A Person-Centered Exploration of Mental and Cognitive Health Risk Profiles in Community-Dwelling Older Adults.

The National Social Life, Health, and Aging Project (NSHAP) measures seven indicators of quality of life (QoL) and psychological health. The measures used for happiness, self-esteem, depression, and loneliness are well established in the literature. Conversely, measures of anxiety, stress, and self-reported emotional health were modified for their use in this unique project. The purpose of this paper is to provide (a) an overview of NSHAP's QoL assessment and (b) evidence for the adequacy of the modified measures. First, we examined the psychometric properties of the modified measures. Second, the established QoL measures were used to examine the concurrent validity of the modified measures. Finally, gender- and age-group differences were examined for each modified measure. The anxiety index exhibited good internal reliability and concurrent validity. Consistent with the literature, a single-factor structure best fit the data. Stress was satisfactory in terms of concurrent validity but with only fair internal consistency. Self-reported emotional health exhibited good concurrent validity and moderate external validity. The modified indices used in NSHAP tended to exhibit good internal reliability and concurrent validity. These measures can confidently be used in the exploration of QoL and psychological health in later life and its many correlates.

The National Social Life, Health, and Aging Project: An Introduction

National Social Life, Health, and Aging Project (NSHAP) included five unique mental health measures in Waves 1 and 2 that researchers can use to measure the overall emotional health of participants: depressive symptoms, happiness-unhappiness, anxiety symptoms, perceived stress, and felt loneliness. For each, we detail the rationale for its development and explain how to score, analyze, and interpret results. NSHAP developed its measures by modifying traditional short-form scales to improve response efficiency and reduce respondent burden. Scoring protocols and interpretations were developed for each measure. U.S. population estimates for older adults born between 1920 and 1947 were generated using age-eligible samples from Waves 1 and 2. NSHAP's protocols yielded U.S. prevalence rates similar to other nationally representative studies of older adults and comparable between waves. Higher estimates of anxiety symptoms and perceived stress in Wave 2 compared with Wave 1 were explained by age, administration mode, and time period. Analytic strategies for longitudinal analyses are provided. In Wave 2, mental health generally was worse at older ages, with women having more symptoms at younger ages than men. Women had fewer anxiety symptoms at the oldest ages. NSHAP's mental health measures were successfully integrated into the project's survey and showed acceptable external reliability as well as moderately stable individual characteristics across the 5 years between Waves 1 and 2. Depressive symptoms and unhappiness may form a mental health cluster in the elderly, distinct from anxiety symptoms, perceived stress, and felt loneliness. Gender differences in age-specific patterns of mental health were evident using the exact age of participants rather than the traditional decade groupings. Administration mode and time period (between 2005-2006 and 2010-2011) were determined to be potential confounds that need to be accommodated in longitudinal analyses of aging, whereas sample composition was not an issue for interpreting mental health measures.

We empirically examine how marriage and marital quality are related to sleep characteristics as measured by actigraphy and self-report in a nationally–representative probability sample of community-dwelling older adults, the National Social Life, Health and Aging Project (NSHAP). We find that married individuals experience better quality sleep compared to the unmarried. The associations are stronger for actigraphy sleep characteristics than for survey responses about sleep. Among the married, better relationship quality was associated with better sleep quality. Using data from the subset of married respondents from whom we have actigraphy data for both members of the couple, we find significant within-couple correlations for bedtimes, waking times and sleep duration estimated from actigraphy, but not for actigraphy measures of sleep quality (fragmentation and WASO). Further, we find that wives’ mental health, but not physical health, influences their husbands’ sleep. However, husbands’ mental and physical health had no influence on their wives’ sleep. These results point to a potential role for sleep in well-established disparities in health by marital status among older adults.

