Exploring Patterns of Human Mortality and Aging: A Reliability Theory Viewpoint.

The most important manifestation of aging is an increased risk of death with advancing age, a mortality pattern characterized by empirical regularities known as mortality laws. We highlight three significant ones: the Gompertz law, compensation effect of mortality (CEM), and late-life mortality deceleration and describe new developments in this area. It is predicted that CEM should result in declining relative variability of mortality at older ages. The quiescent phase hypothesis of negligible actuarial aging at younger adult ages is tested and refuted by analyzing mortality of the most recent birth cohorts. To comprehend the aging mechanisms, it is crucial to explain the observed empirical mortality patterns. As an illustrative example of data-directed modeling and the insights it provides, we briefly describe two different reliability models applied to human mortality patterns. The explanation of aging using a reliability theory approach aligns with evolutionary theories of aging, including idea of chronic phenoptosis. This alignment stems from their focus on elucidating the process of organismal deterioration itself, rather than addressing the reasons why organisms are not designed for perpetual existence. This article is a part of a special issue of the journal that commemorates the legacy of the eminent Russian scientist Vladimir Petrovich Skulachev (1935-2023) and his bold ideas about evolution of biological aging and phenoptosis.

Actuarial Aging Rates in Human Cohorts.

Aging rate is an important characteristic of human aging. Attempts to measure aging rates through the Gompertz slope parameter lead to a conclusion that actuarial aging rates were stable during the most of the 20th century, but recently demonstrate an increase over time in the majority of studied populations. These findings were made using cross-sectional mortality data rather than by the analysis of mortality of real birth cohorts. In this study we analyzed historical changes of actuarial aging rates in human cohorts. The Gompertz parameters were estimated in the age interval 50-80 years using data on one-year cohort age-specific death rates from the Human Mortality Database (HMD). Totally, data for 2,294 cohorts of men and women from 76 populations were analyzed. Changes of the Gompertz slope parameter in the studied cohorts revealed two distinct patterns for actuarial aging rate. In higher mortality Eastern European countries actuarial aging rates showed continuous decline from the 1910 to 1940 birth cohort. In lower mortality Western European countries, Australia, Canada, Japan, New Zealand, and USA actuarial aging rates declined from the 1910th to approximately 1930th cohort and then increased. Overall, in 50 out of 76 populations (68%) actuarial aging rate demonstrated decreasing pattern of change over time. Compensation effect of mortality (CEM) was tested for the first time in human cohorts and the cohort species-specific lifespan was estimated. CEM was confirmed using cohort data and human cohort species-specific lifespan estimates were similar to the estimates obtained for the cross-sectional data published earlier.

On the Commentary by Anatoly I. Mikhalsky Published in Biochemistry (Moscow), Vol. 88, No. 1, pp. 162-163 (2023).

Caution is needed in using cohort data when studying age-related mortality dynamics, because mortality depends not only on age, but also on the changing living conditions over time. A hypothesis is proposed for further testing that the actuarial aging rate may even decrease in more recent birth cohorts of people due to improved living conditions.

Trends in Human Species-Specific Lifespan and Actuarial Aging Rate.

The compensation effect of mortality (CEM) was tested and species-specific lifespan was estimated using data on one-year age-specific death rates from the Human Mortality Database (HMD). CEM was confirmed using this source of the data and human species-specific lifespan estimates were obtained, which were similar to the estimates published before. Three models (Gompertz-Makeham, Gompertz-Makeham with mean-centered age, and Gompertz) produced similar estimates of the species-specific lifespan. These estimates demonstrated some increase over time. Attempts to measure aging rates through the Gompertz slope parameter led to the conclusion that actuarial aging rates were stable during most of the 20th century, but recently demonstrated an increase over time in the majority (74%) of studied populations. This recent phenomenon is most likely caused by more rapid historical decline of mortality at the younger adult age groups compared to the older age groups, thus making the age gradient in mortality steeper over time. There is no biomedical reason to believe that human aging rates accelerated recently, so that the actuarial aging rate is probably not a good measure of true aging rate (rate of functional loss). Therefore, better measures of aging rate need to be developed.

Protective Effects of Familial Longevity Decrease With Age and Become Negligible for Centenarians.

