通过性别和健康流行度度量推导和比较健康寿命分布:统计矩和最大熵方法。

IF 2.5 2区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Rami Cosulich, Vanessa di Lego, Virginia Zarulli
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引用次数: 0

摘要

背景:关于健康寿命的文献通常侧重于平均值(即健康预期寿命)。最近的研究已经开始通过调查整个健康寿命分布,特别是健康寿命的标准偏差来扩展这一重点,它捕获了个体间的差异。尽管取得了这些进展,但在健康指标和性别的分布差异方面,研究差距仍然存在。这项研究旨在比较60岁时不同健康指标和性别之间的健康寿命分布。方法:我们使用来自欧洲健康、老龄化和退休调查和人类死亡率数据库的数据。采用马尔可夫链模型估计健康寿命分布的前三个统计矩。然后应用最大熵法推导出全分布。采用健康寿命统计和海灵格距离比较男女之间的分布。结果:在大多数健康测量中,男性在年轻时健康损失的概率高于女性,女性的健康预期寿命更长。雄性分布较分散,模态较低。对于大多数健康指标,健康寿命分布呈负偏态,模式年龄(即最可能丧失健康的年龄)高于健康预期寿命年龄。在各种健康测量中,男性比女性健康寿命更长的概率低于50%,在没有心血管疾病的情况下,男性的健康寿命最低。相比之下,男性没有关节炎或风湿病的时间比女性长50%以上。男性和女性之间的分布最相似的是生活中没有任何慢性病和生活中不超过一种慢性病。结论:本研究扩展了健康寿命研究的范围,通过对分布模式的观察和基于健康寿命生存期统计和海灵格距离的正式比较来补充对统计矩的关注,这是健康寿命领域首次应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Deriving and comparing healthy longevity distributions by gender and health prevalence measures: a statistical moments and maximum entropy approach.

Background: The literature on healthy longevity has typically focused on average values (i.e., healthy life expectancy). Recent studies have started to expand this focus by investigating the whole healthy lifespan distribution, especially the standard deviation of healthy longevity, which captures inter-individual variation. Despite these advancements, research gaps remain on how distributions differ by health indicator and sex. This study aimed to compare healthy longevity distributions at age 60 between different health measures and sexes.

Methods: We used data from the Survey of Health, Ageing and Retirement in Europe and the Human Mortality Database. A Markov chain model was used to estimate the first three statistical moments of healthy longevity distributions. The maximum entropy method was then applied to derive the full distributions. The healthy lifespan outsurvival statistic and the Hellinger distance were used to compare distributions between males and females.

Results: For most health measures, the probabilities of health loss at younger ages were higher for males than for females, and females had a longer healthy life expectancy. Males had more dispersed distributions with a lower mode. For most health measures, healthy longevity distributions were negatively skewed, with a mode age (i.e., the age with the highest probability of health loss) higher than the healthy life expectancy age. The probability for a man to have a longer healthy lifespan than a female was below 50% for various health measures and was the lowest for living free of cardiovascular disease. In contrast, the probability for a man to live free of arthritis or rheumatism for longer than a female was above 50%. The most similar distributions between males and females were observed with life free of any chronic conditions and life with no more than one chronic condition.

Conclusions: This study extended the scope of healthy longevity research by complementing a focus on the statistical moments with observations on the mode of the distributions and with formal comparisons based on the healthy lifespan outsurvival statistic and the Hellinger distance, which are applied for the first time in the healthy longevity field.

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来源期刊
Population Health Metrics
Population Health Metrics PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH-
CiteScore
6.50
自引率
0.00%
发文量
21
审稿时长
29 weeks
期刊介绍: Population Health Metrics aims to advance the science of population health assessment, and welcomes papers relating to concepts, methods, ethics, applications, and summary measures of population health. The journal provides a unique platform for population health researchers to share their findings with the global community. We seek research that addresses the communication of population health measures and policy implications to stakeholders; this includes papers related to burden estimation and risk assessment, and research addressing population health across the full range of development. Population Health Metrics covers a broad range of topics encompassing health state measurement and valuation, summary measures of population health, descriptive epidemiology at the population level, burden of disease and injury analysis, disease and risk factor modeling for populations, and comparative assessment of risks to health at the population level. The journal is also interested in how to use and communicate indicators of population health to reduce disease burden, and the approaches for translating from indicators of population health to health-advancing actions. As a cross-cutting topic of importance, we are particularly interested in inequalities in population health and their measurement.
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