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Prevalence of obesity and overweight, its clinical markers and associated factors in a high risk South-Asian population.

Amin F, Fatima SS, Islam N, Gilani AH - BMC Obes (2015)

Bottom Line: Variability in body composition between ethnic groups in South-Asians is significant and may not be truly reflected by BMI alone, which may result in misclassification.A P value of less than 0.05 was considered significant.Considering the rising prevalence of non-communicable diseases, BF%, WC, WHR and BMI measurements are convenient and feasible means of identifying population at risk and hence addressing it through public awareness and early detection.

View Article: PubMed Central - PubMed

Affiliation: Natural Product Research Unit, Department of Biological and Biomedical Sciences, The Aga Khan University Medical College, Karachi, 74800 Pakistan.

ABSTRACT

Background: Obesity is a global epidemic, which is a risk factor for cardiovascular diseases and metabolic abnormalities. It is measured by body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), body fat (BF) distribution and abdominal fat mass, each having its own merits and limitations. Variability in body composition between ethnic groups in South-Asians is significant and may not be truly reflected by BMI alone, which may result in misclassification. This study therefore, aims to determine the frequency of obesity, body fat composition and distribution, in a high risk population of an urban slum of Karachi, Pakistan. This survey included 451 participants selected by systematic sampling who were administered pre-tested questionnaires on socio-demographics, diet and physical activity. Chi-square was used to determine the association between categorical variables and multiple linear regression was used for quantitative variables. A P value of less than 0.05 was considered significant.

Results: Classified by BMI, 29% study subjects were overweight and 21% obese (58.7% with central obesity). Body fat percent (BF%) classified 81% as overweight. Females were more obese (P 0.03) with higher prevalence of central obesity (P <0.001) and WHR (P 0.003) but with a lower muscle mass (P 0.001). Activity score and muscle mass showed inverse linear association with BF% whereas, WC, weight, BMI and WHR had a positive linear association with BF%. The relationship between BMI and BF% was quadratic with a weaker association at lower BMI. Adjusting for socio-demographic variables, BF%, weight, diastolic blood pressure (DBP), BMI and score on the diet questionnaire had a positive linear association with WC, while WC, WHR and BP had a positive linear association with BF%. BF%, muscle content and WC had a positive linear association with BMI.

Conclusion: Considering lower cut-offs for South-Asians BMI and WC, this study showed a high prevalence of obesity among a sub-urban population of Karachi, which was even higher when BF% was measured. Considering the rising prevalence of non-communicable diseases, BF%, WC, WHR and BMI measurements are convenient and feasible means of identifying population at risk and hence addressing it through public awareness and early detection.

No MeSH data available.


Related in: MedlinePlus

Association of waist-hip ratio with body fat percentage. (P <0.001 spearman correlation co-efficient rs = 0.31).
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Fig5: Association of waist-hip ratio with body fat percentage. (P <0.001 spearman correlation co-efficient rs = 0.31).

Mentions: Total activity-METS (Figure 1) and muscle mass (Figure 2) had a significantly inverse linear association with BF% whereas; WC (Figure 3), weight (Figure 4) and WHR (Figure 5) had a positive linear association. The relationship between BMI and BF% was quadratic (Figure 6).Figure 1


Prevalence of obesity and overweight, its clinical markers and associated factors in a high risk South-Asian population.

Amin F, Fatima SS, Islam N, Gilani AH - BMC Obes (2015)

Association of waist-hip ratio with body fat percentage. (P <0.001 spearman correlation co-efficient rs = 0.31).
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4510896&req=5

Fig5: Association of waist-hip ratio with body fat percentage. (P <0.001 spearman correlation co-efficient rs = 0.31).
Mentions: Total activity-METS (Figure 1) and muscle mass (Figure 2) had a significantly inverse linear association with BF% whereas; WC (Figure 3), weight (Figure 4) and WHR (Figure 5) had a positive linear association. The relationship between BMI and BF% was quadratic (Figure 6).Figure 1

Bottom Line: Variability in body composition between ethnic groups in South-Asians is significant and may not be truly reflected by BMI alone, which may result in misclassification.A P value of less than 0.05 was considered significant.Considering the rising prevalence of non-communicable diseases, BF%, WC, WHR and BMI measurements are convenient and feasible means of identifying population at risk and hence addressing it through public awareness and early detection.

View Article: PubMed Central - PubMed

Affiliation: Natural Product Research Unit, Department of Biological and Biomedical Sciences, The Aga Khan University Medical College, Karachi, 74800 Pakistan.

ABSTRACT

Background: Obesity is a global epidemic, which is a risk factor for cardiovascular diseases and metabolic abnormalities. It is measured by body mass index (BMI), waist circumference (WC), waist-hip ratio (WHR), body fat (BF) distribution and abdominal fat mass, each having its own merits and limitations. Variability in body composition between ethnic groups in South-Asians is significant and may not be truly reflected by BMI alone, which may result in misclassification. This study therefore, aims to determine the frequency of obesity, body fat composition and distribution, in a high risk population of an urban slum of Karachi, Pakistan. This survey included 451 participants selected by systematic sampling who were administered pre-tested questionnaires on socio-demographics, diet and physical activity. Chi-square was used to determine the association between categorical variables and multiple linear regression was used for quantitative variables. A P value of less than 0.05 was considered significant.

Results: Classified by BMI, 29% study subjects were overweight and 21% obese (58.7% with central obesity). Body fat percent (BF%) classified 81% as overweight. Females were more obese (P 0.03) with higher prevalence of central obesity (P <0.001) and WHR (P 0.003) but with a lower muscle mass (P 0.001). Activity score and muscle mass showed inverse linear association with BF% whereas, WC, weight, BMI and WHR had a positive linear association with BF%. The relationship between BMI and BF% was quadratic with a weaker association at lower BMI. Adjusting for socio-demographic variables, BF%, weight, diastolic blood pressure (DBP), BMI and score on the diet questionnaire had a positive linear association with WC, while WC, WHR and BP had a positive linear association with BF%. BF%, muscle content and WC had a positive linear association with BMI.

Conclusion: Considering lower cut-offs for South-Asians BMI and WC, this study showed a high prevalence of obesity among a sub-urban population of Karachi, which was even higher when BF% was measured. Considering the rising prevalence of non-communicable diseases, BF%, WC, WHR and BMI measurements are convenient and feasible means of identifying population at risk and hence addressing it through public awareness and early detection.

No MeSH data available.


Related in: MedlinePlus