Sociodemographic and health correlates of sleep in U.S. Hispanic older adults

Elder mistreatment has negative consequences for older adults' health and well-being. As such, scholars aim to understand its causes, the contexts in which it occurs, how to prevent victimization, and how to design interventions for mistreated older adults. This paper provides a detailed overview of the 2015-2016 National Social Life, Health, and Aging Project (NSHAP) Round 3 Elder Mistreatment Module (EMM) to encourage further research on the topic. This paper reviews previous elder mistreatment scholarship, describes the EMM, provides descriptive analyses of elder mistreatment among community-dwelling older adults, and discusses promising approaches and limitations to future research with these data. The EMM includes 10 stem questions to measure elder mistreatment behaviors experienced since age 60 and 2 follow-up questions about perceived severity and the identity of the perpetrator. The stem questions can be analyzed individually or combined into a scale, and researchers can account for severity as a robustness check. Analysts can also group the measures into specific types of elder mistreatment. A major strength of the EMM is its ability to identify perpetrators in victims' core social networks. The NSHAP Round 3 EMM provides scholars an opportunity to study older Americans' mistreatment experiences, particularly as they relate to their physical and mental health, their social networks and personal relationships, and their broader social contexts.

Social isolation and loneliness (SI/L) are increasingly prevalent in older adults and connected with worse outcomes in later life. Previous research has focused on the effects of SI/L on cognitive functioning in older adults. However, fewer studies have investigated the pathways from cognitive impairment to SI/L. Mental health and social networks may serve as intermediate constructs that help to account for the link between cognition and SI/L. The present study examined the predictive pathways from cognitive functioning to SI/L through mental health and quality of relationships using data from the National Social Life, Health and Aging Project (NSHAP). Community-dwelling older adults (N = 4,337, Mage=67.63, SD = 10.95) completed a cognitive assessment and mental health and social functioning surveys. Structural equation modeling produced satisfactory fit indices, CFI=.97, TLI=.96, RMSEA=.03. Specifically, higher cognitive functioning predicted higher perceived quality of social relationships (β=.22, p<.001), fewer mental health symptoms (β=-.25, p<.001), greater frequency of social interaction (β=.22, p<.001), and higher self-reported loneliness (β=.18, p<.001). Additionally, higher quality of social relationships predicted less social isolation (β=.22, p<.001) and loneliness (β=-.14, p<.001), whereas greater mental symptoms predicted greater social isolation (β=-.13, p<.001) and loneliness (β=.66, p<.001). Less loneliness in the context of lower cognitive functioning may reflect a sense of subjective closeness with fellow older adults experiencing normative cognitive change. Older adults experiencing cognitive decline may benefit from interventions addressing mental health symptoms, fortifying social supports, and compensatory cognitive strategies to improve social functioning and overall well-being

The goals of this paper were: (a) to promote research using the National Social Life, Health and Aging Project (NSHAP) Wave 2 data by providing relevant background information for a broad range of chronic conditions and (b) to provide a framework for combining these chronic conditions into informative comorbidity indices. The chronic conditions measured in NSHAP Wave 2 were grouped across several health domains: cardiovascular, endocrine and metabolic, cancer, lung, inflammatory and bone, neurological, and sensorimotor. Prevalences for each condition were reported as percentages and were also estimated separately by age group and gender. Additionally, 2 comorbidity indices were created: a Modified Charlson Comorbidity Index (CCI) that included conditions associated with mortality risk and the NSHAP Comorbidity Index (NCI) that included conditions from the Modified CCI as well as additional conditions related to overall health and function. Hypertension, incontinence, arthritis, heart conditions, cancer, and diabetes were the most prevalent conditions. In general, prevalences of most chronic conditions increased with age. Additionally, there were several notable gender differences in chronic condition prevalence. Due to the inclusion of highly prevalent conditions, such as hypertension and incontinence, the mean comorbidity index score of the NCI was higher than that of the Modified CCI. Wave 2 of NSHAP included a variety of measures assessing the chronic conditions that are the most prevalent in older adults. These data are a valuable resource for the study of the impact of chronic conditions on overall health and aging.

