Inflammatory Breast Carcinoma (IBC), the most aggressive type of breast tumor with unique clinicopathological presentation, is hypothesized to have distinct etiology with a socioeconomic status (SES) component. Using the Surveillance, Epidemiology and End Results (SEER) Program data for 2004–2007, we compare incidence rates of IBC to non-inflammatory locally advanced breast cancer (LABC) among racial/ethnic groups with different SES. The analysis includes women 20–84 years of age. To examine evidence for the distinct etiology of IBC, we analyzed age-distribution patterns of IBC and non-inflammatory LABC, using a mathematical carcinogenesis model. Based on the Collaborative Staging Extension codes, 2,942 incident IBC cases (codes 71 and 73) and 5,721 non-inflammatory LABC cases (codes 40–62) were identified during the four-year study period. Age-adjusted rates of IBC among non-Hispanic White and Hispanic women were similar (2.5/100,000 in both groups). Similar rates were also found in non-inflammatory LABC in these two groups (4.8/100,000 and 4.2/100,000, respectively). In African-American women, the IBC (3.91/100,000) and non-inflammatory LABC (8.47/100,000) rates were greater compared with other ethnic/racial sub-groups. However, the ratio of rates of IBC/non-inflammatory LABC was similar among all the racial/ethnic groups, suggesting that African-American women are susceptible to aggressive breast tumors in general but not specifically to IBC. The mathematical model successfully predicted the observed age-specific rates of both examined breast tumors and revealed distinct patterns. IBC rates increased until age 65 and then slightly decreased, whereas non-inflammatory LABC rates steadily increased throughout the entire age interval. The number of critical transition carcinogenesis stages (m-stages) predicted by the model were 6.3 and 8.5 for IBC and non-inflammatory LABC, respectively, supporting different etiologies of these breast tumors.
Epidemiology; Inflammatory breast cancer; Etiology
We evaluated effects of the APOE polymorphism (carriers versus noncarriers of the e4 allele) and age trajectories of total cholesterol (CH) and diastolic blood pressure (DBP) on mortality risk in the Framingham Heart Study (original cohort). We found that long-lived carriers and noncarriers have different average age trajectories and long-lived individuals have consistently higher levels and less steep declines at old ages compared to short-lived individuals. We applied the stochastic process model of aging aimed at joint analyses of genetic and nongenetic subsamples of longitudinal data and estimated different aging-related characteristics for carriers and noncarriers which otherwise cannot be evaluated from data. We found that such characteristics differ in carriers and noncarriers: (1) carriers have better adaptive capacity than noncarriers in case of CH, whereas for DBP the opposite situation is observed; (2) mean allostatic trajectories are higher in carriers and they differ from “optimal” trajectories minimizing mortality risk; (3) noncarriers have lower baseline mortality rates at younger ages but they increase faster than those for carriers resulting in intersection at the oldest ages. Such observations strongly indicate the presence of a genetic component in respective aging-related mechanisms. Such differences may contribute to patterns of allele- and sex-specific mortality rates.
To utilize the Medicare Files of Service Use (MFSU) to evaluate patterns in the incidence of aging-related diseases in the U.S. elderly population.
Age-specific incidence rates of nineteen aging-related diseases were evaluated with the National Long Term Care Survey (NLTCS) and the Surveillance, Epidemiology, and End Results (SEER) Registry data both linked to MSUF (NLTCS-M and SEER-M, respectively), using a developed algorithm for individual date at onset evaluation.
A random sample from the entire U.S. elderly population (Medicare beneficiaries) was used in NLTCS, and 26% of U.S. population is covered by the SEER Registry data.
34,077 individuals from NLTCS-M and 2,154,598 from SEER-M.
Individual medical histories were reconstructed using information on diagnoses coded in MFSU, dates of medical services/procedures, and Medicare enrollment/disenrollment.
