The Australian Centre for Housing Research, The University of Adelaide, Adelaide, SA, 5005, Australia.
The ALIVE National Centre for Mental Health Research Translation, The University of Melbourne, Melbourne, Australia.
Qual Life Res. 2024 Aug;33(8):2207-2217. doi: 10.1007/s11136-024-03683-3. Epub 2024 Jun 10.
Research on health-related quality of life (HRQoL) trajectory patterns for people with disabilities (PwD) is scant. Understanding the HRQoL trajectory patterns for PwDs and investigating their relationship with disability types and socioeconomic factors can have important implications for Australia's welfare policy.
We analysed data from waves 11 to 21 of the Household, Income and Labour Dynamics in Australia (HILDA) survey of respondents aged 15 + years of the PwDs. The analytic sample consists of 3724 self-reported disabled individuals and 34,539 observations in total. The SF-6D utility score is our HRQoL measure. Group-based trajectory modelling was utilised to identify trajectory groups, and multinomial logistic regression was employed to determine the baseline factors associated with trajectory group membership.
The study identified four distinct types of HRQoL trajectories (high, moderate improving, moderate deteriorating and low HRQoL trajectories). Psychosocial disability types followed by physical disability types had a high Relative Risk Ratio (RRR) in the low group compared with high trajectory group membership of PwDs (psychosocial: 6.090, physical: 3.524). Similar, results followed for the moderate improving group albeit with lower RRR (psychosocial: 2.868, Physical: 1.820). In the moderate deteriorating group, the disability types were not significant as this group has a similar profile to high group at the baseline. Compared with males, females had a higher RRR in low and moderate versus high improving HRQoL trajectories (low: 1.532, moderate improving: 1.237). Comparing the richest class to the poorest class, socioeconomic factors (income and education) predicted significantly lower exposure for the richer class to the low and medium HRQoL trajectories groups (RRR < 1).
Different forms of disability, demographic and socioeconomic factors have distinct effects on the HRQoL trajectories of disabled individuals. Healthcare and economic resource efficiency might be improved with targeted government policy interventions based on disability trajectories.
针对残疾人群(PwD)健康相关生活质量(HRQoL)轨迹模式的研究甚少。了解 PwD 的 HRQoL 轨迹模式,并调查其与残疾类型和社会经济因素的关系,对澳大利亚的福利政策具有重要意义。
我们分析了澳大利亚家庭、收入和劳动力动态调查(HILDA)第 11 波至 21 波中年龄在 15 岁及以上的 PwD 受访者的数据。分析样本由 3724 名自我报告的残疾个体和 34539 个观测值组成。SF-6D 效用评分是我们的 HRQoL 衡量标准。使用基于群组的轨迹建模来识别轨迹群组,并使用多项逻辑回归确定与轨迹群组成员身份相关的基线因素。
研究确定了四种不同类型的 HRQoL 轨迹(高、中改善、中恶化和低 HRQoL 轨迹)。与高轨迹组 PwD 相比,精神心理残疾类型随后是身体残疾类型,低轨迹组的相对风险比(RRR)较高(精神心理:6.090,身体:3.524)。类似的结果也适用于中改善组,尽管 RRR 较低(精神心理:2.868,身体:1.820)。在中恶化组中,残疾类型并不显著,因为该组在基线时与高组具有相似的特征。与男性相比,女性在低和中改善与高 HRQoL 轨迹之间的 RRR 较高(低:1.532,中改善:1.237)。与最贫穷阶层相比,将最富有阶层与收入和教育等社会经济因素进行比较,可显著预测最富有阶层在低和中 HRQoL 轨迹组中较低的暴露率(RRR<1)。
不同形式的残疾、人口统计学和社会经济因素对残疾个体的 HRQoL 轨迹有不同的影响。基于残疾轨迹的有针对性的政府政策干预可能会提高医疗保健和经济资源的效率。