Prevalence and Determinants of Obesity among Workers in Lomé (Togo)
M.P. N`cho Mottoh,
Obesity is increasing throughout the world, particularly in low- and middle-income populations, leading to an increase of cardiovascular diseases rates, suggesting more primary prevention programs in these populations. However, there are few data on this risk factor in our country. This cross sectional survey aimed to determine the prevalence of obesity and its risk factors among workers in Lomé. A questionnaire was filled out on the life style and the anthropometric data and blood pressure were taken in all the respondents. Plasma total cholesterol and fasting glucose have also been measured. The prevalence of obesity (Body Mass Index (BMI)>30 kg m-2) was 30.6% and that of abdominal obesity was 39.4%. Being female (p<0.0001), low education level (OR = 2.45 95% CI: 1.78-4.55, p = 0.001) and lack of physical activity (OR = 3.57 95% CI = 2.34-9.67, p = <0.001) were the main factors significantly associated with obesity. BMI was positively correlated to age (r = 0.145, p = 0.0004), diastolic blood pressure (r = 0.10, p = 0.013) and waist circumference was positively correlated to age (r = 0.381, p<0.0001), systolic blood pressure (r = 0.289, p = 0.0001) and diastolic blood pressure (r = 0.194, p<0.0001), but there was no correlation between anthropometric data and total serum cholesterol and fasting glucose. The prevalence of obesity was high in the workers population of Lomé especially in female and is associated with low education level and lack of physical activity.
to cite this article:
F. Damorou, K. Yayehd, M.P. N`cho Mottoh, T. Tcherou, E. Ehlan, N.W. N`da and F. Randrianarisoa, 2013. Prevalence and Determinants of Obesity among Workers in Lomé (Togo). Research Journal of Cardiology, 6: 19-27.
Received: March 07, 2012;
Accepted: June 08, 2012;
Published: July 15, 2013
According to the American Heart Association, obesity is an independent cardiovascular
risk factor. Obesity is epidemic and its prevalence is increasing worldwide
(Lopez-Jimenez et al., 2006). WHO estimated that
there are more than 1.1 billion adults overweight in the world and related a
rapid rising of obesity in low- and middle-income populations concerning more
than 115 million people suffering from obesity-related problems (WHO,
Several prospective epidemiological studies have shown a relationship between
overweight and cardiovascular morbidity and mortality and total mortality (McGee,
2005; Ford et al., 2002; Hu
et al., 2004). Overweight is associated with a cluster of metabolic
and cardiovascular risk factors (Haslam and James, 2005;
Veghari and Golalipour, 2007) and there is evidence
link between obesity and the risk for cardiovascular diseases (CVD) (Eisenmann
et al., 2005; Poirier et al., 2006;
Badaruddoza et al., 2011), glucose intolerance
and type 2 diabetes mellitus (Kopelman, 2000; Afoakwah
and Owusu, 2011), cancer occurring and asthma (Batty
et al., 2005; Calle et al., 2003;
Mathew et al., 2009), premature mortality (Adams
et al., 2006) and health service costs (Maaten
et al., 2008). Unhealthy lifestyle including dietary intake and lack
of physical activity has been incriminated in several studies as possible causal
factors in developing countries (Gonzalez-Suarez et al.,
2009; Suleiman et al., 2009; Veghari
and Golalipour, 2007).
In Togo, there are few data on the prevalence of obesity in the population hence, the interest of this study. The aim of the present study was to determine the prevalence of obesity and its relationship with other risk factors among workers in Lomé.
MATERIALS AND METHODS
This cross sectional survey was performed among 207 employees of a governmental institution (ministry of agriculture) and 303 market workers in Lomé, between September 1st and October 14, 2011.
Data collection and procedures: Data have been collected by a medical
team composed of three doctors and six nurses. The interview lasted average
10 min per person. A questionnaire has been filled out on the lifestyle (tobacco
smoking, lipids and fatty foods, regular exercise) and educational status. Weight
and height were measured using an adult hospital lever balance with participants
wearing light clothing and no shoes or extra articles. The Body Mass Index (BMI)
of Quetelet was calculated using weight in kilogram divided by the square of
the height in meter. The BMI was classified using the WHO classification of
BMI. The respondents were classified in four groups: the thin respondents with
BMI<18.5 kg m-2, respondents with normal weight if the BMI comprised
between 18.5 and 24.9 kg m-2, overweight respondents in which the
BMI was between 25 and 29.9 kg m-2 and obese respondents having a
BMI≥30 kg m-2. The severity of obesity was stratified in three
stages: Moderate obesity with BMI ranging between 30 and 34.9 kg m-2,
mild obesity for BMI ranging between 35 and 39.9 kg m-2 and morbid
obesity for BMI≥40 kg m-2 (WHO, 2000).