It is known that biological relatives of long-lived individuals demonstrate lower mortality and longer life span compared to relatives of shorter-lived individuals, and at least part of this advantage is likely to be genetic. Less information, however, is available about effects of familial longevity on age-specific mortality trajectories. We compared mortality patterns after age 50 years for 10 045 siblings of US centenarians and 12 308 siblings of shorter-lived individuals (died at age 65 years). Similar comparisons were made for sons and daughters of longer-lived parents (both parents lived 80 years and more) and shorter-lived parents (both parents lived less than 80 years) within each group of siblings. Although relatives of longer-lived individuals have lower mortality at younger ages compared to relatives of shorter-lived individuals, this mortality advantage practically disappears by age 100 years. To validate this observation further, we analyzed the survival of 3 408 US centenarians born in 1890-1897 with known information on maternal and paternal life span. We found using the Cox proportional hazards model that both maternal and paternal longevity (life span 80+ years) is not significantly associated with survival after age 100 years. The results are compatible with the predictions of reliability theory of aging suggesting higher initial levels of system redundancy (reserves) in individuals with protective familial/genetic background and hence lower initial mortality. Heterogeneity hypothesis is another possible explanation for the observed phenomena.

Patterns of mortality during pandemic: An example of Spanish flu pandemic of 1918.

Now the attention of the whole world is focused on the developing pandemic of the coronavirus infection COVID-19. This article discusses mortality patterns of the deadliest epidemic in the last 120 years - the Spanish flu pandemic of 1918. Statistical sources from Italy and the USA, published shortly after the pandemic, were analyzed. The analysis was carried out for mortality from all causes, since in this case inaccuracies associated with establishing the causes of death are minimized. Despite the fact that the first cases of the Spanish flu appeared in the United States as early as March 1918, this first wave of epidemic practically did not affect the total mortality rate. The main peak of mortality in 1918 occurred in October 1918 both in the USA and Italy, with a gradual decrease in mortality over several months. Analysis of age-specific mortality demonstrates a significant increase in mortality at middle ages (20-50 years) in 1918 compared with 1917. Analysis of mortality trends using the method of latent variables shows a significant increase in the background mortality factor in 1918, which turned out to be higher for Italy than the mortality losses during the Second World War. The Spanish flu pandemic differs from the current coronavirus pandemic, because of significant increase in mortality of middle-aged people, while the COVID-19 pandemic causes a more marked increase in mortality among the elderly. With this, the COVID-19 pandemic is more like the recent flu epidemics than the earlier Spanish flu pandemic.

Are We Approaching a Biological Limit to Human Longevity?

Until recently human longevity records continued to grow in history, with no indication of approaching a hypothetical longevity limit. Also, earlier studies found that age-specific death rates cease to increase at advanced ages (mortality plateau) suggesting the absence of fixed limit to longevity too. In this study, we reexamine both claims with more recent and reliable data on supercentenarians (persons aged 110 years and older). We found that despite a dramatic historical increase in the number of supercentenarians, further growth of human longevity records in subsequent birth cohorts slowed down significantly and almost stopped for those born after 1879. We also found an exponential acceleration of age-specific death rates for persons older than 113 years in more recent data. Slowing down the historical progress in maximum reported age at death and accelerated growth of age-specific death rates after age 113 years in recent birth cohorts may indicate the need for more conservative estimates for future longevity records unless a scientific breakthrough in delaying aging would happen. The hypothesis of approaching a biological limit to human longevity has received some empirical support and it deserves further study and testing.

New Trend in Old-Age Mortality: Gompertzialization of Mortality Trajectory.

There is great interest among gerontologists, demographers, and actuaries in the question concerning the limits to human longevity. Attempts at getting answers to this important question have stimulated many studies on late-life mortality trajectories, often with opposing conclusions. One group of researchers believes that mortality stops growing with age at extreme old ages, and that hence there is no fixed limit to the human life span. Other studies found that mortality continues to grow with age up to extreme old ages. Our study suggests a possible solution to this controversy. We found that mortality deceleration is best observed when older, less accurate life span data are analyzed, while in the case of more recent and reliable data there is a persistent mortality growth with age. We compared the performance (goodness of fit) of two competing mortality models - the Gompertz model and the Kannisto ("mortality deceleration") model - at ages of 80-105 years using data for 1880-1899 single-year birth cohorts of US men and women. The mortality modeling approach suggests a transition from mortality deceleration to the Gompertzian mortality pattern over time for both men and women. These results are consistent with the hypothesis about disappearing mortality deceleration over time due to improvement in the accuracy of age reporting. In the case of more recent data, mortality continues to grow with age even at very old ages. This observation may lead to more conservative estimates of future human longevity records.

