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Obesity, Central Obesity, Overweight and Diabetes: Women are the
Journal of Women's Health Care

Journal of Women's Health Care
Open Access

ISSN: 2167-0420

+44-7360-538437

Research Article - (2014) Volume 3, Issue 3

Obesity, Central Obesity, Overweight and Diabetes: Women are the Most Affected in Burkina Faso

Yaméogo Téné Marceline1,2*, Sombié Issiaka1,3, Ag Ouéaogo S Macaire1,2, Kyélem Carole Gilberte1,2, Yaméogo Aimé Arsène1,2, Rouamba Nadège4, Lankoandé Djingri2, Pr Ag Sawadogo Apollinaire2,5 and Prabo Y Joseph5
1Higher Institute of Health Sciences [INSSA], University of Bobo–Dioulasso, Burkina Faso, West Africa
2SourôSanou Teaching Hospital [CHU-SS] of Bobo-Dioulasso, Burkina Faso, West Africa
3West African Health Organization, West Africa
4BC National Hospital [HNBC], Burkina Faso, West Africa
5Health Sciences Education and Research Unit, University of Ouagadougou, Burkina Faso, West Africa
*Corresponding Author: Yaméogo Téné Marceline, Higher Institute of Health Sciences [INSSA], University of Bobo–Dioulasso, Burkina Faso, West Africa, Tel: +226 70 07 51 40 Email:

Abstract

Objective: To determine the importance of obesity and analyze the relationship between general obesity and central obesity in persons with diabetes monitored in Bobo-Dioulasso teaching hospital.
Methods: We used a sample of 380 persons with diabetes recruited through a study on compliance with follow-up examinations. Overweight and obesity were researched using the Quételet index, or Body Mass Index [BMI], which is defined as the individual’s mass divided by the square of their height, as well as waist size. Univariate analysis and multivariate regression were used [p<0.05].
Results: We found that 22.6% were obese [n=86], 29.2% were overweight [n=111] and 65.3% had central obesity [n=240]. The majority of obese [98.8%] and overweight cases [87.4%] and also 40.0% of those with normal BMI [n=160] and 8.6% of underweight cases [n=23] had central obesity. Being a woman was associated with general and central obesity. In a univariate analysis, obese were more likely to be woman, educated, have low incomes, reside in urban areas and have central obesity and a metabolic syndrome; central obesity is associated with being a woman, having a low income, residing in an urban area and having hypertension, obesity and a metabolic syndrome. In a multivariate analysis, being a woman, educated and having central obesity was found to be associated with obesity. On the other hand, being a woman, residing in an urban area and having hypertension, obesity and a metabolic syndrome remained associated with central obesity.
Conclusion: Obesity, and above all, central obesityis a big problem in persons with diabetes, particularly in women in Bobo-Dioulasso, and waist size seems to be a better measurement compared to BMI. These results call for more organized diabetes care and prevention in Burkina Faso.

Keywords: Obesity, Central obesity, Diabetes, Women, Burkina faso

Introduction

Obesity is one of the main determinants of the occurrence of cardiovascular diseases, arterial hypertension, diabetes and metabolic syndrome [1-4]. In persons with diabetes, obesity further increases the risk of the occurrence of cardiovascular diseases [5]. Thus, nowadays, it is recommended that obesity be prevented through nutrition education and regular exercise in order to reduce the risk of diabetes and cardiovascular diseases.

Obesity can be studied using several indicators, including Body Mass Index [BMI], abdominal circumference, waist size, abdomen-towaist ratio and abdomen-to-height ratio. Studies have shown that the measures of central obesity such as abdominal circumference, waist size, abdomen-to-waist ratio and abdomen-to-height ratio are better risk indicators for cardiovascular diseases than BMI [6-15] et are better able to predict diabetes [16-18].

In Africa, several studies have shown that the prevalence of obesity, overweight and excess weight as determined by BMI varies, but that women are predominately affected by obesity [19-24]. In Burkina, the presence of obesity and overweight are a reality, and numerous studies support this finding. In fact, in the city of Ouagadougou, the prevalence of adult overweight [BMI > 25 kg/m2] is estimated to be between 34 and 36% in women, between 14 and 16% in men [25,26] and at 8.7% in students between 13 and 25 years old [27]. In adults, the prevalence of obesity [BMI 30 kg/m2] is 5.5% in men and 21.9% in women [28]. In persons with diabetes monitored at the Yalgado Ouédraogo University Hospital in the same city there is 17th years ago, the prevalence of overweight and obesity in men and women was estimated to be 34% and 28%, respectively [29]. In Bobo-Dioulasso, Burkina’s second city, few publications exist on the impact of obesity in both the general population as well as in persons with diabetes.

