Dataset: Behavioral Risk Factor Surveillance

About this Dataset

Behavioral Risk Factor Surveillance

1993-2010 Health-Related Quality of Life Data

About this dataset

By monitoring trends, disparities, and determinants present within this dataset of HRQOL measures, public health programs can be made more effective. Population health needs can then be identified based upon fluctuations fo und in data sets such as these and used to inform decision making and development regarding policy and program changes.

The data provided in this set includes values from specific questions asked during surveys over the subject period, along with notation related to geography, category, topic addressed in the survey question ,data source ,value type ,unit type ,footnote symbols used to record responses as well sample size per response given or other special note relevant to individual entries found within this dataset regarding Health-Related Quality of Life records between 1993 - 2010

More Datasets

For more datasets, click here.

Featured Notebooks

🚨 Your notebook can be here! 🚨!

How to use the dataset

We will explain how you can use this dataset for further research into the topic areas it covers.

The first step is to become familiar with the columns within this dataset. Each column is defined by one or more attributes which describe what values it holds: Year, LocationAbbr, LocationDesc, Category, Topic, Question, DataSource, Data_Value_Unit, Data_Value_Type ,Data_Value_Footnote_Symbol ,Data_Value_StdErr ,Sample Size ,Break Out ,Break Out Category and GeoLocation.

Once you have familiarised yourself with these columns you can start exploring the data they contain by filtering or sorting information relating only to specific values or criteria. This process allows a researcher to focus on a specified area within their research piece rather than try decipher too much detail all at once from multiple sources of data inside one report/dataset. This process makes analysis much easier as analysis has been pre-processed for you meaning statistical tests according for example correlations are now much easy possible between those that meet your filter criteria in order make hypothesise about possible trends present in relation surveyed topic(s).

Furthermore once know what subset of data need analyse closer our secondary form analysis will require us define exact appropriate measures correctly measure performance against hypothesise theories on potential trends that were previously outlined through initial exploration filters applied earlier stage our research journey into taking closer look at certain results certain selection filters previously applied throughout initial preliminary exploration phase eliminate outliers configure appropriately settings accurately target right important resources help build case being investigated greater depth clarification understanding its wider context respective topics related HRQOL Surveillance datasets collection include Summary Measure Unhealthy Days BRFSS Validated Population Health Surveillance used formulate programmes policy developments make sure population get maximum benefit such services also Evaluation Programme via systems currently place track progress similar areas widely popular today both career field public healthcare sector .

Finally using all adopted methods described above effective way navigating understand uncovering mainly HRQOL Surveillance hopefully result quality well curated results create powerful impact meaningful solutions related preventable diseases long term plan battle those persistent worrying ailments highlighted particular subject matter timely manner which subsequently have positive effects knock

Research Ideas

Analyzing historical trends of HRQOL over time to inform public health policy and decision making,

Using the data to identify potential disparities in quality of life between gender, age, geographic areas or other groups, and

Investigating the impact of different initiatives on population health by comparing pre- and post-implementation trend data on the HRQOL measures

Acknowledgements

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

License

License: Open Database License (ODbL) v1.0

You are free to:

Share - copy and redistribute the material in any medium or format.

Adapt - remix, transform, and build upon the material for any purpose, even commercially.

You must:

Give appropriate credit - Provide a link to the license, and indicate if changes were made.

ShareAlike - You must distribute your contributions under the same license as the original.

Keep intact - all notices that refer to this license, including copyright notices.

No Derivatives - If you remix, transform, or build upon the material, you may not distribute the modified material.

No additional restrictions - You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

Columns

File: rows.csv

Column name	Description
Year	Year in which the data was collected. (Integer)
LocationAbbr	Abbreviation of the location from which the data was collected. (String)
LocationDesc	Description of the location from which the data was collected. (String)
Category	Type of question asked in the survey. (String)
Topic	Broad topic area related to the data. (String)
Question	Detailed information about the question asked. (String)
DataSource	Source of the data. (String)
Data_Value_Unit	Unit used for measurement purposes. (String)
Data_Value_Type	Type of answer given by respondents. (String)
Data_Value_Footnote_Symbol	Symbols used in association with the data. (String)
Data_Value_Std_Err	Standard error associated with the data. (Float)
Sample_Size	Total sample size related to the data. (Integer)
Break_Out	Specific breakdown categories identified within the data. (String)
Break_Out_Category	General category under which the breakdown has been placed. (String)
GeoLocation	Geographical location indicator for the data. (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 Health.

Tables

Rows

@kaggle.thedevastator_behavioral_risk_factor_surveillance.rows

1.43 MB
126464 rows
26 columns


CREATE TABLE rows (
  "index" BIGINT,
  "year" DOUBLE,
  "locationabbr" VARCHAR,
  "locationdesc" VARCHAR,
  "category" VARCHAR,
  "topic" VARCHAR,
  "question" VARCHAR,
  "datasource" VARCHAR,
  "data_value_unit" VARCHAR,
  "data_value_type" VARCHAR,
  "data_value" DOUBLE,
  "data_value_footnote_symbol" VARCHAR,
  "data_value_footnote" VARCHAR,
  "data_value_std_err" VARCHAR,
  "low_confidence_limit" DOUBLE,
  "high_confidence_limit" DOUBLE,
  "sample_size" DOUBLE,
  "break_out" VARCHAR,
  "break_out_category" VARCHAR,
  "geolocation" VARCHAR,
  "categoryid" VARCHAR,
  "topicid" VARCHAR,
  "questionid" VARCHAR,
  "locationid" BIGINT,
  "breakoutid" VARCHAR,
  "breakoutcategoryid" VARCHAR
);