Late-life mortality is underestimated because of data errors.

Knowledge of true mortality trajectory at extreme old ages is important for biologists who test their theories of aging with demographic data. Studies using both simulation and direct age validation found that longevity records for ages 105 years and older are often incorrect and may lead to spurious mortality deceleration and mortality plateau. After age 105 years, longevity claims should be considered as extraordinary claims that require extraordinary evidence. Traditional methods of data cleaning and data quality control are just not sufficient. New, more strict methodologies of data quality control need to be developed and tested. Before this happens, all mortality estimates for ages above 105 years should be treated with caution.

Mortality Trajectories at Exceptionally High Ages: A Study of Supercentenarians.

The growing number of persons surviving to age 100 years and beyond raises questions about the shape of mortality trajectories at exceptionally high ages, and this problem may become significant for actuaries in the near future. However, such studies are scarce because of the difficulties in obtaining reliable age estimates at exceptionally high ages. The current view about mortality beyond age 110 years suggests that death rates do not grow with age and are virtually flat. The same assumption is made in the new actuarial VBT tables. In this paper, we test the hypothesis that the mortality of supercentenarians (persons living 110+ years) is constant and does not grow with age, and we analyze mortality trajectories at these exceptionally high ages. Death records of supercentenarians were taken from the International Database on Longevity (IDL). All ages of supercentenarians in the database were subjected to careful validation. We used IDL records for persons belonging to extinct birth cohorts (born before 1895) since the last deaths in IDL were observed in 2007. We also compared our results based on IDL data with a more contemporary database maintained by the Gerontology Research Group (GRG). First we attempted to replicate findings by Gampe (2010), who analyzed IDL data and came to the conclusion that "human mortality after age 110 is flat." We split IDL data into two groups: cohorts born before 1885 and cohorts born in 1885 and later. Hazard rate estimates were conducted using the standard procedure available in Stata software. We found that mortality in both groups grows with age, although in older cohorts, growth was slower compared with more recent cohorts and not statistically significant. Mortality analysis of more numerous 1884-1894 birth cohort with the Akaike goodness-of-fit criterion showed better fit for the Gompertz model than for the exponential model (flat mortality). Mortality analyses with GRG data produced similar results. The remaining life expectancy for the 1884-1894 birth cohort demonstrates rapid decline with age. This decline is similar to the computer-simulated trajectory expected for the Gompertz model, rather than the extremely slow decline in the case of the exponential model. These results demonstrate that hazard rates after age 110 years do not stay constant and suggest that mortality deceleration at older ages is not a universal phenomenon. These findings may represent a challenge to the existing theories of aging and longevity, which predict constant mortality in the late stages of life. One possibility for reconciliation of the observed phenomenon and the existing theoretical consideration is a possibility of mortality deceleration and mortality plateau at very high yet unobservable ages.

Historical Evolution of Old-Age Mortality and New Approaches to Mortality Forecasting.

