Our objective was to present normative data across dimensions of physical and cognitive performance as well as a range of disease classifications as a function of gender, race, residence, and educational attainment. Overall, our results point to clear and highly consistent differences as a function of these variables, suggesting that differences and disparities observed with younger samples (
Au et al., 2004;
Dore et al., 2007) are also observed into the second century of life.
Analysis of gender differences point toward better physical and cognitive functioning for male centenarians compared with female centenarians. Where gender differences exist in terms of diseases, the pattern is largely similar, with the exception that male centenarians are more likely to experience neurological disorders than female centenarians, and to report use of alcohol and tobacco, although data such as these may also be subject to considerable under-reporting (
Graham, 1986).
With regard to race differences, the pattern is largely similar, with more consistent evidence that white centenarians experience better physical and cognitive functioning than do African Americans. This is true for the small number of diseases for which there are racial differences. Most notably, diabetes and hypertension are much more prevalent among African American than white centenarians (Mokdad et al., 2003). On the other hand, white centenarians are much more likely to have osteoporosis (Looker et al., 1997). Differences in blood pressure are limited to DBP. African Americans are more likely to report past or current smoking than whites (Husten et al., 1997 reported that smoking cessation rates were higher among whites than African Americans), and to be overweight or obese (Mokdad et al., 2003).
Community versus institutional living forms yet another consistent axis that differentiates physical and cognitive functioning and disease among centenarians. As would be expected community-living centenarians reported considerably better physical functioning than their institutional-living counterparts on nearly every measure and on every cognitive measure administered. Those living in facilities were more likely to have used alcohol in the past, whereas those in the community were more likely to report current alcohol use. Prevalence of disease was also much higher among centenarians living in institutions than in the community, although it is important to recognize that the institutional setting also provides great opportunities for recognition and diagnosis than community residence. There is also considerable potential for confounding effects in the association between disease categories and residential status. The same characteristic (e.g., lack of partner) may be a risk factor for both nursing home placement and depression.
Educational attainment provided the final dimension across which differences were considered. Here, the most consistent differences were found as a function of those with less than high school versus those with more than high school education, followed by those with less than high school education compared with those having at least some high school education. It is important to note, however, that for many domains, individuals who completed high school had lower performance than individuals with at least some high school, although it is not clear why this should be the case. One possibility is that individuals forced to leave high school prior to graduation had different opportunities and experiences than those who graduated but did not continue to college, making them effectively more similar to individuals with education beyond high school. Most studies employ years of formal education as controls, but do not include other proxies for education. It is extremely important to adjust for education and proxies for education when comparing ethnic/racial groups (Aiken-Morgan, Sims, & Whitfield, 2008). The work of Aiken-Morgan et al.(2008) makes it clear that years of formal education is far from a pure or reliable indicator of “true education level,” and that reading ability is a very important control in this respect. These investigators found that magnitude of differences in performance between African American samples and European American samples decreased with adjustment for reading ability, although they were not attenuated. These investigators urge the use of multiple proxy variables for education in studies involving comparisons between African American samples and cognitive performance. It is clear that a much more concerted effort is needed with respect to studies of African American cohorts and other ethnic groups. If this effort is made, cross-sectional designs will generate important hypotheses for further studies, especially the prospective and longitudinal studies that are needed.
Only a single difference was observed in terms of educational attainment and disease, such that prevalence of diabetes was highest among those with the lowest and highest levels of educational attainment. This differs somewhat from previous research with younger samples which has suggested only that low educational attainment is associated with higher risk of diabetes mellitus (
Bachman et al., 2003;
Steinvil et al., 2008). Although prevalence in the former groups was still more than twice as high as in the second group, this does suggest that clinicians may wish to pay attention to the possibility of diabetes mellitus among this highly educated group which may possess knowledge of appropriate health behaviors but also a surfeit of resources that may lead to diabetes, greater opportunity for business and social activities that involve consumption of enjoyable but non-nutritional and cholesterol lowering food and drink. With regard to diseases and health habits, it may not be sufficient to focus only on those individuals with the lowest levels of education but also on those with greater access to resources.
