Following a standard protocol, participants had a range of physical measurements collected by the trained staff using well‐calibrated instruments. Standing height was measured using a Seca 202 device. After the height measurements, weight and body composition were measured using a Tanita BC418MA body composition analyser. The analyser produces segmental readings of body composition for fat mass, fat‐free mass, and predicted muscle mass in the trunk, right arm, left arm, right leg, and left leg based on the bioelectrical impedance analysis. The right and left arms/legs were combined as a whole. We calculated the FMR as fat mass divided by the predicted muscle mass of the corresponding part and was categorized into quintiles (Q1–Q5) from the lowest (Q1) to highest (Q5) values. BMI was calculated as weight in kilograms divided by height in meters squared.
202 device
Manufactured by Seca
Sourced in Germany, United Kingdom
The Seca 202 is a portable and accurate height measurement device. It features a measuring range of 60 to 210 cm and provides precise height measurements to the nearest millimeter. The device is designed for easy and efficient use in medical and clinical settings.
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Lab products found in correlation
Bc418ma body composition analyser, by Tanita (4 mentions)
Bc418ma body composition analyzer, by Tanita (4 mentions)
Bc 418ma, by Tanita (3 mentions)
Ge lunar idxa, by GE Healthcare (2 mentions)
Bc418ma body composition analyser, by Seca (1 mentions)
Digital blood pressure monitor, by Omron (1 mentions)
705 it electronic blood pressure monitor, by Omron (1 mentions)
19 protocols using 202 device
1
Body Composition Assessment Protocol
2
Anthropometric Measurements in UK Biobank
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Weight and height were measured at the initial UK Biobank assessment centre—weight in light clothing and unshod was measured using Tanita BC418MA body composition analyser to the nearest 100g, and height to the nearest cm using at Seca 202 device. These were used to calculate BMI (kg/m2).
3
Cardiovascular Disease Risk Factors
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At baseline, the height of study participants was measured using a Seca 202 device at the assessment centre (field ID: 12144-0.0), body mass index was derived manually from measures of standing height and weight (field ID: 21001.0.0), systolic blood pressure was measured using an automated reading from an Omron Digital blood pressure monitor (field ID: 4080-0.0). Educational attainment was defined as in a previous study 47 , using questionnaire data on qualifications to estimate the number of years spent in full-time education (field ID: 6138). Coronary artery disease cases were diagnosed using International Classification of Disease (10 th edition) (ICD10) and Operating Procedure System (OPS) codes from either hospital events (Hospital Episode Statistics) or underlying cause of death from the death register.
The following ICD10 (I21, I22, I23, I24, I25, Z955) and OPS codes (K40-K46, K471, K49, K50, K75) 48 were used to classify diseased cases.
The following ICD10 (I21, I22, I23, I24, I25, Z955) and OPS codes (K40-K46, K471, K49, K50, K75) 48 were used to classify diseased cases.
4
Anthropometric Measures of Adiposity
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Body mass index (BMI), waist circumference (WC), whole body fat (WBF) and obesity constituted the primary measures of adiposity. Standing height (cm) was measured using a Seca 202 device and waist circumference (cm) was enumerated using a Wessex non-stretchable sprung tape. Weight and whole body fat mass was measured using electrical bio-impedance with the Tanita BC-418 MA body composition analyser.
Body Mass Index (BMI) was derived by dividing weight (kilograms) by square of standing height (square metres). Obesity was expressed as per as the World Health Organization's definition (cut-offs for BMI≥30 Kg/m 2 ). Anthropometrics were assessed by trained technicians at the collection centres as the participants wore light clothes and no shoes.
Body Mass Index (BMI) was derived by dividing weight (kilograms) by square of standing height (square metres). Obesity was expressed as per as the World Health Organization's definition (cut-offs for BMI≥30 Kg/m 2 ). Anthropometrics were assessed by trained technicians at the collection centres as the participants wore light clothes and no shoes.
5
Blood Pressure Measurement and Adjustment in UK Biobank
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Blood pressure was measured using the Omron 705 IT electronic blood pressure monitor (OMRON Healthcare Europe B.V. Kruisweg 577 2132 NA Hoofddorp). SBP and DBP were derived as the mean of the two recorded automated measurements (UK Biobank Fields 4079, 4080), except for 1,141 individuals who only had one recorded reading. MAP estimation was calculated using the traditional formula: MAP = DBP + 1/3(SBP-DBP). Height (Field 50) was measured using a Seca 202 device (Seca, Birmingham, UK). For individuals who reported use of anti-hypertensive medications through questionnaires in UK biobank (Fields 6177, 6153), their SBP and DBP were adjusting by adding 15 mmHg and 10 mmHg respectively to the mean recorded readings26 (link),37 (link). The ID numbers of the arterial stiffness devices used were obtained from Field 4206 in UK Biobank.
