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Table of Contents
ORIGINAL ARTICLE
Year : 2020  |  Volume : 8  |  Issue : 1  |  Page : 11-14

Sensitivity and specificity of waist circumference as a screening tool for assessment of obesity in rural population


1 Department of General Medicine, KLE University of Higher Education and Research's, Jawaharlal Nehru Medical College, Belgaum, Karnataka, India
2 Department of Biochemistry, KLE University of Higher Education and Research's, Jawaharlal Nehru Medical College, Belgaum, Karnataka, India
3 Department of Physiology, KLE University of Higher Education and Research's, Jawaharlal Nehru Medical College, Belgaum, Karnataka, India

Date of Submission21-Jul-2019
Date of Acceptance01-Nov-2019
Date of Web Publication14-Jan-2020

Correspondence Address:
Dr. Jayaprakash S Appajigol
Department of Medicine, KLE University of Higher Education and Research's, Jawaharlal Nehru Medical College, Belgaum - 590 010, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/AJIM.AJIM_31_19

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  Abstract 


Context: Prevalence of obesity increasing worldwide, including in the rural populations. Waist circumference (WC) and body mass index (BMI) are closely related in measuring obesity. Measuring WC is easier than measuring height and weight for calculating BMI. Therefore, WC measurement can be used as obesity detecting tool. Aims: The aim of the study is to estimate the prevalence of obesity in a rural population and to assess the sensitivity and specificity of WC values for identifying obesity. Settings and Design: It was a cross-sectional study conducted in rural places of North Karnataka. Material and Methods: Height, weight, and WC of each participant were measured. WC was measured at the midpoint between the inferior margin of the last rib and iliac crest. Statistical Analysis Used: Statistical analyses were performed using MedCalc for Windows. The area under the receiver operating characteristics derived by plotting 100 specificity along the X-axis and sensitivity along the Y-axis. Results: Abdominal obesity measured by WC showed that 114 participants were obese with a prevalence of 36.08%. Prevalence of obesity by taking BMI of ≥25 kg/m2 as cutoff showed 15.82%. We found that presently recommended WC cutoff value for males had 66.67% sensitivity and for females had 89.47% sensitivity to diagnose obesity. Conclusions: WC can be used as screening tool for identifying obesity. Considerable variation in sensitivity was found among different studies. Unlike BMI, universal cutoff may not be possible with WC. More studies are needed to assess the relationship of different obesity surrogates to cardiovascular morbidity and mortality.

Keywords: Body mass index, obesity, prevalence, rural, waist


How to cite this article:
Appajigol JS, Somannavar MS, Araganji RR. Sensitivity and specificity of waist circumference as a screening tool for assessment of obesity in rural population. APIK J Int Med 2020;8:11-4

How to cite this URL:
Appajigol JS, Somannavar MS, Araganji RR. Sensitivity and specificity of waist circumference as a screening tool for assessment of obesity in rural population. APIK J Int Med [serial online] 2020 [cited 2020 Jan 23];8:11-4. Available from: http://www.ajim.in/text.asp?2020/8/1/11/275979




  Introduction Top


The burden of cardiovascular disease (CVD) in India and other developing countries is expected to double in the next two decades. CVDs are going to be the single major cause of death.[1] Obesity and other metabolic diseases are rapidly increasing. Obesity is a risk factor for diabetes mellitus, hypertension, CVDs, dyslipidemias, and for many more noncommunicable diseases. Overweight, obesity, and morbid obesity increase mortality rates from 7% to 20%, 45% to 94%, and 176%, respectively.[2] The World Health Organization data show 39% of adults aged 18 and above are overweight and 13% are obese.[3] A remarkable rise has been observed in the prevalence of obesity among Indians.[4] As per the ICMR-INDIAB-3 study done in India, the prevalence of generalized obesity, defined by body mass index (BMI) of more than or equal to 25 kg/m 2 was 24.6%, 16.6%, 11.8%, and 31.3% among residents of Tamil Nadu, Maharashtra, Jharkhand, and Chandigarh, whereas the prevalence of abdominal obesity was 26.6%, 18.7%, 16.9%, and 36.1%, respectively. Abdominal obesity was defined as a waist circumference (WC) ≥90 cm for men and ≥80 cm for women.[5] In a study conducted in Urban North India (New Delhi), the overall prevalence of generalized obesity was 50.1%, whereas abdominal obesity was 68.9%.[6]

Measurement of obesity by magnetic resonance imaging and computed tomography is highly accurate and valid but are costly and not feasible for every day clinical use. Therefore, WC and BMI are commonly used tools for abdominal obesity and generalized obesity measurement, respectively. WC and BMI are closely related in measuring excess fat deposition. Measuring WC is easier than measuring height and weight for calculating BMI. Therefore, WC measurement can be used as obesity detecting tool in busy primary care clinics of remote and rural setups. Hence, the present study was conducted in the rural area with the aim to estimate the prevalence of obesity and to assess the sensitivity and specificity of WC values for identifying obesity.


