The relationship between SF-6D utility scores and lifestyle factors across three life stages: evidence from the Australian Longitudinal Study on Women’s Health

Association of body mass index from childhood to mid-adulthood with health-related quality of life in mid-adulthood

PURPOSE

Most studies regarding the association of obesity with health-related quality of life (HRQoL) have assessed obesity at only one or two time points. We aimed to examine the associations of life course body mass index (BMI) from childhood with health-related quality of life (HRQoL) in mid-adulthood.

METHODS

Data were from a cohort study of Australian children (n = 2254, mean baseline age 12.0 (2.0) years in 1985, 46.8% male). Weight and height were measured at baseline and measured or self-reported on average 20, 25, and 30 years later. Age and sex-standardised BMI-z score was calculated at each time point. Physical and mental HRQoL and health state utilities (HSUs) were measured by SF-12 and SF-6D at the last adult follow-up. Linear regression was used to examine the associations adjusting for age, sex, and childhood health status.

RESULTS

Higher BMI-z score in childhood (βadjusted - 1.39, 95% CI - 1.73 to - 1.05) and increasing BMI-z score from childhood to young adulthood (βadjusted - 1.82, 95% CI - 2.17 to - 1.46) and from young to mid-adulthood (βadjusted - 1.77, 95% CI - 2.28 to - 1.26) were associated with lower physical HRQoL in mid-adulthood. Similar results were found for mid-adulthood HSUs (βadjusted ranged - 0.006 to - 0.014, all P < 0.05). Only increasing BMI-z score from young to mid-adulthood significantly related to poorer mental HRQoL (βadjusted - 0.74, 95% CI - 1.29 to - 0.19) in mid-adulthood.

CONCLUSION

High BMI from childhood to mid-adulthood had only modest associations with HRQoL and HSUs, with effects on physical HRQoL most apparent.

Impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life of Australians: a population-based longitudinal data analysis

Background

Health risk factors, including smoking, excessive alcohol consumption, overweight, obesity, and insufficient physical activity, are major contributors to many poor health conditions. This study aimed to assess the impact of health risk factors on healthcare resource utilization, work-related outcomes and health-related quality of life (HRQoL) in Australia.

Methods

We used two waves of the nationally representative Household, Income, and Labor Dynamics in Australia (HILDA) Survey from 2013 and 2017 for the analysis. Healthcare resource utilization included outpatient visits, hospitalisations, and prescribed medication use. Work-related outcomes were assessed through employment status and sick leave. HRQoL was assessed using the SF-6D scores. Generalized estimating equation (GEE) with logit or log link function and random-effects regression models were used to analyse the longitudinal data on the relationship between health risk factors and the outcomes. The models were adjusted for age, sex, marital status, education background, employment status, equilibrium household income, residential area, country of birth, indigenous status, and socio-economic status.

Results

After adjusting for all other health risk factors covariates, physical inactivity had the greatest impact on healthcare resource utilization, work-related outcomes, and HRQoL. Physical inactivity increased the likelihood of outpatient visits (AOR = 1.60, 95% CI = 1.45, 1.76 p < 0.001), hospitalization (AOR = 1.83, 95% CI = 1.66-2.01, p < 0.001), and the probability of taking sick leave (AOR = 1.31, 95% CI = 1.21-1.41, p < 0.001), and decreased the odds of having an above population median HRQoL (AOR = 0.48, 95% CI = 0.45-0.51, p < 0.001) after adjusting for all other health risk factors and covariates. Obesity had the greatest impact on medication use (AOR = 2.02, 95% CI = 1.97-2.29, p < 0.001) after adjusting for all other health risk factors and covariates.

Conclusion

Our study contributed to the growing body of literature on the relative impact of health risk factors for healthcare resource utilization, work-related outcomes and HRQoL. Our results suggested that public health interventions aim at improving these risk factors, particularly physical inactivity and obesity, can offer substantial benefits, not only for healthcare resource utilization but also for productivity.

Large-Scale Population-Based Surveys Linked to Administrative Health Databases as a Source of Data on Health Utilities in Australia

OBJECTIVES

Large-scale health surveys that contain quality-of-life instruments are a rich source of health utility data for health economic evaluations, especially when linked to routinely collected, administrative health databases. We derived health utility values for a wide range of health conditions using a large Australian cohort study linked to population-wide health databases.

