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Overnutrition and associated factors among adults aged 20 years and above in
fishing communities in the urban Cape Coast Metropolis, Ghana
Article  in  Public Health Nutrition · May 2012
DOI: 10.1017/S1368980012002698 · Source: PubMed
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Public Health Nutrition: 16(4), 591–595 doi:10.1017/S1368980012002698
Overnutrition and associated factors among adults aged
20 years and above in fishing communities in the urban
Cape Coast Metropolis, Ghana
Kingsley KA Pereko1,*, Jacob Setorglo2, William B Owusu3, Joyce M Tiweh4 and
Emmanuel K Achampong5
1Department of Community Medicine, School of Medical Sciences, University of Cape Coast, Cape Coast,
Ghana: 2Department of Biochemistry, School of Medical Sciences, University of Cape Coast, Cape Coast,
Ghana: 3Department of Nutrition and Food Science, University of Ghana, Accra, Ghana: 4Department of
Ophthalmology Komfo Anokye Teaching Hospital, Kumasi, Ghana: 5Department of Medical Education,
University of Cape Coast, Cape Coast, Ghana
Submitted 16 December 2010: Final revision received 16 February 2012: Accepted 17 April 2012: First published online 29 May 2012
Abstract
Objective: The study aimed to highlight the determinants of overnutrition
(overweight plus obesity) in fishing communities and establish if these were the
same as reported elsewhere in Ghana.
Design: Cross-sectional study.
Setting: The study was conducted in Idun, Ola and Duakor fishing communities
in Cape Coast, Ghana.
Subjects: Adults (n 252) aged 20 to 50 years.
Results: Results showed that 32 % of participants were overweight/obese (BMI $
25?0 kg/m2). Participants’ mean age was 31?7 (SD 1?0) years, they had 13?7 (SD 8?1)
mean years of formal education, their median monthly income was $US 7?4
(interquartile range $US 3?3, 20?0) and their median daily energy intake was
7?3 (interquartile range 5?3, 9?8) MJ. Significant associations (P, 0?05) were
found between BMI and gender, age, years of education, fat intake and marital
status. Females were almost eight times more likely to be overweight/obese
than males (adjusted OR5 7?7; 95 % CI 3?6, 16?4). Persons aged $40 years were
about six times more likely to be overweight/obese than those aged 20–29 years
(adjusted OR5 6?1; 95 % CI 2?6, 14?1). Married people were nearly three times
more likely to be overweight/obese than singles (adjusted OR5 2?8; 95 %
Cl 1?4, 5?7). People with more than 13 years of formal education (adjusted
OR5 0?3; 95 % CI 0?1, 0?9) and people with .30 % fat contribution to daily Keywords
energy intake (adjusted OR5 0?3; 95 % CI 0?1, 0?6) had reduced odds of being Overnutrition
overweight/obese. Macronutrient
Conclusions: Overnutrition was prevalent in the fishing communities and associated Formal education
with factors such as age, gender, marital status, educational status and fat intake. Energy
Overnutrition, a major public health issue of the devel- mellitus, hypertension, dyslipidaemia, coronary artery dis-
oped world, is a growing menace in the developing eases and some cancers(1,4). Seidell(5) found obesity to be
world already burdened with undernutrition and infec- 1?5–2?0 times higher in women than men from countries
tious diseases(1). Gupta and Kockar(2) indicate obesity to with low gross national product. Studies in adolescents have
be one of the most neglected public health problems found an association of BMI with gender, ethnicity and food
according to WHO. Hajian-Tilaki and Heidari(3) state that habits. In other studies, obesity has been found to be higher
obesity is an undesirable outcome of changing lifestyles among married women than unmarried(6). Socio-economic
and behaviours. Overnutrition is an emerging problem in status has been found to have an inverse relationship with
segments of Sub-Saharan African society particularly where obesity in the developed world; however, the opposite
lifestyles have become urbanized and Westernized(4). The is the case in the developing world(7). Work by Amoah(8) in
issue of overnutrition has become very important as a result urban and rural Accra, Ghana showed crude prevalences of
of its debilitating effect on health. Obesity increases the risk overweight and obesity of 23?4% and 14?1%, respectively,
for many serious and morbid conditions, such as diabetes among adults aged 25 years and above. Females recorded
