- 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
- Well Being Data
- Health Related Quality of Life
- Quality of Life Measures
- Quality of Life Scale
- Health Status Statistics
BRFSS Health Related Quality of Life
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).
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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.
About this Dataset
John Snow Labs; Centers for Disease Control and Prevention;
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Well Being Data, Health Related Quality of Life, Quality of Life Measures, Quality of Life Scale, Health Status Statistics
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
|Year||Identifies the year in which the data is collected for years 2010 and prior (1993-2017).||date||-|
|State_Abbreviation||The two-digit abbreviation to represent different states of United States.||string||-|
|State||Full description of different states of United States where the survey questionnaires belong.||string||-|
|Topic_Description||Depicts the topic within the survey of Behavioral Risk Factors (BRFs).||string||-|
|Survey_Question||The questions included in the survey questionnaire.||string||-|
|Response||The response received.||string||-|
|Data_Value_Type||It identifies the type of different data values.||string||-|
|Data_Value||The actual value or responses collected against each of the survey questions.||number||level : Ratio|
|Data_Value_Footnote||It identifies the actual footnote value or responses collected against each of the survey questions.||string||-|
|Low_Confidence_Limit||The lower limit of the confidence interval.||number||level : Ratio|
|High_Confidence_Limit||The upper limit of the confidence interval.||number||level : Ratio|
|Sample_Size||The sample size identifies the target individuals who gave responses to different survey questions.||integer||level : Ratio|
|Breakout||It identifies the actual Breakout value or responses collected against each of the survey questions.||string||-|
|Breakout_Category||It identifies the categories of different breakout values.||string||-|
|Latitude||Identifies the geographical location Latitude.||number||-|
|Longitude||Identifies the geographical location Longitude.||number||-|
|Topic_ID||The alphanumeric identity of the topic.||string||-|
|Question_ID||The identity of the survey questions.||string||-|
|Location_ID||The numerical identity of the location.||integer||level : Nominal|
|Response_ID||The alphanumeric identity of different responses.||string||-|
|Year||State Abbreviation||State||Topic Description||Survey Question||Response||Data Value Type||Data Value||Data Value Footnote||Low Confidence Limit||High Confidence Limit||Breakout||Breakout Category||Latitude||Longitude||Topic ID||Question ID||Location ID||Response ID|
|2012||GU||Guam||Age||What is your age?||55-64 years||Crude Prevalence||13.1||11.4||14.9||BO1||CAT1||13.444304||144.793731||Topic02||AGE||66||RESP014|
|2012||GU||Guam||Age||What is your age?||35-44 years||Crude Prevalence||21.2||18.1||24.2||SEX2||CAT2||13.444304||144.793731||Topic02||AGE||66||RESP012|
|2020||AL||Alabama||Depression||Ever told you that you have a form of depression?||Yes||Crude Prevalence||19.7||17.4||22.0||EDUCA4||CAT5||32.84057112||-86.63186076||TOPIC17||ADDEPEV3||1||RESP046|
|2020||AL||Alabama||Diabetes||Have you ever been told by a doctor that you have diabetes?||Yes, pregnancy-related||Crude Prevalence||0.8||0.5||1.1||RACE01||CAT4||32.84057112||-86.63186076||TOPIC18||DIABETE4||1||RESP051|
|2020||AL||Alabama||Diabetes||Have you ever been told by a doctor that you have diabetes?||No, pre-diabetes or borderline diabetes||Crude Prevalence||1.5||1.1||1.9||BO1||CAT1||32.84057112||-86.63186076||TOPIC18||DIABETE4||1||RESP052|
|2013||GU||Guam||Overall Health||How is your general health?||Excellent||Crude Prevalence||24.5||18.4||30.7||AGE01||CAT3||13.444304||144.793731||Topic41||GENHLTH||66||RESP056|
|2013||GU||Guam||Marital Status||What is your marital status?||Partnered||Crude Prevalence||7.8||5.2||10.5||EDUCA2||CAT5||13.444304||144.793731||Topic38||MARITAL||66||RESP038|
|2013||PR||Puerto Rico||Age||What is your age?||25-34 years||Crude Prevalence||20.4||17.4||23.3||EDUCA3||CAT5||18.220833||-66.590149||Topic02||AGE||72||RESP011|
|2020||AL||Alabama||Blood Stool Test||Adults aged 50-75 who have had a blood stool test within the past year (variable calculated from one or more BRFSS questions)||Had a blood stool test in the past year||Crude Prevalence||10.0||5.6||14.4||INCOME1||CAT6||32.84057112||-86.63186076||TOPIC08||_RFBLDS4||1||RESP190|
|2011||GU||Guam||Age||What is your age?||45-54 years||Crude Prevalence||18.5||11.1||25.8||RACE3||CAT4||13.444304||144.793731||Topic02||AGE||66||RESP013|