Survivors of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) often experience chronic symptoms that include fatigue, shortness of breath, and brain fog. The collection of ongoing post-COVID-19 symptoms have been classified as Post-Acute Sequela of SARS-CoV-2 (PASC). Older adult patients are especially susceptible to experiencing PASC related complications and have a high risk for long-term cognitive impairment symptoms. Definitions for categorizing PASC- associated cognitive impairment and neuropsychological assessments used to evaluate cognitive impairment are inconsistent between studies examining older adults. This systematic review aims to identify which neuropsychological tests best identify cognitive impairments associated with PASC and suggest a guide to standardize the measurement of PASC-related cognitive impairments. Through a literature search using PubMed, we included within this review 14 studies that fulfilled our inclusion and exclusion criteria evaluating middle-aged and older adult populations affected by PASC-associated cognitive impairments. The majority of the studies used tests designed to screen for general cognitive function to test for the prevalence of cognitive impairment, with the most common one being Montreal Cognitive Assessment (MoCA), followed by MMSE and TICS. MoCA reported the highest prevalence of the general cognitive screeners which suggests higher sensitivity and specificity. Telephone Interview for Cognitive Status (TICS) demonstrated similar scores as MoCA despite administration being remote while MMSE identified the lowest prevalence. Four studies also used domain-specific cognitive evaluations and reported instances of cognitive impairment in individuals who had previously tested healthy. Furthermore, the results gathered in this review were stratified based on disease symptom severity. This review identifies MoCA to be better suited for evaluating general cognitive impairment in older adults. TICS has the added utility in being able to access a wider range of older adults through remote screening. Disease severity must be clearly defined to allow better comparisons between studies and allow for standardization. Early identification of PASC-associated cognitive impairment in middle-aged and older adults can be performed using general cognitive function evaluations and administering a baseline cognitive evaluation one month after infection is suggested.

Significant health inequalities exist between different castes and ethnic communities in India, and identifying the roots of these inequalities is of interest to public health research and policy. Research on caste-based health inequalities in India has historically focused on general, government-defined categories, such as “Scheduled Castes,” “Scheduled Tribes,” and “Other Backward Classes.” This method obscures the diversity of experiences, indicators of well-being, and health outcomes between castes, tribes, and other communities in the “scheduled” category. This study analyzes data on 699,686 women from 4,260 castes, tribes and communities in the 2015-2016 Demographic and Health Survey of India to: (1) examine the diversity within and overlap between general, government-defined community categories in both wealth, infant mortality, and education, and (2) analyze how infant mortality is related to community category membership and socioeconomic status (measured using highest level of education and household wealth). While there are significant differences between general, government-defined community categories (e.g., scheduled caste, backward class) in both wealth and infant mortality, the vast majority of variation between communities occurs within these categories. Moreover, when other socioeconomic factors like wealth and education are taken into account, the difference between general, government-defined categories reduces or disappears. These findings suggest that focusing on measures of education and wealth at the household level, rather than general caste categories, may more accurately target those individuals and households most at risk for poor health outcomes. Further research is needed to explain the mechanisms by which discrimination affects health in these populations, and to identify sources of resilience, which may inform more effective policies.