The Prevalence of Obesity in a Rural Setting in Port Harcourt, Rivers State

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Greener Journal of Medical Sciences

Vol. 11(2), pp. 149-158, 2021

ISSN: 2276-7797

Copyright ©2021, the copyright of this article is retained by the author(s)

https://gjournals.org/GJMS

 

The Prevalence of Obesity in a Rural Setting in Port Harcourt, Rivers State

Daka I.R.1*; Amaewhule M.N.2; Wekhe C.3

1Department of Pharmacology, Rivers State University, Port Harcourt, Nigeria.

2Department of Internal Medicine, Rivers State University, Port Harcourt, Nigeria.

3Department of Radiology, Rivers State University, Port Harcourt, Nigeria.

ARTICLE INFO ABSTRACT
Article No.: 101421105

Type: Research

Full Text: HTML, EPUB

Background: Obesity is a state of excess storage of body fat. It is currently quantitated by means of the body mass index (BMI), calculated from BMI= height in meters/weight in kilograms squared. However the BMI scale generally correlates with the degree of obesity and with risk. The prevalence of Obesity has been on the increase in our environment. The objective of this study is to assess the prevalence of Obesity but little information is available from developing countries where new cases of Obesity are increasingly diagnosed. Method: We examined BMI amongst apparently healthy adult population. A cross-sectional study was conducted amongst 107 adults- 80 females and 27 males between the ages of 18 years and 80years for a period of 3 months using convenience sampling. They were first administered a structured questionnaire to obtain their socio-demographic data and lifestyle characteristics after which anthropometric assessment was performed. Results: This shows that 74.8% were females and 25.2% were males. About 46.7% of the respondents were self-employed followed by 17.8% unemployed and 6.5% were students. Overall , 85.2% males have normal BMI while 14.8% males have a high BMI.66.2% females have a normal BMI while 33.8% have a high BMI. Conclusion: The prevalence of Obesity is more in females than males in this study. 44.9% had abdominal obesity, 29.0% had central obesity, this calls for more education of the populace and positive attitude and appropriate intervention towards addressing the relevant risk factors of Obesity thereby preventing future cardiovascular complications including metabolic syndrome in the general population.
Accepted: 15/10/2021

Published: 18/10/2021

*Corresponding Author

Daka I.R.

E-mail: iyaeneomidaka@ gmail.com

Keywords: Obesity; prevalence; adult population
   

 

 

INTRODUCTION

 

Obesity is a state of excess adipose tissue mass. Although often viewed as equivalent to increased body weight, this need not be the case-lean but muscular individuals may be overweight by numerical standards without having adiposity. Body weights are distributed continuously in populations so that choice of a medically meaningful distinction between lean and obese is somewhat arbitrary. Obesity is therefore more effectively defined by assessing its linkage to morbidity or mortality. Overweight and obesity are the fifth leading risk of global death with at least 2.8 million adults deaths each year from complications of overweight and obesity.[2] The World Health Organization stated that 1.9 billion of the world population are overweight while 650 million are obese as at 2016.[2] In addition, 44% of diabetes mellitus burden, 23% of ischemic heart diseases, and 7%–41% of certain cancer burden are attributable to overweight and obesity.

 

Worldwide prevalence of 2 billion if overweight included, 700 million obese Nigeria adult prevalence is less than 10%.In USA a third obese, a third overweight. In USA African American are most obese ethnic group with 45% obese, followed by Mexican Americans. Most obese population are the Pacific Islanders. Not very common nationally 8% in adults (Akinkugbe O 1992).Rare, 1 – 3% in rural regions (Okesina AB 1999).Higher in urban regions, up to 40% obese or overweight in Ife (Ojofeitimi EO et al 2007).Commoner in females F:M of 3.0.Fairly common in S. E Nigeria due to cultural practices.

