Influence of female gender on the prevalence of metabolic syndrome in normal-weight and overweight/obese adults in South-South Nigeria

AK Ajeigbe; OF Adewolu; CL Uche; IH Ojelabi; OE Olukoyejo; OJ Jokanola; OO Odun-Afolabi; ES Idogun

doi:10.4103/njhs.njhs_17_22

ORIGINAL ARTICLE

Year : 2023 | Volume : 23 | Issue : 1 | Page : 5-9

Influence of female gender on the prevalence of metabolic syndrome in normal-weight and overweight/obese adults in South-South Nigeria

AK Ajeigbe¹, OF Adewolu², CL Uche³, IH Ojelabi¹, OE Olukoyejo¹, OJ Jokanola¹, OO Odun-Afolabi¹, ES Idogun²
¹ Department of Chemical Pathology, Obafemi Awolowo University, Ile-Ife, Nigeria
² Department of Chemical Pathology, University of Benin, Benin, Nigeria
³ Department of Haematology, Abia State University, Aba, Nigeria

Date of Submission	14-Jul-2022
Date of Decision	19-Dec-2022
Date of Acceptance	29-Dec-2022
Date of Web Publication	17-Jul-2023

Correspondence Address:
Dr. A K Ajeigbe
Department of Chemical Pathology, Obafemi Awolowo University, Ile-Ife
Nigeria

Source of Support: None, Conflict of Interest: None

Check

DOI: 10.4103/njhs.njhs_17_22

Abstract

Background: Metabolic syndrome is a recognised public health concern due to the increasing incidence of obesity worldwide. However, non-obese normal-weight individuals may also present with metabolic syndrome.
Objective: The objective of this study was to compare the prevalence of metabolic syndrome amongst normal-weight and overweight/obese individuals as well as determine the gender influence.
Materials and Methods: A total of 102 apparently healthy controls were recruited for this study. Information on demography and medical history was obtained using an interviewer-administered questionnaire. Blood pressure (BP) and anthropometric parameters were obtained using standard instruments followed by 5 ml of blood collected from the antecubital vein of each participant. The blood specimens were separated using a centrifuge to yield plasma and serum for fasting plasma glucose (FPG) and total cholesterol assays, respectively. The Adult Treatment Panel III criteria for metabolic syndrome were used to determine the presence of metabolic syndrome. Participants were stratified into normal weight (non-obese) and above normal weight (overweight and obese) using body mass index (BMI). The above-normal weight participants were further stratified into overweight and Class I, II and III obesity using the corresponding BMI. Student's t-test was used to compare groups. The alpha level was set at P < 0.05.
Results: The overweight/obese (53.9 ± 12.3 years) participants were significantly older than the normal-weight participants (43.9 ± 15.8 years), P < 0.05, with a male-to-female ratio of 0.85:1 and 1.6:1, respectively. Systolic BP (130.9 ± 21.3 mmHg) and FPG (6.5 ± 2.7 mmol/L) were significantly higher in above normal weight than normal weight (121.3 ± 17.3 mmHg and 5.1 ± 1.5 mmol/L). Metabolic syndrome was present in 47.4% and 7.7% of overweight/obese and normal weight, respectively, while females had a significantly higher proportion of metabolic syndrome in both the above normal weight (31.6%) and the normal weight (7.7%), respectively.
Conclusion: Females and older individuals may likely develop metabolic syndrome irrespective of BMI. Normal-weight individuals have a lower prevalence of metabolic syndrome.

Keywords: Female gender, metabolic syndrome, normal weight, obese, overweight

How to cite this article:
Ajeigbe A K, Adewolu O F, Uche C L, Ojelabi I H, Olukoyejo O E, Jokanola O J, Odun-Afolabi O O, Idogun E S. Influence of female gender on the prevalence of metabolic syndrome in normal-weight and overweight/obese adults in South-South Nigeria. Niger J Health Sci 2023;23:5-9

How to cite this URL:
Ajeigbe A K, Adewolu O F, Uche C L, Ojelabi I H, Olukoyejo O E, Jokanola O J, Odun-Afolabi O O, Idogun E S. Influence of female gender on the prevalence of metabolic syndrome in normal-weight and overweight/obese adults in South-South Nigeria. Niger J Health Sci [serial online] 2023 [cited 2023 Dec 10];23:5-9. Available from: http://www.https://chs-journal.com//text.asp?2023/23/1/5/381738

