Determinants of Regional Obesity (Visceral and Subcutaneous Obesity) within Cardiovascular Risk Factors in the Cardiology Department of the University Clinics of Kinshasa ()
1. Introduction
Obesity is now a real public health problem (HP) for both developed and developing countries. Obesity is epidemic worldwide affecting adults as well as children and adolescents [1]. More than half of the adult population would be overweight or obese in 2030 [2]. An increase in the prevalence of overweight and obesity has been observed in adults, this is also seen in adolescents in recent dec-ades [3]. Progress is also confirmed by some work carried out in developing countries, particularly in Africa [4] [5] [6] [7]. In the Democratic Republic of Congo (DRC), the data is patchy [8] [9] [10] [11] [12]. Obesity, especially VAT, is a cardiovascular risk factor (CVRF). It is accompanied by metabolic complica-tions including diabetes mellitus (DM) type 2, in a context of metabolic syndrome (MS) [13]. Cardiovascular risk assessment studies specify the role of vis-ceral adiposity, however, its assessment is not common practice in our country, the Democratic Republic of Congo (DRC). Obesity is a complex chronic pathol-ogy both in terms of pathophysiology and management [14]. It is a heterogene-ous disease on the phenotypic level which evolves in several phases (constitu-tion, maintenance, aggravation) whose determinants are multiple. We cannot therefore speak of a single disease, but rather of various types of obesity and medical situations. The development of fat mass is under the influence of genetic factors which are expressed as a function of environmental and behavioral fac-tors. Changes in diet and reduction in physical activity lead to an imbalance in the energy balance. There are also psychosocial and biological factors. It is most often associated with other CVRFs, in the context of (MS), hence the need for preventive measures to reduce cardiovascular risk. The objective of the present study is to research the frequency of regional obesity (by impedancemetry) as well as their determinants within the CVRF in patients followed in cardiology at the University Clinics of Kinshasa (UCK) in the DRC.
2. Material and Methods
This cross-sectional and analytical study took place over a period of 3 months (from July 1 to September 31, 2014) in the Cardiology department of the UCK (DRC). Given the absence of a prevalence, and based on the general sampling formula Ni (minimum size) ≥ (Za)2 xpx (1 − p)/(W)2 where P = prevalence (=0, 50 due to lack of data, W = range (0.05), confidence level (1 − a), a = 0.05 for 95%, Za = 1.96, sample size was calculated at 3.84 × 0.50 × 0.50/(0.05)2 = 384. By adding 10% of non-respondents, the height was estimated at ≥422.
Sampling was convenient and involved all patients followed in cardiology who voluntarily agreed to participate in the study. The parameters of interest were: demographic parameters (age, sex), intoxication parameters (alcohol and tobacco intake), hemodynamic parameters (history of hypertension, blood pressure or BP), biochemical parameters (total cholesterol or CT, HDL-cholesterol, LDL-cholesterol, glycemia) and impedancemetric parameters i.e. percentage or % of visceral obesity, subcutaneous obesity and muscle mass (MM).
Alcoholism was defined as consumption of more than 20 grams of alcohol, i.e. 2 glasses per day for women and more than 30 grams, or 3 glasses for men. [15]. Blood pressure was measured using an OMRON brand device, the values considered were the averages of the last 2 measurements (after resting for 5 minutes). Thus HBP was defined by a BP ≥ 140/90 mmHg [16].
Body composition (Visceral and subcutaneous obesity, MM) was calculated using a KARADA SCAN OMRON brand device (special scale with body composition monitor for electrical impedance) whose principle is based on bio-impedance. The device sends an extremely weak current of 50 KHz and <500 MA into the human body, in order to determine the amount of fatty tissue taking into account weight, height, age and gender. The conditions for measuring the bio-impedance were: a rest of at least 2 hours without taking anything, the scale being placed on a hard and horizontal surface, the subject in a standing position [17].
SPSS version 21 software was used for data entry and statistical analyses. Results were expressed as mean ± SD or median, with extremes depending on whether the data distribution was Gaussian or not. The comparison of the groups was made using the chi-square or Student’s t test depending on the case (proportions or means). Multivariate analysis (logistic regression) was used to find the determinants of regional obesity within the CVFR. The statistical significance threshold was set at p < 0.05. All patients who participated in the study signed the informed consent document.
