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In , Benn described BMI's fundamental statistical relationship as (Weight/ Height P) where the height power P (termed the Benn Index) is. height; and the relationship between weight and height differs significantly between males and females. The use of a single BMI standard for. Calculate BMI by dividing weight in pounds (lbs) by height in inches The correlation between the BMI and body fatness is fairly strong1,2,3,7.
Many studies in the paediatric literature have shown that the value of the Benn Index varies with gestational age 20 and during childhood development. First, we examine the impact of age on the BMI—height relationship between ages 16 and 75 years. Second, recognizing the increasing prevalence of overweight and obesity in England over the past two decades, 24 we explore whether or not the BMI—height relationship has changed over this time period.
Methodologically, we extend to an adult population our analyses of the BMI—height relationship in young children 15 and determine whether this relationship differs by gender, by age group, and over time, and explore for influences of potential confounders, such as smoking and income.
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Methods and procedures Data source The Health Survey for England HSE is a series of annual cross-sectional surveys, piloted in and run in full sinceto monitor the health of the English population. The survey methodology follows a multistage, stratified probability sampling design and originally had a sample ofbut this was increased to around 16 in A fresh sample of participants is invited each year by selecting private households at random in a geographically dispersed sampling frame. Weight is measured to the nearest g using electronic scales after removal of shoes or bulky clothing participants were not weighed if they were pregnant, unsteady on their feet or chair-bound.
Height, to the nearest millimetre, was measured using a portable stadiometer.
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We included only individuals where both a valid height and weight measurement were recorded. Those who were considered by the interviewer to have unreliable measurements were excluded from the analysis. We extracted the core variables of person identifier, year, age and validated with height and weight BMI, together with smoking status and equivalized household income for sensitivity analysis.
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Statistical analyses The relationship between height group by quartile and BMI was first explored graphically by gender and calendar time; simple regressions were used to assess the dependence of BMI on height, stratified by gender.
An F test was used to test for an interaction between height quartile and gender in a regression model with BMI as the outcome and height quartile, gender, and their interaction as predictors.
We then used a more complex regression model to investigate interactions and non-linear effects, in which log weight was taken as the response and regressed on log height as a continuous variable. We fitted separate models for males and females; we corrected for age and calendar time and allowed interactions between them.
The variable log height was constrained to be linear, but age and calendar time were allowed to have non-linear effects.
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Silver Spring14 3pp. Beyond body mass index.
Measures of body composition in blacks and whites: High adiposity and high body mass index-for-age in US children and adolescents overall and by race-ethnic group. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet,pp. Evaluation of body fat in fatter and leaner y-old African American and white children: Body-mass index and risk of 22 specific cancers: Epub Aug Inflammation- sensitive plasma proteins are associated with future weight gain.
Aug ; 52 Oxidative stress in obesity: