Predictors of Mortality in 2,249 Nonagenarians—The Danish 1905‐Cohort Survey

Nybo, Hanne; Petersen, Hans Christian; Garcı́a-Dorado, David; Jeune, Bernard; Andersen, Kjeld; McGue, Matt; Vaupel, James W.; Christensen, Kaare

doi:10.1046/j.1532-5415.2003.51453.x

Cited by 238 publications

(280 citation statements)

References 38 publications

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“…those factors (among socio-demographic, physiological, clinical and haematochemical parameters) that are able to predict survival in the oldest old. On the whole, the survival analysis on the total Italian 90+ population demonstrated the longevity advantage of females, and it confirmed that factors often found to predict mortality in middle-aged and younger elderly, such as marital status, low education, blue collar type of occupation, smoking and every day alcohol intake, lost their importance at advanced ages, since they did not influence mortality (Nybo et al 2003). Moreover, it confirmed the predictive power of good physical ability (self-sufficiency for the basic ADL items), intact cognitive functioning (SMMSE test), positive self-rated health, absence of past myocardial infarction, BMI and hand grip strength over the median for future survival.…”

Section: Discussionsupporting

confidence: 62%

“…Therefore, given this increasing importance of the functional status as a predictor of survival, it is worth noting that, at an even more exceptional old age (after age 100), survival is mainly dependent on physiological reserve, physical and cognitive functions, as found in a study on Swedish centenarians (Hagberg and Samuelsson 2008). In spite previous studies showed that poor self-rated health was associated with increased mortality only in women (Nybo et al 2003), our results indicated that "excellent/good" self-reported health might be considered as one of the factors predicting survival in the oldest old, as found in more recent studies on old subjects from Calabria (Montesanto et al 2010) and from Denmark (Dato et al 2012). These data suggest the effectiveness of self-reported health, very simple to collect, as a surrogate measure of comorbidity and disability (Passarino et al 2007).…”

Section: Discussionmentioning

confidence: 99%

“…SMMSE scores range from 0 (lowest cognitive function) to 30 (highest cognitive function). The categorisation proposed by Nybo was used to assess the cognitive status: "severe cognitive impairment" (0-17 points), "mild" (18-23 points) and "un-impairment" (24-30 points) (Nybo et al 2003). In case of a proxy interview (i.e.…”

Section: Data Collectionmentioning

confidence: 99%

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Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Cevenini¹,

Cotichini²,

Stazi³

et al. 2013

AGE

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In a scenario of increasing life expectancy worldwide, it is mandatory to identify the characteristics of a healthy aging phenotype, including survival predictors, and to disentangle those related to environment/ lifestyle versus those related to familiarity/genetics. To this aim we comprehensively characterised a cohort of 1,160 Italian subjects of 90 years and over (90+, mean age 93 years; age range 90-106 years) followed for 6 years survival, belonging to 552 sib-ships (familiar longevity) recruited (2005)(2006)(2007)(2008) within the EU-funded GEHA project in three Italian geographic areas (Northern, Central and Southern Italy) different for urban/rural and socio-economical characteristics. On the whole, the following factors emerged as significant predictors of survival after 90 years of age: absence of cognitive impairment and physical disability, high hand grip strength scores and body mass index (BMI) values, "excellent/good" self-reported health, high haemoglobin and total cholesterol levels and low creatinine levels. These parameters, excluding BMI values, were also significantly associated within sib-ships, suggesting a strong familial/genetic component. Geographical micro-heterogeneity of survival predictors emerged, such as functional and physical status being more important in Southern than in Central and Northern Italy. In conclusion, we identified modifiable survival predictors related to specific domains, whose role and importance vary according to the geographic area considered and which can help in interpreting the genetic results obtained by the GEHA project, whose major aim is the comprehensive evaluation of phenotypic and genetic data.