Knowledge of future mortality levels and trends is important for actuarial practice but poses a challenge to actuaries and demographers. The Lee-Carter method, currently used for mortality forecasting, is based on the assumption that the historical evolution of mortality at all age groups is driven by one factor only. This approach cannot capture an additive manner of mortality decline observed before the 1960s. To overcome the limitation of the one-factor model of mortality and to determine the true number of factors underlying mortality changes over time, we suggest a new approach to mortality analysis and forecasting based on the method of latent variable analysis. The basic assumption of this approach is that most variation in mortality rates over time is a manifestation of a small number of latent variables, variation in which gives rise to the observed mortality patterns. To extract major components of mortality variation, we apply factor analysis to mortality changes in developed countries over the period of 1900-2014. Factor analysis of time series of age-specific death rates in 12 developed countries (data taken from the Human Mortality Database) identified two factors capable of explaining almost 94 to 99 percent of the variance in the temporal changes of adult death rates at ages 25 to 85 years. Analysis of these two factors reveals that the first factor is a "young-age" or background factor with high factor loadings at ages 30 to 45 years. The second factor can be called an "oldage" or senescent factor because of high factor loadings at ages 65 to 85 years. It was found that the senescent factor was relatively stable in the past but now is rapidly declining for both men and women. The decline of the senescent factor is faster for men, although in most countries, it started almost 30 years later. Factor analysis of time series of age-specific death rates conducted for the oldest-old ages (65 to 100 years) found two factors explaining variation of mortality at extremely old ages in the United States. The first factor is comparable to the senescent factor found for adult mortality. The second factor, however, is specific to extreme old ages (96 to 100 years) and shows peaks in 1960 and 2000. Although mortality below 90 to 95 years shows a steady decline with time driven by the senescent factor, mortality of centenarians does not decline and remains relatively stable. The approach suggested in this paper has several advantages. First, it is able to determine the total number of independent factors affecting mortality changes over time. Second, this approach allows researchers to determine the time interval in which underlying factors remain stable or undergo rapid changes. Most methods of mortality projections are not able to identify the best base period for mortality projections, attempting to use the longest-possible time period instead. We observe that the senescent factor of mortality continues to decline, and this decline does not demonstrate any indications of slowing down. At the same time, mortality of centenarians does not decline and remains stable. The lack of mortality decline at extremely old ages may diminish anticipated longevity gains in the future.

The Future of Human Longevity.

Recent scientific publications suggest that human longevity records stopped increasing. Our finding that the mortality of centenarians has not decreased noticeably in recent decades (despite a significant mortality decline in younger age groups) is consistent with this suggestion. However, there is no convincing evidence that we have reached the limit of human life span. The future of human longevity is not fixed and will depend on human efforts to extend life span.

Predictors of Exceptional Longevity: Effects of Early-Life and Midlife Conditions, and Familial Longevity.

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890-1891 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are occupation as a farmer at age 40, Northeastern region of birth in the United States, and birth in the second half of year. A gender-specific predictor of female longevity is the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880-1895. We found that male gender of centenarian has a significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival compared to wives of centenarians' brothers. This finding demonstrates an important role of shared familial environment and lifestyle in human longevity. The results of this study suggest that familial background, some early-life conditions and midlife characteristics play an important role in longevity.

Biodemography of old-age mortality in humans and rodents.

The growing number of persons living beyond age 80 underscores the need for accurate measurement of mortality at advanced ages and understanding the old-age mortality trajectories. It is believed that exponential growth of mortality with age (Gompertz law) is followed by a period of deceleration, with slower rates of mortality increase at older ages. This pattern of mortality deceleration is traditionally described by the logistic (Kannisto) model, which is considered as an alternative to the Gompertz model. Mortality deceleration was observed for many invertebrate species, but the evidence for mammals is controversial. We compared the performance (goodness-of-fit) of two competing models-the Gompertz model and the logistic (Kannisto) model using data for three mammalian species: 22 birth cohorts of U.S. men and women, eight cohorts of laboratory mice, and 10 cohorts of laboratory rats. For all three mammalian species, the Gompertz model fits mortality data significantly better than the "mortality deceleration" Kannisto model (according to the Akaike's information criterion as the goodness-of-fit measure). These results suggest that mortality deceleration at advanced ages is not a universal phenomenon, and survival of mammalian species follows the Gompertz law up to very old ages.

New Developments in the Biodemography of Aging and Longevity.