Introduction

Obesity, as a non-communicable disease, is increasingly recognised as a cause of morbidity and mortality amongst African descent. This is due to the changes in lifestyle and westernisation. Obesity is linked to other chronic diseases such as hypertension and Type 2 diabetes through the development of metabolic syndrome.^[1] Metabolic syndrome is a constellation of signs and symptoms related to an underlying metabolic abnormality, of which overweight or obesity is cardinal. Furthermore, known as Raven's disease, it is a biological and anthropometric disturbance with a clinically prominent marker of overweight usually abdominal obesity.^[2] There are varying reports of the prevalence of metabolic syndrome amongst Africans based on criteria used to define metabolic syndrome and population-based factors such as age and sex. However, there is a rise in the prevalence of metabolic syndrome up to 50%^[3] amongst Africans and it is a public health concern. In Nigeria, a West African country, a prevalence rate of 35.1% was reported while lower values of 21.8% and 25.6% were reported from South and East Africa, respectively.^{[4],[5],[6],[7],[8]} Most reports on the prevalence of metabolic syndrome were in obese individuals and few data on the prevalence amongst non-obese normal-weight individuals. We, therefore, assessed and compared the prevalence of metabolic syndrome amongst normal-weight and overweight/obese individuals and determined the influence of gender on the prevalence in these two groups.

Materials and Methods

This was a cross-sectional descriptive study involving individuals attending the centre for disease control of a tertiary hospital for routine medical check-ups. Ethical clearance was obtained from the ethics and research committee of the hospital. Adults aged 18 years and above were recruited using a simple random sampling method based on every alternate eligible participant. Excluded were individuals with known chronic medical conditions such as diabetes mellitus, hypertension, dyslipidaemia and chronic kidney disease as well as those non-fasted and who did not give consent.

A semi-structured interviewer-administered questionnaire was used to obtain information on sociodemographic parameters, medical and family history as well as social history. Anthropometric parameters such as height, weight and abdominal circumference were measured using a weighing scale with the attached meter by Sica Limited and measuring tape in centimetre, kilogram and centimetre, respectively. To measure the weight, participants were allowed to remove shoes and any heavy clothing before mounting the scale and heads were kept in the upright position after which the readings were taken in kilogram (kg) by the investigator. Two readings were taken for each participant and the average was recorded. Height was taken using a standard measuring meter attached with the scale; participants were asked to remove head ties and caps before applying the measuring ruler close to the crown of the head. After which, the meter was adjusted and measurement was taken and recorded in meter (m). The abdominal circumference was measured using a measuring tape around the waist passing through the level of the iliac crest and readings were taken at the level of umbilicus in centimetre (cm). The body mass index (BMI) was calculated using the formula by Quetelet (weight [kg]/height [m^[2]]) and recorded in kg/m^[2].

The blood pressure (BP) of each participant was later measured using a sphygmomanometer. Two readings at the 30-min interval were taken for each participant and the mean value was recorded in mmHg.

Five millilitres of venous blood was collected from the antecubital fossa and 2.5 ml each was dispensed into fluoride oxalate and plain bottles for fasting plasma glucose (FPG) and total cholesterol assays, respectively. Samples in plain bottles were allowed to clot before centrifugation. All specimens were placed in a centrifuge and allowed to spin for 1000 g for 5 min. Corresponding plasma and serum were harvested and discharged into Eppendorf tubes and stored at − 20°C until enough pool for assay. Randox reagent kits were used to assay glucose and total cholesterol and absorbance were determined by Spectrum Lab 22PC spectrophotometer. Glucose concentration in plasma was determined using glucose oxidase method and absorbance was read by spectrophotometer at a wavelength of 492 nm. Total cholesterol concentration in serum was determined by the cholesterol oxidase method provided by Randox Laboratories and absorbance was read at 500 nm using a spectrophotometer. Participants were stratified into normal-weight (non-obese) and above-normal weight (overweight/obese) groups using a cutoff of 18.5–24.9 kg/m^[2] and ≥25 kg/m^[2], respectively. The above-normal weight participants were further stratified into overweight and obese Classes I (mild), II (moderate) and III (severe) using the corresponding BMI of 25–29.9 kg/m^[2], 30–34.9 kg/m^[2], 35–39.9 kg/m^[2] and ≥40 kg/m^[2], respectively.^[9] To make a diagnosis of metabolic syndrome, selected criteria by the National Cholesterol Education Panel Adult Treatment Panel III were used based on the limited funds: metabolic syndrome was considered present irrespective of BMI staging if abdominal circumference exceeded 88 cm and 102 cm in females and males, respectively, with at least any two other criteria, namely FPG >5.6 mmol/L (110 mg/dL), systolic BP >130 mmHg and diastolic BP >85 mmHg.^[10]