In order to fill this gap in studies that exist on obesity in Bobo- Dioulasso, the objective of this study is to analyze the relationship between general obesity and central obesity in persons with diabetes. The results provide guidance to launch a campaign to prevent the occurrence of cardiovascular diseases in the city as well as the whole western region of Burkina Faso.

Methods

We conducted a descriptive cross-sectional study with a sample of 380 consenting persons with diabetes, monitored in Bobo-Dioulasso teaching hospital and recruited on an ongoing basis through a study on compliance with para-clinical monitoring. Assuming that at least 50% of people with diabetes accede to the para-clinical monitoring, with an accuracy of 5% and an alpha error of 5% [IC to 95%], we selected a sample of 388 persons with diabetes; 8 of them were not weighed because of their bedridden state. They have not been taken into account in the assessment of obesity.

We collected information in individual records about each person with diabetes’ socio-demographic characteristics, knowledge of cardiovascular risk factors, exercise habits, follow-up examinations, weight, height and waist size.

Obesity was determined using the Quételet index, or Body Mass Index [BMI], which is defined as the individual’s mass divided by the square of their height, as well as waist size. A person was considered overweight if their BMI was greater than or equal to 25 kg/m2 and less than 30 kg/m2. Central obesity was defined as a waist size of greater than or equal to 94 cm in men and 80 cm in women.

A descriptive analysis of the data was performed, followed by a study of the relationship between overweight, general obesity, central obesity and characteristics of persons with diabetes, using Pearson’s Chi-squared test with a statistical significance of 5%.

Results

Socio-demographic characteristics

The average age of the 380 persons with diabetes was 53.2 years [95% CI: 51.9 - 54.5]. Persons with diabetes at or over the age of 40 years represented 85.8% of the cases. The average age at the discovery of diabetes was 48.2 years [95% CI:46.8 - 49.5]. There were 224 female participants, representing 58.9% of the sample population and giving a sex ratio of 0.7. In terms of occupation, 152 were housewives [40.0%], 68 salaried employees [17.9%], 47 traders [12.4%], 46 farmers/ shepherds [12.1%], 43 retirees [11.3%], 7 high school or university students [1.8%] and 17 unemployed [4.5%]. Persons with diabetes who were educated represented 43.2% of the sample population [n=164], and urban residents represented 85.3% [n=324]. In terms of support for care, only 6 persons with diabetes [1.6%] benefited from health insurance.

Importance of overweight and obesity based on BMI

BMI varied from 13.4 to 55.4 kg/m2 with an average of 25.9 kg/m2 [95% CI: 25.4 - 26.5 kg/m2]. The distribution of persons with diabetes based on their BMI indicates that more than half of them [51.8%] had excess weight [BMI over 25/kg/m2]. Among those who had excess weight, we found that 86 [22.6%] were obese and 111 [29.2%] overweight (Table 1). We found that 5.8% of obese had a BMI over 40 kg/m2.

BMI Frequency Percentage
<18 23 6.1
18-24.9 160 42.1
25-29.9 111 29.2
30 and over 86 22.6
Total 380 100.00

Table 1: Distribution of persons with diabetes monitored at CHU-SS in Bobo-Dioulasso based on BMI, 2011.

Importance of central obesity

Waist size was measured and varied from 53 cm to 181 cm, with an average of 91.3 cm [95% CI: 89.9 - 92.7 cm]. Two-hundred forty eight [248] persons with diabetes [65.3%] were considered to have central obesity.

Obesity based on BMI and waist size

Table 2 gives the distribution of persons with diabetes based on BMI and central obesity. There is a statistically significant relationship between BMI and central obesity [p<0.001]. We found that 98.8% of those considered obese, 87.4% of those considered overweight, 40.0% with normal BMI and 8.6% of those who are underweight have central obesity.

  BMI  
Central Obesity <18 18-24.9 25-29.9 30 and over Total
No 21 96 14 1 132
Yes 2 64 97 85 248
Total 23 160 111 86 380
Pearson chi2 =144.235 Pr=0.000

Table 2: Relationship between Body Mass Index (BMI) and Central Obesity in persons with diabetes at CHU-SS in Bobo-Dioulasso, 2011.

