Study participants were women aged 70–79 years; 21% were African American, the rest Caucasian. Numbers of chronic diseases present (of 11) were as follows: one among 37%, two in 22%, and more than three in 14%. Ten percent were frail and 45% prefrail. Comparatively, 39% of those who were frail had more than three diseases, versus 20% of those prefrail and 3% of the nonfrail (p = .01), whereas 9% of those who were frail and 38% of the nonfrail reported none of these diseases (see , panel B, footnote for the 11 diseases).
Table 2. Aggregation of System Abnormalities and Joint Association With Frailty. (A) Multisystem Deficit Profile: Conditional Probabilities of Meeting Deficit Criteria Within Latent Classes (N = 704) and (B) Independent Association of Class 2 Cluster of 2.9 System (more ...)
, panel A, displays mean levels for 12 measures within six physiological systems, along with the proportion meeting criteria for abnormal levels, by frailty status. These data indicate significant dose–response or threshold associations of each measure with frailty status, with 1.8- to 3.6-fold increases in the proportion with abnormal levels in frail compared with nonfrail. Folate and vitamin B12 were the exceptions; note that this study was performed before folate fortification of flour and cereal grain products became mandated in the United States.
Combining the five micronutrients into a summary measure of number at deficient levels, we then evaluated the independent associations of abnormal levels of eight different physiological systems with frailty, adjusting for confounders. , panel B, shows that, when adjusting for each of the seven other independent variables, two or more micronutrients at deficient levels, adiposity, and slowed fine motor speed were each significantly associated with 2.6- to 3.4-fold increases in the likelihood of being frail (p < .01). The direction of association was positive for each of the other three independent variables but not significant after adjustment for the seven others. Previously, univariable analyses (adjusted only for age, education, race, and number of chronic diseases) showed similar but stronger associations of each of these measures, separately, with frailty; among these, low IGF-1 was also significantly associated with frailty (OR 2.1, 95% confidence interval [CI] 1.1–4.2; data not shown).
To assess whether frailty was associated with an increased number of systems impaired, regardless of individually significant associations, we took four complementary approaches. First, the mean numbers of individual systems at abnormal levels (and 95% CIs) were as follows: nonfrail, 1.3 (1.1–1.4); prefrail, 1.8 (1.7–1.9); and frail, 2.7 (2.4–3.0). Second, displays a nonlinear increase in frailty prevalence with increasing number of abnormal physiological systems (p < .01 for quadratic trend).
Figure 2. Association of number of physiological systems at abnormal levels with being frail, women aged 70–79 years (p < .01 for qualitative trend). (A) Prevalence of being frail by number of dysregulated systems at baseline. (B) Number of system (more ...)
Third, we assessed the risk of frailty or prefrailty by number of systems at abnormal levels. indicates that those with three, four, or five or more systems at abnormal levels were most likely to be frail. Half of those frail had three or more systems at abnormal levels, compared with 25% of the prefrail and 16% of the nonfrail (p < .01, unadjusted); less than 21% of the frail had zero or one system abnormal (of eight). There was a dose–response relationship between the number of systems at abnormal levels and risk of frailty, increasing from ORs of 4.8 for those with one to two systems abnormal (compared with zero) to 11- and 26-fold increased risk for those with three to four and five or more systems at abnormal levels, respectively (95% CIs did not include 1). There was also an intermediate level of risk for each number of systems abnormal in association with prefrail status ().
We also evaluated whether each individual system was independently associated with frailty when the number of systems was also in the model. The number of systems abnormal was strongly predictive of the likelihood of frailty, whereas the individual systems were not, with the exception of fine motor speed (data not shown). These findings consistently indicate that the frailty phenotype is associated with multiple physiological abnormalities.
Fourth, we evaluated whether any subgroups of this population had distinct profiles of multisystem deficits, to understand whether specific clusters of deficits mattered, or the issue was aggregate burden. LCA identified a two-class model as providing an adequate fit to the observed data, based on goodness-of-fit statistics (, panel A). Estimated prevalences for these two mutually exclusive “classes,” classes 1 and 2, were 69.6% and 30.4%, respectively (, panel A). Class 1 appears to represent a subset of the population with one or no systems (ie, 1.3 systems on average) at abnormal levels, whereas the 30% in class 2 are a subset with multiple systems abnormal, that is, 2.9 on average. LCA also provides the probabilities that someone in a class will have a given level (normal or abnormal) on each of the physiological measures assessed. For example, in , panel A, considering IL-6, the conditional probability .153 means that, on average, 15.3% of the women who were in class 1 had IL-6 levels greater than 4.6 pg/mL, in contrast to 48.5% of those in class 2. The prevalence of abnormal levels of each measure increased progressively from classes 1 to 2, with the most dramatic increases in prevalence being associated with deficient fine motor speed (an increase of 6.5-fold, from .089 to .577), anemia (3.8-fold), and inflammation (3.2-fold; , panel A). Further analysis of the 256 (28) possible patterns indicated little evidence as to dominating patterns of change between classes 1 and 2 (data not shown), consistent with no subgroups of systems involved.
We then evaluated whether the two classes in the population, as aforementioned, were associated with frailty status. , panel B, shows that class 2, with multisystem decrements (vs class 1 isolated decrements, as in , panel A), was independently associated with being frail (compared with not frail), with OR of 2.6 (95% CI 1.2–5.5), adjusting for number of comorbid diseases, age, race, and education. Furthermore, the number of comorbid diseases was associated with frailty independent of multisystem abnormalities (per class 2), and the strength of association approximated those of the class 2 associations. In separate analyses, the association of class 2 with being frail remained significant after individually controlling for each of the eight system measures; the latter were not themselves significant in these models with the exception of fine motor speed (data not shown).