  Materials and Methods Top


The study was conducted in a village called Jakanaykana koppa, 22 km away from our medical college. This village was selected, as it was feasible, and it has minimal influence of urbanization. The population of the village was around 950. Electoral list had 682 people in it. Depending on the sample size required, we screened every alternate person according to the electoral voter list. Moreover, if a person denies consent or does not meet eligible criteria, the very next person was included in the study. The ethics committee of the Jawaharlal Nehru Medical College, Belgaum, approved the protocol.

Measuring tape, analog weighing scale, and stadiometer were the study tools. Height, weight, and WC of each participant were measured. WC was measured at the midpoint between the inferior margin of the last rib and the iliac crest. Secondary causes of obesity such as hypothyroidism, pregnancy, and ascites were excluded from the study. The body weight was measured in light clothing with the help of standardized analog weighing machine. Height was measured with the participant standing upright on a level surface with heels together with shoes removed. Participants were classified as obese if BMI (computed as weight in kilograms divided by the square of the height in meters) was ≥25. [Table 1] shows the classification of BMI as per the WHO and Asia-Pacific guidelines.[7] In this study, obesity using BMI was diagnosed as per Asia-Pacific classification.
Table 1: Obesity classification according to the WHO and Asia-Pacific guidelines

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Statistical analyses were performed using MedCalc for Windows, version 18.10.2 (MedCalc Software, Ostend, Belgium). Sensitivity and specificity of the recommended WC cutoff were calculated as true positive/(true positive + false negative) and true negative/(true negative + false positive), respectively. Area under the receiver operating characteristics (ROCs) derived by plotting 100 specificity along the X-axis and sensitivity along the Y-axis. To compare the area under ROCs of the two risk scores, DeLong method was used.[8] Optimal cutoff values calculated by considering sensitivity and specificity.


  Results Top


The data of 316 participants were available for analysis. There were 180 (56.96%) male and 136 (43.04%) female participants. The mean age of participants was 45.38 years, ranging from 18 to 82 years.

Abdominal obesity measured by WC showed that 114 participants were obese with the prevalence of 36.08%. Abdominal obesity was more common in females than males. Females with WC ≥80 cm, defined as abdominal obesity, constituted 84 (46.67% of female participants) participants. Males with WC ≥90 cm, defined as obesity, constituted 30 (22.06% of male participants) participants. The WC significantly correlated with BMI (Overall R = 0.64). The WC among males had better correlation as compared to female participants (R value in males: 0.75; R value in females: 0.64).

The prevalence of obesity by taking BMI of ≥25 kg/m 2 as cutoff showed that 50 (15.82%) participants were obese. Obesity was more prevalent in females (21.11%) than males (8.82%). There were 40 (12.66%) people with BMI between 23 and 24.9 kg/m 2, classified under the category of overweight [Figure 1].
Figure 1: Participants in each body mass index category

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We found that presently recommended WC cutoff value of 90 cm for males had 66.67% sensitivity and 82.26% specificity to diagnose obese individuals, and WC cutoff value of 80 cm for females had 89.47% sensitivity and 64.79% specificity for the same.

In the present study, among males, WC cutoff value of 83.82 cm had a better diagnostic accuracy to identify obesity with sensitivity 100%, specificity 66.13%, and area under curve (AUC) (0.910; 95% confidence interval [CI]: 0.849–0.941) [Figure 2].
Figure 2: Receiver operating characteristic analysis of waist circumference cutoff for identification of obesity (body mass index ≥25) among males (n = 136)

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Among females, WC cutoff value of 86.36 cm had a better diagnostic accuracy to identify obesity with sensitivity 84.21%, specificity 88.73%, and AUC (0.902; 95% CI: 0.849–0.952) [Figure 3].
Figure 3: Receiver operating characteristic analysis of waist circumference cutoff for identification of obesity (body mass index ≥25) among females (n = 180)

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  Discussion Top


Studies have shown that for health promotion, measuring WC has many merits over the more troublesome ways of measurements for adiposity. Furthermore, there is evidence that, compared with BMI, the WC may be the better predictor of health risk. Measurement of WC is a simple procedure that can be used by physicians to identify abdominal obesity, which predisposes for developing many serious complications of obesity and metabolic syndrome.[8] Abdominal obesity is defined as having WC measurements ≥90 cm and 80 cm for males and females, respectively.[9] The present study found that the sensitivity of currently recommended WC cutoff is 66.67% and 89.47% for identifying obesity (BMI ≥25 kg/m 2, according to the Asia-Pacific classification of obesity) among men and women, respectively. Moreover, among males and females, WC cutoff values of 83.82 cm and 86.36 cm, respectively, have a better diagnostic accuracy to identify obesity. Abdominal obesity was defined as a WC ≥90 cm for men and ≥80 cm for women.[5] The study done in rural Kolkata showed that for men, 86.5 cm and for women, 78.5 cm. WC cutoff has a better diagnostic accuracy to detect obesity (BMI ≥25 kg/m 2).[10] A Malaysian study results shown that WC cutoffs of 86 cm for men and 79 cm for women were more accurate in detecting obesity (BMI ≥25 kg/m 2).[11]