Obesity, central obesity and persons with diabetes’ characteristics

Table 3 shows the distribution of persons with diabetes based on obesity, central obesity and other characteristics included in our study in a univariate and multivariate analysis.

  Number of cases Obesity Central Obesity
  (N=380)
Characteristics   %   OR adjusted p %   OR adjusted p
    Crude OR [95% CI] Crude OR [95% CI]
    [95% CI]   [95% CI]  
Sexe
Male 156 4.5 1     32.2 1    
Female 224 35.3 11.6 [5.2 - 25.9]a 5.6 [2.2- 14.4] 0 88.4 16.1 [9.5 - 27.4]g 19.9 [8.3 – 47.9] 0
 
Age
< 40 years 54 22.2 1     53.7 1    
40 and over 326 22.7 1.0 [0.5 - 2.0]     67.2 1.8 [0.9 – 3.2]    
 
Income
Yes 204 18.1 0.6 [0.4 - 0.9]b   0.3 53.9 0.3 [0.2 – 0.5]h   0.2
No 176 27.8 1     78.3 1    
 
Residence
Urban 324 25 1     71.3 1    
Rural 56 8.9 0.3 [0.1 - 0.7]c   1 30.4 0.2 [0.1 – 0.3]i 0.2 [0.09 - 0.6] 0.002
Educated
Yes 164 29.9 2.1 [1.3 - 3.3]d 1.9 [1.1 - 3.5] 0.02 70.7 1.5 [0.9 – 2.4]    
No 216 17.1 1     61.1 1    
  Number of cases Obesity Central Obesity
  (N=380)
Characteristics   %   OR adjusted p %   OR adjusted p
    Crude OR [95% CI] Crude OR [95% CI]
    [95% CI]   [95% CI]  
Exercise                  
Yes 26 19.2 1     69.2 1    
No 354 22.9 1.3 [0.5 – 3.4]     65 0.8 [0.3 – 1.9]    
Hypertension                  
Yes 214 24.3 1.3 [0.8 – 2.0]     74.8 2.6 [1.7 – 4.1]j 3.1 [1.6 – 5.8] 0
No 166 20.5 1     53 1    
Metabolic syndrome                  
Yes 184 31 2.6 [1.6 – 4.3]e   0.1 94 1    
No 196 14.8 1     38.3 0.3 [0.2 – 0.4]k 0.3 [0.2 – 0.6] 0
Central Obesity                  
Yes 248 34.3 68.3 [9.4 – 497.2]f 31.6 [4.1- 241.6] 0.001        
No 132 0.8 1            
Obesity                  
Yes           98.8 68.3 [9.4 – 497.2]l 41.5 [5.1 –340.7] 0.001
No           55.4 1    
a: p=0.000 b: p=0.02 c: p=0.008 d: p=0.003 e: p=0.000 f: p=0.000
g: p=0.000 h: p=0.000 i: p=0.000 j: p=0.000 k: p=0.000 l: p=0.000

Table 3: Obesity, overweight based on BMI, central obesity and characteristics of persons with diabetes in Bobo-Dioulasso, Burkina Faso, 2011.

Persons with diabetes who are obese are more likely to be woman, educated, have low incomes, reside in urban areas and have central obesity and a metabolic syndrome.

We found that central obesity is associated with being a woman, having a low income, residing in an urban area and having hypertension, obesity and a metabolic syndrome.

In a multivariate analysis, being a woman, educated and having central obesity was found to be associated with obesity. On the other hand, being a woman, residing in an urban area and having hypertension, obesity and a metabolic syndrome remained associated with central obesity. We found relation between general and central obesity but only central obesity was associated to the metabolic syndrome and hypertension.

Discussion

In total, we found that 22.6% of persons with diabetes have general obesity, 29.2% are overweight and 65.3% have central obesity. The majority of persons with diabetes with general obesity [98.8%] and who are overweight [87.4%] and even the 40.9% who have a normal BMI and the 8% that are underweight have central obesity.

In a multivariate analysis, being a woman, educated and having central obesity was found to be associated with obesity. On the other hand, being a woman, residing in an urban area and having hypertension, obesity and a metabolic syndrome remained associated with central obesity.