The majority of diseases (e.g., prostate cancer, asthma, diabetes) had a monotonic decline (or decline following short period of increase) in incidence with age. A monotonic increase of incidence with age with a subsequent leveling off and decline was observed for myocardial infarction, stroke, heart failure, ulcer, and Alzheimer’s disease. An inverted U-shaped age pattern was detected for lung and colon carcinomas, Parkinson’s disease, and renal failure. The results obtained from the NLTCS-M and SEER-M were in agreement (excluding an excess for circulatory diseases in the NLTCS-M). A sensitivity analysis proved the stability of the evaluated incidence rates.
The developed computational approaches applied to the nationally representative Medicare-based datasets allows reconstruction of age patterns of disease incidence in the U.S. elderly population at the national level with unprecedented statistical accuracy and stability with respect to systematic biases.
Medicare; chronic disease onset; comorbidity
Background and Objective: The influence of genes on human lifespan is mediated by biological processes that characterize body's functioning. The age trajectories of these processes contain important information about mechanisms linking aging, health, and lifespan. The objective of this paper is to investigate regularities of aging changes in different groups of individuals, including individuals with different genetic background, as well as their connections with health and lifespan. Data and Method: To reach this objective we used longitudinal data on four physiological variables, information about health and lifespan collected in the Framingham Heart Study (FHS), data on longevity alleles detected in earlier study, as well as methods of statistical modeling. Results: We found that phenotypes of exceptional longevity and health are linked to distinct types of changes in physiological indices during aging. We also found that components of aging changes differ in groups of individuals with different genetic background. Conclusions: These results suggest that factors responsible for exceptional longevity and health are not necessary the same, and that postponing aging changes is associated with extreme longevity. The genetic factors which increase lifespan are associated with physiological changes typical of healthy and long-living individuals, smaller mortality risks from cancer and CVD and better estimates of adaptive capacity in statistical modeling. This indicates that extreme longevity and health related traits are likely to be less heterogeneous phenotypes than lifespan, and studying these phenotypes separately from lifespan may provide additional information about mechanisms of human aging and its relation to chronic diseases and lifespan.
age trajectories; physiological variables; longevity genes; genetic dose; integrative genetic mortality model
Progress in unraveling the genetic origins of healthy aging is tempered, in part, by a lack of replication of effects, which is often considered a signature of false positive findings. We convincingly demonstrate that the lack of genetic effects on an aging-related trait can be due to trade-offs in the gene action. We focus on the well-studied apolipoproetin E (APOE) e2/3/4 polymorphism and on lifespan and ages at onset of cardiovascular diseases (CVD) and cancer, using data on 3,924 participants of the Framingham Heart Study Offspring cohort. Kaplan-Meier estimates show that the e4 allele carriers live shorter lives than the non-e4 allele carriers (log rank=0.016). The adverse effect was attributed to the poor survival of the e4 homozygotes, whereas the effect of the common e3/4 genotype was insignificant. The e3/4 genotype, however, was antagonistically associated with onsets of those diseases predisposing to an earlier onset of CVD and a later onset of cancer compared to the non-e4 allele genotypes. This trade-off explains the lack of a significant effect of the e3/4 genotype on survival; adjustment for it in the Cox regression model makes the detrimental effect of the e4 allele highly significant (p=0.002). This trade-off is likely caused by the lipid-metabolism-related (for CVD) and non-related (for cancer) mechanisms. An evolutionary rationale suggests that genetic trade-offs should not be an exception in studies of aging-related traits. Deeper insights into biological mechanisms mediating gene action are critical for understanding the genetic regulation of a healthy lifespan and for personalizing medical care.
Aging; Longevity regulation; mortality; trade-offs; disease; lifespan; genetics
Adenocarcinomas (ACs) and squamous cell carcinomas (SCCs) differ by clinical and molecular characteristics. We evaluated the characteristics of carcinogenesis by modeling the age patterns of incidence rates of ACs and SCCs of various organs to test whether these characteristics differed between cancer subtypes.