*Corresponding author: Email kpereko@gmail.com r The Authors 2012
592 KKA Pereko et al.
higher rates than males. Obesity increased with age and UNISCALE (UNICEF electronic scale 890) and a UNICEF
the rate was found to be higher among urban high-class adult microtoise (UNICEF, Copenhagen, Denmark),
residence compared with low-class residence and in respectively, which were calibrated to ensure accuracy of
urban compared with rural locations. Individuals with the measures. Weight was measured with the participants
higher educational status recorded higher prevalence in light clothing, with the scale on a level stable surface,
than those with lower education. A study in Accra involving to the nearest 0?1 kg. Participants were weighed while
Ghanaian civil servants found obesity prevalence of 10% standing unsupported, bare footed and looking forward,
among males and 36% among females(9). However, the with their hands by their side, and were not holding any
subject of obesity in Ghana receives much less attention metallic or other object that could influence the SECA
than it deserves despite the growing menace(10). The scale. Weight measurements were read only when the
present study aimed to highlight the determinants of digital reader was stable. Height of the participants in
overweight in three fishing communities to establish if bare feet was measured to the nearest 0?5 cm using a
these were the same as those reported elsewhere in standard microtoise. In measuring height, the head bar of
Ghana. The specific objectives were to: (i) examine the the microtoise was placed securely on the floor and the
participants’ sociodemographic characteristics (such as tape fully drawn. The free end was secured with a nail to
gender, occupation, marital status and years of educa- a suitable vertical surface above the head bar. The head
tion); (ii) assess their BMI and the dietary intake; and (iii) bar was then raised above the height of the participant,
determine the associations between sociodemographic who was instructed to stand upright directly below the
characteristics, dietary intake and BMI. point of attachment and positioned such that the Frank-
fort plane of his/her head was horizontal. The participant
was instructed to inspire and to hold his/her breath while
Methodology the head bar was lowered to the crown of the head, and a
direct height reading in centimetres was taken. This was
The present study was a cross-sectional one involving all administered by the interviewer.
252 adults aged 20 to 50 years from the fishing commu- Using the WHO reference for BMI, participants were
nities of Ola, Duakor and Idun of the Cape Coast classified into the following categories: BMI,18?5 kg/m2
metropolis in Ghana. These communities had a total (thin), BMI5 18?5–24?9 kg/m2 (normal weight), BMI5
population of 10 708, comprising 7375, 1039 and 2294, 25?0–29?9 kg/m2 (overweight) and BMI$ 30?0 kg/m2
respectively(11). Given an adult population size of 10 708 (obese)(13). In the present paper, ‘overnutrition’ is taken
in the three communities and an expected frequency of to include overweight and obesity (BMI$ 25?0 kg/m2).
23?4 % urban adult overweight and obesity prevalence, Occupation of the participants was classified into sedentary
with worst acceptable frequency of 28?6 % at 95 % con- and manual. For the study purposes, those who by their
fidence interval, a sample size of 249 was needed for the occupation spend more than five out of eight working
study (Epi Info version 3?5?1; Centers for Disease Control hours in the day moving or doing manual work were
and Prevention, Atlanta, GA, USA). From the total popu- considered physically active, while sedentary participants
lation of the chosen communities, weighting was used to were those who spend more than five out of the eight
estimate the number of participants required from each working hours in a day sitting or not doing manual work.
