Sex Differences in the Construct Overlap of Frailty and Depression: Evidence from the Health and Retirement Study

Abstract

OBJECTIVES To determine the degree of diagnostic overlap between frailty and depression and investigate whether gender differences in symptom endorsement influence this overlap. DESIGN Cross-sectional latent class analysis. SETTING Data come from the 2008 wave of the Health and Retirement Study, a nationally-representative longitudinal survey of health characteristics among older adults. PARTICIPANTS Community-dwelling adults aged 65 and older completing a generalhealth questionnaire and consenting to physical measurements (N=3,665). MEASUREMENTS Frailty was measured using criteria developed in the Cardiovascular Health Study and depressive symptoms were measured using the 8-item Center for Epidemiologic Studies Depression scale. RESULTS Frailty and depression were best modelled as two distinct but highly correlated constructs with 3-classes and 4-classes of symptom response respectively. Measurement overlap was high among both men and women. Approximately 73% of individuals with severe depressive symptoms, and 86% of individuals with primarily somatic depressive symptoms, were categorized as concurrently frail. The degree of construct overlap between depression and frailty did not significantly vary by gender, but women were significantly more likely to endorse all frailty and depressive symptoms. CONCLUSION Measures of depression and frailty identify substantially overlapping populations of older men and women. More frequent endorsement of depressive symptoms, but not differential endorsement of somatic symptoms may contribute to the higher prevalence of frailty among women. The symptom of exhaustion is particularly important to the correlation between these two conditions. Findings will inform efforts by clinicians and researchers to refine the definition of geriatric syndromes like frailty and to develop effective interventions.

Incorporating Persistent Pain in Phenotypic Frailty Measurement and Prediction of Adverse Health Outcomes

“…For instance, we were unable to determine whether decreases in BMI were intentional, and therefore some weight loss may reflect purposeful change. Although this modification was necessary based on available data, it may explain why the weight loss criterion was poorest at discriminating between frailty classes, consistent with prior research (7,17,22). Second, operationalization of persistent pain did not account for different etiologic mechanisms or localizations of pain, potentially confounding pain due to injury or surgery with pain due to systemic dysfunction or illness.…”

“…As in prior studies of phenotypic frailty (7,17), we used latent class analysis (LCA) to evaluate internal construct validity. The goal of LCA is to identify discrete subpopulations (classes) of individuals distinguished by similar criteria patterns (18), assuming that criteria covariation is primarily explained by membership in a certain class.…”

Serum Dehydroepiandrosterone Sulfate and Incident Depression in the Elderly: The Pro.V.A. Study

“…36 On the contrary, high SPPB scores were protective for the onset of depression, confirming that higher performance levels are associated with a lower risk of depression. 37 Our findings suggest that serum DHEAS concentrations have a protective role in the elderly, but its role could be attenuated in some conditions such as in sedentary lifestyle and frailty, and so further specific research about these populations is necessary.…”

Medical Co-Morbidity, Brain Disease, and The Future of Geriatric Psychiatry

“…Similar to other recent findings of sex differences, frailty characteristics, particularly gait speed, were associated with faster progression to death in elderly depressed women, but not in depressed men (hazard ratio [HR], 1.84; 95% confidence interval [CI], 1.05e3.21). 6,7 These accumulating data support the interrelatedness of the two syndromes and raise key questions: do depression and frailty co-occur; is one a prodrome or risk factor for the other; and are there common underlying mechanism(s), including sarcopenia, hyperglycemia, and changes in sex and growth hormone levels, that give rise to each? An integrated clinical and research approach to the evaluation of these syndromes is imperative.…”