
==== Front
Medicine (Baltimore)
Medicine (Baltimore)
MD
Medicine
0025-7974
1536-5964
Lippincott Williams & Wilkins Hagerstown, MD

39029085
MD-D-24-00275
00087
10.1097/MD.0000000000038880
3
3700
Research Article
Observational Study
Relationship of anthropometrics and blood pressure to identify people at risk of hypertension and obesity-related conditions in Nigerian rural areas
Sunday Obaje Godwin PhD godwin.sunday@funai.edu.ng
a
Okorie Sonia-Love PhD koriesonialove@gmail.com
a
Ogugua Egwu Augustine PhD egwuoc@gmail.com
a
Muracki Jarosław PhD jaroslaw.muracki@usz.edu.pl
b
Kurtoglu Ahmet PhD akurtoglu@bandirma.edu.tr
c
Alotaibi Madawi H. PhD Mahalotaibi@pnu.edu.sa
d
https://orcid.org/0000-0002-1100-4301
Elkholi Safaa M. PhD d*
a Department of Human Anatomy, Faculty of Basic Medical Sciences, College of Medical Sciences Alex Ekwueme Federal University, Abakaliki, Nigeria
b Department of Physical Culture and Health, Institute of Physical Culture Sciences, University of Szczecin, Szczecin, Poland
c Department of Coaching Education, Faculty of Sport Science, Bandirma Onyedi Eylul University, Bandirma, Turkey
d Department of Rehabilitation Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia.
* Correspondence: Safaa M. Elholi, Department of Rehabilitation Sciences, College of Health and Rehabilitation Sciences, Princess Nourah Bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia (e-mail: smelkholi@pnu.edu.sa).
19 7 2024
19 7 2024
103 29 e3888007 1 2024
17 6 2024
19 6 2024
Copyright © 2024 the Author(s). Published by Wolters Kluwer Health, Inc.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.

The prevalence of obesity and hypertension is increasing, particularly in the urban areas. However, there is limited research on the relationship between obesity and hypertension in the rural areas of southeastern Nigeria. The present study aimed to investigate the association between anthropometric parameters and adiposity indicators and the risk of hypertension with obesity-related conditions, based on a descriptive study of people living in the southeastern rural areas of Nigeria. The cluster sampling procedure randomly recruited study participants. Finally, 200 participants (100 male and 100 female) aged 18 to 25 years were included in the study. A simplified correlation analysis was used to derive the adjusted indicators in relation to age and sex. This study found that females generally had a higher body mass index (BMI), waist circumference (WC), and Z-score, whereas systolic blood pressure (SBP) was higher in men. A high correlation was found between the body shape index (ABSI) and BMI (r = −.529, P < .001), WC (r = .399, P < .001) and Z-score (r = .982, P < .001) in male participants. In females, there was a high correlation between ABSI and BMI, blood pressure (BP), and Z score in female participants (r = −.481, P < .000; r = −.267, P = .007; r = .941, P < .000). In male participants, BMI was correlated with diastolic blood pressure (DBP; r = .236, P = .018), SBP (r = .282, P = .005), Z score (r = −.539, P < .000), and WC (r = .541, P < .001). This study highlights the importance of considering a range of anthropometric measurements and health parameters when assessing health risks and identifying potential interventions. In addition, the body shape index may be a particularly useful tool for predicting health risks in both men and women. In contrast, correlations between various health parameters can provide insights into the underlying mechanisms and risk factors.

anthropometric measurements
body shape index
cardiovascular disease
diastolic blood pressure
hypertension
systolic blood pressure
OPEN-ACCESSTRUE
==== Body
pmc1. Introduction

There is a growing prevalence of obesity and hypertension in Nigeria[1,2] and there is a strong need for effective strategies to address these public health challenges. New concepts, such as the body shape index (ABSI) and visceral adiposity index are novel indicators of visceral obesity associated with cardiometabolic risk factors.[3,4] In other climates, the Chinese visceral adiposity index (CVAI)[3] has been developed specifically for the Chinese population, which is calculated using a combination of anthropometric and metabolic parameters, including body mass index (BMI), waist circumference (WC), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C): CVAI = [WC/39 + 0.5 × BMI × (TG/1.7) × (1/HDL-C)] × 100. Interestingly, higher visceral adiposity index values indicate more significant levels of visceral adiposity,[5,6] which is associated with an increased risk of cardiometabolic diseases such as hypertension, diabetes, and cardiovascular diseases. In Nigeria, cardiovascular-related issues are more prevalent, and novel indicators, such as ABSI, are required. ABSI = WC/[(BMI^(2/3)) × (height^(1/2))], where height was measured in meters, and ABSI was reported as an index of abdominal obesity, which has been shown to be a better predictor of mortality risk than traditional measures such as BMI or waist circumference alone.[7–9]