 

Health risks associated with obesity include coronary heart disease and other atherosclerotic cardiovascular diseases, stroke, type 2 diabetes mellitus, high blood pressure, kidney disease, sleep apnea, osteoarthritis, gallstones, fatty liver disease, stress incontinence, and other gynecological abnormalities (amenorrhea and menorrhagia) and various cancers.[3] Sabir et al. reported obesity and increasing age are the major risk factors fueling increased prevalence of type 2 diabetes mellitus among Nigerians.[4] Dankyau et al. reported high prevalence of overweight and obesity among tertiary hospital workers in Northern Nigeria.[5] High prevalence of hypertension was reported by Owolabi et al. among health-care workers in Nigeria despite their awareness of the disease.[6] It has also been reported that increased body mass index (BMI) predisposes to certain cancers.[7]Analysis of data from the 1980 National Heights and Weights Survey estimates that the prevalence of obesity in England stood at 6% of men and 9% of women aged 16 and over with 0.1% of men and 0.4% of women living with severe obesity.

Overweight and obesity were previously considered as the problem of the high-income countries as two-third of the USA population are obese; they are now on the increase in low- and middle-income countries, most especially in the urban settings.[8] In Nigeria,[9] the prevalence of obesity ranges from 8.1% to 22.2%. According to Hruby and Hu, nutritional transition, sedentary lifestyle, changing methods of transportation and increasing urbanization are fuelling non-communicable diseases.[10] Poor eating habits including increased consumption of energy-dense food, high level of sugar, and saturated fats combined with physical inactivity have led to increased prevalence of overweight and obesity in many parts of the world.[11]Moreover, there is a paucity of data on Obesity and other non-communicable diseases in this part of the country. As with other developing countries worldwide, Nigeria is experiencing an epidemiological transition in the health of its adult populace. This is mainly due to the adoption of western lifestyle as well as genetic and socio-economic factors and this has led to an increase in the prevalence of Obesity

This study aims to assess the prevalence of Obesity and its risk factors in a rural community in the Niger Delta region of Southern Nigeria.

 

 

MATERIALS AND METHOD

 

This was a cross-sectional, descriptive, community-based study is to be carried out using a total of 107 adults; in Amadi-ama and Fimie communities in Port-Harcourt City Local Government Area of Rivers state, in Southern Nigeria. Approval for this study was obtained from the Ethics Committee of the Rivers State Ministry of Health, Port-Harcourt.

The participants were all apparently healthy adults aged between 20-80 years and were chosen via convenience sampling. The communities were initially sensitized about this study via town criers and church announcements and those that met the inclusion criteria were told to meet in church halls for screening. All the individuals who gave their consent were included in the study. Pregnant and lactating women as well as those who are obviously ill or wheel-chair bound were excluded from the study. Strict Covid-19 prevention protocols were adhered to.

A screening questionnaire, was given to participants and no monetary or any form of inducement was required of them.

The requirements for participation include being >18yearsof age with no previous history of hypertension or diabetes.

Anthropometric evaluation- Well trained examiners measured the anthropometric indices and participants were required to wear light, thin clothing and no shoes.

The indices are:

 

a) BMI (Body mass index is body weight/square of height, and the unit is kg/metre square.

b) Blood pressure

c) Blood sugar

d) Lipid profile

 

The body weight was measured using an analogue medical scale while the height was measured with a standard stadiometer. They were measured to the nearest 0.1kg and 0.1cm respectively.

The classes of BMI reported by WHO are ;

 

18.5-24.9kg/m2-normal

25.0-29.9kg/m2-overweight

>30kg/m2–obesity

 

Classes of obesity include: class I -30-34kg/m2

 

class II- 35-39.9kg/m2

class III- >40Kg/m2

 

Blood pressure was measured with a clinically validated electronic sphygmomanometer – OMRON digital fully automated blood pressure monitor. Values were obtained after resting for 5mins in a seated position, with 30 seconds interval between cuff inflation.

An average of 3 measurements were taken, and care was taken to select the cuff size according to the participant’s arm circumference.

Assessments were performed in a dedicated room, with optimum temperature and lightning while respecting privacy.