Histotype-specific incidence rates of 14 ACs and 12 SCCs from the SEER Registry (1973–2003) were analyzed by fitting several biologically motivated models to observed age patterns. A frailty model with the Weibull baseline was applied to each age pattern to provide the best fit for the majority of cancers. For each cancer, model parameters describing the underlying mechanisms of carcinogenesis including the number of stages occurring during an individual’s life and leading to cancer (m-stages) were estimated. For sensitivity analysis, the age-period-cohort model was incorporated into the carcinogenesis model to test the stability of the estimates. For the majority of studied cancers, the numbers of m-stages were similar within each group (i.e., AC and SCC). When cancers of the same organs were compared (i.e., lung, esophagus, and cervix uteri), the number of m-stages were more strongly associated with the AC/SCC subtype than with the organ: 9.79±0.09, 9.93±0.19 and 8.80±0.10 for lung, esophagus, and cervical ACs, compared to 11.41±0.10, 12.86±0.34 and 12.01±0.51 for SCCs of the respective organs (p<0.05 between subtypes). Most SCCs had more than ten m-stages while ACs had fewer than ten m-stages. The sensitivity analyses of the model parameters demonstrated the stability of the obtained estimates.
A model containing parameters capable of representing the number of stages of cancer development occurring during individual’s life was applied to the large population data on incidence of ACs and SCCs. The model revealed that the number of m-stages differed by cancer subtype being more strongly associated with ACs/SCCs histotype than with organ/site.
Small sample size of genetic data is often a limiting factor for desirable accuracy of estimated genetic effects on age-specific risks and survival. Longitudinal non-genetic data containing information on survival or disease onsets of study participants for whom the genetic data were not collected may provide an additional “reserve” for increasing the accuracy of respective estimates. We present a novel method for joint analyses of “genetic” (covering individuals for whom both genetic information and mortality/morbidity data are available) and “non-genetic” (covering individuals for whom only mortality/morbidity data were collected) subsamples of longitudinal data. Our simulation studies show substantial increase in the accuracy of estimates in such joint analyses compared to analyses based on genetic subsample alone. Application of this method to analysis of the effect of common apolipoprotein E (APOE) polymorphism on survival using combined genetic and non-genetic subsamples of the Framingham Heart Study original cohort data showed that female, but not male, carriers of the APOE e4 allele have significantly worse survival than non-carriers, whereas empirical analyses did not produce any significant results for either sex.
model; combining data; Framingham Heart Study; mortality; APOE; sex differences
Exceptional survival results from complicated interplay between genetic and environmental factors. The effects of these factors on survival are mediated by the biological and physiological variables, which affect mortality risk. In this paper, we evaluated the role of blood glucose (BG) in exceptional survival using the Framingham Heart Study data for the main (FHS) and offspring (FHSO) cohorts. We found that: (i) the average cross-sectional age patterns of BG change over time; (ii) the values of BG level among the longest lived individuals in this study differ for different sub-cohorts; (iii) the longitudinal age patterns of BG differ from those of cross-sectional ones. We investigated mechanisms forming average age trajectories of BG in the FHS cohort. We found that the two curves: one, characterizing the average effects of allostatic adaptation, and another, minimizing mortality risk for any given age, play the central role in this process. We found that the average BG age trajectories for exceptional survivors are closer to the curve minimizing mortality risk than those of individuals having shorter life spans. We concluded that individuals whose age trajectories of BG are located around the curve minimizing chances of premature death at each given age have highest chances of reaching exceptional longevity.
