Theadom Alice, Rodrigues Miriam, Ranta Annemarei, Poke Gemma, Love Donald, Jones Kelly, Ao Braden Te, Hammond-Tooke Graeme, Parmar Priya, O'Grady Gina, Roxburgh Richard
National Institute for Stroke and Applied Neurosciences, Auckland University of Technology, 90 Akoranga Dr, Northcote, 0627, New Zealand.
Neurology Department, Auckland City Hospital, Auckland, New Zealand.
Qual Life Res. 2022 Jun;31(6):1657-1666. doi: 10.1007/s11136-021-03046-2. Epub 2021 Nov 27.
To determine the impact of genetic muscle disorders and identify the sociodemographic, illness, and symptom factors influencing quality of life.
Adults (aged 16-90 years) with a confirmed clinical or molecular diagnosis of a genetic muscle disorder identified as part of a nationwide prevalence study were invited to complete an assessment of the impact of their condition. Quality of life was measured using the World Health Organization Quality of Life questionnaire. Impact was measured via the prevalence of symptoms and comparisons of quality of life against New Zealand norms. Multivariate regression models were used to identify the most significant predictors of quality of life domains.
490/596 participants completed the assessment (82.2% consent rate). Quality of life was lower than the general population on physical (t = 9.37 p < 0.0001, d = 0.54) social (t = 2.27 p = 0.02, d = 0.13) and environmental domains (t = 2.28 p = 0.02, d = 0.13), although effect sizes were small. No difference was found on the psychological domain (t = - 1.17 p = 0.24, d = 0.07). Multivariate regression models (predicting 42%-64% of the variance) revealed personal factors (younger age, being in employment and in a relationship), symptoms (lower pain, fatigue, and sleep difficulties), physical health (no need for ventilation support, fewer activity limitations and no comorbidities), and psychosocial factors (lower depression, anxiety, behavioural dyscontrol and higher self-efficacy, satisfaction with health care and social support) contributed to improved quality of life.
A range of factors influence the quality of life in adults diagnosed with a genetic muscle disorder and some may serve as targets for multi-faceted intervention.
确定遗传性肌肉疾病的影响，并识别影响生活质量的社会人口学、疾病和症状因素。
作为一项全国患病率研究的一部分，被确诊患有遗传性肌肉疾病的临床或分子诊断的成年人（年龄在16 - 90岁之间）受邀完成对其病情影响的评估。使用世界卫生组织生活质量问卷来测量生活质量。通过症状患病率以及将生活质量与新西兰标准进行比较来衡量影响。多元回归模型用于识别生活质量领域最重要的预测因素。
490/596名参与者完成了评估（同意率为82.2%）。在身体（t = 9.37，p < 0.0001，d = 0.54）、社会（t = 2.27，p = 0.02，d = 0.13）和环境领域，生活质量低于一般人群，尽管效应量较小。在心理领域未发现差异（t = -1.17，p = 0.24，d = 0.07）。多元回归模型（预测方差的42% - 64%）显示个人因素（年龄较小、就业和处于恋爱关系中）、症状（疼痛较轻、疲劳和睡眠困难较少）、身体健康（无需通气支持、活动受限较少且无合并症）以及心理社会因素（抑郁、焦虑、行为失控程度较低且自我效能感较高、对医疗保健和社会支持满意）有助于提高生活质量。
一系列因素影响被诊断患有遗传性肌肉疾病的成年人的生活质量，其中一些因素可作为多方面干预的目标。