In our study, we found that obesity was a major problem in persons with diabetes. In fact, 1 in 5 persons with diabetes had general obesity and nearly 1 in 3 had central obesity. This calls for the prioritization of a campaign for persons with diabetes in our practice in order to prevent the occurrence of cardiovascular diseases. In comparing our results to those of other African studies, the global prevalence of obesity in our study was higher than the 16% reported in Ivory Coast [30] and lower than the 34.72% reported in Burundi [31] and the 28% reported in Ouagadougou [29]. The difference between the results could be explained by different nutritional contests and lifestyle in the various cities. Regardless of the study, the significance of obesity and overweight in persons with diabetes is a reality in Africa.

The prevalence of central obesity was 65.3% while the prevalence of general obesity was 22.6%. In population based studies in African region and elsewhere, central obesity was found more frequent than general obesity [32,33]. In addition, our study population is people with diabetes. Diabetes is known to be strongly associated with central obesity rather than general obesity, which would explain our observation [34].

Generally, the majority of those who were considered obese as well as those who were overweight had central obesity. On the other hand, 40.0% of those with a normal BMI and 8.6% of those who were underweight also had central obesity. In multivariate analysis we found relation between general and central obesity but only central obesity was associated to the metabolic syndrome and hypertension. These results confirm that central obesity is the best measure of obesity as a risk factor for cardiovascular complications [6-15]. It must be recommended as a measure instead of BMI, which leaves many persons with diabetes at risk for undiagnosed cardiovascular diseases.

General obesity and central obesity were more significant in women than in men in our study. The same observation was made in several studies in persons with diabetes in Cameroon, Kenya, South Africa, Tanzania and Zimbabwe [19-24]. The difference between men and woman could be explained in our case by the more frequent exposure of women to sugary and greasy foods at ceremonies like marriages and baptisms. In addition, with the advent of mopeds, few women who live in cities exercise regularly. Finally, the perception that excess weight is related to good living conditions means that women have the tendency to gain weight after getting married, a sign of a better quality of life in their household. In Kenya, a population study found that more than half of people who are overweight underestimate their weight, and that in all weight categories based on BMI, more than a third preferred to be in the overweight or obese categories [35]. It emphasizes the necessity of educating and raising awareness about excess weight and its relationship to the occurrence of cardiovascular diseases, particularly of people implicated in meal preparation in Africa.

The distribution of obesity based on BMI in persons with diabetes based on their residential zone which we found in this study in univariate analysis has also been reported in several studies in Africa. But in our study, only central obesity is associated to patient residence. In Cameroon, Kenya and Tanzania [19,20,22], persons with diabetes who live in urban areas were more obese than those living in rural areas. The difference between urban and rural areas could be explained by the difference in lifestyles. In Burkina Faso, a study found that for pregnant women living in rural areas [36] and those considered obese living in cities, high-calorie diets were related to modern foods that are more commonly found in cities than in rural areas [25]. In addition, the difference in access to modern means of transportation which are found in cities, expose more urban residents to sedentary lifestyles.

We found in our study that central obesity was related to low incomes, which can be taken as a proxy indicator for socio-economic status. Our finding seems contrary to what has been found in Ouagadougou and elsewhere in Africa where in the general population, obesity is linked to better living conditions [28,37]. The difference in the sex ratio in our study could explain the difference.

Conclusion

The results of our study show that obesity, overweight and central obesity affect more than half of the persons with diabetes in Bobo- Dioulasso, especially women; and confirm that central obesity is the best measure of obesity as a risk factor for cardiovascular complications. That calls for the urgent creation of a nutrition and cardiovascular diseases prevention program in our setting.