mortality risk; stochastic process model of aging; allostatic adaptation; age-specific physiological norm; blood glucose; Framingham Heart Study
We analyzed relationship between the risk of onset of “unhealthy life” (defined as the onset of cancer, cardiovascular diseases, or diabetes) and longitudinal changes in body mass index, diastolic blood pressure, hematocrit, pulse pressure, pulse rate, and serum cholesterol in the Framingham Heart Study (original cohort) using the stochastic process model of human mortality and aging. The analyses demonstrate how decline in resistance to stresses and adaptive capacity accompanying human aging can be evaluated from longitudinal data. We showed how these components of the aging process, as well as deviation of the trajectories of physiological indices from those minimizing the risk at respective ages, can lead to an increase in the risk of onset of unhealthy life with age. The results indicate the presence of substantial gender difference in aging related decline in stress resistance and adaptive capacity, which can contribute to differences in the shape of the sex-specific patterns of incidence rates of aging related diseases.
stress resistance; adaptive capacity; age-dynamics; physiological norm; Framingham Heart Study
HIV-1-positive patients clear the human papillomavirus (HPV) infection less frequently than HIV-1-negative. Datasets for estimating HPV clearance probability often have irregular measurements of HPV status and risk factors. A new transitional probability-based model for estimation of probability of HPV clearance was developed to fully incorporate information on HIV-1-related clinical data, such as CD4 counts, HIV-1 viral load (VL), highly active antiretroviral therapy (HAART), and risk factors (measured quarterly), and HPV infection status (measured at 6-month intervals).
Methodology and Findings
Data from 266 HIV-1-positive and 134 at-risk HIV-1-negative adolescent females from the Reaching for Excellence in Adolescent Care and Health (REACH) cohort were used in this study. First, the associations were evaluated using the Cox proportional hazard model, and the variables that demonstrated significant effects on HPV clearance were included in transitional probability models. The new model established the efficacy of CD4 cell counts as a main clearance predictor for all type-specific HPV phylogenetic groups. The 3-month probability of HPV clearance in HIV-1-infected patients significantly increased with increasing CD4 counts for HPV16/16-like (p<0.001), HPV18/18-like (p<0.001), HPV56/56-like (p = 0.05), and low-risk HPV (p<0.001) phylogenetic groups, with the lowest probability found for HPV16/16-like infections (21.60±1.81% at CD4 level 200 cells/mm3, p<0.05; and 28.03±1.47% at CD4 level 500 cells/mm3). HIV-1 VL was a significant predictor for clearance of low-risk HPV infections (p<0.05). HAART (with protease inhibitor) was significant predictor of probability of HPV16 clearance (p<0.05). HPV16/16-like and HPV18/18-like groups showed heterogeneity (p<0.05) in terms of how CD4 counts, HIV VL, and HAART affected probability of clearance of each HPV infection.
This new model predicts the 3-month probability of HPV infection clearance based on CD4 cell counts and other HIV-1-related clinical measurements.
Relationships between aging, disease risks, and longevity are not yet well understood. For example, joint increases in cancer risk and total survival observed in many human populations and some experimental aging studies may be linked to a trade-off between cancer and aging as well as to the trade-off(s) between cancer and other diseases, and their relative impact is not clear. While the former trade-off (between cancer and aging) received broad attention in aging research, the latter one lacks respective studies, although its understanding is important for developing optimal strategies of increasing both longevity and healthy life span. In this paper, we explore the possibility of trade-offs between risks of cancer and selected major disorders. First, we review current literature suggesting that the trade-offs between cancer and other diseases may exist and be linked to the differential intensity of apoptosis. Then we select relevant disorders for the analysis (acute coronary heart disease [ACHD], stroke, asthma, and Alzheimer disease [AD]) and calculate the risk of cancer among individuals with each of these disorders, and vice versa, using the Framingham Study (5209 individuals) and the National Long Term Care Survey (NLTCS) (38,214 individuals) data. We found a reduction in cancer risk among old (80+) men with stroke and in risk of ACHD among men (50+) with cancer in the Framingham Study. We also found an increase in ACHD and stroke among individuals with cancer, and a reduction in cancer risk among women with AD in the NLTCS. The manifestation of trade-offs between risks of cancer and other diseases thus depended on sex, age, and study population. We discuss factors modulating the potential trade-offs between major disorders in populations, e.g., disease treatments. Further study is needed to clarify possible impact of such trade-offs on longevity.
