Search

Purpose: To compare health-related quality of life (HRQoL) between mothers and females who were voluntarily or involuntarily childless, across their reproductive years., Methods: 4100 females born in 1973-78 from the Australian Longitudinal Study on Women's Health were followed for 22 years. Motherhood status was defined by females' reports in Survey 8 (2018, 40-45 years) on their fertility, attempts to conceive, use of in vitro fertilization and fertility hormones, and number of children. HRQoL was assessed in each survey using the 36-Item Short Form Survey (SF-36). Linear mixed models were used to assess the associations between motherhood status and HRQoL., Results: Over 22 years, compared with females who were voluntarily childless, mothers on average had better HRQoL (shown by scores 1.5 to 3.4 points higher on five of the eight SF-36 subscales), while females who were involuntarily childless scored 2.2 to 3.0 points lower on three of eight SF-36 subscales. Compared with females who were voluntarily childless, teen mothers (age at first birth < 20 years) scored lower on role limitations due to physical problems subscale (b = -5.5, 95% CI: -9.3, -1.6), while females with either two, or three or more children scored 1.6 to 4.8 points higher on seven of eight SF-36 subscales., Conclusions: Females who were childless had poorer HRQoL than mothers. Further research is needed to understand the underlying mechanisms, which could inform policymakers on how to reduce the health disparities and improve long-term health outcomes for females., (© 2023. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Purpose: To examine the prospective associations between body mass index (BMI) and health-related quality of life (HRQoL)., Methods: Data were extracted from a longitudinal, nationally representative sample of 9916 men and women aged 18 years and over who were followed annually between 2006 and 2016 in the Household, Income and Labour Dynamics in Australia (HILDA) survey. HRQoL was assessed using the self-administered SF-36 questionnaire annually between 2006 (baseline) and 2016. BMI was calculated from self-reported height and weight and was classified into the following four categories of baseline BMI: underweight (< 18.5 kg/m 2 ), normal weight (18.5-24.9 kg/m 2 ), overweight (25-29.9 kg/m 2 ) and obese (≥ 30 kg/m 2 ). We used linear mixed-effects regression models to investigate the associations between change in BMI (kg/m 2 ) and concurrent changes in HRQoL scores over 11 years., Results: BMI gain was associated with deterioration of Physical Component Summary (PCS) (P < 0.001), but not with change in Mental component summary (MCS) over the 11-year period. BMI gain was inversely associated (P < 0.001) with five of the eight HRQoL domains (physical functioning, role physical, bodily pain, general health and vitality) with a significant graded association according to baseline BMI category. Over the 11-year study period, every unit increase in PCS was associated with a decrease of 0.02 (P < 0.001), 0.03 (P < 0.001) and 0.04 (P < 0.001) BMI units per year among participants who were normal, overweight and obese at baseline, respectively. Five of the eight domains of HRQoL (physical functioning, role physical, bodily pain, general health and vitality) were inversely associated with BMI (P < 0.001) with a significant graded association according to baseline BMI category., Conclusions: Weight gain was not only associated with deterioration of HRQoL, and vice versa. The bi-directional association was stronger for physical than mental domains of HRQoL.