Regarding the relationship between BMI, WC, systolic blood pressure (SBP), and diastolic blood pressure (DBP), a study conducted in a rural Chinese population found that combining BMI and waist circumference was a better predictor of obesity-related hypertension than either measure alone.[10] Others found a positive correlation between BMI and blood pressure among older adults,[11,12] and a community-based study in Nigeria found that both BMI and WC were significantly associated with hypertension and cardiometabolic syndrome in semi-urban and rural communities.[13]

The association between hypertension and generalized obesity in rural southwestern Nigeria has been reported previously. As hypertension is a significant public health concern, and Africa has the greatest disease burden, obesity is a well-established risk factor for hypertension and other chronic diseases. The prevalence of obesity and hypertension is increasing, particularly in the urban areas.[14,15] However, there is limited research on the relationship between obesity and hypertension in the rural areas of southeastern Nigeria. Understanding this relationship in body composition among the eastern population will add to the body of knowledge in anthropometric studies for identifying individuals at risk of hypertension and for developing effective prevention and treatment strategies. In this context, we assumed the following hypothesis to be realized in our research: (H1a) There will be potential gender-specific d variations in the health metrics; (H1b) There will be a significant correlation between ABSI and blood pressure across genders. Also, we assume that there will be a correlation between ABSI and BMI, blood glucose level (BGL) and WC across genders, as seen in other populations for weighted health interventions.[8] This study is particularly important given the increasing prevalence of both hypertension and obesity in Nigeria and the challenges in managing these conditions in rural communities.

2. Methods

2.1. Study location

Ikwo is a local government in the Ebonyi State, Nigeria. The people who live in this area are known as the Ikwo people or Ikwo subjects. They are primarily of Igbo origin and speak the Ikwo dialect. The Ikwo people are known for their rich cultural heritage, which includes traditional music, dances, and festivals. They are also known for their agricultural practices, with yams and cassava being staple crops in the region.

2.2. Study design and participants

This was a descriptive study, and participants were selected by cluster random sampling: Study population was defined, as in; it was the adult subjects from Igbo ethnicity. By dividing the population into clusters, the gender, demography, and community-specificity were used as hallmarks (because they share some common characteristics). Randomly selected clusters were used to choose a predetermined number of clusters from the clusters. In this, the selected clusters became representatives of the entire population. To ensure that all individuals in selected clusters represented study population, every adult in the chosen clusters covered for both males and females within the study area. A total of 200 participants (100 each for males and females) free of physical disabilities or disorders between 18 and 25 years of age who were students in the Federal Government Institution in the local government were recruited at baseline between April 2021 and October 2022. Written informed consent was obtained from each participant after fully explaining the study to them during oral defense, which was approved by the Ethics Committee of Alex Ekwueme Federal University Ndufu Alike, Ebonyi State (number ERN/FBMS/027, date April 1, 2021).

2.3. Study anthropometric measurements

The anthropometric measurements, study design, and participant characteristics used in this study were adopted from previous studies.[16–18] Height was measured to the nearest 0.1 cm with participants standing erect, while weight was measured to the nearest 0.5 kg using a digital stadiometer. WC was measured at the midpoint between the lowest rib and the iliac crest to the nearest 0.1 cm. The participants were measured twice, and the average value was used for the analyses. BMI was calculated as weight (kg) divided by height (m) squared. ABSI was defined as WC/((BMI)2/3 × (height)1/2).