Waist circumference was measured midway between the iliac crest and the lower
most margin of the ribs with bare belly and at the end of normal expiration
and the hip girth was measured at the intertrochanteric level according to the
WHO guidelines. The waist circumference of >88 cm for females and
102 cm for male respondents were considered abnormal (Expert
Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults,
The supine blood pressure in both two arms was measured by a nurse using a
manual sphygmomanometer, twice after 10 min rest using appropriate cuff size
and Accoson brand of mercury sphygmomanometer (Mancia et
al., 2007). Systolic Blood Pressure (SBP) and Diastolic Blood Pressure
(DBP) were the first and fifth Korotkoff sounds, respectively. The mean of three
readings, five minutes apart, was determined. Hypertension was defined as SBP
greater than or equal to 140 mmHg and/or DBP equal to or greater than 90 mmHg.
The Joint National Committee 7 (JNC 7) classification was used to stratify this
populations blood pressure (Chobanian et al.,
Smoking was defined as the fact to smoke at least one cigarette per day. The education level was categorized in the following way: Illiterate, primary school, secondary school and university level. Less than secondary school has been consider as low education level.
Lipids and fatty foods (Consumption more than twice a week of the following foods: groundnut sauces, palm nut sauces, cracklings, bad quality oil, butters, fast-foods) and regular exercise were checked.
Blood samples were taken during fasting. Serum total cholesterol and fasting glucose were measured in all the respondents. High levels were defined for a total serum cholesterol >200 mg dL-1 and a fasting glucose >110 mg dL-1.
Ethical considerations: Consent was required and obtained after clear explanations on the objectives of this study according to the declaration of Helsinki. Each respondents answers and medical data were kept confidential. After the screening, councils have been provided to all the respondents and some of them were referred to the hospitals.
Data analysis: Continuous variables are presented as the Mean±SD and categorical variables are presented as the number and its corresponding percentage. The χ2 test was used for categorical variables and the ANOVA test or t-test for continuous variables. Correlation coefficients were determined by linear regression to assess the relationship between anthropometric data, age, blood pressure, plasma total cholesterol and fasting glucose.
Odds Ratios (OR) and 95% confidence intervals (95% CI) were calculated using
a logistic regression analysis. The p-values<0.05 were considered to be statistically
significant. All statistical analyses were performed using the Center of Diseases
Control (CDC) Epi-Info version 7 software.
Table 1 shows the characteristics of the respondents according to the profession. There was no significant difference between mean age of two professional groups (p = 0.78). There was a female prevalence in the market workers (242 women vs. 61 men, sex ratio: 0.25) whereas, one noted a male prevalence in the governmental institution (68 women vs. 139 men, sex-ratio: 2.04). Secondary school has been achieved by 178 (86%) employees in the ministry vs. 62 (20.5%) market workers, p<0.0001, 85.7% of workers had fatty foods and 9.0% of them did regular exercise.
|| Characteristics of the respondents according to the profession
|Data are in n (%) otherwise precise, BMI: Body mass index,
WC: Waist circumference, HBP: High blood pressure
The prevalence of HBP was 36.3% and smoking was exclusively seen in male (2.9%). Among the overweight 151 respondents, there was a non significant male prevalence (34.5% in male vs. 26.4% in female, p = 0.05). We noticed a female prevalence among obese workers (6.5% in male vs. 46.1% in female, p<0.0001) and also a high female prevalence for abdominal obesity (57.7% in female vs. 11% in male, p<0.0001). There was no gender difference in mean plasma cholesterol (174±69.6 mg dL-1 in female vs. 166.4±79.3 in male, p = 0.25) and fasting glucose (65.5±19.6 in female vs. 71.6±48.1 in male, p = 0.127) (Table 2).
The prevalence of obesity increased from low age to high ages with two picks (Fig. 1): The first pick at 35-44 years (34.3%) and the second one at 55-64 years (40%).
Table 3 shows the correlation coefficients between anthropometric
data and other risk factors. There was a positive correlation between anthropometric
data and age (BMI: r = 0.145, WC: r = 0.381), DBP (BMI: r = 0.10, WC: r = 0.194);
only WC showed a positive correlation with SBP (r = 0.289, p = 0.0001). There
was no correlation between anthropometric data and serum total cholesterol (BMI:
r = 0.020; WC: r = 0.034) and fasting glucose (BMI: r = 0.027; WC: r =
0.003). Low education level (OR = 2.45; 95% CI: 1.78-4.55, p = 0.001)
and lack of physical activity (OR = 3.57; 95% CI = 2.34-9.67, p = <0.001)
were the main factors significantly associated with obesity; logistic regression
shows a strong association between HBP (high blood pressure) and WC (OR = 2.36;
95% CI: 1.41-3.94, p = 0.001); this difference persisted after adjusting for
age and sex (Table 4); contrary there was no association with
high cholesterol (OR = 0.43 95% CI: 0.24-0.75, p = 0.003) and fasting glucose
(OR = 1.32 95% CI: 0.23-7.34, p = 0.75).
|| Characteristics of the respondents according to gender
|BMI: Body mass index, WC: Waist circumference, Data are in
n (%) otherwise they are precise
|| Prevalence of overweight and obesity in different age-groups,
p = 0.07
|| Odds ratios between WC and conventional risk factors
|*Odds ratios adjusted for age and sex
This cross sectional survey was performed in two significant professional groups of the economy of the municipality of Lomé: There was a female prevalence among the market workers but a male prevalence among the employees of the governmental institution; this reflects a real contrast in our country where women are generally less educated and then are few in civil services. Thus, nearly 80% of women in the market had an educational level lower than secondary school. There was no significant difference between the average ages of the respondents of these two activity sector. The frequency of obesity was 30.8% with a significant female prevalence, p<0.0001 and that of abdominal obesity was 39.4% with also a significant female prevalence.