Purpose: Physical health-related quality of life (HRQoL) is associated with adverse health outcomes, including hospitalizations and all-cause mortality. However, little is known about how physical HRQoL changes over time in older people and the predictors of this trajectory. This study (a) identified trajectories of physical HRQoL among older people and (b) explored whether economic factors, social health or stressful life events impact physical HRQoL trajectories., Method: A cohort of 12,506 relatively 'healthy' community-dwelling Australians aged ≥ 70 years (54.4% females), enrolled in the ASPREE Longitudinal Study of Older Persons (ALSOP) study and was followed for six years. Economic factors, social health and life events in the last 12 months were assessed through a questionnaire at baseline. Physical HRQoL was measured by using the 12-item short form at baseline and annual follow-ups. Growth mixture and structural equation modelling were used to identify physical HRQoL trajectories and their predictors., Results: Four physical HRQoL trajectories were identified-stable low (7.1%), declining (9.0%), stable intermediate (17.9%) and stable high (66.0%). Living in more disadvantaged areas, having a lower household income, no paid work, no voluntary work, loneliness and stressful life events (i.e. spousal illness, friend/family illness, financial problem) were associated with a 10%-152% higher likelihood of being in the stable low or declining physical HRQoL trajectory than the stable high group., Conclusion: Specific stressful life events had a greater impact on adverse physical HRQoL trajectories in older people than other factors. Volunteering may prevent physical HRQoL decline and requires further investigation., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Objective: Patient-reported outcomes of health-related quality-of-life (HRQoL) are important descriptors of population health. A recent Australian adolescent population survey provided a unique opportunity to derive preference-based HRQoL., Methods: Data from 2967 adolescents aged 11-17 years were analysed. An interviewer-led parent/carer questionnaire was administered for demographic variables and mental disorders of adolescents during previous 12 months using the Diagnostic Interview Schedule for Children. A self-report survey was administered to derive HRQoL using the child health utility nine-dimensions instrument (CHU-9D). Weighted HRQoL was derived for several demographic groups, mental disorder diagnosis, and youth risk behaviours., Results: The total population had a mean utility of 0.78 [standard deviation (SD): 0.20]. Males had a significantly higher mean utility (0.81, SD 0.18) than females (0.76, SD: 0.21) (Cohen's d = 0.23, p < 0.001), and utility decreased with age for both males and females (p < 0.001). Family type and some parent/carer variables were associated with significant lower HRQoL scores with small effect size. Youth risk behaviours were associated with reduced HRQoL with moderate effect sizes. Adolescents who self-harmed, had suicidal ideation, or had a mental disorder had significantly lower utilities scores with moderate to large effect sizes compared to those who did not have such conditions., Conclusions: This study has provided contemporary Australian population norms for HRQoL in adolescents that may be used as cross comparison between studies as well as indicators allowing estimation of population health (e.g. estimation of the burden of disease) and can be used to populate future economic models., (© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

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 CHA 2 DS 2 -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.

Purpose: Identify aspects of quality of life (QoL) important to Australian informal carers and explore how well the Adult Social Care Outcomes Toolkit for Carers, Care-related Quality of Life instrument and Carer Experience Scale capture these aspects in the Australian context., Methods: Online questionnaires were completed by Australian informal carers. Socio-demographics, open-ended questions: positive/negative aspects of caring and QoL aspects missing from the instruments, and ranking of the instrument domains was used to explore the content of the instruments. Instruments were scored using preference-weighted value sets (reported in another paper). Content analysis was used to analyse the open-ended responses. Chi-squared test looked at differences in domain importance. Descriptive analyses summarised all other information., Results: Eight themes were identified: Behaviour-mood of the care recipient, Caring responsibilities, Finances, Health, Own life, Perception of carers, Relationship with care recipient and Support. Many aspects of carer QoL mentioned as missing in the instruments appeared covered by the domains, of which all were reported as important. The highest ranked domain was relationship with the care recipient. The influence of the care recipient specific support, behaviour/mood and health on carer QoL appear absent in all instruments., Conclusion: The content of the three instruments appears relevant in an Australian setting. The influence of care recipient's health and well-being on carer QoL should be considered, along with spillover effects. A content and/or face validity analysis is required to confirm differences in item interpretation in Australian informal carers., (© 2023. The Author(s).)

Background: Physical and mental component summary scores (PCS and MCS, respectively) are often used to summarise SF-36 quality of life subscales. This paper investigates PCS and MCS across the life course and compares the trajectories obtained from two different methods of calculation., Methods: The Australian Longitudinal Study on Women's Health is a population-based study with three cohorts of women and SF-36 surveys taken at multiple time points. Scoring coefficients for each component score were determined using factor analysis with uncorrelated (orthogonal) and correlated (oblique) rotation at the baseline survey, which were then used to compute correlated and uncorrelated PCS and MCS scores at each survey (scaled to have mean of 50 and standard deviation of 10 at baseline)., Results: For both methods, PCS declined progressively across the lifespan, while MCS rose in young and mid-age women to a peak and subsequently declined in later life. Differences were apparent between correlated and uncorrelated scores, most notably for MCS in the older cohort, where correlated MCS reached 54.6 but still less than uncorrelated MCS, with a random effects model indicating 1.63 (95% confidence intervals 1.58-1.67) units difference; it then declined to a score of 51.2 by the last survey and the difference widened to 3.44 (3.38-3.50) units compared with the uncorrelated MCS., Conclusions: PCS and MCS have distinct trajectories through life, with differences in results from correlated and uncorrelated component summary scores. The divergence is most notable with MCS, especially for older women, suggesting that correlated MCS and PCS should be used when examining change in health over time in this age group.