Blood pressure (BP) measurement (mm Hg). Participants sat comfortably with their arms positioned at the level of the heart during the measurement. Demographic and clinical parameters were recorded using a prestructured questionnaire and standard sphygmomanometer by trained health workers to record details of blood pressure and cardiovascular diseases. The measurements were repeated 3 times at 30-second intervals, and the average was used for analysis. Hypertension was defined as SBP ≥ 140 mm Hg and/or DBP ≥ 90 mm Hg, and/or the use of antihypertensive medication.[19]

2.4. Statistical analyses

Statistical analyses were performed using the Statistical Package for the Social Sciences (IBM-SPSS, Chicago, Illinois, version 25) in 2009. The normality of the data in the study was determined using the Kolmogorov–Smirnov test (P > .05). In addition, Levene test was applied to ensure homogeneity of variances. The data were normally distributed. Therefore, an Independent Sample t Test was used to analyze the data between sexes. In addition, the Pearson Correlation Coefficient test was used to determine the correlation between the data. Cohen’s d effect size with 95% confidence interval was calculated to define the magnitude of pairwise comparisons for the pre- and posttests. The effect size magnitude was described as follows: <0.2 = trivial, 0.2 to 0.6 = small effect, >0.6 to 1.2 = moderate effect, >1.2 to 2.0 = large effect, and > 2.0 = very large.[18] Statistical significance was set at P < .05.

3. Results

3.1. Demographic characteristics of the study participants

A total of 200 participants (100 males and 100 females) were included in this study. Means of age for men and women were 21.27 ± 1.93 and 21.07 ± 1.75 years, respectively. The baseline characteristics of the study participants in terms of BMI, WC, and Z scores were higher in women than in men. The SBP was higher in males (Table 1 and Fig. 1). The effect of ABSI on some selected anthropometrics like the BMI and blood pressures was well pronounced in women, as the statistical test in the study showed significant correlations (Table 2).

Table 1 Sample characteristics by gender.

Parameters	Male
n = 100
M ± SD	Female
n = 100
M ± SD	t value	Cohen’s d	P value	
Age (yr)	21.27 ± 1.93	21.07 ± 1.75	0.765	0.10	.445	
Height (m)	1.77 ± 0.06	1.63 ± 0.07	14.347	2.14	<.001	
Weight (kg)	69.70 ± 11.05	66.47 ± 4.62	1.913	0.38	.057	
BMI (kg/m2)	22.06 ± 3.18	24.84 ± 4.62	−4.953	0.70	<.001	
WC (m)	0.31 ± 0.02	0.32 ± 0.03	−3.009	0.39	.003	
ABSI	0.030 ± 0.002	0.030 ± 0.001	−0.564	0.21	.573	
Z-score	−13.50 ± 0.71	−11.93 ± 0.49	−17.939	2.57	<.001	
SBP	125.69 ± 12.58	118.40 ± 11.95	4.200	0.59	<.001	
DBP	80.17 ± 9.80	79.76 ± 10.33	0.288	0.04	.774	
BGL	95.61 ± 12.09	94.48 ± 14.41	0.601	0.08	.549	
ABSI = body shape index, BGL = blood glucose level, BMI = body mass index, DBP = diastolic blood pressure, SBP = systolic blood pressure, WC = waist circumference.

Table 2 The correlations between BSI and systolic and diastolic blood pressure, blood glucose level and BMI.

		ABSI	BMI	SBP	DBP	BGL	WC	Z-score	
ABSI	Male		r = −.529, P = .000**	r = −.008, P = .934	r = −.112, P = .265	r = .113, P = .187	r = .399, P = .000**
	r = .982, P = .000**	
Female	
							
BMI	Male			r = .282, P = .005**	r = .236, P = .018*	r = .018, P = .863	r = .541, P = .000**	r = −.539, P = .000**	
Female	r = −.481, P = .000**							
SBP	Male				r = .605, P = .000**	r = .141, P = .163	r = .331, P = .001**	r = −.057, P = .574	
Female	r = −.267, P = .007**	r = .119, P = .238						
DBP	Male					r = .094, P = .355	r = .181, P = .071	r = −.137, P = .174	
Female	r = −.170, P = .091	r = .048, P = .633	r = .713, P = .000**					
BGL	Male					
	r = .156, P = .122	r = .115, P = .254	
Female	r = −.116, P = .250	r = .231, P = .021*	r = −.286, P = .004**	r = −.129, P = .202				
WC	Male						
	r = .355, P = .000**	
Female	r = .080, P = .431	r = .819, P = .000**	r = −.035, P = .732	r = −.073, P = .470	r = .168, P = .094			
Z-score	Male							
	
Female	r = .941, P = .000**	r = −.316, P = .001**	r = −.263, P = .008**	r = .178, P = .077	r = −.089, P = .378	r = −.255, P = .010*		
ABSI = body shape index, BMI = body mass index, BGL = blood glucose level, DBP = diastolic blood pressure, SBP = systolic blood pressure, WC = waist circumference.