Results

A total of 102 individuals were recruited for this study in a male-to-female ratio of 1. The study showed that the overweight/obese (53.9 ± 12.3 years) individuals were significantly older than the normal weight (43.9 ± 15.8 years), P < 0.05 [Table 1]. There were more females (53.9%) in the overweight/obese group, whereas the normal-weight group had more males (61.5%). This was, however, not significant [Table 2].

Table 1: Demography, anthropometry and biochemical parameters between normal weight and overweight/obese

Click here to view

Table 2: Effect of gender on anthropometry and biochemical parameters amongst participants

Click here to view

The overweight/obese group had a higher waist circumference, systolic BP and FPG (103.5 ± 12.4 cm, 130.9 ± 21.3 mmHg and 6.5 ± 2.7 mmol/L) than the normal weight (85.8 ± 6.9 cm, 121.3 ± 17.3 mmHg and 5.1 ± 1.5 mmol/L), respectively, which were significant, P < 0.05 [Table 1].

There was a significant gender influence on the mean BMI only for the above-normal weight group as the females had higher BMI (32.5 ± 6.9 kg/m^[2] ^vs. 29.7 ± 4.9 kg/m^[2]) than the males, P < 0.05. Similarly, the mean abdominal circumference, systolic BP and FPG were higher amongst the overweight/obese females than their male counterparts. However, this was not significant [Table 2]. In addition, the majority of the overweight/obese group were either overweight or obese Class I [Table 2].

Abdominal obesity, defined as waist circumference >88 cm or 102 cm in females and males, respectively, was present in 52.6% of overweight/obese females against 26.5% for their male counterparts. This was significant, P < 0.05. Similarly, the proportion (11.5%) of normal-weight females with abdominal obesity was significantly different from the normal-weight males [Table 3].

Table 3: Prevalence of metabolic syndrome and abdominal amongst above-normal weight and normal-weight participants

Click here to view

A total of 36 participants (47.4%) in the overweight/obese group had metabolic syndrome against 7.7% in the normal-weight group [Table 3]. It was also observed that more (31.6%) overweight/obese females had metabolic syndrome which was significantly higher than 15.8% found for their male counterparts, P < 0.05 [Table 3]. On the other hand, only two females in the normal-weight group had metabolic syndrome, which was not significant [Table 3].

Discussion

This study found that obesity is common amongst apparently healthy controls attending outpatient clinics for routine medical screening. Amongst these adults, older age groups are more predisposed to overweight and obesity and the female gender has a higher tendency to be overweight or in obesity Class I. This supports the report that individuals with obesity are more likely to be older (48.19 ± 15.48 years) than an individual with normal weight (41.6 ± 17.6 years).^[11]

The anthropometry showed that the above-normal weight individuals had larger waist circumferences than the normal weight, especially the females. Similar to previous reports, abdominal obesity was found to be highly prevalent amongst obese individuals, particularly females.^[11] Abdominal obesity was reported as the most common component of metabolic syndrome and suggested as the strongest predictor of metabolic syndrome.^[11] In support of this, this study also observed that abdominal obesity was present amongst the non-obese normal-weight females, which was significant. This central obesity may be due to the accumulation of omental fats which confers additional cardiovascular risk.^[1] This is also contrary to reports of previous studies that the female fat distribution is peripheral while that of males is central. This central abdominal fat distribution amongst females requires further exploration. Abdominal obesity found in this study irrespective of the BMI has a propensity towards the release of inflammatory markers with prothrombotic state.^[12],[13] These adipokines and chemical mediators such as interleukin-6, tumour necrosis factor-alpha, leptin and resistin are elevated in obese individuals which may lead to endothelial injury and vascular hypertrophy.^[14],[15]

