Specific features of the oldest old from the Longevity Blue Zones in Ikaria and Sardinia

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Highlights

  • Longevity Blue Zones” (LBZs) are areas with an unusually high proportion of oldest old.

  • Analysis of nonagenarians in the LBZs may reveal factors associated with population longevity.

  • Self‒perceived optimism and self‒rated health record significantly higher scores in the LBZs.

  • Genetic markers show a limited association with the longevity of LBZ populations.

  • Healthier behaviors and lifestyle factors might favor population longevity.

Abstract

Human longevity may be found in single individuals as well as in the population as a whole (“population longevity”). Longevity Blue Zones (LBZs), which are areas with an unusually high number of oldest old, have been identified in Sardinia and the Greek island of Ikaria. We compared the lifestyle, health status and some genetic markers of the LBZ populations with those of reference populations from Italy and Greece; the data were extracted from the GEHA database. In the LBZs, the proportion of individuals who never married or were married and still living with their spouse was significantly greater. Nonagenarians males and females with a high self‒perception of optimism and/or a high score for self-rated health were also found in larger proportions in LBZs. Among the variables with lower frequency were the proportion of the widowed, the percentage of subjects who had suffered a stroke and the frequency of Apoε4 and Apoε2 and the TT genotype of FOXO3A gene. Compared to behavioral and health indicators, the impact of genetic factors might be relatively less important in the LBZs. Nevertheless, further research is needed to identify potential epigenetic traits that might play a predominant role due to the interaction between genetics and the human and physical environments.

Introduction

Some individuals may live considerably longer than most other people; this phenomenon is known as longevity. The age threshold at which a person is regarded as “long-lived” has changed over time, as the lifespan of human beings has increased. Decades ago, the age threshold for identifying the so-called “oldest old” was fixed at 85 years (Suzman et al., 1992), whereas more recent studies, such as the GEHA, an EU-funded research project, consider longevity as starting at the age of 90 years (Franceschi et al., 2007; Cevenini et al., 2014). Usually, longevity studies address individual longevity and are aimed at identifying specific traits or life trajectories of sporadic long-lived persons. Yet, populations in which longevity is shared by a large portion of their members have been identified, i.e., in these populations the percentage of oldest old and the average life expectancy are greater than usually expected. The term population longevity has been proposed as a more appropriate term in this context (Poulain et al., 2013; Poulain, 2019). The existence of such populations raises the question of whether the factors responsible for the high number of oldest old are the same as those responsible for individual longevity. In this article, we present the results of a preliminary attempt to compare two populations displaying high levels of population longevity ‒ one living in the mountainous area of the Sardinia, Italy, and the other living on the Greek island of Ikaria. The features of nonagenarians from these locations have been compared with corresponding data concerning nonagenarians’ siblings in mainland Italy and Greece, obtained from the GEHA study (Skytthe et al., 2011), representative of individual longevity.

Considerable research has been devoted to the analysis of centenarians or near‒centenarians taken as a model of extreme individual longevity (Franceschi et al., 2000, 2007; Poon et al., 1992; Motta et al., 2005; Sebastiani et al., 2010). In most cases the methodology of these studies entails a random selection of participants (both centenarians and younger controls). In such conditions, these very old persons are actually representative of individual longevity since they display an extreme phenotype, exceedingly rare among people living in the same physical and social environment. This approach seeks to find out why these persons live longer than their close relatives, co-residents and other members of the local community, and tries to outline the characteristics of individual longevity and any possible association between individual traits and extreme survival. Many of these studies were carried out from a single disciplinary perspective, such as demography, sociology, anthropology, psychology, epidemiology, nutrition or genetics, and the impact of other disciplines manifested only marginally through control covariates. Currently, investigations involving the collaborative efforts of researchers from several disciplines within an integrated approach are quite rare (Carey and Vaupel, 2005). This fact is unacceptable since successful aging is a complex achievement that requires the contribution of numerous and heterogeneous factors.

