BRFSS Health Related Quality of Life

$79 / year

This dataset includes information regarding the data are from the Behavioral Risk Factor Surveillance System (BRFSS). All respondents to the BRFSS are non-institutionalized adults, 18 years old or older. This dataset comprises of Topic Description, Survey Question, Data Value, High and Low Confidence Limits, Breakout Category, Geo Location Latitude and Longitude for Health Related Quality of Life (HRQOL).

Complexity

The Behavioral Risk Factor Surveillance System (BRFSS) which is also the data source for this dataset, is a continuous, state-based surveillance system that collects information about modifiable risk factors for chronic diseases and other leading causes of death. This dataset is provided by Centers for Disease Control and Prevention (CDC), National Center for Chronic Disease Prevention and Health Promotion Division of Population Health, Health-Related Quality of Life Annual trend data.

Health Related Quality of Life (HRQOL) surveillance is used to identify unmet population health needs including recognizing trends, disparities, and determinants of health in the population. Self-assessed health status is also a more powerful predictor of mortality and morbidity than many objective measures of health. HRQOL measures make it possible to demonstrate scientifically the impact of health on quality of life, going well beyond the old paradigm that was limited to what can be seen under a microscope.

HRQOL surveillance data can be used to inform decision making, and program and policy development. To assure that the population is benefiting from public health programs, HRQOL surveillance data can be used for program evaluation. A compact set of HRQOL measures including a summary measure of unhealthy days have been developed and validated for population health surveillance and have been widely used since 1993.

Focusing on HRQOL as an outcome can bridge boundaries between disciplines and between social, mental, and medical services. Several recent federal policy changes underscore the need for measuring HRQOL to supplement public health’s traditional measures of morbidity and mortality. Healthy People 2000, 2010, and 2020 identified quality of life improvement as a central public health goal.

– HRQOL is related to both self-reported chronic diseases (diabetes, breast cancer, arthritis, and hypertension) and their risk factors (body mass index, physical inactivity, and smoking status).
– Measuring HRQOL can help determine the burden of preventable disease, injuries, and disabilities, and can provide valuable new insights into the relationships between HRQOL and risk factors.
– Measuring HRQOL will help monitor progress in achieving the nation’s health objectives.

Analysis of HRQOL surveillance data can identify subgroups with relatively poor perceived health and help to guide interventions to improve their situations and avert more serious consequences. Interpretation and publication of these data can help identify needs for health policies and legislation, help to allocate resources based on unmet needs, guide the development of strategic plans, and monitor the effectiveness of broad community interventions.

This dataset belongs to the category of Health Status/Healthy Days. The data value unit used for analysis in this dataset is percentage. The Category ID used here is HLT001.

Date Created

2015-06-03

Last Modified

2017-10-26

Version

2017-10-26

Update Frequency

Irregular

Temporal Coverage

1993-2010

Spatial Coverage

United States

Source

John Snow Labs => Centers for Disease Control and Prevention

Source License URL

John Snow Labs Standard License

Source License Requirements

N/A

Source Citation

N/A

Keywords

Well Being Data, Health Related Quality of Life, Quality of Life Measures, Quality of Life Scale, Health Status Statistics

Other Titles

BRFSS Health Related Well Being Data, BRFSS Health Related Quality of Life, BRFSS Quality of Life Measures, Vital Behavioral Risk Factors Data for Health Related Quality of Life, Using BRFSS to Analyze Health Related Quality of Life

Name Description Type Constraints
YearIdentifies the year in which the data is collected for years 2010 and prior (1993-2010).date-
State_AbbreviationThe two-digit abbreviation to represent different states of United States.stringrequired : 1
StateFull description of different states of United States where the survey questionnaires belong.stringrequired : 1
Topic_DescriptionDepicts the topic within the survey of Behavioral Risk Factors (BRFs).stringrequired : 1 enum : Array
Survey_QuestionThe questions included in the survey questionnaire.stringrequired : 1
Data_Value_TypeIt identifies the type of different data values.stringrequired : 1 enum : Array
Data_ValueThe actual value or responses collected against each of the survey questions.numberlevel : Ratio
Data_Value_FootnoteIt identifies the actual footnote value or responses collected against each of the survey questions.string-
Low_Confidence_LimitThe lower limit of the confidence interval.numberlevel : Ratio
High_Confidence_LimitThe upper limit of the confidence interval.numberlevel : Ratio
Sample_SizeThe sample size identifies the target individuals who gave responses to different survey questions.integerlevel : Ratio
BreakoutIt identifies the actual Breakout value or responses collected against each of the survey questions.stringrequired : 1 enum : Array
Breakout_CategoryIt identifies the categories of different breakout values.stringrequired : 1 enum : Array
LatitudeIdentifies the geographical location Latitude.-
LongitudeIdentifies the geographical location Longitude.-
Topic_IDThe alphanumeric identity of the topic.stringrequired : 1
Question_IDThe identity of the survey questions.stringrequired : 1
Location_IDThe numerical identity of the location.integerrequired : 1 level : Nominal
Breakout_IDThe alphanumeric identity of different responses.stringrequired : 1
Breakout_Category_IDRefers to the categories ID for different breakout values.stringrequired : 1
YearState_AbbreviationStateTopic_DescriptionSurvey_QuestionData_Value_TypeData_ValueData_Value_FootnoteLow_Confidence_LimitHigh_Confidence_LimitSample_SizeBreakoutBreakout_CategoryLatitudeLongitudeTopic_IDQuestion_IDLocation_IDBreakout_IDBreakout_Category_ID
USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.92.83734417MaleGenderMENTHLTHMHL00259GEN2GPSEX
USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.122.225767275+Age GroupMENTHLTHMHL00259Age7GPAGE
USNationwideMental HealthMean mentally unhealthy daysAverage number of days43.94.11200442FemaleGenderMENTHLTHMHL00259GEN3GPSEX
2003USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.92.7398039MaleGenderMENTHLTHMHL00259GEN2GPSEX
2010USNationwideMental HealthMean mentally unhealthy daysAverage number of days32.93.1157620MaleGenderMENTHLTHMHL00259GEN2GPSEX
2008USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.92.73145873MaleGenderMENTHLTHMHL00259GEN2GPSEX
2007USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.92.73150971MaleGenderMENTHLTHMHL00259GEN2GPSEX
2004USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.92.73110127MaleGenderMENTHLTHMHL00259GEN2GPSEX
1995USNationwideMental HealthMean mentally unhealthy daysAverage number of days21.72.3866575+Age GroupMENTHLTHMHL00259Age7GPAGE
2010USNationwideMental HealthMean mentally unhealthy daysAverage number of days2.122.26151975+Age GroupMENTHLTHMHL00259Age7GPAGE