6
Anthropometric and Body Composition Measures
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At baseline, trained staff measured standing height using the Seca 202 device and body weight using the Tanita BC-418MA [28 ]. The Wessex non-stretchable sprung tape measure was used to measure waist and hip circumference. BMI was calculated as weight in kilograms divided by height in meters squared, waist-to-hip ratio was computed as waist circumference (cm) divided by hip circumference (cm) and waist-to-height ratio was computed as waist circumference (cm) divided by height (cm). The Tanita BC-418MA body composition analyser was used to assess bioelectrical impedance measures including total body fat percentage and trunk fat percentage. Measurements were performed on participants in light clothing after removal of shoes and heavier outer clothes. Participants were asked to stand briefly in bare feet on the analysers footpads and hold the handles where measurements of bio-impedance were taken.
7
Anthropometric Measurements in UK Biobank
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At the UK Biobank baseline interview, trained staff measured standing height using the Seca 202 device (Seca, Hamburg, Germany). BMI was calculated by dividing weight (kg) by the square of standing height (m2). The Wessex non-stretchable sprung tape measure (Wessex, UK) was used to measure waist circumference at the level of the umbilicus. The Tanita BC-418MA body composition analyzer (Tanita, Tokyo, Japan) was used to measure body fat per cent using bioelectrical impedance. DXA was used to measure fat per cent on a subset of 2457 participants included in the present study, beginning in 2014 using the GE-Lunar iDXA (GE Healthcare, Chicago, Illinois, USA).
8
Anthropometric and Body Composition Analysis
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At the enrolment visit, the Tanita BC418MA body composition analyser (Tanita, Tokyo, Japan) was used to measure the participants’ whole body fat mass, whole body fat percentage, whole body fat free mass, trunk fat mass, trunk fat percentage, trunk fat free mass and leg fat mass. The participants’ waist and hip circumferences were measured using Wessex nonstretchable sprung tape measures (Wessex, United Kingdom), and standing height was determined using the Seca 202 device (Seca, Hamburg, Germany). BMI, body fat mass index (FMI;15 (link),16 (link)) and trunk fat mass index (TFMI15 (link),16 (link)) were calculated by dividing weight (kg), whole body fat mass (kg.) and trunk fat mass (kg.), respectively, by the square of standing height (m2). Waist to hip ratio (WHR) was calculated by dividing waist circumference by the corresponding hip circumference.
9
Cardiovascular Risk Assessment Using Nonlaboratory FRS
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CVD risk was calculated at baseline (2006–2010) and first follow‐up (2014–2020) using the nonlaboratory FRS.2 This method estimates risk based on the following variables: age (categorical), sex (binary), BMI (categorical), systolic blood pressure (categorical), antihypertensive medication use (binary), smoking (binary), and diabetes status (binary) (Data S1 ). It differs from the original FRS method by using BMI instead of total cholesterol concentrations, which were not available in the UK Biobank for the time points used in this analysis.2 The change in nonlaboratory FRS from baseline (2006–2010) to first follow‐up (2014–2020) was used, because the change followed a normal distribution. A binary variable was created for FRS indicating low (<10%) and high (>10%) CVD risk.41 , 42 Weight (in kilograms) was measured by digital scales (Tanita BC‐418MA body analyzer; Tanita Corporation of America, Arlington Heights, IL), and standing height (in centimeters) was measured using a Seca 202 device (Seca, Hamburg, Germany).43 BMI (in kilograms per square meter) was calculated from information on weight (in kilograms) divided by height (in meters) squared. These were grouped into underweight (≤18.5 kg/m2), normal weight (>18.5 to ≤24.9 kg/m2), overweight (>24.9 to ≤29.9 kg/m2), or obese (>29.9 kg/m2) according to World Health Organization classification.44
10
Comprehensive Body Composition Evaluation
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UK Biobank evaluated FM (kg) and FFM (kg) with electrical bio‐impedance (Tanita BC418MA body composition analyzer) at baseline interview. The whole body as well as site‐specified (truck, leg, and arm) FM/FFM were evaluated. Detailed descriptions of the procedures used to measure body composition can be found on the study website.14 UK Biobank also evaluated body composition in 5170 participants using dual‐energy X‐ray absorptiometry(DXA). Assessment of body composition by bio‐impedance and DXA showed high correlation (FFM: r = 0.96, FM: r = 0.86). Trained staff measured standing height using the Seca 202 device (Seca, Hamburg, Germany) and assessed waist/hip circumference with the Wessex non stretchable sprung tape measure (Wessex, United Kingdom). BMI was calculated as the ratio of weight to squared height. We obtained WHR by dividing waist circumference by hip circumference.
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