The higher systolic BP found amongst the above-normal weight group supports earlier reports of cardiovascular risks associated with obesity. This is attributed to some chemokines and hormones released by adipocytes which may evoke vascular injury.^[14],[15] Similarly, higher FPG in the impaired range found for the above-normal weight group may be associated with increased adiposity. Previous studies reported that abnormal plasma glucose concentration is a factor related to metabolic syndrome.^{[11],[16],[17],[18]} It has been suggested that hypertension, dyslipidaemia and dysglycaemia are individual risk factors for cardiovascular disease or a component of metabolic syndrome.^[1]

This study found that the prevalence of metabolic syndrome was 47.4% amongst above-normal weight participants as against the 7.7% in the normal weight. This is similar to earlier reports.^[4],[11] Reports from studies around Africa revealed a prevalence of 35.1%, 35.73%, 38.98%, and 42% in Northwestern Nigeria, Morocco, Western Cameroon, and Johannesburg respectively,^{[4],[6],[8],[19]} A lower prevalence of 21.8% was found in South Africa.^[5] This finding support reports that metabolic syndrome is prevalent amongst above-normal weight individuals.^[11] However, some factors like lifestyle and genetics may play a role in its pathogenesis. In addition, a previous study amongst teachers in Malaysia reported a prevalence of 8.3% for metabolic syndrome in the non-obese normal BMI and found 29.9% for those overweight.^[19] This is similar to the findings in this study; however, males had a higher prevalence contrary to this study. Similarly, a prevalence of 15.1% for metabolic syndrome was reported in South India amongst individuals with <25 kg/m^[2] BMI.^[20] This higher prevalence has been attributed to the higher tendency of those with Indian ethnicity to develop abdominal obesity, hypertension, dyslipidaemia, glucose intolerance and hyperinsulinaemia.^[21]

It was observed from this study that the prevalence of metabolic syndrome is higher amongst females as against the above-normal weight male counterparts similar to previous studies. A study in Cameroon reported the prevalence of metabolic syndrome in women to be 46.11% and 14.01% in males^[11] while a prevalence of 40.12% in women against 18.6% in males was reported from Morocco.^[6],[16] In Northwestern Nigeria, the prevalence of metabolic syndrome in women was 42.83% against 36% in males.^{[4],[22],[23]} The female gender predisposition to metabolic syndrome has been attributed to increased adipose tissue, obesity and less physical activities.^[24]

Metabolic syndrome as a constellation of anthropometric and biochemical parameters was found in 31.6% of the above-normal weight females, significantly different from 15.8% of males showing that a gender predisposition may exist with a possible higher tendency in females. In addition, the prevalence of metabolic syndrome for non-obese normal-weight females which was not significant further supports the role of the female gender. Thus, there may be gender influence on the development of metabolic syndrome which appears to be dependent on the magnitude of BMI. That is, as the BMI increases, the possible risk of metabolic syndrome may also increase in women. Therefore, at normal BMI, the prevalence of metabolic syndrome is low, but at higher BMI, the prevalence appears high amongst females, as shown in this study. Similarly, for increased BMI within the obesity range, the risk of metabolic syndrome amongst females appears to double the male counterparts. Clinicians should be aware that non-obese individuals can present with metabolic syndrome which places them at risk of cardiometabolic diseases similar to the obese.

This study was not without limitations in that serum triglycerides and HDL-cholesterol were not assayed together with other biochemical criteria for Met.S. This was due to financial constraints. Also, the inclusion of individuals with chronic cardiometabolic conditions like hypertension, diabetes mellitus, and dyslipidemia may influence the study outcome.

Conclusion

The prevalence of metabolic syndrome is higher amongst above-normal weight individuals, and female gender may be a risk factor associated with it irrespective of BMI.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

