L Score as a Novel Anthropometric Measure for Obesity Screening in Adult Individuals: An Exploratory Study
DOI:
https://doi.org/10.3889/oamjms.2020.3549Keywords:
L score, Obesity, Overweight, Retromalleolar fossa, ScreeningAbstract
BACKGROUND: Obesity is one of today’s most neglected public health problems, affecting every region of the world. Early identification of increased weight gain among the population is paramount to prevent the attendant complications associated with obesity.
OBJECTIVES: The primary objective of this study was to measure the distribution of L score in the representative population and the secondary objective was to identify an association between L score values and other measures of obesity such as body mass index, waist circumference, waist-to-height ratio, neck circumference (NC), and total body fat percentage.
METHODS: This study was conducted in the departments of plastic surgery and endocrinology of a tertiary care institute. The L score (a measure of fullness of the lateral retromalleolar fossa in the lower limb) was assessed in all the participating individuals. Statistical analysis was performed using the Statistical Package for the Social Sciences version 19.0. p < 0.05 was considered as statistically significant in statistical analysis.
RESULTS: Among the 50 participants taken in this study, 24 had L score 0, 15 had score 1, and 11 had score 2. The participants with L score 1 and 2 had higher obesity, higher NC, and more body fat percentage compared to those having score 0. All the participants with L score 2 were overweight and had central obesity.
CONCLUSIONS: The L score measure has a potential for simple and rapid screening of at-risk population for overweight and obesity.
Downloads
Metrics
Plum Analytics Artifact Widget Block
References
NCD Risk Factor Collaboration (NCD-RisC). Worldwide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: A pooled analysis of 2416 population-based measurement studies in 128•9 million children, adolescents, and adults. Lancet. 2017;390(10113):2627-42. https://doi.org/10.1530/ey.15.13.20 PMid:29029897
India Fact Sheet, National Family Health Survey-4, 2015-16. Available from: http://www.rchiips.org/nfhs/pdf/NFHS4/India.pdf. [Last accessed on 2019 Jan 21].
Kinlen D, Cody D, O’Shea D. Complications of obesity. QJM. 2018;111(7):437-43. https://doi.org/10.1093/qjmed/hcx152 PMid:29025162
Duren DL, Sherwood RJ, Czerwinski SA, Lee M, Choh AC, Siervogel RM, et al. Body composition methods: Comparisons and interpretation. J Diabetes Sci Technol. 2008;2(6):1139-46. https://doi.org/10.1177/193229680800200623 PMid:19885303
The WHO STEP Wise Approach to Chronic Disease Risk Factor Surveillance (STEPS) Instrument (Core and Expanded). Available from: http://www.who.int/ncds/surveillance/steps/STEPS_Instrument_v2.1.pdf. [Last accessed on 2019 Jan 20].
Misra A, Chowbey P, Makkar BM, Vikram NK, Wasir JS, Chadha D, et al. Consensus statement for diagnosis of obesity, abdominal obesity and the metabolic syndrome for Asian Indians and recommendations for physical activity, medical and surgical management. J Assoc Physicians India. 2009;57:163-70. PMid:19582986
Agarwal SK, Misra A, Aggarwal P, Bardia A, Goel R, Vikram NK, et al. Waist circumference measurement by site, posture, respiratory phase, and meal time: Implications for methodology. Obesity (Silver Spring). 2009;17(5):1056-61. https://doi.org/10.1038/oby.2008.635 PMid:19165166
Verma M, Rajput M, Sahoo SS, Kaur N. Neck circumference: Independent predictor for overweight and obesity in adult population. Indian J Community Med. 2017;42(4):209-13. https://doi.org/10.4103/ijcm.ijcm_196_16 PMid:29184320
Durnin JV, Womersley J. Body fat assessed from total body density and its estimation from skinfold thickness: Measurements on 481 men and women aged from 16 to 72 years. Br J Nutr. 1974;32(1):77-97. https://doi.org/10.1079/bjn19740060 PMid:4843734
Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr., et al. The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. JAMA. 2003;289(19):2560-72. https://doi.org/10.1001/jama.289.19.2560 PMid:12748199
Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem. 1972;18(6):499-502. https://doi.org/10.1093/clinchem/18.6.499 PMid:4337382
Misra A, Shrivastava U. Obesity and dyslipidemia in South Asians. Nutrients. 2013;5(7):2708-33. https://doi.org/10.3390/nu5072708 PMid:23863826
Romero-Saldaña M, Tauler P, Vaquero-Abellán M, López-González AA, Fuentes-Jiménez FJ, Aguiló A, et al. Validation of a non-invasive method for the early detection of metabolic syndrome: A diagnostic accuracy test in a working population. BMJ Open. 2018;8(10):e020476. https://doi.org/10.1136/bmjopen-2017-020476 PMid:30344164
Ahbab S, AtaoÄŸlu HE, Tuna M, Karasulu L, Cetin F, Temiz LU, et al. Neck circumference, metabolic syndrome and obstructive sleep apnea syndrome; evaluation of possible linkage. Med Sci Monit. 2013;19:111-7. https://doi.org/10.12659/msm.883776 PMid:23403781
Downloads
Published
How to Cite
Issue
Section
Categories
License
Copyright (c) 2020 Devi Prasad Mohapatra, Jaya Prakash Sahoo, Madhusmita Mohanty Mohaptra, Sitanshu Sekhar Kar, Sridharan Kalyani, Ayan Roy (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
http://creativecommons.org/licenses/by-nc/4.0