Obesity Worlds

In this dataset, various factors are considered to analyze the health and lifestyle of respondents. The binary variable "Gender" takes a value of 1 for males and 0 for females. "Age" represents the respondent's age in years, providing insight into the demographic composition. The presence of a family history of overweight individuals is denoted by the variable "family_history_with_overweight," where 1 signifies the existence of such a history and 0 indicates the absence.

Dietary habits are reflected in variables such as "FAVC," indicating frequent consumption of high-caloric foods, and "FCVC," denoting the regular intake of vegetables. The number of main meals consumed daily is captured by "NCP," with values of 0, 1, and 2 representing 1-2 meals, 3 meals, and more than 3 meals, respectively. "CAEC" quantifies the amount of food consumed between meals on a scale from 0 to 3.

Health-related behaviors include "SMOKE," indicating smoking habits, and "CH2O," measuring daily water intake on a scale of 0 to 2. The monitoring of caloric intake is represented by "SCC," where 1 signifies adherence to such monitoring. Physical activity levels are expressed through "FAF," ranging from 0 to 3. The time spent looking at screens is captured by "TUE" on a scale of 0 to 2, providing insights into sedentary behaviors.

Alcohol consumption frequency is coded in "CALC," with values ranging from 0 to 3. Modes of transportation are illustrated by the variables "Automobile," "Bike," "Motorbike," "Public_Transportation," and "Walking," each having a value of 1 for the respondent's primary mode and 0 for others.

The target variable, "NObeyesdad," categorizes respondents as obese (1) or not (0), offering a crucial health indicator. This dataset amalgamates diverse aspects of lifestyle, dietary choices, and health-related behaviors, enabling a comprehensive analysis of factors influencing obesity. By examining the interplay of these variables, researchers and healthcare professionals can gain valuable insights into patterns and trends contributing to obesity within this population.