3. Results
3.1. Frequency of Regional Obesity and General Patient Characteristics
Of a total of 642 patients who participated in the study, the frequency of visceral obesity was 45.5% with no significant difference (p = 0.148) between the two sexes (Figure 1).
Figure 2, on the other hand, shows a frequency of subcutaneous obesity of 60.7% with a predominance (p < 0.001) for the female sex (70.9% n = 322/454 vs. 36.2% n = 68/188).
Figure 3 shows a significant increase (p < 0.001) in the frequency of visceral obesity with increasing age and a decrease from advanced age (≥60 years).
Figure 4, on the other hand, shows a tendency for the regression of the frequency of subcutaneous obesity to see-saw with age (p < 0.001) but with a clear reduction from advanced age (≥60 years).
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Figure 1. Frequency of visceral obesity in the entire group and in both sexes.
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Figure 2. Frequency of subcutaneous obesity in the entire group and in both sexes.
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Figure 3. Frequency of visceral obesity according to age.
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Figure 4. Frequency of subcutaneous obesity according to age.
3.2. Frequency of Other Cardiovascular Risk Factors
Table 1 shows the distribution of CVRF in the entire group and in both sexes. The mean age of the patients was 57.5 ± 14.4 years. The women were older than the men (p = 0.002). The frequency of HBP was 90.7% with predominance in women (p = 0.015). The frequency of the other CVRF is described in Table 1. In general, men were more affected (p < 0.05) by tobacco and alcohol intake, CRF and subclinical atherosclerosis (ATS) while women were more affected (p < 0.05) by physical inactivity, obesity on BMI and WC.
3.3. Cardiovascular Risk Factors and Regional Obesity
Table 2 shows the distribution of CVRF according to regional obesity. Patients with visceral obesity presented higher frequencies (p < 0.05) of advanced age, smoking, HBP, DM and obesity on BMI and WC. There was no difference between the two sexes (p ≥ 0.05).
On the other hand, patients with subcutaneous obesity presented higher frequencies (p < 0.05) of tobacco use, alcohol use, physical inactivity, obesity/overweight on BMI and on WC, hypertriglyceridemia and ATS. The highest frequency of subcutaneous obesity concerned women (<0.001).
3.4. Determinants of Regional Obesity within CVRF
3.4.1. Visceral Obesity
Table 3 shows that in univariate analysis, age ≥ 60 years, smoking, HBP, DM, obesity/BMI and abdominal obesity/WC emerged as determinants of visceral obesity. After adjustment (multivariate analysis), advanced age, smoking, obesity on BMI had emerged as independent determinants of visceral obesity. Thus advanced age has multiplied the occurrence of visceral obesity by 2, smoking by 2, obesity on BMI by 4 and obesity on WC by 2.
3.4.2. Subcutaneous Adipose Tissue (SAT) Fat Mass
For subcutaneous obesity, age ≥ 60 years, female gender, alcohol intake, physical inactivity, obesity/BMI, overweight, abdominal obesity/WC, and hypertriglyceridemia had emerged as determinants (univariate analysis). After adjustment (multivariate analysis), advanced age, female gender, alcohol intake, obesity/overweight on BMI, obesity on WC and hypertriglyceridemia were independently associated with the occurrence of subcutaneous obesity. Thus advanced age multiplied the occurrence of subcutaneous obesity by 4, alcohol intake by 0.3, obesity on BMI by 16, overweight on BMI by 11, obesity on WC by 4 and hypertriglyceridemia of 4 (Table 4).
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Table 1. Distribution of cardiovascular risk factors in the entire group and in both sexes.
Abbreviations: HBP = High blood pressure, DM = Diabetes mellitus, CRF = Chronic renal failure, BMI = body mass index, WC = waist circumference, PP = pulse pressure, ATS = sub-clinical atherosclerosis.
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Table 2. Cardiovascular risk factors and regional obesity.
Abbreviations: HBP = High Blood Pressure, DM = Diabetes mellitus, CRF = Chronic renal failure, BMI = body mass index, WC = waist circumference, PP = pulse pressure, ATS = sub-clinical atherosclerosis.
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Table 3. Factors associated with visceral obesity within CVRF.
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Table 4. Factors associated with subcutaneous obesity within CVRF.