Multivariate analyses elaborate on these bivariate associations in two key ways. First, they suggest that many of the associations with gender and race can likely be attributable to differences in residential status and / or educational attainment. In multifactorial ANOVAs, all of the cognitive differences associated with gender vanish, leaving differences only in two measures of strength and direct assessment of IADLs. Similarly, race differences are limited to scores on the GDRS as the only cognitive domain and on direct assessment of BADLs for physical performance. Not surprisingly, the remaining differences are greatest for residential status in terms of physical performance and greatest for educational attainment for cognitive status. Second, adding health variables to our model, generally added little over and above the importance of these four dimensions. This is similar to the findings of an earlier paper on norms for cognitive measures using younger samples (
Dore et al., 2007). Overall, our multivariate models generally account for roughly one quarter of the variance in cognitive and physical performance measures (median values .26 and .24, respectively, compared with a median value for cognitive measures of .16 in
Dore et al., 2007), suggesting important systematic sources of variation within this sample of centenarians.
It is difficult to over-state the importance of population aging for society, or to fully capture the extent of changes which are occurring as a result of these demographic shifts. It is only recently that living until old age has become a normal and expected aspect of the life-cycle; and, recent demographic research suggests that these changes are likely to continue for the foreseeable future, with critical importance for cognitive functioning, physical performance, health and health behaviors and lifetime history of disease. Using Perls and colleagues' (Evert et al. 2004) classifications of New England Centenarian Study (NECS) centenarians as survivors (onset of chronic disease prior to age 80), delayers (onset of chronic disease after age 80) or escapers (absence of chronic disease),
Arnold and colleagues (2010) have found that the modal category is survivor (43%) with only 17% of centenarians reaching this centenarian status as escapers. These proportions are similar to both the NECS study with 19% escapers data and a Danish study of the 1905 birth cohort with 19% escapers (
Engberg et al., 2009).
Olshansky et al. (2009) suggest that official government projections are even likely to underestimate the extent of population aging in the coming decades because they do not account for likely advances in biomedical technology that can delay the onset and progression of major fatal diseases or perhaps slow the aging process itself.
Similarly, existing assessment tools may not be adequate to capture the full range of cognitive functioning and physical performance in centenarians. Recently,
Cress and colleagues (2010) have demonstrated how multiple physical performance indicators can be combined using item response theory methods in order to derive a continuously scaled measure of physical performance that has greater concurrent and predictive (of mortality) validity than existing scales developed for use with younger samples. Further, these methods appear useful with the younger samples as well, providing the possibility of cross-walking measures across samples of different ages or which differ in terms of underlying functioning. The broad range of cognitive measures available in the Georgia Centenarian Study suggests this may be a fruitful future area of inquiry. Similarly, it may be worthwhile to consider the possibility of developing ways to equate measures across the many disparate data sets which include centenarians in order to derive meaningful estimates across pooled samples, or to compare different cohorts of centenarians on cognitive and physical performance measures. Because this sample represents approximately .02% of the members of their birth cohort, it is important to bear in mind that this sample is already highly selected. Selection forces out of the population may diminish as larger proportion of future cohorts reach centenarian status, changing definitions of what is “normal” (i.e., primary aging) as well as what is “normative” (i.e., prevalent) in a sample for which a majority (57%) have scores on the Global Deterioration Rating Scale between 4 and 7, suggesting high rates of cognitive impairment. It might be argued that data for persons 98 years and beyond cannot be described as normal; consequently, we have only presented descriptive data not norms. We counter this argument with three observations. This notion comes from a psychometric tradition, e.g., the Wechsler Adult Intelligence Scale, suggesting that what is true for youth is the norm. Second, norms do not imply a standard that applies to most people. It cannot be argued that surviving into very old age is not normal, or we would not see this phenomenon. Given the large number of persons surviving into their second century of life, it is imperative that the neuropsychologists to be able to compare the cognitive ability and function with those of their patients and to do so relative to their own age cohort. First and foremost, our normative data are provided for the clinical neuropsychologist, neurologists, psychologists, and health professionals involved in cognitive and functional diagnostics with these exceptional individuals. Finally, we note several limitations in the present study. Although ideal, longitudinal data are difficult to collect with this age group, and fraught with selective attrition. Similarly, many measures appropriate for use with younger samples cannot be used with a large proportion of our sample due to ceiling and floor effects, or because they would have been too taxing in light of all of the other constructs evaluated in this study. Additionally, some variables were obtained, of necessity, by self-report. Centenarians may have limited availability of proxy reporters and self-report may be difficult to obtain due to sensory or cognitive impairments. Finally, we did not have access to measures of premorbid intelligence such as reading ability and so had to rely instead on educational attainment.
The publisher's final edited version of this article is available at 
