bw (version 1.0.0)

adult_weight: Dynamic Adult Weight Change Model

Description

Estimates weight change given energy and sodium intake changes at individual level.

Usage

adult_weight(bw, ht, age, sex, EIchange = matrix(0, ncol =
  abs(ceiling(days/dt)), nrow = length(bw)), NAchange = matrix(0, ncol =
  abs(ceiling(days/dt)), nrow = length(bw)), EI = NA, fat = rep(NA,
  length(bw)), PAL = rep(1.5, length(bw)), pcarb_base = rep(0.5,
  length(bw)), pcarb = pcarb_base, days = 365, dt = 1,
  checkValues = TRUE)

Arguments

bw

(vector) Body weight for model (kg)

ht

(vector) Height for model (m)

age

(vector) Age of individual (yrs)

sex

(vector) Sex either "female" or "male"

EIchange

(matrix) Matrix of caloric intake change (kcals)

NAchange

(matrix) Vector of sodium intake change (mg)

Optional

EI

(vector) Energy Intake at Baseline.

fat

(vector) Vector containing fat mass. Recall that

PAL

(vector) Physical activity level.

pcarb_base

(vector) Percent carbohydrates at baseline.

pcarb

(vector) Percent carbohydrates after intake change.

days

(double) Days to run the model.

dt

(double) Time step for model; default 1 day (dt = 1)

checkValues

(boolean) Check whether the values from the model are biologically feasible.

Details

EIchange and NAchange must be consumption change matrices. Each row should represent consumption at each day. That is, each row of EIchange and NAchange represents a day in consumption change since baseline. Consumption change is non-cummulative and it's all from baseline. As an example, EIchange <- rep(-100, 50) represents that each day -100 kcals are reduced from consumption.

References

Chow, Carson C, and Kevin D Hall. 2008. The Dynamics of Human Body Weight Change. PLoS Comput Biol 4 (3):e1000045.

Hall, Kevin D. 2010. Predicting Metabolic Adaptation, Body Weight Change, and Energy Intake in Humans. American Journal of Physiology-Endocrinology and Metabolism 298 (3). Am Physiological Soc: E449<U+2013>E466.

Hall, Kevin D, and Peter N Jordan. 2008. Modeling Weight-Loss Maintenance to Help Prevent Body Weight Regain. The American Journal of Clinical Nutrition 88 (6). Am Soc Nutrition: 1495<U+2013>1503.

Hall, Kevin D, Gary Sacks, Dhruva Chandramohan, Carson C Chow, Y Claire Wang, Steven L Gortmaker, and Boyd A Swinburn. 2011. Quantification of the Effect of Energy Imbalance on Bodyweight. The Lancet 378 (9793). Elsevier: 826<U+2013>37. A New Predictive Equation for Resting Energy Expenditure in Healthy Individuals. The American Journal of Clinical Nutrition 51 (2). Am Soc Nutrition: 241<U+2013>47.

See Also

model_plot for plotting the results and model_mean for aggregate data estimation. child_weight implements a similar model for children.

Examples

# NOT RUN {
#EXAMPLE 1: INDIVIDUAL MODELLING
#--------------------------------------------------------
#For one female in a diet of 100 kcal reduction. 
adult_weight(80, 1.8, 40, "female", rep(-100, 365))

#Same female also reducing sodium in -25mg
adult_weight(80, 1.8, 40, "female", rep(-100, 365), rep(-25, 365))

#Same female modelled for 400 days
adult_weight(80, 1.8, 40, "female", rep(-100, 400), rep(-25, 400), days = 400)

#Same female reducing -50 kcals per 100 days and not reducing sodium
kcalvec <-c(rep(-50, 100), rep(-100, 100), rep(-150, 100), rep(-200, 100))
adult_weight(80, 1.8, 40, "female", kcalvec, days = 400)

#Same female with known energy intake
adult_weight(80, 1.8, 40, "female", rep(-100, 365), rep(-25, 365), EI = 2000)

#Same female with known fat mass
adult_weight(80, 1.8, 40, "female", rep(-100, 365), rep(-25, 365), fat = 32)

#Same female with known fat mass and known energy consumption
adult_weight(80, 1.8, 40, "female", rep(-100, 365), rep(-25, 365), EI = 2000, fat = 32)

#EXAMPLE 2: DATASET MODELLING
#--------------------------------------------------------

#Antropometric data
weights <- c(45, 67, 58, 92, 81)
heights <- c(1.30, 1.73, 1.77, 1.92, 1.73)
ages    <- c(45, 23, 66, 44, 23)
sexes   <- c("male", "female", "female", "male", "male") 

#Matrix of energy consumption reduction: 
EIchange <- rbind(rep(-100, 365), rep(-200, 365), rep(-200, 365), 
                  rep(-123, 365), rep(-50, 365))

#Returns a weight change matrix and other matrices
model_weight <- adult_weight(weights, heights, ages, sexes, 
                             EIchange)["Body_Weight"][[1]]

# }