Population-Based Health Measure, Part I: Can Commonly Used Survey Items be Grouped to Reflect Key Aspects of Health-Related Quality of Life?

Willi Horner-Johnson, PhD*, Gloria Krahn, PhD, MPH, Elena Andresen, PhD, Trevor Hall, PsyD & the RRTC Expert Panel on Health Status Measurement

*Presenting Author

Introduction

Health related quality of life (HRQOL) is an important indicator of public health. HRQOL reflects an increased appreciation for not only how long one lives, but also how well. HRQOL can encompass elements of physical health, mental health, social health, and role functioning.

The Centers for Disease Control and Prevention’s (CDC) Behavioral Risk Factor Surveillance System (BRFSS) includes a number of HRQOL items that can be used to monitor the health status of the nation. A 4-item set of HRQOL questions has been in continuous use since 1993. The first of these questions measures perceived general health (excellent, very good, good, fair, or poor). The remaining questions ask how many days out of the past thirty the respondent has had poor physical health, poor mental health, or activities limited by poor health. Five additional “healthy days” questions addressing pain, stress, depression, sleep, and vitality were included as an optional BRFSS module beginning in 1995.

The BRFSS HRQOL items have typically been analyzed independently. However, previous research indicates strong relationships among the core questions, suggesting that the items could be combined into 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.

Research Objective

The objective of this study was to examine relationships among the BRFSS HRQOL items in order to: 1) develop summary scores by combining items, and 2) determine what key aspects of HRQOL can be measured using these summary scores.

Methods

The BRFSS is a telephone survey of non-institutionalized adults (age 18 or older). The survey focuses on key health risk and protective factors. It is implemented in each state and U.S. territory, and is a key source of information for public health policy and practice.

This study used 2001 and 2002 BRFSS data from the states and territories that included all nine HRQOL questions in those years. Twelve states (Alaska, Arizona, Delaware, Georgia, Maryland, Minnesota, Nebraska, New Jersey, Ohio, Tennessee, Utah, Virginia) and the District of Columbia used all nine HRQOL questions in 2001, yielding a sample size of 47,179. Nine states (California, Hawaii’i, Iowa, Kentucky, Minnesota, Missouri, New Jersey, Rhode Island, Virginia) and Guam used all nine questions in 2002, resulting in a sample size of 45,413. We conducted initial analyses with 2001 data and repeated them with 2002 data.

We used an analysis method called exploratory factor analysis. Factor analysis is a statistical method that examines numerical relationships among items to identify factors (or latent variables) that describe the commonality among items. Factor analysis is a way of condensing information so that a small number of factors can be used to represent responses to a larger number of individual questions.

Results

A two-factor structure emerged from both years of data. The two factors reflected two aspects of HRQOL: physical and mental. Our findings did not identify any additional components of HRQOL as measured by the nine HRQOL items of the BRFSS. Factor loadings from 2001 are shown in Table 1. Items were considered to load on a factor if they were above 0.40. If an item loaded above 0.40 on both factors, the item was assigned to the factor on which it had the highest loading, provided there was a difference of at least 0.25. Factor loadings using the 2002 data were very similar to those shown for 2001.

Table 1: Factor Loadings from 2001 Data

The general health item loaded only on the physical HRQOL factor. This finding suggests that using this single question may be useful for assessing physical health, but is less helpful for assessing HRQOL more broadly. Days physical health not good, days activities limited, and pain days also were part of the physical factor.

The mental HRQOL factor included days mental health not good, stress days, depressed days, and days without enough rest or sleep. The question about feeling very healthy and full of energy loaded on both factors. This may be because it is measuring two separate issues. Feeling very healthy is likely to be interpreted primarily in terms of physical health (as is the case with the general health item), whereas feeling full of energy may be more closely related to feelings of getting enough rest or sleep, which was part of the mental health factor in this study.

Summary scores for physical and mental HRQOL were created based on the items that loaded on each factor. Because the question about feeling healthy and full of energy loaded about equally on both factors, we decided not to include it in each summary score. Therefore, there were two scales with four items each. Both scales demonstrated acceptable reliability. The physical HRQOL scale had an alpha of 0.78 in 2001 and 0.77 in 2002. The mental HRQOL scale had an alpha of 0.78 in both 2001 and 2002.

We used the summary scores we found to compare groups of people based on various chronic conditions measured by the BRFSS. We found that adults with diabetes, arthritis, or asthma scored lower on both the physical and the mental HRQOL scales. Adults over age 65 scored lower on the physical HRQOL scale than younger adults, but scored higher on the mental HRQOL scale. These group differences are consistent with previous research.

Conclusions

This study provides support for condensing eight of the nine HRQOL questions used in the BRFSS into two summary scores or scales for measuring physical HRQOL and mental HRQOL.

Implications

These scales provide a means of including more complete information about physical and mental HRQOL than is available from single items, while limiting the number of individual variables required for a given analysis. Understanding more about these questions and how they measure HRQOL in the general population provides a foundation for examining how the measures perform for specific groups of people. The next step of our analyses is to determine whether the same factor structure applies to people with and without disabilities.

Reference

A full write-up of this study is published in Public Health Reports:

Horner-Johnson, W., Krahn, G.L., Andresen, E.M., Hall, T., and the RRTC: Health & Wellness Expert Panel on Health Status Measurement. (2009). Developing summary scores of health-related quality of life for a population-based survey. Public Health Reports, 124(1).

 

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