No abstract

Puerto Rico is aging more rapidly than almost any country, with 2020 estimates placing its population share of adults older than 65 as being the 10 th highest in the world. Unlike most locales, Puerto Rico's aging is driven by both a) the culmination of long-running fertility and mortality trends, and b) high levels of outmigration of working-age adults, which contributes both directly (removal of young people) and indirectly (reduced births) to its pace of population aging. This article offers an overview of the main issues surrounding population aging in Puerto Rico. Policymakers and government leaders must plan for Puerto Rico's unconventional population aging, which will exacerbate traditional concerns about the sustainability of government services and long-term economic prospects. Additional concerns emerge related to reduced social support networks and their impact on caregiving dynamics and implications for health. Puerto Rico's unique history and political relationship with the United States presents challenges and benefits for its aging population. Research on aging in Puerto Rico and public health policies must adapt to the needs of the country's aging society.

Background and Objectives Social support networks of older adults have been linked to their health and well-being; however, findings regarding the effects of specific network characteristics have been mixed. Additionally, due to demographic shifts increasing numbers of older adults live outside of traditional family structures. Previous studies have not systematically examined the resulting complexity and heterogeneity of older adults’ social networks. Our objectives were to examine this complexity and heterogeneity by developing a multidimensional typology of social networks that simultaneously considers multiple structural and functional network characteristics, and to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort. Research Design and Methods Participants included 5,192 adults aged 57–85 years in the National Social Life, Health, and Aging Project at rounds 1 (2005–2006) and 3 (2015–2016). Data were collected on social relationships including network size, diversity, frequency of contact, and perceived support and strain in relationships. We used latent class analysis to derive the network typology and multinomial logistic regression to examine differences in network type membership by sociodemographic characteristics, health characteristics, and birth cohort. Results Older adults were classified into 5 distinct social network types: (i) large, with strain; (ii) large, without strain; (iii) small, diverse, low contact; (iv) small, restricted, high contact; and (v) medium size and support. Membership in these network types varied by age, gender, marital status, race/ethnicity, education, mental health, and birth cohort. Discussion and Implications Network typologies can elucidate the varied interpersonal environments of older adults and identify individuals who lack social connectedness on multiple network dimensions and are therefore at a higher risk of social isolation.

Background Cognitive impairment is associated with increased mortality rates in late life, but it is unclear whether worse cognition predicts working-age mortality. Methods The data come from a US national survey (N=3,973 aged 32–84 at cognitive testing in 2004–06, mean age 56.6, 56.3% female; N=3,055 retested in 2013-18 at ages 42–94, mean age 64.6, 56.6% female; mortality follow-up through 2019). We use Cox hazard models to investigate whether cognition is associated with mortality below age 65, how the magnitude of this risk compares with the risk in later life, and whether the association persists after adjusting for potential confounders. Results Worse cognition is associated with mortality, but the demographic-adjusted hazard ratio (HR) diminishes with age from 2.0 per SD (95% CI 1.7-2.4) at age 55 to 1.4 (95% CI 1.3–1.6) at age 85. In the fully-adjusted model, the corresponding HRs are 1.4 (95% CI 1.2–1.7) and 1.3 (95% CI 1.1-1.4), respectively. The absolute differences in mortality by level of cognition, however, are larger at older ages because mortality is rare at younger ages. The fully-adjusted model implies a 2.7-percentage point differential in the estimated percentage dying between ages 55 and 65 for those with low cognition (1 SD below the overall mean, 5.7%) vs. high cognition (1 SD above the mean, 3.0%). The corresponding differential between age 75 and 85 is 8.4 percentage points (24.6% vs. 16.2%, respectively). Conclusion Cognitive function may be a valuable early warning sign of premature mortality, even at working ages, when dementia is rare.

Background Little is known about how depressive symptoms and glial fibrillary acid protein (GFAP) concentrations taken together may influence cognitive functioning. Understanding this relationship may inform strategies for screening and early intervention to decrease rate of cognitive decline. Methods This study sample includes 1,169 participants from the Chicago Health and Aging Project (CHAP), consisting of 60% Black participants and 40% White participants, and 63% female participants and 37% male participants. CHAP is a population-based cohort study of older adults with a mean age of 77 years. Linear mixed effects regression models tested the main effects of depressive symptoms and GFAP concentrations and their interactions on baseline cognitive function and cognitive decline over time. Models included adjustments for age, race, sex, education, chronic medical conditions, BMI, smoking status, and alcohol use, and their interactions with time. Results The interaction of depressive symptomology and GFAP (β= -.105 (SE=.038), p=.006) on global cognitive function was statistically significant. Participants with depressive symptoms including and above the cut off and high log of GFAP concentrations had more cognitive decline over time, followed by participants with depressive symptoms below the cut off and high log of GFAP concentrations, depressive symptom scores including and above the cut off and low log of GFAP concentrations, and depressive symptom scores below the cut off and low log of GFAP concentrations. Conclusions Depressive symptoms have an additive effect on the association between the log of GFAP and baseline global cognitive function.