References

1.	Mathew B, Francis L, Kayalar A, Cone J. Obesity: Effects on cardiovascular disease and its diagnosis. J Am Board Fam Med 2008;21:562-8.
2.	Lee SE, Han K, Kang YM, Kim SO, Cho YK, Ko KS, et al. Trends in the prevalence of metabolic syndrome and its components in South Korea: Findings from the Korean National Health Insurance Service Database (2009-2013). PLoS One 2018;13:e0194490.
3.	Fezeu L, Balkau B, Kengne AP, Sobngwi E, Mbanya JC. Metabolic syndrome in a sub-Saharan African setting: Central obesity may be the key determinant. Atherosclerosis 2007;193:70-6.
4.	Sabir AA, Jimoh A, Iwuala SO, Isezuo SA, Bilbis LS, Aminu KU, et al. Metabolic syndrome in urban city of North-Western Nigeria: Prevalence and determinants. Pan Afr Med J 2016;23:19.
5.	Owolabi EO, Goon DT, Adeniyi OV, Adedokun AO, Seekoe E. Prevalence and correlates of metabolic syndrome among adults attending healthcare facilities in Eastern Cape, South Africa. Open Public Health J 2017;10:148-59.
6.	El Brini O, Akhouayri O, Gamal A, Mesfioui A, Benazzouz B. Prevalence of metabolic syndrome and its components based on a harmonious definition among adults in Morocco. Diabetes Metab Syndr Obes 2014;7:341-6.
7.	Omuse G, Maina D, Hoffman M, Mwangi J, Wambua C, Kagotho E, et al. Metabolic syndrome and its predictors in an urban population in Kenya: A cross sectional study. BMC Endocr Disord 2017;17:37.
8.	Dandji M, Zambou F, Dangang D, Nana F, Tchouanguep F. Prevalence of metabolic syndrome in adult men of dschang health district in Western Cameroon. World J Nutr Health 2018;6:1-10.
9.	CDC. About Adult BMI. Available from: https.//www.cdc.gov/healthyweight/assessing/bmi/adult_bmi/index.html.
10.	Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults. Executive summary of the third report of the National Cholesterol Education Program (NCEP) Expert Panel on detection, evaluation, and treatment of high blood cholesterol in adults (Adult Treatment Panel III). JAMA 2001;285:2486-97.
11.	Marbou WJ, Kuete V. Prevalence of metabolic syndrome and its components in Bamboutos division's adults, west region of Cameroon. Biomed Res Int 2019;2019:9676984.
12.	Kern PA, Saghizadeh M, Ong JM, Bosch RJ, Deem R, Simsolo RB. The expression of tumor necrosis factor in human adipose tissue. Regulation by obesity, weight loss, and relationship to lipoprotein lipase. J Clin Invest 1995;95:2111-9.
13.	Hotamisligil GS, Arner P, Caro JF, Atkinson RL, Spiegelman BM. Increased adipose tissue expression of tumor necrosis factor-alpha in human obesity and insulin resistance. J Clin Invest 1995;95:2409-15.
14.	Lundgren CH, Brown SL, Nordt TK, Sobel BE, Fujii S. Elaboration of type-1 plasminogen activator inhibitor from adipocytes. A potential pathogenetic link between obesity and cardiovascular disease. Circulation 1996;93:106-10.
15.	Steppan CM, Bailey ST, Bhat S, Brown EJ, Banerjee RR, Wright CM, et al. The hormone resistin links obesity to diabetes. Nature 2001;409:307-12.
16.	Kaur J. A comprehensive review on metabolic syndrome. Cardiol Res Pract 2014;2014:943162.
17.	Ki NK, Lee HK, Cho JH, Kim SC, Kim NS. Factors affecting metabolic syndrome by lifestyle. J Phys Ther Sci 2016;28:38-45.
18.	Cornier MA, Dabelea D, Hernandez TL, Lindstrom RC, Steig AJ, Stob NR, et al. The metabolic syndrome. Endocr Rev 2008;29:777-822.
19.	Lee SC, Hairi NN, Moy FM. Metabolic syndrome among non-obese adults in the teaching profession in Melaka, Malaysia. J Epidemiol 2017;27:130-4.
20.	Geetha L, Deepa M, Anjana RM, Mohan V. Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians. J Diabetes Sci Technol 2011;5:439-46.
21.	Misra A, Khurana L. The metabolic syndrome in South Asians: Epidemiology, determinants, and prevention. Metab Syndr Relat Disord 2009;7:497-514.
22.	Sodjinou R, Agueh V, Fayomi B, Delisle H. Obesity and cardio-metabolic risk factors in urban adults of Benin: Relationship with socio-economic status, urbanisation, and lifestyle patterns. BMC Public Health 2008;8:84.
23.	Isezuo SA, Ezunu E. Demographic and clinical correlates of metabolic syndrome in Native African type-2 diabetic patients. J Natl Med Assoc 2005;97:557-63.
24.	Sabir AA, Isezuo SA, Ohwovoriole AE. Dysglycaemia and its risk factors in an urban Fulani population of northern Nigeria. West Afr J Med 2011;30:325-30.