About 80% of all cancers are diagnosed in the elderly and up to 75% of cancers are associated with behavioral factors. An approach to estimate the contribution of various measurable factors, including behavior/lifestyle, to cancer risk in the US elderly population is presented. The nationally representative National Long-Term Care Survey (NLTCS) data were used for measuring functional status and behavioral factors in the US elderly population (65+), and Medicare Claims files linked to each person from the NLTCS were used for estimating cancer incidence. The associations (i.e., relative risks) of selected factors with risks of breast, prostate, lung and colon cancers were evaluated and discussed. Behavioral risk factors significantly affected cancer risks in the US elderly. The most influential of potentially preventable risk factors can be detected with this approach using NLTCS-Medicare linked dataset and for further deeper analyses employing other datasets with detailed risk factors description.
Time trajectories of medical costs-associated with onset of twelve aging-related cancer and chronic noncancer diseases were analyzed using the National Long-Term Care Survey data linked to Medicare Service Use files. A special procedure for selecting individuals with onset of each disease was developed and used for identification of the date at disease onset. Medical cost trajectories were found to be represented by a parametric model with four easily interpretable parameters reflecting: (i) prediagnosis cost (associated with initial comorbidity), (ii) cost of the disease onset, (iii) population recovery representing reduction of the medical expenses associated with a disease since diagnosis was made, and (iv) acquired comorbidity representing the difference between post- and pre diagnosis medical cost levels. These parameters were evaluated for the entire US population as well as for the subpopulation conditional on age, disability and comorbidity states, and survival (2.5 years after the date of onset). The developed approach results in a family of new forecasting models with covariates.
BACKGROUND AND PURPOSE
Improvement in recovery rates may contribute to increase in healthy life expectancy. It is unclear, however, whether such changes take place because health researchers traditionally deal with changes in incidence and survival from diseases. The purpose of this paper is to test the presence of time trends in the recovery rate from stroke.
METHOD AND DATA
We compared age patterns of recovery rates from stroke evaluated in two subsequent sub-cohorts represented in the NLTCS data linked with the Medicare service use files.
We found statistically significant increase in recovery rate between 1994 and 1999 for females, but not for males.
Time trends in recovery rate from stroke exist and can be detected from available data. The roles of influential factors and causes of gender difference in recovery improvement deserve further studies.
recovery trends; sensitivity analyses; healthy life span; compression of morbidity; survival after stroke
Multiple functions of the beta2-adrenergic receptor (ADRB2) and angiotensin-converting enzyme (ACE) genes warrant studies of their associations with aging-related phenotypes. We focus on multimarker analyses and analyses of the effects of compound genotypes of two polymorphisms in the ADRB2 gene, rs1042713 and rs1042714, and 11 polymorphisms of the ACE gene, on the risk of such an aging-associated phenotype as myocardial infarction (MI). We used the data from a genotyped sample of the Framingham Heart Study Offspring (FHSO) cohort (n = 1500) followed for about 36 years with six examinations. The ADRB2 rs1042714 (C→G) polymorphism and two moderately correlated (r2 = 0.77) ACE polymorphisms, rs4363 (A→G) and rs12449782 (A→G), were significantly associated with risks of MI in this aging cohort in multimarker models. Predominantly linked ACE genotypes exhibited opposite effects on MI risks, e.g., the AA (rs12449782) genotype had a detrimental effect, whereas the predominantly linked AA (rs4363) genotype exhibited a protective effect. This trade-off occurs as a result of the opposite effects of rare compound genotypes of the ACE polymorphisms with a single dose of the AG heterozygote. This genetic trade-off is further augmented by the selective modulating effect of the rs1042714 ADRB2 polymorphism. The associations were not altered by adjustment for common MI risk factors. The results suggest that effects of single specific genetic variants of the ADRB2 and ACE genes on MI can be readily altered by gene–gene or/and gene–environmental interactions, especially in large heterogeneous samples. Multimarker genetic analyses should benefit studies of complex aging-associated phenotypes.