community. Based on the weighting, eighty-one, eighty- The data were entered and analysed using the IBM
four and eighty-seven participants were randomly chosen SPSS version 20?0 statistical software package (IBM Corp,
from Ola, Duakor and Idun, respectively. Healthy-looking Armonk, NY, USA). A nutrition database (ESHA Food
adults who self-reported absence of any ailment were ProcessorR 6?02(14)) and the Ghanaian food composition
included in the study while pregnant women and ill table(15) were used in estimating nutrient intakes. Means,
persons were excluded. A multistage sampling procedure standard deviations and ranges were calculated for con-
was used. This involved the random selection of three tinuous variables, while frequencies and proportions
out of four fishing communities in the urban metropolis. were calculated for categorical variables. The associations
Systematic random sampling was used to select the houses between demographic factors, dietary intake and BMI were
in the communities. If there was more than one household assessed using the x2 test and logistic regression technique.
in the same house, simple random sampling was used Differences in means among males and females were
to select a respondent. Data were collected on socio- determined using the independent-samples t test.
demographic factors using a semi-structured questionnaire
and on dietary intake using a 24h recall questionnaire.
The 24h dietary recall was conducted on one weekend and Results
two weekdays for each of the respondents.
Data on anthropometry were collected following a In all 252 adults participated in the present study, of
standard protocol by taking two repeated measures(12). whom 40?1% were male and 59?9% were female (Table 1).
Weight and height measures were taken using a Participants’ mean age was 31?7 (SD 1?0) years and they had
Overnutrition and associated factors 593
Table 1 Descriptive statistics (demographic characteristics, anthropometric measures) of the study population: adults aged 20 to 50 years
from three fishing communities in the urban Cape Coast metropolis, Ghana
Males (n 101) Females (n 151) Both sexes (n 252)
Mean SD Range Mean SD Range Mean SD Range
Age (years) 31?6 8?1 20?0–51?0 31?7 8?9 20–50 31?7 1?0 20–51
Years of education 8?4 4?4 0?0–22?0 7?8 4?4 0?0–19?0 13?7 8?1 0?0–22?0
Weight (kg) 65?9 8?2 48?2–89?0 65?4 14?8 39?0–111?8 65?6 12?6 39?0–111?8
Height (m) 1?7 0?1 1?0–2?0 1?6* 0?1 1?2–1?8 1?6 0?1 1?0–2?0
BMI (kg/m2) 23?3 6?6 17?8–29?9 25?8* 6?1 18?7–27?1 24?8 6?4 17?8–29?9
*Mean values were significantly different from those of males (independent-samples t test): P, 0?05.
Table 2 Descriptive statistics (income, dietary intake) of the study population: adults aged 20 to 50 years from three fishing communities in
the urban Cape Coast metropolis, Ghana
Males (n 101) Females (n 151) Both sexes (n 252)
Median IQR Median IQR Median IQR
Monthly income ($US) 10?0 6?7, 22?2 6?7 3?3, 20?0 7?4 3?3, 20?0
Energy (kJ) 9?0 6?8, 11?2 6?5 4?7, 8?7 7?3 5?3, 9?8
% of energy from fat 22?0 14?0, 34?5 24?0 15?0, 36?6 23?0 14?3, 36?0
% of energy from protein 11?0 10?0, 14?0 12?0 10?0, 14?6 12?0 10?0, 14?0
% of energy from carbohydrate 67?0 53?5, 74?0 61?0 51?0, 71?0 62?0 52?0, 72?0
IQR, interquartile range.
13?7 (SD 8?1) mean years of formal education. Mean BMI of Discussion
24?8 (SD 6?4) kg/m2 was recorded for both sexes. Females
had a significantly higher mean BMI (25?8kg/m2) than In Ghana, studies show that overnutrition is gradually
males (23?3kg/m2). becoming an important issue following the increasing
The median monthly income of the participants was prevalence of overweight and obesity in most parts of the
$US 7?4 (interquartile range (IQR) $US 3?3, 20?0; Table 2). country. Information on the situation will be an important
The participants’ median energy intake was 7?3 (IQR 5?3, element for early management and prevention of over-
9?8) MJ and the median percentage contributions of weight and obesity to avert its health-debilitating effects.
macronutrients to daily energy intake were 23?0 (IQR Work by Amoah(8) found an overweight prevalence of
14?3, 36?0) % for fat, 12?0 (IQR 10?0, 14?0) % for protein slightly over 23 % in the urban population. The present
and 62?0 (IQR 52?0, 72?0) % for carbohydrate (Table 2). study, however, found about 32 % overnutrition pre-
The results indicated an overweight/obesity prevalence valence among the study population in the urban fishing
of 32% (Table 3). More females (45?7%) than males community. Factors that were found to be associated with
(13?9%, P, 0?05) were found to be in the overweight/ this phenomenon were age, marital status, gender, years
obese category. A significant difference in the propor- of formal education and dietary fat intake.
tion of overweight/obesity was found between married Age was found to be associated with overnutrition; the
persons (20?3%) and singles (45?0%, P, 0?05; Table 3). present study indicated 2?3 times increased odds of
Females were almost eight times more likely to be overweight/obesity among people aged 30–39 years
overweight/obese than males (adjusted OR5 7?7; 95 % CI compared with those aged 20–29 years and a 6?1 times
3?6, 16?4; Table 4). People aged $40 years were about six increased likelihood for persons aged $40 years. This
times more likely to be overweight/obese than those confirms van der Sande et al.’s(4) study that recorded
aged 20–29 years (adjusted OR5 6?1; 95 % CI 2?6, 14?1; higher obesity prevalence among women aged .35 years.
Table 4). Married people were almost three times more Biritwum et al.(10) and Beltaifa et al.(16) also found
likely to be overweight/obese than singles (adjusted increasing obesity prevalence with increasing age. The
OR52?8; 95% Cl 1?4, 5?7; Table 4). Compared with 13 years present study found an association between marital status
of education or less, participants with more than 13 years of and overweight, with married persons being 2?8 times
education were 70?0% less likely to be overweight/obese more likely to be overweight/obese compared with
(adjusted OR50?3; 95% CI 0?1, 0?9; Table 4). Participants unmarried persons. This result affirms studies by Biritwum
with .30% contribution to daily energy intake from fat et al.(10) and Rguibi and Belahsen(6). Females were
were 70?0% less likely to be overweight/obese (adjusted 7?7 times more likely to be overweight/obese than males
OR50?3; 95% CI 0?1, 0?6; Table 4) than those with #30% of in the present study and this confirms findings by van der
daily energy intake from fat. Sande et al.(4) and Biritwum et al.(10) who reported similar
594 KKA Pereko et al.
Table 3 Demographic characteristics and dietary intake according to overweight/obesity status: adults aged 20 to
50 years from three fishing communities in the urban Cape Coast metropolis, Ghana
Not overweight/obese Overweight/obese
(BMI,25?0 kg/m2) (BMI$ 25?0 kg/m2)
n % n %
Total sample 169 67?1 83 32?9
Gender
Male 87 86?1 14 13?9*
Female 82 54?3 69 45?7*
Monthly income ($US)
#10 62 59?6 42 40?4
.10 60 65?2 32 34?2
Occupation
Sedentary 79 63?2 46 36?8
Manual 90 70?9 37 29?1
Marital status
Single 98 79?7 25 20?3*
Married 71 55?0 58 45?0*
Years of education
#13 139 64?1 78 35?9*
.13 29 85?3 5 14?7*
% contribution of fat to daily energy intake
#30 95 60?5 62 39?5*
.30 74 77?9 21 22?1*
% contribution of carbohydrate to daily energy intake
#60 38 67?9 18 32?1
.60 131 66?8 65 33?2
% contribution of protein to daily energy intake
#20 164 68?0 77 32?0
.20 5 45?5 6 54?5
*Proportions were significantly different from those in the not overweight/obese group (x2 test): P, 0?05.
