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.