Within the context of public health, health-related quality of life (HRQOL) is recognized as an important health outcome, in addition to morbidity and mortality.1–3
HRQOL reflects an increased appreciation for not only how long one lives, but also how well one lives. HRQOL can encompass elements of physical health, mental health, social health, and role functioning.4,5
To stimulate the development of surveillance mechanisms for tracking HRQOL at the state and national levels, the Centers for Disease Control and Prevention (CDC) convened a group of experts in the early 1990s to develop a definition, conceptual model, and measures of HRQOL.6
The working group's efforts resulted in a set of four surveillance questions for inclusion in the Behavioral Risk Factor Surveillance System (BRFSS). The BRFSS is an ongoing random-digit-dialed telephone survey of non-institutionalized civilian adults (≥18 years of age) designed to assess risk and protective behaviors associated with disease. It is implemented in each state and U.S. territory, and is a key source of data for informing public health policy and practice.7–9
The four HRQOL questions measure: (1
) self-perceived health (excellent, very good, good, fair, or poor), (2
) number of days out of the past 30 that physical health was not good, (3
) number of days out of the past 30 that mental health was not good, and (4
) number of days out of the past 30 that usual activities were limited by poor physical or mental health. These four “core” questions were first included in the BRFSS in 19936
and have been included in each subsequent year.
In 1995, CDC added five supplemental “healthy days” questions in an optional BRFSS module. These five questions assess number of days out of the past 30 that the respondent has experienced pain interfering with usual activities; felt sad, blue, or depressed; felt worried, tense, or anxious; not gotten enough rest or sleep; or felt very healthy and full of energy. Together with the four core questions, these items have demonstrated good test-retest reliability10
and have been used with populations that vary in age, gender, race11,12
The healthy days questions have also been used to describe the health of groups with known health conditions including arthritis16
and to compare groups based on risk factors such as obesity.18
Use of the items individually, however, provides a series of information fragments about specific symptoms as opposed to a cohesive picture of health. Previous research indicates strong relationships among the core questions, suggesting that the items could be combined into summary scores.6
Empirically derived summary scores would reduce the potential for spurious findings by limiting the number of separate analyses needed in studying HRQOL. The richness of information provided by multiple items would be consolidated into a parsimonious, multidimensional assessment of population health.
Public health professionals currently combine two of the items (days physical health not good, and days mental health not good) into a summary measure called the Healthy Days Index.7
An alternative strategy for creating summary scores uses factor analysis. Factor analysis is a statistical method that examines numerical relationships among items to identify those factors (or latent variables) that describe the commonality among items. Factor analysis is a means of condensing information so that a small number of factors can be used to represent responses to a larger number of individual questions.19
Mielenz and colleagues20
conducted a factor analysis of the nine BRFSS HRQOL questions as answered by people with arthritis in North Carolina. Their analysis found two factors, or possible subscales, among these nine HRQOL items for their sample. The purpose of the present study was to examine the same nine HRQOL questions in large, multistate, population-based samples to determine whether the same or different underlying factors could be identified in the general population that would lead to the development of one or more summary scores. Such scores could be used to summarize population health, compare among groups, or describe changes in HRQOL based on multi-item constructs rather than individual questions.