Table 4 Logistic regression coefficients and 95% confidence According to van der Sande et al.(4), nothing can be done
intervals for predictor variables of overnutrition (BMI$25?0 kg/m2): about the age and sex susceptibility but lifestyle modifica-
adults aged 20 to 50 years from three fishing communities in the (8)
urban Cape Coast metropolis, Ghana tions are possible. Contrary to Amoah’s and Biritwum
et al.’s(10) finding of increasing obesity prevalence among
R 2 (0?29)
persons with higher education, the present study found
Variable OR 95% CI reduced odds of overweight/obesity among persons with
Age (years) higher education compared with those having basic or no
20–29 1?0 (ref.) formal education. This could be attributed to the fact that
30–39 2?3 1?1, 5?1 more highly educated persons are aware of the negative
$40 6?1 2?6, 14?1
Sex consequences of being overweight such as the develop-
Male 1?0 (ref.) ment of chronic diseases, and hence take measures to
Female 7?7 3?6, 16?4 prevent it. In their study of obesity among adults aged 20 to
Years of formal education
#13 1?0 (ref.) 70 years, Hajian-Tilaki and Heidari
(3) also found an inverse
.13 0?3 0?1, 0?9 relationship between the risk of obesity and high level of
Marital status education. Beltaifa et al.(16) indicated a higher prevalence
Single 1?0 (ref.)
Married 2?8 1?4, 5?7 among women with intermediary educational status. Per-
% contribution of fat to daily energy sons whose fat intake contributed .30% of daily energy
intake intake were found less likely to be overweight/obese in the
#30 1?0 (ref.)
.30 0?3 0?1, 0?6 present study. This could possibly be attributed to the
occupation they undertake. Males found to consume more
ref., reference category. fat probably undertake energy-demanding activities, hence
The regression coefficient for the entire model; R 25 0?21.
accounting for the observation.
results. Females have a greater physiological propensity
to become obese than males. Coupled with the sedentary Conclusions
occupations of women in the area, they have a greater
chance to become overweight/obese than males who Overweight and obesity was prevalent in fishing commu-
engage in energy-demanding activities such as fishing. nities in the Cape Coast urban metropolis, Ghana. Factors
Overnutrition and associated factors 595
such as age, gender, marital status, education and fat intake aged 20–70 years, in the North of Iran. A population-based
were associated with overnutrition in this community. study and regression approach. Obes Rev 8, 3–10.
4. van der Sande MAB, Caesay SM, Milligan PJM et al. (2001)
Further prospective research is recommended for assessing
Obesity and undernutrition and cardiovascular risk factors
the factors accounting for overweight and obesity. Health in rural and urban Gambian communities. Am J Public
education on healthy lifestyles is recommended. Health 91, 1641–1644.
5. Seidell JC (2005) Epidemiology of obesity. Semin Vasc Med
5, 3–14.
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This research received no specific grant from any funding Epidemiol Rev 29, 29–48.
agency in the public, commercial or not-for-profit sectors. 8. Amoah AG (2003) Obesity in adult residents of Accra,
There are no conflicts of interest. The authors’ contribu- Ghana. Ethin Dis 13, 2 Suppl. 2, 29–101.
tions are as follows: K.K.A.P., Principal Investigator; 9. Addo J, Smeeth L & Leon DA (2009) Obesity in urban civil
servants in Ghana. Association with pre-adult wealth and
J.M.T., Co-Principal Investigator; J.S., project staff training, adult socio-economic status. J Pubic Health 123, 365–370.
manuscript writing and review; W.B.O., supervisor, statisti- 10. Biritwum RB, Gyapong J & Mensah G (2005) The
cian; E.K.A., data entry, manuscript writing and review. The epidemiology of obesity in Ghana. Ghana Med J 39, 82–85.
11. Ghana Statistical Service (2002) 2000 Population and
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Housing Census. Special Report on 20 Largest Localities.
the Cape Coast Metropolitan Health Directorate and Accra: GSS.
Assembly Members of the three project communities. They 12. Ismail M & Manandhar M (1999) Better Nutrition for Elderly
also appreciate the participation of the Duakor, Idun and People. Assessment and Action, p. 71. London: HelpAge
International and London School of Hygiene and Tropical
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