Blood pressure values were categorised as follows:

 

(1) Normal: <120/80mm/hg

(2) Pre-hypertension: 120-139/80-89mm/hg

(3) Stage 1: 140-159/90-99mm/hg

(4) Stage 2: > 160/100mm/hg

 

Blood measurements- Blood sugar was assessed using a glucometer and strip, after the participant’s thumb is pricked in order to get a drop of blood on the strip. While the lipid level was obtained using a 5ml syringe and needle to collect at least 5mls of venous blood into a heparin containing bottle and samples sent to the chemical pathology laboratory for analysis.

Some form of education on life style modification was also given to the participants accordingly.

Data were analysed using the IBM SPSS Version 23.0.

 

 

RESULTS

 

Socio-demographics

 

A total of 107 respondents between the ages of 23 and 80 years were screened for general and anthropometric characteristics of Obesity. Majority were females (74.8%; n=80), married (58.9%; n=63) and between 41 and 50 (37.4%; n=40). The mean age was 49.4±13.7 years. The results also revealed that 43 (40.2%) of the respondents had tertiary education, 50 (46.7%) were self-employed and 67 (62.6%) earned less than N100,000 as monthly income, which is considered low (table 1).

Table 1: Socio-demographic Characteristics

  Frequency (n=107) Percent
Age    
21-30 years 9 8.4
31-40 years 19 17.8
41-50 years 40 37.4
51-60 years 15 14.0
Over 60 years 24 22.4
Mean Age (SD) 49.4 (13.7)  
Sex    
Male 27 25.2
Female 80 74.8
Marital Status    
Single 20 18.7
Married 63 58.9
Divorced 1 0.9
Separated 3 2.8
Widowed 20 18.7
Level of Education    
Primary 27 25.2
Secondary 32 29.9
Tertiary 43 40.2
Non-formal 5 4.7
Occupation    
Self-employed 50 46.7
Unemployed 19 17.8
Student 7 6.5
Others 24 22.4
Civil Servant 5 4.7
Retired 2 1.9
Monthly Income    
Low 67 62.6
Medium 20 18.7
High 20 18.7

SD=Standard deviation

Prevalence of Obesity

The prevalence of the various components of metabolic syndrome was also accessed and it was found that 70 (65.4%) of the respondents had high blood pressure, 54 (50.5%) had raised blood sugar, 48(44.9%) had abdominal obesity, 31(29.0%) had central obesity, 18 (16.8%) had reduced high density lipoprotein cholesterol, 6 (5.6%) had raised triglyceride (table 2).

Table 2: Prevalence of Obesity in the study population

  Frequency (n=107) Percent
High blood pressure 70 65.4
Raised blood sugar 54 50.5
Abdominal obesity 48 44.9
Central obesity 31 29.0
Reduced high density lipoprotein cholesterol 18 16.8
Raised triglyceride 6 5.6

Table 3: Prevalence of Metabolic Syndrome( Obesity as a component) by Respondents’ Socio-demographics

  Metabolic syndrome p-value
  Present (n=44) Absent (n=63)    
Age group        
21-30 1 (11.1%) 8 (88.9%) 8.783 0.067
31-40 4 (21.1%) 15 (78.9%)    
41-50 20 (50.0%) 20 (50.0%)    
51-60 7 (46.7%) 8 (53.3%)    
Over 60 12 (50.0%) 12 (50.0%)    
Gender        
Male 7 (25.9%) 20 (74.1%) 3.444 0.063
Female 37 (46.3%) 43 (53.8%)    
Marital status        
Single 2 (10.0%) 18 (90.0%) 12.885# 0.009*
Married 28 (44.4%) 35 (55.6%)    
Separated 2 (66.7%) 1(33.3%)    
Widowed 11 (55.0%) 9 (45.0%)    
Divorced 1 (100.0) 0 (0.0%)    
Level of education        
Non-formal 2(40.0%) 3 (60.0%) 1.967# 0.617
Primary 9 (33.3%) 18 (66.7%)    
Secondary 12 (37.5%) 20 (62.5%)    
Tertiary 21 (48.8%) 22 (51.2%)    
Occupation        
Self-employed 23 (46.0%) 27 (54.0%) 9.422# 0.084
Unemployed 8 (42.1%) 11 (57.9%)    
Student 0 (0.0%) 7 (100.0%)    
Others 8 (33.3%) 16 (66.7%)    
Civil servant 3 (60.0%) 2(40.0%)    
Retired 2 (100.0%) 0 (0.0%)    
Monthly income        
Low 27(40.3%) 40 (58.7%) 0.153 0.926
Medium 9 (45.0%) 11 (55.0%)    
High 8 (40.0%) 12 (60.0%)    

