic criteria in Europe. Lancet 1999;354:617-21.
4Khaw KT, Wareham N, Bingham S, Luben R, Welch A, Day N. Association of hemoglobin A1c with cardiovascular disease and mortality in adults: The European prospective investigation into cancer in Norfolk. Ann Intern Med 2004;141:413-20.
5Selvin E, Steffes MW, Zhu H, Matsushita K, Wagenknecht L, Pankow J, et al. Glycated hemoglobin, diabetes, and cardiovascular risk in nondiabetic adults. N Engl J Med 2010;362:800-11.
6Ogah OS, Madukwe OO, Chukwuonye II, Onyeonoro UU, Ukegbu AU, Akhimien MO, et al. Prevalence and determinants of hypertension in Abia State Nigeria: Results from the Abia State Non-Communicable Diseases and Cardiovascular Risk Factors Survey. Ethn Dis 2013;23:161-7.
7Ogah OS, Okpechi I, Chukwuonye II, Akinyemi JO, Onwubere BJ, Falase AO, et al. Blood pressure, prevalence of hypertension and hypertension related complications in Nigerian Africans: A review. World J Cardiol 2012;4:327-40.
8Ulasi II, Ijoma CK, Onodugo OD. A community-based study of hypertension and cardio-metabolic syndrome in semi-urban and rural communities in Nigeria. BMC Health Serv Res 2010;10:71.
9Isezuo SA, Sabir AA, Ohwovorilole AE, Fasanmade OA. Prevalence, associated factors and relationship between prehypertension and hypertension: A study of two ethnic African populations in Northern Nigeria. J Hum Hypertens 2011;25:224-30.
10World Medical Association Declaration of Helsinki: Ethical principles for medical research involving human subjects. JAMA 2000;284:3043-5.
11Mancia G, De Backer G, Dominiczak A, Cifkova R, Fagard R, Germano G, et al. 2007 Guidelines for the management of arterial hypertension: The Task Force for the Management of Arterial Hypertension of the European Society of Hypertension (ESH) and of the European Society of Cardiology (ESC). Eur Heart J 2007;28:1462-536.
12Cohen S, Kamarck T, Mermelstein R. A global measure of perceived stress. J Health Soc Behav 1983;24:385-96.
13Oyeyemi AL, Oyeyemi AY, Adegoke BO, Oyetoke FO, Aliyu HN, Aliyu SU, et al. The Short International Physical Activity Questionnaire: Cross-cultural adaptation, validation and reliability of the Hausa language version in Nigeria. BMC Med Res Methodol 2011;11:156.
14Snedecor GW, Cochran WG. Statistical Methods. Iowa City. Iowa State University Press; 1989.
15Klein BE, Klein R, Moss SE. Blood pressure in a population of diabetic persons diagnosed after 30 years of age. Am J Public Health 1984;74:336-9.
16Teuscher A, Egger M, Herman JB. Diabetes and hypertension. Blood pressure in clinical diabetic patients and a control population. Arch Intern Med 1989;149:1942-5.
17Vaishnava H, Bhasin RC. Hypertension in Indian diabetics. J Chronic Dis 1969;21:691-702.
18Cleary PA, Orchard TJ, Genuth S, Wong ND, Detrano R, Backlund JY, et al. The effect of intensive glycemic treatment on coronary artery calcification in type 1 diabetic participants of the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study. Diabetes 2006;55:3556-65.
19Soedamah-Muthu SS, Colhoun HM, Abrahamian H, Chan NN, Mangili R, Reboldi GP, et al. Trends in hypertension management in Type I diabetes across Europe, 1989/1990-1997/1999. Diabetologia 2002;45:1362-71.
20Nilsson PM, Cederholm J, Zethelius BR, Eliasson BR, Eeg-Olofsson K, Gudbj Rnsdottir S. Trends in blood pressure control in patients with type 2 diabetes: Data from the Swedish National Diabetes Register (NDR). Blood Press 2011;20:348-54.
21Ogunleye OO, Ogundele SO, Akinyemi JO, Ogbera AO. Clustering of hypertension, diabetes mellitus and dyslipidemia in a Nigerian population: A cross sectional study. Afr J Med Med Sci 2012;41:191-5.
22Authors/Task Force Members, Rydén L, Grant PJ, Anker SD, Berne C, Cosentino F, et al. ESC Guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: The Task Force on diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and developed in collaboration with the European Association for the Study of Diabetes (EASD). Eur Heart J 2013;34:3035-87.