METHODS

Short-Form 6-Dimension utility values were calculated for 56 094 adults, aged 47+ years, in the New South Wales 45 and Up Study who completed the Social, Economic, and Environmental Factors survey (2010-2011). Mean utilities were summarized for major health conditions identified through self-report, hospital records, primary cancer notifications, and claims for government-subsidized prescription medicines and medical services. To identify unique associations between health conditions and utilities, beta regression was performed. Utility values were analyzed by time to death using linked death records.

RESULTS

Mean Short-Form 6-Dimension utility was 0.810 (95% confidence interval [CI] 0.809-0.811), was age dependent, and was higher in men than women. Utilities for serious health conditions ranged from 0.685 (95% CI 0.652-0.718) for lung cancer to 0.800 (95% CI 0.787-0.812) for melanoma whereas disease-free respondents had a mean of 0.859 (95% CI 0.858-0.861). Most health conditions were independently associated with poorer quality of life. Utility values also declined by proximity to death where participants sampled 6 months before death had a mean score of 0.637 (95% CI 0.613-0.662).

CONCLUSIONS

Our data offer a snapshot of the health status of an older Australian population and show that record linkage can enable comprehensive ascertainment of utility values for use in health economic modeling.

Utility Decrements Associated with Adult Overweight and Obesity in Australia: A Systematic Review and Meta-Analysis

OBJECTIVE

The aim was to conduct a systematic review and meta-analysis of health state utility decrements associated with overweight and obesity in adults 18 years and over, for use in modelled economic evaluations in Australia.

METHODS

A systematic review was conducted in nine databases to identify studies that reported health state utility values by weight status. Random-effects meta-analysis was used to synthesise average utility decrements (from healthy weight) associated with overweight, all obesity and obesity classes 1, 2 and 3. Heterogeneity surrounding utility decrements was assessed via sub-group analysis, random-effects meta-regression and sensitivity analyses.

RESULTS

Twelve studies were found for which data were used to synthesise utility decrements, estimated as overweight = 0.020 (95% confidence interval 0.010-0.030), all obesity = 0.055 (0.034-0.076), obesity class 1 = 0.047 (0.017-0.077), class 2 = 0.072 (0.028-0.116) and class 3 = 0.084 (0.039-0.130). There was considerable heterogeneity in our results, which could be accounted for by the different ages and utility instruments used in the contributing studies.

CONCLUSIONS

Our results demonstrate that elevated weight status is associated with small but statistically significant reductions in utility compared with healthy weight, which will result in reduced quality-adjusted life years when extrapolated across time and used in economic evaluations.

Utility estimations of health states of older Australian women with atrial fibrillation using SF-6D

PURPOSE

To estimate SF-6D utility scores for older women with atrial fibrillation (AF); calculate and compare mean utility scores for women with AF with various demographic, health behaviours, and clinical characteristics; and develop a multivariable regression model to determine factors associated with SF-6D utility scores.

METHODS

This study evaluated N = 1432 women diagnosed with AF from 2000 to 2015 of the old cohort (born 1921-26) of the Australian Longitudinal Study on Women's Health (ALSWH) who remained alive for at least 12 months post first recorded AF diagnosis. Self-reported data on demographics, health behaviours, health conditions, and SF-36 were obtained from the ALSWH surveys, corresponding to within three years of the date of the first record of AF diagnosis. Linked Pharmaceutical Benefits Scheme (PBS) data determined the use of oral anticoagulants and comorbid conditions, included in CHA₂DS₂-VA (Congestive heart failure, Hypertension, Age ≥ 75 years, Diabetes, Stroke or TIA, Vascular disease and Age 65-74 years) score calculation, were assessed using state-based hospital admissions data. Utility scores were calculated for every woman from their SF-36 responses using the SF-6D algorithm with Australian population norms. Mean utility scores were then calculated for women with various demographic, health behaviours, and clinical characteristics. Ordinary Least Square (OLS) regression modelling was performed to determine factors associated with these utility scores. Two different scenarios were used for the analysis: (1) complete-case, for women with complete data on all the SF-36 items required to estimate SF-6D (N = 584 women), and (2) Multiple Imputation (MI) for missing data, applied to missing values on SF-36 items (N = 1432 women). MI scenario was included to gauge the potential bias when using complete data only.

