There are many challenges inherent in trying to learn something about aging through analysis of the demographics of extreme human longevity. First of all, there are just not that many supercentenarians, making it very hard to obtain enough data to make statistically sound inferences about health, tied as it is to the many complex and varied processes of aging. Secondly, and as illustrated by the paper here, much of the data that might otherwise be useful is of poor quality due to issues of fraud and lax recordkeeping.
The concentration of remarkable-aged individuals, within geographic regions or 'blue zones' or within databases of people exceeding extreme age thresholds, has stimulated diverse efforts to understand factors driving survival patterns in these populations. Populations within remarkable-age databases and 'blue zone' regions have been subject to extensive analysis of lifestyle patterns, social connections, biomarkers, and genomic variants, under the assumption that these represent potential drivers behind the attainment of remarkable age.
However, alternative explanations for the distribution of remarkable age records appear to have been overlooked or downplayed. Previous work has noted the potential of bad data, population illiteracy or population heterogeneity to explain remarkable age patterns. More recent investigations revealed a potential role of errors, and potential operator biases in generating old-age survival patterns and data. In turn, these findings prompted a response with potentially disruptive implications: that, under such models, the majority if not all remarkable age records may be errors.
Here, we explore this possibility by linking civil registration rates and socioeconomic data to per-capita rates of remarkable age attainment, using data from every known centenarian (individuals aged 100 or over), semisupercentenarian (SSCs; aged 105 or over), and supercentenarian (aged 110 or over) from the USA, France, Japan, the United Kingdom, and Italy. These data reveal that remarkable age attainment is predicted by regional indicators of error and fraud including greater poverty, higher illiteracy, higher crime rates, worse population health, greater levels of material deprivation, shorter average lifespans, fewer old people, and the absence of birth certificates. In addition, French and Italian historical data indicate that supercentenarians are not likely to be born into longer-lived cohorts, but are born into undifferentiated or shorter-lived populations relative to their contemporary national averages.
Supercentenarian birthdates also exhibit 'age heaping' distributional patterns that are strongly indicative of manufactured birth data. Finally, fewer than 15% of exhaustively validated supercentenarians are associated with either a birth certificate or a death certificate, even in populations with over 95% death certificate coverage. As such, these findings suggest that extreme age data are largely a result of vital statistics errors and patterns of fraud, raising serious questions about the validity of an extensive body of research based on the remarkable reported ages of populations and individuals.