Provide recommendations for researchers on the use of the Big Five personality battery in the National Social Life, Health, and Aging Project (NSHAP), and ensure that the battery does proxy the Big Five. Also, describe the levels of Big Five traits across gender and age. We used an Exploratory Structural Equation Model (ESEM) to analyze NHSAP's personality battery, comparing NSHAP with the National Longitudinal Study of Midlife in the United States (MIDUS) and the Health and Retirement Study (HRS). ESEM revealed a 5-factor structure in the NSHAP battery, but with considerable cross-loadings. When these cross-loadings were not included in the model, model fit notably worsened. Reliabilities of Big Five scales were comparable to the HRS and MIDUS, even though NSHAP's battery is shorter. Women were considerably more Agreeable than men, although this gender gap closed among the oldest in the sample (80 years or older). Researchers will be able to make use of NSHAP's personality battery to examine a range of social, biological, and psychological factors at older ages, in light of individuals' general traits. We recommend models which allow for cross-loadings.

We describe each childhood background measure available in the National Social Life, Health, and Aging Project (NSHAP), report preliminary population estimates for each measure by age and gender, and validate the childhood measures by showing that the associations between the NSHAP childhood measures and later-life health outcomes are consistent with previous studies on this topic. Childhood background measures included family life happiness, family structure, parental educational attainment, perceived financial situation, experience of violence, witness of violence, childhood health, and place of birth. We measured self-rated health, depressive symptoms, and social support to assess later-life physical, mental, and social health. Logistic and linear regression models were used for the binary and continuous outcome variables, respectively. Older age groups were more likely than those in younger age groups to report a poor financial situation in childhood, lower parental education, and intact family structure and were less likely to have experienced or witnessed a violent event as a child. Growing up in a happy and well-educated family was associated with better physical, mental, and social health in older ages. NSHAP childhood data included a variety of measures assessing the family social environment during childhood, providing a valuable resource for the study of early-life determinants of health and well-being over the life course.

Sex hormones affect physical, mental, and social health, yet their role in mediating social effects on aging is understudied. To facilitate such analyses with the National Social Life, Health & Aging Project Wave 2, we summarize the conceptual background, collection protocols, laboratory assays, and data analysis strategies for biologically active (free) levels of testosterone, estradiol, progesterone, and dehydroepiandrosterone (DHEA). Saliva from passive drool was collected from returning Wave 1 respondents and non-respondents as well as their partners during an in-home interview. Specimens were frozen and sent to Dresden LabService GmbH for duplicate assays of biologically active steroids using identical assay kits from National Social Life, Health, and Aging Project (NSHAP) Wave 1 (SaliCap, Catalog No. RE69995). Overall, 2,772 testosterone, 2,504 estradiol, 2,714 progesterone, and 2,800 DHEA measurements are publically available for Wave 2 analyses. Through a series of weighted linear regressions, all 4 steroids are compared by gender and age and to Wave 1 measurements. Men had higher levels of both free testosterone and progesterone than women; women and men had the same levels of estradiol and DHEA. Both free testosterone and DHEA decreased with age. We also found significant wave effects for all 4 sex hormones. NSHAP Waves 1 and 2 are the first U.S. probability sample studies to measure these 4 salivary sex hormones simultaneously, providing individual profiles 5 years apart. Wave 2 data demonstrate differences by gender and trends by age that are similar to those found in other saliva-based and serum-based studies of free steroid levels. The differences between waves arising from the change in assay laboratory need to be adjusted in future longitudinal analyses using NSHAP Wave 1 and Wave 2 steroid data.

The World Health Organization (WHO) defines health as a "state of complete physical, mental and social well-being and not merely the absence of disease or infirmity." Despite general acceptance of this comprehensive definition, there has been little rigorous scientific attempt to use it to measure and assess population health. Instead, the dominant model of health is a disease-centered Medical Model (MM), which actively ignores many relevant domains. In contrast to the MM, we approach this issue through a Comprehensive Model (CM) of health consistent with the WHO definition, giving statistically equal consideration to multiple health domains, including medical, physical, psychological, functional, and sensory measures. We apply a data-driven latent class analysis (LCA) to model 54 specific health variables from the National Social Life, Health, and Aging Project (NSHAP), a nationally representative sample of US community-dwelling older adults. We first apply the LCA to the MM, identifying five health classes differentiated primarily by having diabetes and hypertension. The CM identifies a broader range of six health classes, including two "emergent" classes completely obscured by the MM. We find that specific medical diagnoses (cancer and hypertension) and health behaviors (smoking) are far less important than mental health (loneliness), sensory function (hearing), mobility, and bone fractures in defining vulnerable health classes. Although the MM places two-thirds of the US population into "robust health" classes, the CM reveals that one-half belong to less healthy classes, independently associated with higher mortality. This reconceptualization has important implications for medical care delivery, preventive health practices, and resource allocation.