The prevalence of obesity was high in this survey. Globally, the prevalence
of obesity ranges from as low as 0.6% in Gambia among males to as high as 80.2%
in Nauru. Among females, obesity ranges from 0.2% in Ethiopia to 78.6% in Nauru
(Krause et al., 1998; WHO,
2011). In western countries, about two thirds of adults in the United States
and United Kingdom are overweight or obese and at least one quarter is obese
(Spiegel and Alving, 2005; Sniehotta
et al., 2011).
In a recent study in the households of Dar Es Salam in Tanzania, obesity was
present in 19.2% of the cases (Shayo and Mugusi, 2011)
with a strong female prevalence, p<0.001; some studies reported that increasing
age, female sex, lack of physical activity (Suleiman et
al., 2009; Shayo and Mugusi, 2011), marriage,
high socioeconomic status (Shayo and Mugusi, 2011) increase
the likelihood for obesity in their population. However, Suleiman
et al. (2009) related a high prevalence of obesity among lower monthly
income populations in Jordanian.
In this study, we observed a strong prevalence of obesity in low educational
level people where obesity is often perceived like a sign of ease. Moreover,
WHO describes obesity as one of the most blatantly visible, yet most neglected
public-health problems that threaten to overwhelm both more and less developed
countries (WHO, 2000); so, obesity have achieved global
recognition as health problems only during the past 10 years, contrary to malnutrition
and infectious diseases, which have always dominated thinking (WHO,
Contrary to that observed in high-income populations and where obesity is becoming
more prevalent among young people and teenagers, the present survey performed
in a low-income country (Togo) highlighted a high prevalence of obesity among
adults. Thanks to the epidemiological transition, increased longevity and the
impact of smoking, high-fat diets and other risk factors for chronic diseases
have now combined to make CVD and cancer the leading causes of death in most
countries. These changes began in higher income populations, but as they gradually
spread to low- and middle-income countries, CVD mortality rates have increased
globally (Gaziano and Gaziano, 2011).
However, some studies related a downward in the trends of obesity in high-income
populations this last decade; as a result, Flegal et
al. (2010) reported that in 2007-2008, the prevalence of obesity was
32.2% among adult men and 35.5% among adult women and that the increases in
the prevalence of obesity previously observed do not appear to be continuing
at the same rate over the past 10 years, particularly for women and possibly
for men. But China, once considered one of the leanest populations in the world,
has experienced rapidly escalating rates of overweight and obesity (Shen
et al., 2012); then, a recent meta-analysis of nationally representative
data by Wang et al. (2006) estimated that the
prevalence of overweight and obesity rose 49.5% between 1992 and 2002, from
20.0 to 29.9%.
In our survey, obesity was positively correlated to age, gender (female), low
educational level and blood pressure. Many other studies reported a strong correlation
between obesity and blood pressure (Afoakwah and Owusu,
2011; Mahajan et al., 2009). Thus, according
to a study performed in Finnish population, Hu et al.
(2004) showed that the risk of CVD associated with obesity was partly mediated
through other risk factors, such as blood pressure, blood lipid and diabetes,
in women particularly and that all obesity indicators predicted the risk of
CVD in men, but in women only BMI had an independent association after adjustment
for the obesity-related risk factors. However, Ulasi et
al. (2011) reported a negative correlation between anthropometric data
and blood pressure in a market population in Nigeria.
Generally, according to the WHO, smoking and lipid consumption are increasing
in our low- and middle-income populations because of aggressive campaigns publicities
led by tobacco firms and the increasing of availability of unhealthy vegetable
oils, fatty and red meat at low cost, making obesity to become one of the main
burden problem to which developing countries will face in next decades (Yusuf
et al., 2001; Mackay and Mensah, 2004).
Limitation of the study: This study was performed among workers population of Lomé, the extension of these results to the whole of the Togolese workers population must be relative because 60% of this population fringe is rural. The diagnosis of hypertension was based on a mean of three blood pressure measurements at one sitting and this may have affected the overall prevalence of hypertension in this study.
The prevalence of obesity was high among workers in Lomé and was correlated
with female sex, age, low education level and high blood pressure. The fight
against obesity in our context will have to pass by a better schooling of the
female population and the sensitizing on the diet, whose focal point will have
to be a reinforcement of the national program of fight against obesity and cardiovascular
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