ArticlePloS one2019
Usefulness of waist-to-height ratio in screening incident metabolic syndrome among Japanese community-dwelling elderly individuals.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 33 citations in OpenAlex.
- A waist-to-height ratio of 0.50 marks declining physical performance in active adults.European journal of clinical nutrition · 2026Article
- Lipid-adiposity indices outperform traditional and derived anthropometric and biochemical indices for discriminating individuals with metabolic syndrome.Frontiers in endocrinology · 2026Article
- Examining determinants of control of metabolic syndrome among older adults with NCDs receiving service at NCD Plus clinics: multilevel analysis.BMC health services research · 2024Article
- Impact of Obesity on Target Organ Damage in Patients with Metabolic Syndrome.Diagnostics (Basel, Switzerland) · 2024Article
- Associations between the waist-to-height ratio index and migraine: A cross-section study of the NHANES 1999-2004.PloS one · 2024Article
- Metabolic Syndrome and Menopause: The Impact of Menopause Duration on Risk Factors and Components.International journal of women's health · 2024Article
- Surrogate indices of insulin resistance using the Matsuda index as reference in adult men-a computational approach.Frontiers in endocrinology · 2024Article
- Diagnostic Accuracy of Waist-to-Height Ratio, Waist Circumference, and Body Mass Index in Identifying Metabolic Syndrome and Its Components in Older Adults: A Systematic Review and Meta-Analysis.Current developments in nutrition · 2024Article
- Relationship Between Neck Circumference and Risk Factors of Metabolic Syndrome in a Bushehr Elderly Health Study.Cureus · 2023Article
- Thigh-hip ratio is significantly associated with all-cause mortality among Japanese community-dwelling men.PloS one · 2023Article
- Metabolic Syndrome and Body Composition Among People Aged 50 Years and Over: Results from The Neyshabur Longitudinal Study on Ageing (NeLSA).Indian journal of clinical biochemistry : IJCB · 2022Article
- Using noninvasive anthropometric indices to develop and validate a predictive model for metabolic syndrome in Chinese adults: a nationwide study.BMC endocrine disorders · 2022Article
- Review
- Comparison of Various Obesity-Related Indices for Identification of Metabolic Syndrome: A Population-Based Study from Taiwan Biobank.Diagnostics (Basel, Switzerland) · 2020Article
- New Simplified Diagnostic Decision Trees for the Detention of Metabolic Syndrome in the Elderly.International journal of environmental research and public health · 2020Article
- External validation of the relative fat mass (RFM) index in adults from north-west Mexico using different reference methods.PloS one · 2019Article
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study examined a range of anthropometric indices and their relationships with metabolic syndrome (MetS). Despite recommendations that central obesity assessment should be employed as a marker of metabolic health, there is no consensus regarding the protocol for measurement. The present study included 720 men aged 71 ± 8 years and 919 women aged 71 ± 7 years from a rural village. We examined the relationship between anthropometric indices {e.g., body mass index (BMI), waist-to-height ratio (WHtR), waist-to-hip ratio (WHpR)}, and MetS based on the modified criteria of the National Cholesterol Education Program's Adult Treatment Panel (NCEP-ATP) III report in a cross-sectional (N = 1,639) and cohort (N = 377) data. A receiver operating curve (ROC) analysis was performed to determine the optimal cut-off value and best discriminatory value of each of these anthropometric indices to predict MetS. In the cross-sectional study, WHtR as well as BMI and WHpR showed significantly predictive abilities for MetS in both genders; and WHtR showed the strongest predictive ability for the presence of MetS. Also in the cohort study, WHtR as well as BMI and WHpR showed significantly predictive abilities for incident MetS in both genders, and in men WHtR showed the strongest predictive ability for incident MetS, but in women BMI showed the strongest predictive ability. In the cross-sectional study, the optimal WHtR cutoff values were 0.52 (sensitivity, 71.0%; specificity, 77.9%) for men and 0.53 (sensitivity, 79.8%; specificity, 75.7%) for women. In the cohort study, the optimal WHtR values were 0.50 (sensitivity, 60.7%; specificity, 73.2%) for men and 0.50 (sensitivity, 75.0%; specificity, 56.1%) for women. Increased WHtR was significantly and independently associated with prevalence of MetS in both genders. These results suggest that WHtR is a useful screening tool for determining metabolic risk in Japanese elderly community dwelling individuals.
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