Although different studies in different parts of the world have advised for different sensitivity and specificity for diagnosing obesity by WC measurements, WC is an important tool to detect obesity-related health complications. A 1 cm increase in WC is associated with a 2% increase in risk of future CVDs.[12] Studies have shown the importance of waist measurement and suggested to include waist measurement in cardiovascular risk assessment. WC is a simple, easily measurable parameter to diagnose obesity. It is more suitable in the outpatient setting as well as during field surveys. Moreover, WC is easy to self-monitor also.

Being community-based study and including the rural population to validate the WC against BMI is the strength of the study. We did not correlate WC with cardiovascular or other metabolic disease outcomes. Instead, we took BMI classification as the gold standard and assessed the performance of WC against BMI. Therefore, the sensitivity of WC is highly dependent on the validity of the BMI cutoff points. Small sample size is an important limitation of the study.


  Conclusions Top


WC can be used as screening tool to identify overweight and obesity, as it showed good sensitivity. Considerable variation in sensitivity was found among the study population in different studies. The findings of the present study and also the previous studies suggest that optimal screening cutoff points may be different in different populations. Unlike BMI, universal cutoff may not be possible with WC. More studies are needed to assess the relationship of different obesity surrogates to cardiovascular morbidity and mortality.

Acknowledgment

We are grateful to villagers of Jakanayakana koppa for participation.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

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Murray CL, Lopez AD. Global Health Statistics: Global Burden of Disease and Injury Series. Vol. 1, 2. Boston: Harvard School of Public Health; 1992.  Back to cited text no. 1
    
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Global BMI Mortality Collaboration, Di Angelantonio E, Bhupathiraju SH, Wormser D, Gao P, Kaptoge S, et al. Body-mass index and all-cause mortality: Individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet 2016;388:776-86.  Back to cited text no. 2
    
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World Health Organization. Fact Sheet: Obesity and Overweight. World Health Organization; 2016. Available from: http://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight. [Last accessed on 2018 Nov 13].  Back to cited text no. 3
    
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Shetty PS. Nutrition transition in India. Public Health Nutr 2002;5:175-82.  Back to cited text no. 4
    
5.
Pradeepa R, Anjana RM, Joshi SR, Bhansali A, Deepa M, Joshi PP, et al. Prevalence of generalized & abdominal obesity in urban & rural India – The ICMR-INDIAB study (Phase-I) [ICMR- NDIAB-3]. Indian J Med Res 2015;142:139-50.  Back to cited text no. 5
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Bhardwaj S, Misra A, Misra R, Goel K, Bhatt SP, Rastogi K, et al. High prevalence of abdominal, intra-abdominal and subcutaneous adiposity and clustering of risk factors among urban Asian Indians in North India. PLoS One 2011;6:e24362.  Back to cited text no. 6
    
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Pan WH, Yeh WT. How to define obesity? Evidence-based multiple action points for public awareness, screening, and treatment: An extension of Asian-Pacific recommendations. Asia Pac J Clin Nutr 2008;17:370-4.  Back to cited text no. 7
    
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DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: A nonparametric approach. Biometrics 1988;44:837-45.  Back to cited text no. 8
    
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Vanltallie TB. Waist circumference: A useful index in clinical care and health promotion. Nutr Rev 1998;56:300-2.  Back to cited text no. 9
    
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Karmakar A, Garg S, Dasgupta A, Paul B, Maharana SP. Sensitivity and specificity of waist circumference as a single screening tool for assessment of overweight and obesity. Int J Community Med Public Health 2017;4:4254.  Back to cited text no. 10
    
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Kee CC, Jamaiyah H, Geeta A, Ali ZA, Safiza MN, Suzana S, et al. Sensitivity and specificity of waist circumference as a single screening tool for identification of overweight and obesity among Malaysian adults. Med J Malaysia 2011;66:462-7.  Back to cited text no. 11
    
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de Koning L, Merchant AT, Pogue J, Anand SS. Waist circumference and waist-to-hip ratio as predictors of cardiovascular events: Meta-regression analysis of prospective studies. Eur Heart J 2007;28:850-6.  Back to cited text no. 12
    


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