给出以下方程式定义：
For men: (10 x w) + (6.25 x h) - (5 x a) + 5
For women:(10 x w) + (6.25 x h) - (5 x a) - 161
位置：
w = weight in kg (1 pound = 0.45359237 kilograms)
h = height in cm (1 inch = 2.54 centimeters)
a = age (in years)
活动因子类别定义：
1.2 if sedentary, little or no exercise and desk job
1.375 if lightly Active, light exercise, or sports 1-3 days a week
1.55 if moderately active, moderate exercise, or sports 3-5 days a week
1.725 if very active, hard exercise, or sports 6-7 days a week
1.9 if extremely active, hard daily exercise or sports and physical job
我正在尝试在给定N-1个变量的情况下进行逆向计算。
例如：
target_calories: 1500
gender: F
weight = 50
height = 170
What is her age?
age = (target_calories - ((10*w) + (6.25*h) + 5))/(-5)
我正在尝试将其概括，这是我到目前为止所做的：
var_table <- tibble(gender = "M",
w_kg = w_kg,
h_cm = h_cm,
age = age,
activity_factor = activity_factor)
var2calc <- names(which(sapply(var_table, anyNA)))
我可以使用许多if-else语句来解决此问题，但我正在尝试使其变得高效而优雅。
我考虑过以上tibble var_table + dplyr verbs中的计算，并给出了缺失的变量值，请根据特定公式进行计算。
请告知最佳方法是什么？