*=Statistically significant; #=Fisher’s Exact Test

The multinomial logistic regression was used to identify significant predictors of metabolic syndrome. None of the socio-demographic variables included in model was found to significantly predict metabolic syndrome with the crude odds ratio, however, when the odds ratio was adjusted for confounders, it was found that age significantly predicted metabolic syndrome. The result showed that the odds of developing metabolic syndrome was about 7.5% less unlikely in persons between 21-30 years of age compared to those above 60 years of age (AOR=0.075, 95% CI for AOR=0.007-0.785, p=0.0.

Table 5: Association of Socio-demographics and Metabolic Syndrome(Obesity as a component)

  COR 95% Confidence Interval for COR p-value AOR 95% Confidence Interval for AOR p-value
    Lower Bound Upper Bound     Lower Bound Upper Bound  
Age group                
21-30 0.125 0.013 1.160 0.067 0.075 0.007 0.785 0.031*
31-40 0.267 0.068 1.042 0.057 0.313 0.069 1.423 0.133
41-50 1.000 0.363 2.751 1.000 1.077 0.342 3.398 0.899
51-60 0.875 0.240 3.185 0.839 0.695 0.168 2.872 0.615
Over 60 1       1      
Gender                
Male 0.407 0.155 1.069 0.068 0.371 0.123 1.119 0.078
Female 1       1      
Level of education                
Non-formal 0.698 0.106 4.607 0.709 0.617 0.075 5.088 0.654
Primary 0.524 0.193 1.422 0.205 0.358 0.118 1.087 0.070
Secondary 0.629 0.247 1.597 0.329 0.564 0.194 1.646 0.295
Tertiary 1       1      
Monthly income                
Low 1.012 0.365 2.805 0.981 0.845 0.242 2.956 0.792
Medium 1.227 0.350 4.307 0.749 1.276 0.296 5.493 0.743
High 1       1      

COR=Crude Odds Ratio; AOR=Adjusted Odds Ratio

Table 6: Frequency distribution of gender, anthropometric parameters and lipid abnormalities of study population

  Gender    
  Male (n=27) Female (n=80) ꭓ2 p-value
         
Blood pressure        
Normal 14 (51.9%) 23 (28.8%) 4.762 0.029*
High 13 (48.1%) 57 (71.2%)    
Fasting blood glucose        
Normal 14 (51.9%) 39 (48.8%) 0.078 0.780
High 13 (48.1%) 41 (51.2%)    
Waist circumference        
Normal 26 (96.3%) 33 (41.2%) 24.729 <0.001*
High 1 (3.7%) 47 (58.8%)    
BMI        
Normal 23 (85.2%) 53 (66.2%) 3.517 0.061
High 4 (14.8%) 27 (33.8%)    
High density lipoprotein cholesterol        
Normal 16 (59.3%) 73 (91.2%) 14.765 <0.001*
Reduced 11 (40.7%) 7 (8.8%)    
Triglyceride        
Normal 25 (92.6%) 76 (95.0%) 0.221 0.641
High 2 (7.4%) 4 (5.0%)    

*=Statistically significant

Table 7: Association between metabolic syndrome(BMI as a component) and Social behaviours /risk factors related to BMI of study population

  Prevalence of metabolic syndrome      
  Present (n=44) Absent (n=63) OR 95% CI

(Lower-Upper Limit)

p-value
Tobacco use          
Never smoked 41 (93.2%) 55 (87.3%) 2.235 0.533-9.370 0.272
Previous smoker 3 (6.8%) 8 (12.7%)      
Alcohol consumption          
Current drinker 10 (22.7%) 18 (28.6%) 0.957 0.354-2.591 0.931
Previous drinker 15 (34.1%) 16 (25.4%) 1.464 0.574-3.737 0.425
Never drank 19 (43.2%) 29 (46.0%)      
Fruit and vegetable consumption          
Adequate 7 (15.9%) 16 (25.4%) 0.547 0.200-1.498 0.241
Inadequate 37 (84.1%) 47 (74.6%)      
Salt consumption          
Add extra salt to meal 6 (13.6%) 10 (15.9%) 0.791 0.257-2.436 0.682
Do not add extra salt to meal 38 (86.4%) 53 (84.1%)      
Engage in physical activity          
Yes 22 (50.0%) 34 (54.0%) 0.881 0.400-1.941 0.753
No 22 (50.0%) 29 (46.0%)      
           

OR=Odds Ratio; *=Statistically significant

DISCUSSION

 

Overweight and obesity are global public health problems that cut across all ages, sex, and races.[12] Overweight and obesity negatively affect most body systems (endocrine, gastrointestinal, nervous, and cardiovascular)[18] and predispose individuals to non-communicable diseases. Complications arising from overweight and obesity create more morbidities for the dwindling population of health-care workers to manage.[13]Health risks associated with obesity include coronary heart disease and other atherosclerotic cardiovascular diseases, stroke, type 2 diabetes mellitus, high blood pressure, kidney disease, sleep apnea, osteoarthritis, gallstones, fatty liver disease, stress incontinence, and other gynecological abnormalities (amenorrhea and menorrhagia) and various cancers.[3] Sabir et al. reported obesity and increasing age are the major risk factors fueling increased prevalence of type 2 diabetes mellitus among Nigerians.[4] Dankyau et al. reported high prevalence of overweight and obesity among tertiary hospital workers in Northern Nigeria.[5] High prevalence of hypertension was reported by Owolabi et al. among health-care workers in Nigeria despite their awareness of the disease.[6] It has also been reported that increased body mass index (BMI) predisposes to certain cancers.[7]Overall , 85.2% males have normal BMI while 14.8% males have a high BMI.66.2% females have a normal BMI while 33.8% have a high BMI. The prevalence of Obesity is more in females than males in this study. 44.9% had abdominal obesity, 29.0% had central obesity, In Nigeria, the prevalence of overweight individuals ranged from 20.3%-35.1%, while the prevalence of obesity ranged from 8.1%-22.2%.

The prevalence of obesity ranges from 8.1% to 22.2%. The prevalence of obesity in this study population was found to be high and this is consistent with other studies done in Nigeria .

.This high figure may be attributed to the epidemiological transition currently being experienced in this country as well as other developing countries in Africa and beyond. There is an increase in the adoption of Western lifestyle and urbanisation characterised by physical inactivity, inadequate consumption of the traditional African diet that is rich in fruits and vegetables and high consumption of Western styled energy-rich food. This leads to obesity, hyperglycemia, hypertension ( the most common components identified in this study) and subsequent developments of other components of metabolic syndrome.Disrupted sleep pattern and chronic stress have been implicated in the causation of overweight and obesity among health-care workers as they bring about subnormal hypothalamus–pituitary–adrenal axis.[20] The biological clock is affected by disturbances in the circadian rhythms. The hypothalamus houses the suprachiasmatic nucleus which is known to generate the circadian rhythm that regulates most physiological processes such as sleep, wakefulness, body temperature, and the production of some hormones such as melatonin (hormone involved in sleep), ghrelin (hunger hormone), leptin (fullness/satiety hormone), and cortisol (stress hormone). These hormones are known to maintain healthy weight. Misalignment in circadian rhythm has been reported among shift workers.[20],[21]