* P < 0.05; **P < 0.01.

Figure 1. Body height, BMI, WC, Z-score, and SBP were examined in males and females. BMI = body mass index, SBP = systolic blood pressure, WC = waist circumference.

3.2. Relationship between anthropometrics, blood pressure levels

The relationships between the data for the male and female participants are shown in Table 2. There was a high correlation between the ABSI results of male participants and BMI (r = −.529, P = .000), WC (r = .399, P = .000), and Z-score (r = .982, P = .000). Male participants’ BMI scores were correlated with SBP (r = .282, P = .005), DBP (r = .236, P = .018), WC (r = .541, P = .000), and Z-score (r = .236, P = .018) −539, P = .000) scores. There was a correlation between SBP and DBP (r = .605, P = .000) and WC (r = .331, P = .001). There was a high correlation between the WC scores of male participants and the Z-score (r = .355, P = .000).

There was a high correlation between the ABSI results of female participants and the BMI (r = −.481, P = .000), SBP (r = −.267, P = .007), and Z score (r = .941, P = 000) results. There was an association between female participants’ BMI scores and the BGL (r = −.286, P = .004), WC (r = .819, P = .000), and Z-score (r = −.263, P = .001). There was a correlation between SBP and DBP (r = .713, P = .000), BGL (r = −.286, P = .004), and Z-score (r = −.263, P = .008). There was a correlation between WC and Z-scores (r = −.255, P = .010).

Table 1 presents the gender characteristics. Accordingly, men’s height (t = 14.347, P < .001, Cohen’s d = 2.14, [−.16, −.12; 95% CI], very large effect), BMI (t = −4.953, P < .001, Cohen’s d = 0.7, [1.6, 3.8; 95% CI], moderate effect), WC (t = −3.009, P = .003, Cohen’s d = 0.39, [.004, .002; 95% CI], small effect), Z-score (t = −17.939, P < .001, Cohen’s d = 2.57, [1.3, 1.7; 95% CI], very large effect), and SBP (t = 4.200, P < .001, Cohen’s d = 0.59, [−10.7, −3.8; 95% CI], moderate effect) were higher than females (Fig. 1).

4. Discussion

To the best of our knowledge, this is the first descriptive study of Igbo ethnicity in southeastern Nigeria to explore the association between ABSI and risk of hypertension and obesity-related conditions. There was a slight increase in blood pressure in males (125.69 ± 12.58) compared to females (118.40 ± 11.95). In the future, more men will be at a higher risk of hypertension than women. Men (1.77 ± 0.06) appeared to be taller than females (1.63 ± 0.07).

We observed a relationship between various anthropometric measurements and health parameters in both men and women (Fig. 1). This study found that women generally had higher BMI, WC, and Z-score values (ABSI), whereas SBP was higher in men. The research also identified the ABSI as a potentially useful premeasurement method for determining men’s BMI and WC. The ABSI is a relatively new measure that considers a person’s height, weight, and waist circumference to calculate mortality risk. This study found a high correlation between the ABSI and BMI, WC, and Z-score in male participants.

In addition, this study found significant correlations between various health parameters in both men and women. For example, in male participants, BMI correlated with SBP, DBP, WC, and Z-scores. SBP was correlated with DBP and WC, whereas WC was correlated with the Z-score. In female participants, BMI was correlated with BGL, WC, and Z-score, whereas SBP was correlated with DBP, BGL, and Z-score. WC was also correlated with Z-score in women.

This study highlighted the importance of considering a range of anthropometric measurements and health parameters when assessing health risks and identifying potential interventions. Our findings suggest that body shape index (ABSI) may be a particularly useful tool for predicting health risks in both men and women. In contrast, correlations between various health parameters can provide insights into the underlying mechanisms and risk factors.