23Stolar MW. Atherosclerosis in diabetes: The role of hyperinsulinemia. Metabolism 1988;37:1-9.
24Capron L, Jarnet J, Kazandjian S, Housset E. Growth-promoting effects of diabetes and insulin on arteries. An in vivo study of rat aorta. Diabetes 1986;35:973-8.
25Rahmouni K, Barthelmebs M, Grima M, Imbs JL, De Jong W. Influence of sodium intake on the cardiovascular and renal effects of brain mineralocorticoid receptor blockade in normotensive rats. J Hypertens 2002;20:1829-34.
26Boustany CM, Bharadwaj K, Daugherty A, Brown DR, Randall DC, Cassis LA. Activation of the systemic and adipose renin-angiotensin system in rats with diet-induced obesity and hypertension. Am J Physiol Regul Integr Comp Physiol 2004;287:R943-9.
27Montagnani M, Golovchenko I, Kim I, Koh GY, Goalstone ML, Mundhekar AN, et al. Inhibition of phosphatidylinositol 3-kinase enhances mitogenic actions of insulin in endothelial cells. J Biol Chem 2002;277:1794-9.
28Grassi G, Dell′Oro R, Facchini A, Quarti Trevano F, Bolla GB, Mancia G. Effect of central and peripheral body fat distribution on sympathetic and baroreflex function in obese normotensives. J Hypertens 2004;22:2363-9.
29Grassi G, Colombo M, Seravalle G, Spaziani D, Mancia G. Dissociation between muscle and skin sympathetic nerve activity in essential hypertension, obesity, and congestive heart failure. Hypertension 1998;31:64-7.
30Schram MT, Henry RM, van Dijk RA, Kostense PJ, Dekker JM, Nijpels G, et al. Increased central artery stiffness in impaired glucose metabolism and type 2 diabetes: The Hoorn Study. Hypertension 2004;43:176-81.
31Ferreira I, Henry RM, Twisk JW, van Mechelen W, Kemper HC, Stehouwer CD, et al. The metabolic syndrome, cardiopulmonary fitness, and subcutaneous trunk fat as independent determinants of arterial stiffness: The Amsterdam Growth and Health Longitudinal Study. Arch Intern Med 2005;165:875-82.
32Safar ME, Thomas F, Blacher J, Nzietchueng R, Bureau JM, Pannier B, et al. Metabolic syndrome and age-related progression of aortic stiffness. J Am Coll Cardiol 2006;47:72-5.
33Nystrom FH, Quon MJ. Insulin signalling: Metabolic pathways and mechanisms for specificity. Cell Signal 1999;11:563-74.
34Rizzoni D, Porteri E, Guelfi D, Muiesan ML, Valentini U, Cimino A, et al. Structural alterations in subcutaneous small arteries of normotensive and hypertensive patients with non-insulin-dependent diabetes mellitus. Circulation 2001;103:1238-44.
35O′Rourke MF. Wave travel and reflection in the arterial system. J Hypertens Suppl 1999;17:S45-7.
36Oladapo OO, Salako L, Sodiq O, Shoyinka K, Adedapo K, Falase AO. A prevalence of cardiometabolic risk factors among a rural Yoruba south-western Nigerian population: A population-based survey. Cardiovasc J Afr 2010;21:26-31.
37Sabir AA, Isezuo SA, Ohwovoriole AE, Fasanmade OA, Abubakar SA, Iwuala S, et al. Rural-urban difference in plasma lipid levels and prevalence of dyslipidemia in Hausa-Fulani of north-western Nigeria. Ethn Dis 2013;23:374-8.
38National Bureau of Statistics (NBS), Federal Government of Nigeria (FGN), Metadata Producer Harmonised Nigeria Living Standard Survey 2008/09; 2012.
39Kuznetsova T, Staessen JA, Kawecka-Jaszcz K, Babeanu S, Casiglia E, Filipovsky J, et al. Quality control of the blood pressure phenotype in the European Project on Genes in Hypertension. Blood Press Monit 2002;7:215-24.
40Ohwovoriole AE, Kuti JA, Kabiawu SI. Casual blood glucose levels and prevalence of undiscovered diabetes mellitus in Lagos Metropolis Nigerians. Diabetes Res Clin Pract 1988;4:153-8.