Classification models are built on a data set of 10 632853853 diabetic and 7779 non-diabetic) participants; these participants (chosen irrespective of their diagnosis for hypertension) have complete records of height, weight, age, gender, ethnicity, hypertension diagnosis and a family history of hypertension and diabetes.
Classification models are built on a data set of 10 6759(6759 hypertensive and 3873 non-hypertensive) participants; these participants (chosen irrespective of their diagnosis for diabetes) have complete records of height, weight, age, gender, ethnicity, diabetes diagnosis and a family history of hypertension and diabetes.
(ii) Body mass index (BMI): based on self-recording of height and current weight.
All subjects underwent physical examination with recording of height, weight, heart rate, systolic and diastolic blood pressure.
A single record of height (to the nearest centimetre) and weight (to the nearest 10th of a kilogram) was taken in light summer clothes without shoes.
All patients had a full history and physical examination, including an accurate recording of height, weight and assessment of pubertal status.
Data collection included sociodemographic characteristics (education, occupation, and income), lifestyle (smoking, drinking, and food frequency questionnaire), assessment of disability (Instrumental Activities of Daily Living scale), global cognitive functioning (Mini Mental State examination) and depression (Centre for Epidemiologic Studies-Depression scale), and recording of height and weight.
These include records of plume height, velocity, acceleration, shape, volume, ash (fine-particle) loading, spreading rate, entrainment coefficient and inclination angle, as well as axial and radial profiles for radius and temperature (if data are radiometric).
Records of neonatal height, body weight and head circumference were compared with those published by the World Health Organization [ 15].
The school health records included measurements of height, weight, and time of measurement (year and month).
Routine recording of GNSS height of a navigating ferryboat may be useful for monitoring of sea-surface height spatiotemporal variations that reflect the Tsushima Warm Current (Ichikawa et al. 2013).
