The global pattern of centenarians highlights deep problems in demography

Saul Justin Newman
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Abstract

Accurate age data is fundamental to medicine, social sciences, epidemiology, and good government. However, recent and heavily disputed debates on data quality have raised questions on the accuracy of demographic data at older ages. Here, we catalogue late-life survival patterns of every country in the world from 1970-2021 using comprehensive estimates of old-age populations provided by global governments and curated by the United Nations. Analysis of 236 nations or states across 51 years reveals that late-life survival data is dominated by anomalies at all scales and in all time periods. Life expectancy at age 100 and late-life survival from ages 80 to 100+, which we term centenarian attainment rate, is highest in a seemingly random assortment of states. The top 10 "blue zone" regions with the best survival to ages 100+ routinely includes Thailand, Kenya and Malawi - respectively now 212th and 202nd in the world for life expectancy, the non-self-governing territory of Western Sahara, and Puerto Rico where birth certificates are so unreliable they were recently declared invalid as a legal document. These anomalous rankings are conserved across long time periods and multiple non-overlapping cohorts, and do not seem to be sampling effects. Instead these patterns suggest a persistent inability, even for nation-states or global organisations, to detect or measure error rates in human age data, with troubling implications for epidemiology, demography, and medicine.
全球百岁老人模式凸显人口学的深层问题
准确的年龄数据是医学、社会科学、流行病学和良好政府的基础。然而,最近关于数据质量的争论引起了人们对老年人口统计数据准确性的质疑。在此,我们利用全球各国政府提供并由联合国整理的老年人口综合估计数据,对 1970-2021 年间世界各国的晚年生存模式进行了编目。对 236 个国家或州 51 年的分析表明,晚年生存数据在所有规模和所有时间段内都以异常现象为主。百岁时的预期寿命和从 80 岁到 100 岁以上的晚年存活率,即我们所说的百岁老人达到率,在看似随机的一些国家中是最高的。100 岁以上存活率最高的前 10 个 "蓝区 "地区通常包括泰国、肯尼亚和马拉维--这三个国家的预期寿命目前分别排在世界第 212 位和第 202 位;非自治领土西撒哈拉;以及波多黎各--那里的出生证明非常不可靠,最近被宣布为无效的法律文件。这些反常的排名在较长的时间段和多个不重叠的队列中保持不变,似乎并不是抽样效应。相反,这些模式表明,即使是民族国家或全球性组织,也始终无法检测或测量人类年龄数据的错误率,这对流行病学、人口学和医学产生了令人担忧的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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