References

  1. Loehr LR,Rosamond WD, Poole C, McNeill AM, Chang PP, et al. (2009) Association of multiple anthropometrics of overweight and obesitywith incident heartfailure: the AtherosclerosisRisk in Communitiesstudy. CircHeart Fail 2: 18-24.
  2. Turkbey EB,McClelland RL, Kronmal RA, Burke GL, Bild DE, et al. (2010) The impact of obesity on the leftventricle: the Multi-EthnicStudy of Atherosclerosis (MESA). JACC Cardiovasc Imaging 3: 266-274.
  3. Cheriyath P, Duan Y, Qian Z, Nambiar L, Liao D (2010) Obesity, physicalactivity and the development of metabolic syndrome: the AtherosclerosisRisk in Communitiesstudy. Eur J CardiovascPrevRehabil 17: 309-313.
  4. Hu YH, Reilly KH, Liang YJ, Xi B, Liu JT, et al. (2011) Increase in body mass index, waistcircumference and waist-to-height ratio isassociatedwith high blood pressure in children and adolescents in China. J Int Med Res 39: 23-32.
  5. Yadav NK,Thanpari C, Shrewastwa MK, Mittal RK (2012) Comparison of lipid profile in type-2 obese diabetics and obese non-diabeticindividuals. Ahospitalbasedstudyfrom Western Nepal. KathmanduUniv Med J (KUMJ) 10: 44-47.
  6. de Koning L, Merchant AT, Pogue J, Anand SS (2007) Waistcircumference and waist-to-hip ratio as predictors of cardiovascularevents: meta-regressionanalysis of prospective studies. EurHeart J 28: 850-856.
  7. Coutinho T,Goel K, Corrêa de Sá D, Kragelund C, Kanaya AM, et al. (2011) Central obesity and survival in subjectswithcoronaryarterydisease: asystematicreview of the literature and collaborative analysiswithindividualsubject data. J Am CollCardiol 57: 1877-1886.
  8. Schneider HJ, Klotsche J, Silber S, Stalla GK, Wittchen HU (2011) Measuring abdominal obesity: effects of height on distribution of cardiometabolicriskfactorsrisusingwaistcircumference and waist-to-height ratio. Diabetes Care 34: e7.
  9. Dhaliwal SS,Welborn TA (2009) Central obesity and multivariablecardiovascularrisk as assessed by the Framingham prediction scores. Am J Cardiol 103: 1403-1407.
  10. Czernochow S, Kengne AP, Stamatakis E, Hamer M, Batty GD (2011) Body mass index, waistcircumference and waist-hip ratio: whichis the betterdiscriminator of cardiovasculardiseasemortalityrisk? Evidence from an individual-participant meta-analysis of 82 864 participants fromninecohortstudies. ObesRev 12:680-687.
  11. Sehested TS, Hansen TW, Olsen MH, Abildstrøm SZ, Rasmussen S, et al. (2010) Measures of overweight and obesity and risk of cardiovasculardisease: a population-basedstudy. Eur J CardiovascPrevRehabil 17: 486-490.
  12. Schneider HJ, Friedrich N, Klotsche J, Pieper L, Nauck M, et al. (2010) The predictive value of differentmeasures of obesity for incident cardiovascularevents and mortality. J Clin EndocrinolMetab 95: 1777-1785.
  13. Park SH, Choi SJ, Lee KS, Park HY (2009) Waistcircumference and waist-to-height ratio as predictors of cardiovasculardiseaserisk in Koreanadults. Circ J 73: 1643-1650.
  14. Lee CM, Huxley RR, Wildman RP, Woodward M (2008) Indices of abdominal obesity are betterdiscriminators of cardiovascularriskfactorsthan BMI: a meta-analysis. J Clin Epidemiol 61: 646-653.
  15. Recio-Rodriguez JI, Gomez-Marcos MA, Patino-Alonso MC, Agudo-Conde C, Rodriguez-Sanchez E, et al. (2012) Abdominal obesity vs generalobesity for identifyingarterialstiffness, subclinicalatherosclerosis and wavereflection in healthy, diabetics and hypertensive. BMC CardiovascularDisorders 12: 3.
  16. Huxley R, James WP, Barzi F, Patel JV, Lear SA, et al. (2008) Ethniccomparisons of the cross-sectionalrelationshipsbetweenmeasures of body size withdiabetes and hypertension. ObesRev 9: 53-61.
  17. DecodaStudy Group, Nyamdorj R, Qiao Q, Lam TH, Tuomilehto J, et al. (2008) BMI comparedwith central obesityindicators in relation to diabetes and hypertension in Asians. Obesity (SilverSpring) 16: 1622-1635.
  18. Mackay M, Haffner S, Wagenknecht L, D’agostino R Jr, Hanley A (2009) Prediction of type 2 diabetesusingalternateanthropometricmeasures in amulti-ethniccohort: the insulinresistanceatherosclerosisstudy. Diabetes Care 32: 956-958.