Biodemography is a promising scientific approach based on using demographic data and methods for getting insights into biological mechanisms of observed processes. Recently, new important developments have happened in biodemographic studies of aging and longevity that call into question conventional aging theories and open up novel research directions. Recent studies found that the exponential increase of the mortality risk with age (the famous Gompertz law) continues even at extreme old ages in humans, rats, and mice, thus challenging traditional views about old-age mortality deceleration, mortality leveling-off, and late-life mortality plateaus. This new finding represents a challenge to many aging theories, including the evolutionary theory that explains senescence by a declining force of natural selection with age. Innovative ideas are needed to explain why exactly the same exponential pattern of mortality growth is observed not only at reproductive ages, but also at very-old postreproductive ages (up to 106 years), long after the force of natural selection becomes negligible (when there is no room for its further decline). Another important recent development is the discovery of long-term 'memory' for early-life experiences in longevity determination. Siblings born to young mothers have significantly higher chances to live up to 100 years, and this new finding, confirmed by two independent research groups, calls for its explanation. As recent studies found, even the place and season of birth matter for human longevity. Beneficial longevity effects of young maternal age are observed only when children of the same parents are compared, while the maternal age effect often could not be detected in across-families studies, presumably being masked by between-family variation. It was also found that male gender of centenarian has a significant positive effect on the survival of adult male biological relatives (brothers and fathers) but not of female relatives. Finally, large gender differences are found in longevity determinants for males and females, suggesting a higher importance of occupation history for male centenarians as well as a higher importance of home environment history for female centenarians.

Predictors of Exceptional Longevity: Effects of Early-Life Childhood Conditions, Midlife Environment and Parental Characteristics.

Knowledge of strong predictors of mortality and longevity is very important for actuarial science and practice. Earlier studies found that parental characteristics as well as early-life conditions and midlife environment play a significant role in survival to advanced ages. However, little is known about the simultaneous effects of these three factors on longevity. This ongoing study attempts to fill this gap by comparing centenarians born in the United States in 1890-91 with peers born in the same years who died at age 65. The records for centenarians and controls were taken from computerized family histories, which were then linked to 1900 and 1930 U.S. censuses. As a result of this linkage procedure, 765 records of confirmed centenarians and 783 records of controls were obtained. Analysis with multivariate logistic regression found that parental longevity and some midlife characteristics proved to be significant predictors of longevity while the role of childhood conditions was less important. More centenarians were born in the second half of the year compared to controls, suggesting early origins of longevity. We found the existence of both general and gender-specific predictors of human longevity. General predictors common for men and women are paternal and maternal longevity. Gender-specific predictors of male longevity are the farmer occupation at age 40, Northeastern region of birth in the United States and birth in the second half of year. A gender-specific predictor of female longevity is surprisingly the availability of radio in the household according to the 1930 U.S. census. Given the importance of familial longevity as an independent predictor of survival to advanced ages, we conducted a comparative study of biological and nonbiological relatives of centenarians using a larger sample of 1,945 validated U.S. centenarians born in 1880-95. We found that male gender of centenarian has significant positive effect on survival of adult male relatives (brothers and fathers) but not female blood relatives. Life span of centenarian siblings-in-law is lower compared to life span of centenarian siblings and does not depend on centenarian gender. Wives of male centenarians (who share lifestyle and living conditions) have a significantly better survival compared to wives of centenarians' brothers. This finding demonstrates an important role of shared familial environment and lifestyle in human longevity. The results of this study suggest that familial background, early-life conditions and midlife characteristics play an important role in longevity.

Mortality Trajectories at Extreme Old Ages: A Comparative Study of Different Data Sources on U.S. Old-Age Mortality.

