Validity of silhouette showcards as a measure of body size and obesity in a population in the African region: A practical research tool for general-purpose surveys
Tóm tắt
The purpose of this study is to validate the Pulvers silhouette showcard as a measure of weight status in a population in the African region. This tool is particularly beneficial when scarce resources do not allow for direct anthropometric measurements due to limited survey time or lack of measurement technology in face-to-face general-purpose surveys or in mailed, online, or mobile device-based surveys. A cross-sectional study was conducted in the Republic of Seychelles with a sample of 1240 adults. We compared self-reported body sizes measured by Pulvers’ silhouette showcards to four measurements of body size and adiposity: body mass index (BMI), body fat percent measured, waist circumference, and waist to height ratio. The accuracy of silhouettes as an obesity indicator was examined using sex-specific receiver operator curve (ROC) analysis and the reliability of this tool to detect socioeconomic gradients in obesity was compared to BMI-based measurements. Our study supports silhouette body size showcards as a valid and reliable survey tool to measure self-reported body size and adiposity in an African population. The mean correlation coefficients of self-reported silhouettes with measured BMI were 0.80 in men and 0.81 in women (P < 0.001). The silhouette showcards also showed high accuracy for detecting obesity as per a BMI ≥ 30 (Area under curve, AUC: 0.91/0.89, SE: 0.01), which was comparable to other measured adiposity indicators: fat percent (AUC: 0.94/0.94, SE: 0.01), waist circumference (AUC: 0.95/0.94, SE: 0.01), and waist to height ratio (AUC: 0.95/0.94, SE: 0.01) amongst men and women, respectively. The use of silhouettes in detecting obesity differences among different socioeconomic groups resulted in similar magnitude, direction, and significance of association between obesity and socioeconomic status as when using measured BMI. This study highlights the validity and reliability of silhouettes as a survey tool for measuring obesity in a population in the African region. The ease of use and cost-effectiveness of this tool makes it an attractive alternative to measured BMI in the design of non-face-to-face online- or mobile device-based surveys as well as in-person general-purpose surveys of obesity in social sciences, where limited resources do not allow for direct anthropometric measurements.
Tài liệu tham khảo
Haslam DW, James WP. Obesity. Lancet. 2005;366(9492):1197–209.
Stokes A. Using maximum weight to redefine body mass index categories in studies of the mortality risks of obesity. Popul Health Metr. 2014;12(1):6.
Fonda SJ, Fultz NH, Jenkins KR, Wheeler LM, Wray LA. Relationship of body mass and net worth for retirement-aged men and women. Research on Aging. 2004;26(1):153–76.
Heo M, Pietrobelli A, Fontaine KR, Sirey JA, Faith MS. Depressive mood and obesity in US adults: comparison and moderation by sex, age, and race. Int J Obes (Lond). 2006;30(3):513–9.
Karnehed N, Rasmussen F, Hemmingsson T, Tynelius P. Obesity and attained education: cohort study of more than 700,000 Swedish men. Obesity (Silver Spring). 2006;14(8):1421–8.
Klarenbach S, Padwal R, Chuck A, Jacobs P. Population-based analysis of obesity and workforce participation. Obesity (Silver Spring). 2006;14(5):920–7.
Loh ES. The economic effects of physical appearance. Soc Sci Q. 1993;74(2):420–38.
Register CA, Williams DR. Wage effects of obesity among young workers. Soc Sci Q. 1990;71:130–41.
Viner RM, Cole TJ. Adult socioeconomic, educational, social, and psychological outcomes of childhood obesity: a national birth cohort study. BMJ. 2005;330(7504):1354.
Kobau R , Bann C, Lewis M, Zack MM, Boardman AM, Boyd R, et al. Mental, social, and physical well-being in New Hampshire, Oregon, and Washington, 2010 Behavioral Risk Factor Surveillance System: implications for public health research and practice related to Healthy People 2020 foundation health measures on well-being. Popul Health Metr. 2013;11(1):19.
Burkhauser RV, Cawley J. Beyond BMI: the value of more accurate measures of fatness and obesity in social science research. J Health Econ. 2008;27(2):519–29.
Clinical Guidelines on the Identification, Evaluation, and Treatment of Overweight and Obesity in Adults--The Evidence Report. National Institutes of Health. Obes Res. 1998;6 Suppl 2:51S–209S.
WHO. STEPwise approach to surveillance (STEPS). 2014 [cited 2014 01.11.2014]; STEPwise approach to surveillance (STEPS)]. Available from: http://www.who.int/chp/steps/en/.
Hattori A, Sturm R. The obesity epidemic and changes in self-report biases in BMI. Obesity (Silver Spring). 2013;21(4):856–60.
Tsai EW , Perng W, Mora-Plazas M, Marin C, Baylin A, Villamor E. Accuracy of self-reported weight and height in women from Bogota. Colombia Ann Hum Biol. 2014;41(5):473–6.
Wen M, Kowaleski-Jones L. Sex and ethnic differences in validity of self-reported adult height, weight and body mass index. Ethn Dis. 2012;22(1):72–8.
Sagna ML, Schopflocher D, Raine K, Nykiforuk C, Plotnikoff R. Adjusting divergences between self-reported and measured height and weight in an adult Canadian population. Am J Health Behav. 2013;37(6):841–50.