4. Discussion
The main results of the present study are as follows: regional obesity (visceral and subcutaneous obesity) was frequent in current practice without gender distinction for visceral obesity but with a female predominance for subcutaneous obesity. Advanced age, tobacco use, alcohol use, physical inactivity, hypertension, DM and CRF were the CVRF found alongside regional obesity. Among these CVRF, the determinants of regional obesity were advanced age, smoking and obesity on BMI for visceral obesity; advanced age, female gender, alcohol intake and obesity on BMI and WC as well as hypertriglyceridemia for subcutaneous obesity.
4.1. Prevalence of Regional Obesity
The present study found frequencies of visceral and subcutaneous obesity of 45.5% and 60.9% respectively. BMI is an indicator usually used in the evaluation of obesity and a guide for population monitoring of weight, but it is an imperfect indicator in the study of the regional distribution of obesity. [18] [19] [20] [21]. It does not provide any information on the distribution of adiposity in individuals. The prevalences of obesity on high BMIs therefore relate only to global and not regional obesity [22] [23]. These prevalences reach 39.6% in adults and 18.5% in children. Thus, additional anthropometric measurements such as the WC prove useful in order to identify individuals characterized by an accumulation of abdominal fat that is especially harmful to health. Indeed, several large-scale epidemiological studies have shown that waist circumference is more closely associated than BMI with the risk of developing chronic diseases such as type 2 diabetes and cardiovascular disease [24] [25].
Obesity, once considered the preserve of industrialized countries, has now become a global epidemic [26]. The frequency of obesity continues to grow. In industrialized countries, the frequency of obesity has increased by between 5% and 10% over the past ten years [27] [28]. An increase in the frequency of obesity is also confirmed by some studies carried out in African countries [29] [30] [31] [32].
4.2. Cardiovascular Risk Factors and Determinants of Regional Obesity
The study of obesity and other cardiovascular risk factors is of great interest in both Difference Between developed Countries and developing Countries. Indeed, studies had shown the constant progression of obesity since the 1990 [33] [34]. Obesity is a chronic disease with multiple etiologies, including genetics, environment, lifestyle and diet. Numerous epidemiological studies have shown the role of obesity as an independent risk factor for CVD [35]. It is also a risk factor for other diseases which are themselves CVRF, namely: DM, dyslipidemia and HBP [36].
Several CVRF may be associated with the onset of obesity. Regarding regional obesity in our study: advanced age (≥60 years), smoking, obesity by BMI were independently associated with the occurrence of visceral obesity while advanced age, female sex, alcohol intake, high BMI (overweight and obesity) were for SAT fat mass. The presence of these risk factors in the obese subject should prompt a search for metabolic syndrome, a major risk factor for CVD.
With age, body composition changes. Lean mass becomes scarce and fat mass tends to accumulate at the visceral level due to the reduction in the level of physical activity. The fact that women are affected in regional (Subcutaneous) obesity gives a picture of the higher level of physical activity in men compared to women.
The impact of smoking on obesity is twofold. Classically, smokers are characterized by weight loss and adiposity due to a reduction in appetite on the one hand (reduction in calorie intake) and on the other hand because nicotine increases energy expenditure at rest by its sympathomimetic effect [37] [38]. This corresponds on average to an increase of 200 kcal in energy expenditure for 25 cigarettes smoked per day, which would amount to a loss of around 10 kg over one year if calorie intake remained unchanged.
However, “heavy” smokers (i.e. smokers who smoke more than 25 cigarettes a day) weigh more than smokers who smoke less [39]. The hypotheses which try to explain this paradoxical phenomenon are the following: first of all, smokers tend to be more sedentary, to eat less healthily and to consume more alcohol compared [40]. In this situation, the harmful effects of physical inactivity and an unhealthy diet outweigh the antagonizing effect of cigarette-related weight gain.
Although BMI is the most frequently used tool for documenting the risks associated with excess weight and for measuring changes in the prevalence of obesity at the population level, the addition of WC makes it possible to appreciate the regional distribution of obesity. Several studies including ours have shown an increase in abdominal obesity within BMI categories. Thus, it is also important to follow the evolution of abdominal obesity and WC in the population. The impedancemetry used in the present study made it possible to study the regional distribution of adiposity.
5. Conclusion
A significant frequency of regional obesity (visceral and subcutaneous obesity) has just been found as determinant among the other cardiovascular risk factors: advanced age, tobacco, obesity on BMI for visceral obesity, and advanced age, alcohol, overweight and obesity on BMI for subcutaneous obesity.