Department of Clinical Epidemiology, Aarhus University and Aarhus University Hospital, Aarhus, Denmark.
Centre d'Estudis Demogràfics, Cerdanyola del Vallès, Barcelona, Spain.
PLoS One. 2023 Sep 1;18(9):e0290962. doi: 10.1371/journal.pone.0290962. eCollection 2023.
In addition to fundamental mortality metrics such as mortality rates and mortality rate ratios, life expectancy is also commonly used to investigate excess mortality among a group of individuals diagnosed with specific diseases or conditions. However, as an average measure, life expectancy ignores the heterogeneity in lifespan. Interestingly, the variation in lifespan-a measure commonly used in the field of demography-has not been estimated for people with a specific condition. Based on recent advances in methodology in research within epidemiology and demography, we discuss two metrics, namely, the average life disparity and average lifetable entropy after diagnosis, which estimate the variation in lifespan for time-varying conditions in both absolute and relative aspects. These metrics are further decomposed into early and late components, separated by their threshold ages. We use mortality data for women with mental disorders from Danish registers to design a population-based study and measure such metrics. Compared with women from the general population, women with a mental disorder had a shorter average remaining life expectancy after diagnosis (37.6 years vs. 44.9 years). In addition, women with mental disorders also experienced a larger average lifespan variation, illustrated by larger average life disparity (9.5 years vs 9.1 years) and larger average lifetable entropy (0.33 vs 0.27). More specifically, we found that women with a mental disorder had a larger early average life disparity but a smaller late average life disparity. Unlike the average life disparity, both early and late average lifetable entropy were higher for women with mental disorders compared to the general population. In conclusion, the metric proposed in our study complements the current research focusing merely on life expectancy and further provides a new perspective into the assessment of people's health associated with time-varying conditions.
除了死亡率和死亡率比等基本死亡率指标外，预期寿命也常用于研究一组患有特定疾病或病症的个体的超额死亡率。然而，作为一种平均指标，预期寿命忽略了寿命的异质性。有趣的是，在人口学领域常用的寿命变异度尚未针对特定条件的人群进行估计。基于流行病学和人口学研究方法的最新进展，我们讨论了两个指标，即平均寿命差异和诊断后平均生命表熵，它们分别从绝对和相对方面估计了时变条件下的寿命变异度。这些指标进一步分解为早期和晚期成分，通过其阈值年龄进行区分。我们使用丹麦登记处的精神障碍女性的死亡率数据设计了一项基于人群的研究，并测量了这些指标。与普通人群中的女性相比，患有精神障碍的女性在诊断后的平均剩余预期寿命更短（37.6 年对 44.9 年）。此外，患有精神障碍的女性还经历了更大的平均寿命变异度，表现在更大的平均寿命差异（9.5 年对 9.1 年）和更大的平均生命表熵（0.33 对 0.27）上。更具体地说，我们发现患有精神障碍的女性早期平均寿命差异较大，晚期平均寿命差异较小。与平均寿命差异不同，早期和晚期平均生命表熵都高于普通人群中的女性。总之，我们研究中提出的指标补充了目前仅关注预期寿命的研究，并为评估与时间相关的条件相关的人们的健康提供了新的视角。