Roberts RJ. Can self-reported data accurately describe the prevalence of overweight? Public Health. 1995;109(4):275–84.
Yoon K, Jang SN, Chun H, Cho S. Self-reported anthropometric information cannot vouch for the accurate assessment of obesity prevalence in populations of middle-aged and older Korean individuals. Arch Gerontol Geriatr. 2014;59(3):584–92.
Stunkard AJ, Sorensen T, Schulsinger F. Use of the Danish Adoption Register for the study of obesity and thinness. Res Publ Assoc Res Nerv Ment Dis. 1983;60:115–20.
Pulvers M, Lee RE, Kaur H, Mayo MS, Fitzgibbon ML, Jeffries SK, et al. Development of a Culturally Relevant Body Image Instrument among Urban African Americans. Obesity Res. 2004;12:1641–51.
Duda RB, Jumah NA, Hill AG, Seffah J, Biritwum R. Interest in healthy living outweighs presumed cultural norms for obesity for Ghanaian women. Health Qual Life Outcomes. 2006;4:44.
Jorga J, Marinkovic J, Maksimovic M, Kentric B, Dordevic I. Parent-child parallel nutritional status assessment using silhouette rating scales. Med Pregl. 2004;57(5–6):231–5.
Siervo M, Montagnese C, Muscariello E, Evans E, Stephan BC, Nasti G, et al. Weight loss expectations and body dissatisfaction in young women attempting to lose weight. J Hum Nutr Diet. 2014;27 Suppl 2:84–9.
Yepes M, Maurer J, Stringhini S, Viswanathan B, Gedeon J, Bovet P. Ideal body size as a mediator for the gender specific association between socioeconomic status and body mass index: Evidence from a low middle income country in the African region. Health Educ Behav. 2015. Manuscript ID HEB-15-0155.R1 (in Press).
Mak KK, McManus AM, Lai CM. Validity of self-estimated adiposity assessment against general and central adiposity in Hong Kong adolescents. Ann Hum Biol. 2013;40(3):276–9.
Nagasaka K, Tamakoshi K, Matsushita K, Toyoshima H, Yatsuya H. Development and validity of the Japanese version of body shape silhouette: relationship between self-rating silhouette and measured body mass index. Nagoya J Med Sci. 2008;70(3–4):89–96.
Acevedo P, Lopez-Ejeda N, Alferez-Garcia I, Martinez-Alvarez JR, Villarino A, Cabanas MD, et al. Body mass index through self-reported data and body image perception in Spanish adults attending dietary consultation. Nutrition. 2014;30(6):679–84.
Bulik CM, Wade TD, Heath AC, Martin NG, Stunkard AJ, Eaves LJ. Relating body mass index to figural stimuli: population-based normative data for Caucasians. Int J Obes Relat Metab Disord. 2001;25(10):1517–24.
Munoz-Cachon MJ, Salces I, Arroyo M, Ansotegui L, Rocandio AM, Rebato E. Overweight and obesity: prediction by silhouettes in young adults. Obesity (Silver Spring). 2009;17(3):545–9.
Adami F, Frainer DES, Almeida FD, de Abreu LC, Valenti VE, Demarzo MMP, et al. Construct validity of a figure rating scale for Brazilian adolescents. Nutrition J. 2012;11:6.
Conti MA, Ferreira ME, de Carvalho PH, Kotait MS, Paulino ES, Costa LS, et al. Stunkard Figure Rating Scale for Brazilian men. Eat Weight Disord. 2013;18(3):317–22.
Maupin JN, Hruschka DJ. Assessing the accuracy of two proxy measures for BMI in a semi-rural, low-resource setting in Guatemala. BMC Public Health. 2014;14:973.
Lynch EB, Kane J. Body size perception among African American women. J Nutr Educ Behav. 2014;46(5):412–7.
Brown SR, Hossain MB, Bronner Y. African American male and female student perceptions of Pulvers Body Images: implications for obesity, health care, and prevention. J Health Care Poor Underserved. 2014;25(3):1328–40.
Pulvers K, Bachand J, Nollen N, Guo H, Ahluwalia JS. BMI-based norms for a culturally relevant body image scale among African Americans. Eat Behav. 2013;14(4):437–40.
Pascal Bovet, William J, Viswanathan B, Madeleine G, Romain S, Yerly P, et al. The Seychelles Heart Study 2004: methods and main findings, M.o.H.a.S. Development, Editor. 2007: Victoria Republic of Seychelles.
National Bureau of Statistics. Employement and earnings by sector. National Bureau of Statistics 2013; Available from: http://www.nsb.gov.sc/.
WHO. Obesity and overweight. Fact sheet N°311 2015 [cited 2015 20.03.2015]; Available from: http://www.who.int/mediacentre/factsheets/fs311/en/.
Engstrom J. Assessment of the reliability of physical measures. Res Nursing Health. 1988;11:383–9.
Gorber SC, Tremblay M, Moher D, Gorber B. A comparison of direct vs. self-report measures for assessing height, weight and body mass index: a systematic review. Obesity Rev. 2007;8(4):307–26.
Harris CV, Bradlyn AS, Coffman J, Gunel E, Cottrell L. BMI-based body size guides for women and men: development and validation of a novel pictorial method to assess weight-related concepts. Int J Obes (Lond). 2008;32(2):336–42.