RESULTS

The mean health utility was estimated to be 0.638 ± 0.119 for the complete dataset and 0.642 ± 0.120 for the dataset where missing values were handled using MI. Using the MI technique, living in regional and remote areas ([Formula: see text]) and the use of oral anticoagulants ([Formula: see text] were positively associated with health utility compared to living in major cities and no use of anticoagulants, respectively. Difficulty to manage on available income [Formula: see text], no/low physical activity [Formula: see text], disability [Formula: see text], history of stroke ([Formula: see text] and history of arthritis [Formula: see text] were negatively associated with health utility.

CONCLUSION

This study presents health utility estimates for older women with AF. These estimates can be used in future clinical and economic research. The study also highlights better health utilities for women living in regional and remote areas, which requires further exploration.

Long-term effect of community-based continence promotion on urinary symptoms, falls and healthy active life expectancy among older women: cluster randomised trial

Background

The long-term effectiveness of group continence promotion delivered via community organisations on female urinary incontinence, falls and healthy life expectancy remains unknown.

Methods

A pragmatic cluster randomised trial was conducted among 909 women aged 65–98 years with urinary incontinence, recruited from 377 community organisations in the UK, Canada and France. A total of 184 organisations were randomised to an in-person 60-min incontinence self-management workshop (461 participants), and 193 to a control healthy ageing workshop (448 participants). The primary outcome was self-reported incontinence improvement at 1-year. Falls and gains in health utility were secondary outcomes.

Results

A total 751 women, mean age 78.0, age range 65–98 completed the trial (83%). At 1-year, 15% of the intervention group versus 6.9% of controls reported significant improvements in urinary symptoms, (difference 8.1%, 95% confidence intervals (CI) 4.0–12.1%, intracluster correlation 0.04, number-needed-to-treat 13) and 35% versus 19% reported any improvement (risk difference 16.0%, 95% CI 10.4–21.5, number-needed-to-treat 6). The proportion of fallers decreased from 42% to 36% in the intervention group (−8.0%, 95% CI −14.8 – −1.0) and from 44% to 34% in the control group (−10.3%, 95% CI −17.4 – −3.6), no difference between groups. Both intervention and control groups experienced a gain in health utility (0.022 points (95% CI 0.005–0.04) versus 0.035 (95% CI 0.017–0.052), respectively), with no significant difference between groups.

Conclusion

Community-based group continence promotion achieves long-term benefits on older women’s urinary symptoms, without improvement in falls or healthy life expectancy compared with participation in a healthy ageing workshop.

Physical activity and body mass shape quality of life trajectories in mid-age women

OBJECTIVE

To determine the combined longitudinal effect of body mass index (BMI) and physical activity (PA) on health-related quality of life (HrQoL), using the SF-6D (SF-36) utility measure.

METHODS

Five waves of self-reported data from the 1946-51 cohort (n=5,200; data collection, 2001-2013) of the Australian Longitudinal Study on Women's Health were used. Mixed effect models were employed to address the objective.

RESULTS

Women with high PA experienced higher HrQoL regardless of BMI group, however, for those healthy or overweight, there was a very small decline in HrQoL over time. Women reporting no PA levels experienced the lowest baseline mean SF-6D score within each BMI group, with decreasing trajectories over the follow-up period. The rate of decline was greatest in women with obesity. Within each BMI group, there was a large, increasing gap in HrQoL between those who reported no and low PA over time. Women with obesity and high PA experienced similar HrQoL trajectories to women with normal weight or overweight with low PA levels. Overweight women with moderate PA experienced similar HrQoL to those with low PA but normal weight.

CONCLUSIONS

PA may mitigate the adverse effect of overweight and obesity on HrQoL at mid-life, at higher activity levels. Implications for public health: PA benefits HrQoL regardless of body mass, with larger gains for those currently not physically active. Moderate to high PA may mitigate the effect of overweight and obesity.