Strong evidence indicates that the quantity and distribution of subcutaneous fatty deposits are associated with different risks of hypertension and obesity-related issues, with abdominal fatty tissues being more strongly related to the risk of hypertension in different ethnicities and regions.[19] Despite the huge contributions from the applications of BMI and WC to define specific obesity, it can differentiate regional tissue fatty components.[20,21] ABSI, as a reliable and newest anthropometric indicator of body fat accumulation, has the same bottlenecks as older anthropometric indices, such as BMI, WC, and hip circumference (HC).[22] Due to the high cost of medical equipment in developing countries, access to computed tomography and magnetic resonance imaging systems to assess body composition in general clinical practice, and large descriptive studies, the newest indicators for body fat have been developed for use in Igboland. Comparative study of BMI and ABSI in predicting high blood pressure among Malaysian adolescents has been known.[23] Our results showed that ABSI had the best performance in association with SBP, DBP, and BGL, with the capacity to determine the incidents of hypertension and obesity-related issues for both sexes in our Nigerian basic medical sciences. The ABSI similarities along sex in our study may be due to the genetic relationship responsible for cardiovascular-related states in different people. Other populations are more susceptible to visceral fat accumulation and, hence, have lower BMI values than those with reduced fatty deposits.[3,21] Consistent with our findings, Ştefănescu et al[24] examined the ability of different body measurements to predict the risk of metabolic syndrome and its components in Peruvian adults. However, it discovered another indicator to be a helpful tool for clinicians to identify individuals at risk for metabolic syndrome in Peru.

The present study had some limitations. It is important to note that this study was conducted in Igbo adults, and may not represent other populations. Additionally, the study was cross-sectional, meaning that it only provides a snapshot of people at a specific point in time, and cannot establish causality. Finally, the study relied on descriptive and correlational analyses only, which may not give predictive capacity of the selected anthropometrics. However, the findings of this study can inform future research on hypertension and obesity in rural and urban areas for the developing nations.

5. Conclusion

Based on the results of the present study, we concluded that the anthropometric characteristics of the participants showed no significant correlation between ABSI and DBP and BGL. In addition, hypertension in men increased as the BMI increased. This shows that the BMI can be used to determine hypertension in men. The results of our study highlight the importance of understanding anthropometric characteristics that affect hypertension. The results of our study are important for the modeling and planning of rehabilitation processes in individuals with hypertension.

Acknowledgments

The authors acknowledge with considerable gratitude all those who volunteered to participate in this study. We thank Prof Austin O. Ibegbu, Dean of the Faculty of Basic Medical Sciences, Alex Ekwueme Federal University, Ndufu Alike, for his administrative support. The authors would like to acknowledge Princess Nourah Bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R535) Princess Nourah Bint Abdulrahman University, Riyadh, Saudi Arabia, for funding this study.

Author contributions

Conceptualization: Obaje Godwin Sunday, Sonia-Love Okorie, Egwu Augustine Ogugua, Ahmet Kurtoglu, Safaa M. Elkholi.

Data curation: Obaje Godwin Sunday, Sonia-Love Okorie, Egwu Augustine Ogugua, Jarosław Muracki.

Formal analysis: Obaje Godwin Sunday, Ahmet Kurtoglu.

Funding acquisition: Madawi H. Alotaibi, Safaa M. Elkholi.

Investigation: Sonia-Love Okorie, Egwu Augustine Ogugua.

Methodology: Obaje Godwin Sunday, Sonia-Love Okorie, Egwu Augustine Ogugua, Jarosław Muracki.

Project administration: Obaje Godwin Sunday, Safaa M. Elkholi.

Software: Jarosław Muracki, Ahmet Kurtoglu.

Supervision: Obaje Godwin Sunday, Ahmet Kurtoglu.

Validation: Madawi H. Alotaibi, Safaa M. Elkholi.

Visualization: Jarosław Muracki, Ahmet Kurtoglu, Safaa M. Elkholi.

Writing – original draft: Obaje Godwin Sunday, Sonia-Love Okorie, Egwu Augustine Ogugua, Jarosław Muracki.

Writing – review & editing: Ahmet Kurtoglu, Madawi H. Alotaibi, Safaa M. Elkholi.

Abbreviations:

ABSI body shape index

BGL blood glucose level

BMI body mass index

BP blood pressure

DBP diastolic blood pressure

SBP systolic blood pressure

WC waist circumference

Princess Nourah bint Abdulrahman University Researchers Supporting Project number (PNURSP2024R535), Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia funded this research.

The authors have no conflicts of interest to disclose.

All data generated or analyzed during this study are included in this published article [and its supplementary information files].

How to cite this article: Sunday OG, Okorie S-L, Ogugua EA, Muracki J, Kurtoglu A, Alotaibi MH, Elkholi SM. Relationship of anthropometrics and blood pressure to identify people at risk of hypertension and obesity-related conditions in Nigerian rural areas. Medicine 2024;103:29(e38880).
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