Name: Antidepressant Use In Scandinavia
Creator: Kaggle
License: https://creativecommons.org/publicdomain/zero/1.0/

About this Dataset

Antidepressant Use In Scandinavia

Antidepressant Use in Scandinavia

A Study of Population Characteristics and Drug Utilization Rates

By [source]

About this dataset

This fascinating dataset examines the use of antidepressant medications among children and adolescents in Denmark, Norway, and Sweden from 2007 until 2017. Through a comprehensive exploration of drug usage along with population characteristics, we can uncover deeper insights into the prevalence of antidepressant use in this demographic and its potential causes. By carefully inspecting this data set which contains details about drug use, census data and associated drug names by code, we can shed light on an important issue with far reaching implications for public health worldwide

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How to use the dataset

This dataset offers an opportunity to analyze antidepressant use among children and adolescents in Denmark, Norway and Sweden from 2007 to 2017. To get started with your analysis, you'll need to familiarize yourself with the dataset. Below are some simple steps for getting acquainted with the available resources:

Familiarize yourself with the column descriptions and data types. Each column contains meaningful information about drug use and population characteristics in the three countries during this window of time.

Review the drug_names file contained in this dataset for a detailed list of drugs associated with each code represented in the main table. This is particularly important because ATC (Anatomical Therapeutic Chemical) codes provide an easy shorthand way of referring to individual medications without being too long-winded or cluttering up columns not relevant to your particular question or hypothesis

Explore correlations between different parameters using crosstabs, scatterplots, or other common visualizations as necessary

Use census data contained in census_data file as a reference when discussing population makeup within any given country during this period

With this approach, you will have all that's necessary to derive meaningful results out of this dataset! Good luck on your exploration!

Research Ideas

Comparing the sex, age and population weights of those using different types of antidepressants in each country

Tracking consumption trends across countries and between genders over time

Correlating antidepressant use with national income indicators such as GDP per capita or overall Mental Health Index scores

Acknowledgements

If you use this dataset in your research, please credit the original authors.
Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication
No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: census.csv

Column name	Description
year	Year of the data (Integer)
sex	Gender of the population (String)
age	Age group of the population (Integer)
cnt	Number of people using the drug (Integer)
country	Country of the population (String)

File: drug_names.csv

Column name	Description
atc	Anatomical Therapeutic Chemical (ATC) code for the drug. (String)
formalname	Formal name of the drug. (String)

Acknowledgements

If you use this dataset in your research, please credit the original authors.
If you use this dataset in your research, please credit .

Tables

Census

@kaggle.thedevastator_antidepressant_use_in_scandinavia.census

4.9 KB
198 rows
5 columns


CREATE TABLE census (
  "year" BIGINT,
  "sex" VARCHAR,
  "age" VARCHAR,
  "cnt" BIGINT,
  "country" VARCHAR
);

Drug Names

@kaggle.thedevastator_antidepressant_use_in_scandinavia.drug_names

3.24 KB
69 rows
2 columns


CREATE TABLE drug_names (
  "atc" VARCHAR,
  "formalname" VARCHAR
);

Drug Use

@kaggle.thedevastator_antidepressant_use_in_scandinavia.drug_use

81.01 KB
9579 rows
10 columns


CREATE TABLE drug_use (
  "atc" VARCHAR,
  "year" BIGINT,
  "sex" VARCHAR,
  "age" VARCHAR,
  "nusers" BIGINT,
  "ddd" DOUBLE,
  "users_pr_1000" DOUBLE,
  "ddd_pr_1000" DOUBLE,
  "country" VARCHAR,
  "drug_group" VARCHAR
);