Population longevity is when the proportion of people surviving to the oldest ages is greater in a given population than in its neighboring areas according to a predetermined threshold deviation (Poulain, 2019). If the oldest members of such a population are also able to maintain a high standard of cognitive and physical functionality until the end of their lives, studying them may prove to be an innovative and promising model in longevity research. Hence, the study of specific long-lived populations is aimed at seeking determinants shared by a sizable percent of people within a given population. The determinants of population longevity could encompass either individual characteristics (factors or traits associated with individual longevity) or contextual factors (related to the global environment surrounding that population) conducive to longevity. A conventional study centered on individual longevity is hardly able to capture these “shared” components peculiar to population longevity. Analysis of population longevity should not be viewed as an alternative to the analysis of individual longevity, but it could potentially complement the more conventional approaches and facilitate the identification of longevity factors acting at the super‒individual level. Although this new approach goes beyond searching for the factors associated with individual longevity, it is still strongly related to them.

Interest in the study of long-lived populations has remained limited due to the following reasons:

  • i

    Identification of a long-lived population and the age validation of its exceptional members are time-consuming and demanding tasks that are not easy to complete due to the lack of documentary evidence, as explained later.

  • ii

    Communities experiencing higher population longevity are often small in size, and the oldest old group may consist of a limited number of individuals; thus the risk of underpowered statistics exists.

  • iii

    More generally, searching for population longevity determinants requires the mastering of several disciplines, which is a relatively complicated task, as specific methods have yet to be developed. A consensus has still not been reached regarding a strategy of analysis that is consistent with the data collected in various disciplines.

The present study is the first attempt to identify the longevity factors largely shared by the populations of two LBZs identified in Sardinia and in Greece. This objective was achieved by comparing the characteristics of nonagenarians living in these populations with the corresponding characteristics of nonagenarian siblings surveyed as part of the GEHA project in mainland Italy and Greece. Our working hypothesis was that long-lived individuals in the LBZs may be somewhat unique, as they may express differently those longevity traits already identified through studies targeted at individual longevity. The impact of these traits may be enhanced by the surrounding physical or social context and shared by several members of these long-lived populations. However, although these specific traits may play a significant role in favoring longevity in a long-lived population, they are likely overlooked in the context of individual longevity, as the subjects do not live in the same environment and social context.

Accordingly, we assumed that, by comparing nonagenarians in the LBZs with GEHA nonagenarians in the respective countries, we could identify the longevity traits in the LBZs as results of their specific favorable socio-cultural and physical environments.

In March 2000, as a result of the validation of individual centenarians in Sardinia (which was done as part of the AKEA project), a specific area was identified in the island's mountains– in this area the proportion of centenarians was significantly higher than in the populations born in the same place (Poulain et al., 2004). This area was called a Longevity Blue Zone (LBZ), and the term has since come to be defined as an area where the population is characterized by a significantly higher level of longevity compared to neighboring regions, and the exceptional longevity of people in this population must be fully validated (Poulain et al., 2007). In practice, an LBZ is defined as a rather limited and homogenous geographical area in which the population shares the same lifestyle and environment and its longevity has been proved to be exceptionally high (Poulain et al., 2013). So far, validated LBZs have been identified in Okinawa (Japan), on the Nicoya peninsula (Costa Rica) and on the island of Ikaria (Greece) (Poulain, 2011; Poulain et al., 2013; Pes and Poulain, 2016).