In a study by Adaja T.M, et al,2018 using NIH criteria, observed that central obesity was seen in nearly two-thirds of the health-care workers. This was higher than the prevalence of central obesity (49.7%) reported by Iwuala et al.[22] We observed that female health-care workers have higher prevalence of obesity. This finding is also in tandem with our study and that of the work of Skaal and Pengpid, among South African health-care workers where female and older health-care workers were more obese than men and younger counterparts with 1 in 3 of the health-care workers suffering from obesity-related health problems.[23] In Ghana, Kasu et al. reported higher prevalence of overweight/obesity among female health-care workers as they are less involved in physical activities than their male counterparts.[24]

The prevalence of metabolic syndrome(Obesity as a component) in this study was found to be 41.1% which is quite high when compared to other studies done in Nigeria and other parts of Africa The socio-demographic factors associated with metabolic syndromeinclude age(41-50 and over 60 years), female sex, marital status (divorced and separated), civil servants, retirees, those with tertiary education has well as medium income earners. However, the only statistically significant variable associated with metabolic syndrome in this study is marital status. Divorced and separated participants have a statistically significant occurrence of metabolic syndrome. This is comparable to another study done elsewhere where it was reported that being in a high quality marriage is associated with a lower risk of metabolic syndrome25. This may be due to the fact that married people are more likely to engage in positive health behaviours than widowed, separated or divorced people26,27. It was also noted in this study that metabolic syndrome has a low prevalence in unmarried participants. Similar studies done among African Americans and also in this part of the country revealed a similar finding28,29. This is most likely because single, unmarried persons tend to be young and metabolic syndrome prevalence increases with age30. However, it may also be due to the fact that unmarried persons tend to have low prevalence of obesity which is an important component and predictor of metabolic syndrome 31.

When the odds ratio was adjusted for confounders, it was found that age significantly predicted metabolic syndrome i.e. the odds of developing metabolic syndrome was 7.5% unlikely in persons between ages 21-30 years when compared to those above 60 years of age. This finding is similar to other studies done previously28,32. This is likely due to the fact that there is a higher propensity towards hypertension, dyslipidemia and obesity in the elderly21,22,23. Also the function of the islet cells tends to decline with age33. There is also a reduction in the level of physical activity with age34. These factors contribute to the increased prevalence of metabolic syndrome in the elderly. In this study, the prevalence of metabolic syndrome is higher in females (46.3%) compared to the males (25.9%). Although this difference is not statistically significant, this difference may be attributed to the greater percentage of women with high blood pressure and increased waist circumference seen in this study which is statistically significant. Abdominal obesity is a major component and predictor of future metabolic syndrome35,36. Women are said to have a higher HDL cholesterol in comparison to men partly due to the fact that they (women) respond to dietary ingestion of cholesterol and fats with a greater increase in HDL cholesterol than men37. The prevalence of overweight and obese individuals in Nigeria is of epidemic proportions. There is a need to pay closer attention to combating these health disorders.

 

 

CONCLUSION

The prevalence of overweight and obesity in a rural setting in Port Harcourt is high. These apparently healthy adult population might be at risk of noncommunicable diseases. Hence, there is a need for advocacy on therapeutic lifestyle modification among the population.The commonest components of metabolic syndrome identified study this are hypertension, hyperglycaemia and abdominal obesity. More so, obesity should be viewed as a disease rather than risk factor for other diseases.

Limitation

The small sample size in this study is a major limitation factor. The findings, therefore should be confirmed with a much larger sample size.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 

 

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Cite this Article: Daka, IR; Amaewhule, MN; Wekhe, C (2021). The Prevalence of Obesity in a Rural Setting in Port Harcourt, Rivers State. Greener Journal of Medical Sciences, 11(2): 149-158.

 

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