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Section: Discussionsupporting

confidence: 62%

Section: Discussionmentioning

confidence: 99%

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Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Cevenini¹,

Cotichini²,

Stazi³

et al. 2013

AGE

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“…The first sample (the Danish 1905-Cohort) included 1,380 subjects aged 93 years (390 males and 990 females), recruited in the framework of a nationwide survey of all Danish people born in Denmark in 1905 (Nybo et al 2001;Nybo et al 2003;Christensen et al 2008). Briefly, 2,262 people participated initially in this survey which included a home-based interview aimed at the collection of socio-demographic information, evaluation of physical, cognitive, depressive status, sensory impairments, medications, selfreported health status, and blood sampling.…”

Section: Samplesmentioning

confidence: 99%

Frailty phenotypes in the elderly based on cluster analysis: a longitudinal study of two Danish cohorts. Evidence for a genetic influence on frailty

Dato

Montesanto

Lagani

et al. 2011

AGE

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Frailty is a physiological state characterized by the deregulation of multiple physiologic systems of an aging organism determining the loss of homeostatic capacity, which exposes the elderly to disability, diseases, and finally death. An operative definition of frailty, useful for the classification of the individual quality of aging, is needed. On the other hand, the documented heterogeneity in the quality of aging among different geographic areas suggests the necessity for a frailty classification approach providing population-specific results. Moreover, the contribution of the individual genetic background on the frailty status is still questioned. We investigated the applicability of a cluster analysis approach based on specific geriatric parameters, previously set up and validated in a southern Italian population, to two large longitudinal Danish samples. In both cohorts, we identified groups of subjects homogeneous for their frailty status and characterized by different survival patterns. A subsequent survival analysis availing of Accelerated Failure Time models allowed us to formulate an operative index able to correlate classification variables with survival probability. From these models, we quantified the differential effect of various parameters on survival, and we estimated the heritability of the frailty phenotype by exploiting the twin pairs in our sample. These data suggest the presence of a genetic influence on the frailty variability and indicate that cluster analysis can define specific frailty phenotypes in each population.

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“…However, the association between alcohol consumption and survival is still largely unexplored among those aged 80 years and older. A study of nonagenarians (90+) did not find the J-or U-shaped association between alcohol and mortality, but results did indicate a higher mortality risk among abstainers compared to drinkers (Nybo et al, 2003). However, the health benefits of moderate alcohol consumption -at any age -is not uncontroversial (for a recent editorial, see Chikritzhs et al, 2015), and alcohol abstinence, particularly in old age, is often due to underlying health problems that constrain alcohol consumption.…”

Section: Introductionmentioning

confidence: 99%

Alcohol consumption in very old age and its association with survival: A matter of health and physical function

Agahi

Kelfve

Lennartsson

et al. 2016

Drug and Alcohol Dependence

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Alcohol consumption in very old age and its association with survival: a matter of health and physical function. Dependence, http://dx.doi.org/10.1016/j. drugalcdep.2015.12.022 Access to the published version may require subscription. N.B. When citing this work, cite the original published paper. Results: Compared to light-to-moderate drinkers, abstainers had lower levels of education and more functional health problems, while heavy drinkers were more often men, had higher levels of education, and no serious health or functional problems. In models adjusted only for age and sex, abstainers died earlier than drinkers. Among light-to-moderate drinkers, each additional drink/month was associated with longer survival, while among heavy drinkers, each additional drink/month was associated with shorter survival. However, after adjusting for personal and health-related factors, estimates were lower and no longer statistically significant. Conclusions: The association between alcohol consumption and survival in very old age seems to have an inverse J-shape; abstention and heavy use is associated with shorter survival compared to light-tomoderate drinking. To a large extent, differences in survival are due to differences in baseline health and physical function. Drug And Alcohol

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Predictors of Mortality in 2,249 Nonagenarians—The Danish 1905‐Cohort Survey

Cited by 238 publications

References 38 publications

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Health status and 6 years survival of 552 90+ Italian sib-ships recruited within the EU Project GEHA (GEnetics of Healthy Ageing)

Frailty phenotypes in the elderly based on cluster analysis: a longitudinal study of two Danish cohorts. Evidence for a genetic influence on frailty

Alcohol consumption in very old age and its association with survival: A matter of health and physical function

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