Validation of Obesity Status Based on Self-Reported Data among Filipina and Indonesian Female Migrant Domestic Workers in Macao (SAR), China
Lei Huang,
Wen Chen,
Andre M. N. Renzaho and
Brian J. Hall
Additional contact information
Lei Huang: Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong 999077, China
Wen Chen: Department of Medical Statistics, School of Public Health, Sun Yat-sen University, Guangzhou 510000, China
Andre M. N. Renzaho: School of Social Sciences and Translational Health Research Institute, Western Sydney University, Penrith 2750, Australia
Brian J. Hall: Global and Community Mental Health Research Group, Department of Psychology, Faculty of Social Sciences, University of Macau, Macau 999078, China
IJERPH, 2020, vol. 17, issue 16, 1-13
Abstract:
Background: Migrant domestic workers are at high risk of overweight and obesity. It is crucial to assess the prevalence of obesity among this migrant population, for surveillance and intervention. Self-reported height and weight are commonly used to derive body mass index (BMI) and assess the prevalence of obesity. The accuracy of BMI from self-reported height and weight in migrant populations remains unknown. The aim of this study was to assess the accuracy of BMI from self-reported measures and identify the optimal adjustment to be made to overweight and obesity cut-off points when using self-reported body mass index among migrant workers. Methods: Self-reported and objectively measured height and weight were obtained from 1388 female Filipina domestic workers and 369 female Indonesian domestic workers recruited using respondent-driven sampling between November 2016 and August 2017. Self-reported BMI (based on self-reported height and weight) and measured BMI (based on objectively measured height and weight) were calculated as weight in kilograms divided by the square of height in meters for all participants (kg/m 2 ). Results: BMI derived from self-reported height and weight was underestimated for both Filipina (z = −27.5, p < 0.001) and Indonesian (z = −9.9, p < 0.001) participants. Applying the gold standard of Asian BMI cut-off points to self-reported BMI, the sensitivity in identifying overweight or obesity was 64.4% for Filipina participants and 78.6% for Indonesian participants and the specificity was 97.9% for Filipina participants and 93.8% for Indonesian participants for overweight or obesity. When self-reported measures were used, the receiver operator characteristic (ROC) curves and the corresponding area under the curve (AUC) indicated optimal cut-off points of 22.0 kg/m 2 and 22.3 kg/m 2 for Filipina and female Indonesian participants for overweight or obesity. Conclusions: Although BMI derived from self-reported height and weight allows for quick and low-cost obesity screening, a considerable underestimation of overweight or obesity prevalence was observed in Filipina and female Indonesian migrant domestic workers in Macao (Special Administrative Region, SAR), China. With the best compromise between sensitivity and specificity, the new cut-off points can be used in future studies to identify overweight or obesity in these two populations using self-reported height and weight.
Keywords: body mass index; height; weight; self-report; cut-off; migrant workers (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://www.mdpi.com/1660-4601/17/16/5927/pdf (application/pdf)
https://www.mdpi.com/1660-4601/17/16/5927/ (text/html)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:17:y:2020:i:16:p:5927-:d:399379
Access Statistics for this article
IJERPH is currently edited by Ms. Jenna Liu
More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().