It is well known from epidemiology that values of indices describing physiological state in a given age may influence human morbidity and mortality risks. Studies of connection between aging and life span suggest a possibility that dynamic properties of age trajectories of the physiological indices could also be important contributors to morbidity and mortality risks. In this paper we use data on longitudinal changes in body mass index, diastolic blood pressure, pulse pressure, pulse rate, blood glucose, hematocrit, and serum cholesterol in the Framingham Heart Study participants, to investigate this possibility in depth. We found that some of the variables describing individual dynamics of the age-associated changes in physiological indices influence human longevity and exceptional health more substantially than the variables describing physiological state. These newly identified variables are promising targets for prevention aiming to postpone onsets of common elderly diseases and increase longevity.
The levels of blood glucose (BG) in humans tend to increase with age deviating from the norm specified for the young adults. Such elevation is often considered as a factor contributing to an increase in risks of disease and death. The proper use of intervention strategies coping with or preventing consequences of BG elevation requires understanding the roles of external forces and intrinsic senescence in this process. To address these issues, we performed analyses of longitudinal data on BG collected in the Framingham Heart Study using methods of descriptive statistics and statistical modeling. The approach allows us to separate effects of persistent external disturbances from “normal” aging related changes due to the senescence process. We found that the BG level corresponding to the lowest mortality risk tends to increase with age. The changes in the shape of the mortality risk with age indicate the aging related decline in resistance to stresses affecting the BG level. The results show that analyzing longitudinal data using advanced methods may substantially increase our knowledge on factors and mechanisms responsible for aging related changes in humans.
physiological norm; aging; allostasis; mortality risk; stress resistance; longitudinal data
Many longitudinal studies of aging collect genetic information only for a sub-sample of participants of the study. These data also do not include recent findings, new ideas and methodological concepts developed by distinct groups of researchers. The formal statistical analyses of genetic data ignore this additional information and therefore cannot utilize the entire research potential of the data. In this paper, we present a stochastic model for studying such longitudinal data in joint analyses of genetic and non-genetic sub-samples. The model incorporates several major concepts of aging known to date and usually studied independently. These include age-specific physiological norms, allostasis and allostatic load, stochasticity, and decline in stress resistance and adaptive capacity with age. The approach allows for studying all these concepts in their mutual connection, even if respective mechanisms are not directly measured in data (which is typical for longitudinal data available to date). The model takes into account dependence of longitudinal indices and hazard rates on genetic markers and permits evaluation of all these characteristics for carriers of different alleles (genotypes) to address questions concerning genetic influence on aging-related characteristics. The method is based on extracting genetic information from the entire sample of longitudinal data consisting of genetic and non-genetic sub-samples. Thus it results in a substantial increase in the accuracy of statistical estimates of genetic parameters compared to methods that use only information from a genetic sub-sample. Such an increase is achieved without collecting additional genetic data. Simulation studies illustrate the increase in the accuracy in different scenarios for datasets structurally similar to the Framingham Heart Study. Possible applications of the model and its further generalizations are discussed.
stochastic process model; allostatic load; age-dependent physiological norm; adaptive capacity; stress resistance
The results of recent experimental and epidemiological studies provide evidence on the connection between carcinogenesis, cancer progression, and aging. Existing models, however, are traditionally focused only on one of these aspects of health deterioration. In this paper, we derive a new model of cancer, which describes the connection between the age at disease onset, the duration of disease, and life span of respective individuals. The model combines ideas used in the two hits model of carcinogenesis with those used in the Le Bras multistate model of aging with constant transition intensities. The model is used in the joint analyses of the U.S. demographic mortality data and SEER data for selected cancers. The results show that the developed approach is capable of explaining links among health history data and provides useful insights on mechanisms of cancer occurrence, disease progression, other aging-related changes, and mortality. Further developments of this model are discussed.