  19. Sobngwi E,Mbanya JC, Unwin NC, Kengne AP, Fezeu L, et al. (2002) Physicalactivity and itsrelationshipwithobesity, hypertension and diabetes in urban and rural Cameroon. Int J ObesRelatMetabDisord 26: 1009-1016.
  20. Mathenge W, Foster A, Kuper H (2010) Urbanization, ethnicity and cardiovascularrisk in a population in transition in Nakuru, Kenya: a population-basedsurvey. BMC Public Health 10: 569.
  21. Alberts M,Urdal P, Steyn K, Stensvold I, Tverdal A, et al. (2005) Prevalence of cardiovasculardiseases and associatedriskfactors in a rural black population of South Africa. Eur J CardiovascPrevRehabil 12: 347-354.
  22. Aspray TJ,Mugusi F, Rashid S, Whiting D, Edwards R, et al. (2000) Rural and urbandifferences in diabetesprevalence in Tanzania: the role of obesity, physicalinactivity and urban living. Trans R Soc Trop Med Hyg 94: 637-644.
  23. Maher D, Waswa L, Baisley K, Karabarinde A, Unwin N, et al. (2011) Distribution of hyperglycaemia and relatedcardiovasculardiseaseriskfactors in low-income countries: a cross-sectional population-basedsurvey in rural Uganda. Int J Epidemiol 40:160-171.
  24. MOH (2005) National Survey: Zimbabwe Non-Communicable DiseaseRiskFactors (ZiNCoDs). Preliminary Report. Ministry of Health and Child Welfare, Zimbabwe.
  25. Becquey E,Savy M, Danel P, Dabiré HB, Tapsoba S, et al. (2010) Dietary patterns of adults living in Ouagadougou and their association withoverweight. Nutr J 9: 13.
  26. Zeba AN, Delisle HF, Renier G, Savadogo B, Baya B (2012) The double burden of malnutrition and cardiometabolicriskwidens the gender and socio-economichealth gap: astudyamongadults in Burkina Faso (West Africa). Public HealthNutr 15: 2210-2219.
  27. Kouéta F, Dao L, Dao F, Djekompté S, Sawadogo J, et al. (2011) [Factorsassociatedwithoverweight and obesity in children in Ouagadougou (Burkina Faso)]. Sante 21: 227-231.
  28. Ouedraogo HZ, Fournet F, Martin-Prével Y, Gary J, Henry MC, et al. (2008) Socio-spatial disparities of obesityamongadults in the urban setting of Ouagadougou, Burkina Faso. Public HealthNutr 11:1280-1287.
  29. Drabo PY, Kabore J, Lengani A, Ilboudo PD (1996) [Diabetesmellitusat the National Hospital Center of Ouagadougou (Burkina Faso)]. Bull Soc PatholExot 89: 185-190.
  30. Oga AS,Tebi A, Aka J, Adouéni KV, Malan KA, et al. (2006) [Diabetes in IvoryCoast: specialepidemiologicalfeatures]. Med Trop (Mars) 66: 241-246.
  31. Nsabiyumva F, Ndikubagenzi J, Baransaka E, Harindavyi H (2011) Aspects épidémiologiques et cliniques de 3620 diabétiques suivis au Centre de lutte contre le Diabète au Burundi. Etude rétrospective sur six ans. Med Afr Noire 58: 345-349.
  32. Chukwuonye II,Chuku A, Onyeonoro UU, Okpechi IG, Madukwe OO, et al. (2013) Prevalence of abdominal obesity in Abia State, Nigeria: results of a population-based house-to-house survey. DiabetesMetabSyndrObes 6: 285-291.
  33. Hajian-Tilaki KO, Heidari B. (2007) Prevalence of obesity, central obesity and the associatedfactors in urban population aged 20-70 years, in the north of Iran: a population-basedstudy and regressionapproach. ObesRev8:3-10.
  34. Balkau B,Deanfield JE, Després JP, Bassand JP, Fox KA, et al. (2007) International Day for the Evaluation of Abdominal Obesity (IDEA): astudy of waistcircumference, cardiovasculardisease, and diabetesmellitusin 168,000 primary care patients in 63 countries. Circulation 116: 1942-1951.
  35. Ettarh R, Van de Vijver S, Oti S,Kyobutungi C2 (2013) Overweight, obesity, and perception of body image amongslumresidents in Nairobi, Kenya, 2008-2009. PrevChronic Dis 10: E212.
  36. Huybregts LF,Roberfroid DA, Kolsteren PW, Van Camp JH (2009) Dietarybehaviour, food and nutrientintake of pregnantwomen in a rural community in Burkina Faso. Matern Child Nutr 5: 211-222.
  37. Amoah AG (2003) Sociodemographic variations in obesityamongGhanaianadults. Public HealthNutr 6: 751-757.
Citation: Marceline YT, Issiaka S, Macaire AOS, Gilberte KC, Arsène YA, et al. (2014) Obesity, Central Obesity, Overweight and Diabetes: Women are the Most Affected in Burkina Faso. J Women’s Health Care 3:155.

Copyright: © 2014 Marceline YT, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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