To identify an LBZ and prove the exceptional longevity of its population, it is necessary to first validate the individual longevity of the people living in the candidate area, i.e., assess accurately the age at death or the extreme survival of the oldest old. Age misreporting and, more specifically, age exaggeration must be eschewed (Poulain et al., 2007). Several populations had claimed to live in longevity areas, but most of these alleged LBZs were later invalidated (Young et al., 2010). Perls (2006) concluded that “such cases of extreme longevity required detailed scrutiny because they are so incredibly rare”. In addition to the validation methodology developed for individual centenarians (Poulain, 2010), the validation of an exceptional population longevity requires several further operational steps, which vary depending on the current availability of data sources specific to the population under scrutiny. Usually, the level of population longevity is estimated by deriving the average of individual survival of all subjects born in a given geographic area. To accomplish this task, exhaustive data on the births and deaths that occurred within that population during at least a century must be available.

The extreme longevity area identified in the mountainous part of Sardinia includes a group of 6 villages in the Barbagia and Ogliastra districts; they contain about 40,000 inhabitants who are mainly engaged in shepherdry and agricultural activities and follow a relatively traditional lifestyle. This population remained isolated for centuries, which contributed to make its gene pool more homogeneous and the preservation of its socio-cultural and anthropological characteristics throughout its history (Pes and Poulain, 2016). Among the non-genetic factors that might account for the exceptional longevity recorded in central Sardinia and the low gender ratio among the oldest people there, the role of physical activity (Pes et al., 2020; Fastame et al., 2020), life satisfaction, optimism, resilience and religiosity (Fastame et al., 2021) and nutrition have been investigated; in particular, the role of traditional foods, typical of a society centered on animal farming has been studied (Pes et al., 2013, 2015; Pes et al., 2021).

Ikaria, the other longevity area considered in this comparative study, is a mountainous Greek island (255 sq km) located in the Eastern Aegean Sea, located between Mykonos and Samos. Its nearly 8000 inhabitants live in three municipal units. Unlike other Greek islands, it has remained relatively poor and isolated. Its inhabitants have kept their traditions alive and preserved their manual occupations, and most of their food is produced locally (Panagiotakos et al., 2011; Georgiopoulos et al., 2017; Legrand et al., 2019; Chrysohoou et al., 2020; Foskolou et al., 2021).

Conventionally, the apparent exceptional longevity of a population is inferred from the existence of an unusually large proportion of centenarians/nonagenarians. To compare longevity levels,centenarian prevalence (CP), i.e., the ratio of the number of living centenarians in a given population to the total resident population, is largely used in the literature as well by the media. However, the reliability of this indicator deserves critical evaluation as it is sensitive to a number of biases related to existing migration flows and changes in fertility behavior. For example, in the case of a population that experienced large-scale immigration flows in the younger generations, or a baby boom later, CP will fail to identify the remarkable survival of persons in old ages as the proportion of elders is artificially lowered. On the contrary, if the younger population drops in number due to emigration, the proportion of elderly may be artificially inflated. In such cases, the prevalence or proportion of the oldest old is no longer reliable for measuring longevity and should not be used for comparison across populations. Nevertheless, CP is still the indicator most frequently used by gerontologists as well as by national and regional authorities that are eager to claim a longevity status for the area of the population concerned.

A closely related indicator, the Centenarian Rate (CR), was proposed by demographers for comparing longevity levels. It was introduced by Robine and Caselli (2005) as the ratio of the number of persons aged 100 years and above, who were 60 and above 40 earlier, living within the same territory. This index can be easily calculated by using census data, and it minimizes the impact of the cohort size and the role of migration, naturalization, fertility and infant mortality as most of these confounding events occur before the age of 60.

Compared to CP and CR, life tables provide a better measurement of longevity and allow one to compare different populations more reliably. The cohort life table is computed from the mortality rates of a given birth cohort observed during one century or longer, while the period life table is calculated for a fictive cohort by considering the mortality rates for each age group at a given time. In most populations, longevity is rising so rapidly that only the same cohorts of different populations can be compared; thus cohort life tables are preferable in such cases. Nevertheless, building a cohort life table is not a straightforward task as different methodologies need to be used. Moreover, ad-hoc data is not always available. As a result, very few countries provide cohort life tables,1 and no such tables currently exist for the two LBZs included in this study.