The growing number of individuals living beyond age 80 underscores the need for accurate measurement of mortality at advanced ages. Our earlier published study challenged the common view that the exponential growth of mortality with age (Gompertz law) is followed by a period of deceleration, with slower rates of mortality increase (Gavrilov and Gavrilova 2011). This refutation of mortality deceleration was made using records from the U.S. Social Security Administration's Death Master File (DMF). Taking into account the significance of this finding for actuarial theory and practice, we tested these earlier observations using additional independent datasets and alternative statistical approaches. In particular, the following data sources for U.S. mortality at advanced ages were analyzed: (1) data from the Human Mortality Database (HMD) on age-specific death rates for 1890-99 U.S. birth cohorts, (2) recent extinct birth cohorts of U.S. men and women based on DMF data, and (3) mortality data for railroad retirees. In the case of HMD data, the analyses were conducted for 1890-99 birth cohorts in the age range 80-106. Mortality was fitted by the Gompertz and logistic (Kannisto) models using weighted nonlinear regression and Akaike information criterion as the goodness-of-fit measure. All analyses were conducted separately for men and women. It was found that for all studied HMD birth cohorts, the Gompertz model demonstrated better fit of mortality data than the Kannisto model in the studied age interval. Similar results were obtained for U.S. men and women born in 1890-99 and railroad retirees born in 1895-99 using the full DMF file (obtained from the National Technical Information Service, or NTIS). It was also found that mortality estimates obtained from the DMF records are close to estimates obtained using the HMD cohort data. An alternative approach for studying mortality patterns at advanced ages is based on calculating the age-specific rate of mortality change (life table aging rate, or LAR) after age 80. This approach was applied to age-specific death rates for Canada, France, Sweden and the United States available in HMD. It was found that for all 24 studied single-year birth cohorts, LAR does not change significantly with age in the age interval 80-100, suggesting no mortality deceleration in this interval. Simulation study of LAR demonstrated that the apparent decline of LAR after age 80 found in earlier studies may be related to biased estimates of mortality rates measured in a wide five-year age interval. Taking into account that there exists several empirical estimates of hazard rate (Nelson-Aalen, actuarial and Sacher), a simulation study was conducted to find out which one is the most accurate and unbiased estimate of hazard rate at advanced ages. Computer simulations demonstrated that some estimates of mortality (Nelson-Aalen and actuarial) as well as kernel smoothing of hazard rates may produce spurious mortality deceleration at extreme ages, while the Sacher estimate turns out to be the most accurate estimate of hazard rate. Possible reasons for finding apparent mortality deceleration in earlier studies are also discussed.

Determinants of exceptional human longevity: new ideas and findings.

Studies of centenarians are useful in identifying factors leading to long life and avoidance of fatal diseases. In this article we consider several approaches to study effects of early-life and midlife conditions on survival to advanced ages: use of non-biological relatives as controls, the within-family analysis, as well as a sampling of controls from the same population universe as centenarians. These approaches are illustrated using data on American centenarians, their relatives and unrelated shorter-lived controls obtained from the online genealogies. The within-family analysis revealed that young maternal age at person's birth is associated with higher chances of exceptional longevity. Comparison of centenarians and their shorter-lived peers (died at age 65 and sampled from the same pool of online genealogies) confirmed that birth timing in the second half of the calendar year predicts survival to age 100. Parental longevity as well as some childhood and midlife characteristics also proved to be significant predictors of exceptional longevity.

Biodemography of exceptional longevity: early-life and mid-life predictors of human longevity.

This study explores the effects of early-life and middle-life conditions on exceptional longevity using two matched case-control studies. The first study compares 198 validated centenarians born in the United States between 1890 and 1893 to their shorter-lived siblings. Family histories of centenarians were reconstructed and exceptional longevity validated using early U.S. censuses, the Social Security Administration Death Master File, state death indexes, online genealogies, and other supplementary data resources. Siblings born to young mothers (aged less than 25 years) had significantly higher chances of living to 100 compared to siblings born to older mothers (odds ratio = 2.03, 95% CI = 1.33-3.11, p = .001). Paternal age and birth order were not associated with exceptional longevity. The second study explores whether people living to 100 years and beyond differ in physical characteristics at a young age from their shorter-lived peers. A random representative sample of 240 men who were born in 1887 and survived to age 100 was selected from the U.S. Social Security Administration database and linked to U.S. World War I civil draft registration cards collected in 1917 when these men were 30 years old. These validated centenarians were then compared to randomly selected controls who were matched by calendar year of birth, race, and place of draft registration in 1917. Results showed a negative association between "stout" body build (being in the heaviest 15 percent of the population) and survival to age 100. Having the occupation of "farmer" and a large number of children (4 or more) at age 30 increased the chances of exceptional longevity. The results of both studies demonstrate that matched case-control design is a useful approach in exploring effects of early-life conditions and middle-life characteristics on exceptional longevity.

Comments on dietary restriction, Okinawa diet and longevity.

Longevity in Okinawa is considered to be a result of traditional low calorie diet. Le Bourg suggests that Okinawa is an example of severe malnutrition, which is harmful for later generations. We believe that current loss of longevity advantage in Okinawa is a result of diet westernization and that the dietary restriction is a valid way of life extension in humans.