aging; cancer; case fatality; duration of disease; Le Bras model; cancer mortality
The potential gain in life expectancy which could result from the complete elimination of mortality from cancer in the U.S. would not exceed 3 years if one were to consider cancer independently of other causes of death. In this paper, we review evidence of trade-offs between cancer and aging as well as between cancer and other diseases, which, if taken into account, may substantially increase estimates of gain in life expectancy resulting from cancer eradication. We also used the Multiple Causes of Death (MCD) data to evaluate correlations among mortalities from cancer and other major disorders including heart disease, stroke, diabetes, Alzheimer’s, Parkinson’s diseases, and asthma. Our analyses revealed significant negative correlations between cancer and other diseases suggesting stronger population effects of cancer eradication. Possible mechanisms of the observed dependencies and emerging perspectives of using dependent competing risks models for evaluating the effects of reduction of mortality from cancer on life expectancy are discussed.
Cancer; Dependent risks; Multiple Causes of Death data; Aging; Apoptosis
An important feature of aging-related deterioration in human health is the decline in organisms’ resistance to stresses, which contributes to an increase in morbidity and mortality risks. In human longitudinal studies of aging, such a decline is not measured directly, so indirect methods of statistical modeling have to be used for evaluating this characteristic. Since medical interventions reflect severity of occurring health disorders, data from Medicare service use files can be used for such modeling. In this paper, we use the National Long Term Care Survey (NLTCS) data merged with the Medicare service use files to investigate dynamics of stress resistance in the U.S. elderly. We constructed individual indices of cumulative deficits and medical costs and investigated their separate and joint effects on dynamics of mortality risks using the quadratic hazard model. We found that males show a faster decline in stress resistance with age than females.
cumulative deficits; medical costs; mortality; quadratic hazard model; stress resistance
Variables measured in longitudinal studies of aging and longevity do not exhaust the list of all factors affecting health and mortality transitions. Unobserved factors generate hidden variability in susceptibility to diseases and death in populations and in age trajectories of longitudinally measured indices. Effects of such heterogeneity can be manifested not only in observed hazard rates but also in average trajectories of measured indices. Although effects of hidden heterogeneity on observed mortality rates are widely discussed, their role in forming age patterns of other aging-related characteristics (average trajectories of physiological state, stress resistance, etc.) is less clear. We propose a model of hidden heterogeneity to analyze its effects in longitudinal data. The approach takes the presence of hidden heterogeneity into account and incorporates several major concepts currently developing in aging research (allostatic load, aging-associated decline in adaptive capacity and stress-resistance, age-dependent physiological norms). Simulation experiments confirm identifiability of model’s parameters.
Aging; Longevity; Quadratic hazard model; Heterogeneity; Variability; Unobserved covariates; Longitudinal studies; Framingham Heart Study
Cross-sectional analyses show that an index of aging-associated health/well-being deficits, called the “frailty index”, can characterize the aging process in humans. This study provides support for such characterization from a longitudinal analysis of the frailty index properties. The data are from the National Long Term Care Survey assessed longitudinally health and functioning of the U.S. elderly in the period 1982 to 1999. In cross-sectional analysis, the frailty index exhibits accelerated increase with age till oldest-old ages (95+), with possible deceleration thereafter. Longitudinal analysis confirms the accelerated accumulation of deficits in aging individuals. The time-dynamics of the frailty index is affected by two sex-sensitive processes: i) selection of robust individuals, resulting in a decline of the mean frailty index with age, and ii) accumulation of deficits associated with physiological aging and its interaction with environment, which results in an accelerated increase of individual frailty index prior to death irrespective of chronological age. Current frailty index levels in individuals are more predictive of death than the index past values. Longitudinal analysis provides strong evidence that the cumulative index of health/well-being deficits can characterize aging-associated processes in humans and predict death better than chronological age during short-term periods.
Frailty index; aging; health; longevity; sex differences