A last indicator named Extreme Longevity Index (ELI) was proposed by researchers when they were assessing the level of longevity in Sardinia (Poulain et al., 2004) as the ratio of the number of centenarians, dead or alive, born during a given period (e.g., in Sardinia, between 1880 and 1914) to the total number of births recorded during the same period. This index, expressed as the number of centenarians per 100,000 newborns, is equivalent to the probability for any person born in that municipality to reach 100 years of age, there or anywhere else. The advantage of such an indicator is that the bias can only result from an under-registration of the centenarians who emigrated, which leads to only a slight underestimation of ELI. A similar indicator has also been computed for assessing the probability of the studied population reaching 90 years of age.

In Sardinia, the municipality of Villagrande Strisaili, the epicenter of the LBZ, was the object of an in‒depth demographic study (Poulain et al., 2011). All birth and death records for the period 1866–2016 were entered into an electronic database, which also includes information about all family links within the population. We also considered the administrative information available in the anagrafe, the Italian population registration system, to identify those who emigrated and died outside the village. By doing so, we succeeded in obtaining the date of and age at death or proof of survival for 98 % of the newborns identified.

In Ikaria, census data and age-at-death statistics were retrieved from the Hellenic Statistical Authority. These were compared with individual data extracted from the δημoτoλoγίων, a locally‒based administrative registry that contains demographic information on all Greek citizens in a given municipality. Unfortunately, for the oldest old on the island, no birth records could be found. Therefore, the extinct-cohort method, which involves exhaustive identification of those surviving and aged above 90, as well as those who had been part of the same birth cohorts and died during the two last decades, was used to estimate the level of population longevity. Individual age validation was successfully achieved during interviews with all those aged 90 years and above in the North-Western part of the island by using a battery of questions on the occurrence of demographic events and the age of close relatives.

Section snippets

Material and methods

The study population included: (i) nonagenarians living in the village of Villagrande Strisaili which is characterized by the highest longevity level (ELI) in the region, especially among men, and (ii) nonagenarians living in the municipal units of Raches and Evdilos in Ikaria, which are characterized by the highest longevity level in Greece according to statistical data provided by the Hellenic Statistical Authority. The study protocol was approved by the local ethics committees. The

Comparative levels of longevity

As stated earlier, the longevity of a given population can be assessed from different indicators. Table 1 illustrates relevant information about our study population. Unfortunately, it is unknown how many newborns Greece and Ikaria had at the turn of the 20th century, and no data is available for Greece in the Human Mortality Database1. Nevertheless, the longevity advantage of the two LBZs over the respective Italian and Greek populations is clearly evident. This advantage is larger for the

Discussion

Exceptional human longevity has become a field of growing interest as research in this field can potentially identify the relevant factors that can help people live a longer and healthier life (Franceschi et al., 2000, 2007; Fortney et al., 2015; Schoenhofen et al., 2006). However, identification of the major determinants that affect the duration of human life has proven intrinsically difficult as longevity is a complex trait resulting from the interaction between genetics, environment and

Conclusions

Populations with exceptionally high longevity could be a promising model in mortality research. LBZs are unique because the populations living there have a significantly higher proportion of long-lived individuals than the population living anywhere else. Our study revealed that nonagenarians from such populations display demographic, lifestyle and genetic traits that are different from the traits of the nonagenarians selected at random from other populations. For example, a greater proportion

Funding

This research was partially supported by an Estonian Research Council grant (PRG71).

Acknowledgments

The authors are very grateful to the Municipality of Villagrande Strisaili especially Mrs. Rita Usai and Simona Rubiu, for their invaluable help to this research. We also thank Dany Chambre, who helped with the data collection and the revision of the text. This research was partially supported by an Estonian Research Council grant (PRG71). Particular thanks go to the GEHA project consortium, whose work was funded by the EU GEHA (GEnetics of Healthy Ageing) Project contract no.

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