Personalised measures of obesity using waist to height ratios from an Australian health screening program

Abstract

Objectives The aim of the current study is to generate waist circumference to height ratio cut-off values for obesity categories from a model of the relationship between body mass index and waist circumference to height ratio. We compare the waist circumference to height ratio discovered in this way with cut-off values currently prevalent in practice that were originally derived using pragmatic criteria. Method Personalized data including age, gender, height, weight, waist circumference and presence of diabetes, hypertension and cardiovascular disease for 847 participants over eight years were assembled from participants attending a rural Australian health review clinic (DiabHealth). Obesity was classified based on the conventional body mass index measure (weight/height 2 ) and compared to the waist circumference to height ratio. Correlations between the measures were evaluated on the screening data, and independently on data from the National Health and Nutrition Examination Survey that included age categories. Results This article recommends waist circumference to height ratio cut-off values based on an Australian rural sample and verified using the National Health and Nutrition Examination Survey database that facilitates the classification of obesity in clinical practice. Gender independent cut-off values are provided for waist circumference to height ratio that identify healthy (waist circumference to height ratio ≥0.45), overweight (0.53) and the three obese (0.60, 0.68, 0.75) categories verified on the National Health and Nutrition Examination Survey dataset. A strong linearity between the waist circumference to height ratio and the body mass index measure is demonstrated. Conclusion The recommended waist circumference to height ratio cut-off values provided a useful index for assessing stages of obesity and risk of chronic disease for improved healthcare in clinical practice.

Labisia pumila standardized extract (SKF7®) reduces percentage of waist circumference and waist‐to‐height ratio in individuals with obesity

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“…This step calls for the recruitment of obese participants defined by a combination of parameters to prevent bias, namely (a) WC >60% of height, (b) BMI, and (c) BW with or without comorbidities who were deemed medically healthy (treated or untreated). 20 The study participants were selected from six (four primary care clinics and two tertiary care hospitals) clinical sites between January 2020 and April 2021.…”

Big data analytics and internet of things for personalised healthcare: opportunities and challenges

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Emerging point of care devices and artificial intelligence: Prospects and challenges for public health

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