ABSTRACTObjective: Building upon the widely known link between physical and mental health, the present study explored the buffering effects of social capital (indicated by social cohesion, social ties, and safety) in the relationship between physical constraint (indicated by chronic conditions and functional disability) and mental distress (indicated by symptoms of depression and anxiety).Method: Using data from 2,264 community-dwelling older adults in the National Social Life, Health, and Aging Project (NSHAP) Wave 2 (Mage = 74.51, SD = 6.67), a latent interaction model was tested. The model of mental distress, including both the main effect of physical constraint and social capital and their latent interaction, presented an excellent fit.Results: The latent constructs of physical constraint (β = .54, p < .001) and social capital (β = –.11, p < .01) not only had a direct effect on mental distress, but their interaction was also significant (β = –.26, p < .001). Subgroup analysis showed that the group with a low level of social capital had a heightened vulnerability to mental distress when faced with physical constraint, whereas the group with a high level of social capital demonstrated resilience.Conclusion: Findings call attention to ways to enhance older individuals' social capital in efforts to promote their health and well-being.

In this article, we seek to provide assistance to those who might want to use data from the National Social Life, Health, and Aging Project (NSHAP) Rounds 1-3 to compare those born in different cohorts. We outline 2 theoretical models that underlie the design of NSHAP-the life course model and the birth cohorts model-and review examples of social and political changes that may have differentially affected cohorts of older adults. Then we present 2 ways that NSHAP data might be used to compare cohorts, show examples of analyses of cohort differences in measures in NSHAP, and discuss features of the data that might affect their use for this purpose. Round 3 of the NSHAP added a group of respondents born between 1948 and 1965, the Baby Boom. Together with data from an earlier cohort, interviewed in Rounds 1-3, these data allow analysis of birth cohorts of older adults in the United States. We show examples of some approaches. Our age-matched cohort differences approach included all observations where the respondent was aged 57-67 at the time of interview in different time periods (3,816 observations overall; 2,316 for the Silent Generation cohort and 1,500 for the Baby Boom cohort). Our second approach, age, period, and cohort effects, models the effects of age and birth year using restricted cubic splines, with one model excluding the linear effect of birth year, and the other excluding the linear effect of period. We present examples of analyses using each of these methods. We describe features of the NSHAP data of which researchers should be aware when conducting cohort analyses with these data.

Amid the COVID-19 pandemic, social distancing has been emphasized for older adults because of their greater physical health risks. Using data from the National Social Life, Health and Aging Project (NSHAP), we examined how older adults may have changed their frequency of contact with others via various modes (i.e., in-person, phone calls, messages, and video calls) since the pandemic started, and how these choices may be impacting their mental health. From September 2020 through January 2021, NSHAP respondents (N=2,554 age 50-94 with data from 2015-16) completed a survey via web, phone, or paper-and-pencil. Although some older adults reported reducing their in-person contact with out-of-household family (38%) and friends (40%) since the pandemic started, some also increased contact with them via remote modes such as phone calls (25% and 16% with family and friends respectively); emails, texts, or social media messages (26 and 21%); and video calls (24 and 18%). Net of demographics, living alone, survey mode, and 2015-16 levels of the respective mental health variables, those who decreased in-person contact with family were less happy (B=-0.12, SE=0.06, p=.035), had higher loneliness scores (B=0.23, SE=0.09, p=.011), and more frequently felt depressed (B=0.10, SE=0.05, p=.055). In the presence of decreased in-person contact, increases in remote modes of contact had no net remediating impact—a pattern also found when analyzing contact with friends. Results indicate a persistent adverse effect of reduced in-person contact on mental health despite increased contact with family and friends via remote means.