Purpose: Health-related quality of life (HRQOL) can be significantly impaired by the presence of chronic conditions such as cardiovascular disease (CVD) and major depressive disorder (MDD). The aim of this paper was to (1) identify differences in HRQOL between individuals with CVD, MDD, or both, compared to a healthy reference group, (2) establish whether the influence of co-morbid MDD and CVD on HRQOL is additive or synergistic and (3) determine the way in which depression severity interacts with CVD to influence overall HRQOL., Methods: Population-based data from the 2007 Australian National Survey of Mental Health and Well-being (NSMHWB) (n = 8841) were used to compare HRQOL of individuals with MDD and CVD, MDD but not CVD, CVD but not MDD, with a healthy reference group. HRQOL was measured using the Assessment of Quality of Life (AQOL). MDD was identified using the Composite International Diagnostic Interview (CIDI 3.0)., Results: Of all four groups, individuals with co-morbid CVD and depression reported the greatest deficits in AQOL utility scores (Coef: -0.32, 95% CI: -0.40, -0.23), after adjusting for covariates. Those with MDD only (Coef: -0.27, 95% CI: -0.30, -0.24) and CVD only (Coef: -0.08, 95% CI: -0.11, -0.05) also reported reduced AQOL utility scores. Second, the influence of MDD and CVD on HRQOL was shown to be additive, rather than synergistic. Third, a significant dose-response relationship was observed between depression severity and HRQOL. However, CVD and depression severity appeared to act independently of each other in impacting HRQOL., Conclusions: HRQOL is greatly impaired in individuals with co-morbid MDD and CVD; these conditions appear to influence HRQOL in an additive fashion. HRQOL alters with depression severity, therefore treating depression and improving HRQOL is of clinical importance.

Objectives: Many studies have investigated anxiety and depression during the menopausal transition. However, there is little understanding of positive aspects of well-being among menopausal women. This paper reports on two studies which investigated how menopausal stage and age accounted for how women felt about their purpose in life, self-acceptance and social role., Method: In Study One, 304 women from a community sample completed structured questionnaires which included questions relating to demographic background and two subscales of the Psychological Well-being Inventory: purpose in life and self-acceptance. In Study Two, 203 participants from Study One returned a follow-up structured questionnaire related to purpose in life and social role., Results: Study One found that the effects of age group and menopausal group could not be separated: All women felt they would be more positive about these well-being measures in the future than they had been in the past and at present. Study Two found that women who were perimenopausal and postmenopausal did not feel as positive about their role/s in life as premenopausal women, regardless of their age., Conclusions: The results suggest that the menopause may indicate to women that their role/purpose in life is changing. It is important that any understanding of the menopause incorporate psychosocial aspects of women's lives. Further longitudinal studies are needed to explore well-being factors and the menopause.

This paper reports the quality of life (QoL) of a large cohort of Australian women three and twelve months after surgery for early stage breast cancer (ESBC), and shows that the impact of disease and treatment on QoL differed by age, education and marital status. Eighty-three percent of eligible patients were recruited; 86% had breast conserving surgery and 14% mastectomy. Response rates were 93% (n = 305) at three months and 88% (n = 291) at one year. Quality of life was measured with the EORTC core questionnaire (QLQ-C30) and an ESBC-specific questionnaire. Multilevel analysis was used to estimate the effects and interactions of time, treatment and patient characteristics. Most symptoms declined between three months and one year, but arm and menopausal symptoms persisted. Emotional, social and role functioning improved over time, and fear of disease recurrence diminished. Younger women faired worse than older women on a broad range of QoL dimensions. Single women and those with less education faired worse on a number of dimensions. The negative impact of mastectomy on body image was greatest among married women, particularly young married women. These sociodemographic distinctions are relevant when discussing treatment options with women facing a diagnosis of ESBC.

While quality of life (QOL) assessment is becoming more common, interpreting the results remains problematic. This paper demonstrates an approach to developing clinically-based interpretations for QOL outcomes, using the QLQ-C30 as an example. The results from 14 published QLQ-C30 studies which group patients by performance status, weight loss, toxicity, extent or severity of disease are collated. Groups with lower clinical status generally have worse QOL. The largest differences are between performance status groups, and the smallest differences are between groups of patients with local disease and those with metastases. The physical and role scores have the largest ranges of means across patient groups, and show the largest differences between clinical groups, while the cognitive and emotional scores have the smallest ranges of means and differences. Sicker groups have larger score standard deviations than healthier groups. Relatively large and small means and differences, and corresponding effect sizes, are presented. Collectively, the results provide a sense of the relative sizes of means and of differences, and of the types of clinical groups which give rise to them, thereby providing clinically-based benchmarks by which to interpret QLQ-C30 results.