Midlife and old-age cardiovascular risk factors, educational attainment, and cognition at 90-years – population-based study with 48-years of follow-up

by Anni Varjonen, Toni Saari, Sari Aaltonen, Teemu Palviainen, Mia Urjansson, Paula Iso-Markku, Jaakko Kaprio, Eero Vuoksimaa

We examined the associations of midlife and old-age cardiovascular risk factors, education, and midlife dementia risk scores with cognition at 90 + years, using data from a population-based study with 48 years of follow-up. Participants were 96 individuals aged 90–97 from the older Finnish Twin Cohort study. Individual cardiovascular risk factors assessed via questionnaires in 1975, 1981, 1990, and 2021–2023 included blood pressure, body mass index, physical activity, and cholesterol, and self-reported educational attainment. The Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) score and an educational-occupational attainment score were used as midlife dementia risk scores. Cognitive assessments included semantic fluency, immediate and delayed recall from a 10-word list learning task, and a composite cognitive score. Regression analyses were conducted with dementia risk factors predicting cognition at 90 + years, adjusting for age, sex, education, follow-up time, and apolipoprotein E genotype (ε4-carrier vs non-carriers). Results showed that higher education and higher educational-occupational score were associated with better cognitive performance in all cognitive measures. Those with high midlife blood pressure scored significantly higher in all cognitive tests than those with normal blood pressure. Conversely, those with high old-age blood pressure scored lower in semantic fluency and composite cognitive score, but not in immediate or delayed recall. Other cardiovascular risk factors and the CAIDE score did not show consistent associations with cognition. Education appears to have a long-lasting protective effect in cognitive aging, whereas midlife and old-age cardiovascular risk factors were not significantly associated with cognition at 90 + years.

Factors associated with prolonged hospitalizations for COVID-19 during the first three waves of the pandemic: Evidence from a Southeastern State of Brazil

by Juliana Rodrigues Tovar Garbin, Franciéle Marabotti Costa Leite, Ana Paula Brioschi dos Santos, Larissa Soares Dell’Antonio, Cristiano Soares da Silva Dell’Antonio, Luís Carlos Lopes-Júnior

A comprehensive understanding of the factors influencing the epidemiological dynamics of COVID-19 across the pandemic waves—particularly in terms of disease severity and mortality—is critical for optimizing healthcare services and prioritizing high-risk populations. Here we aim to analyze the factors associated with short-term and prolonged hospitalization for COVID-19 during the first three pandemic waves. We conducted a retrospective observational study using data from individuals reported in the e-SUS-VS system who were hospitalized for COVID-19 in a state in a southeast state of Brazil. Hospitalization duration was classified as short or prolonged based on a 7-day cutoff, corresponding to the median length of hospital stay during the second pandemic wave. Bivariate analyses were performed using the chi-square test for heterogeneity. Logistic regression models were used to estimate odds ratios (ORs) and their respective 95% confidence intervals (CIs), with statistical significance set at 5%. When analyzing hospitalization duration across the three waves, we found that 51.1% (95%CI: 49.3–53) of hospitalizations in the first wave were prolonged. In contrast, short-duration hospitalizations predominated in the second (54.7%; 95% CI: 52.4–57.0) and third (51.7%; 95% CI: 50.2–53.2) waves. Factors associated with prolonged hospitalization varied by wave. During the first wave, older adults (≥60 years) (OR=1.67; 95%CI: 1.35–2.06), individuals with ≥10 symptoms (OR=2.03; 95%CI: 1.04–3.94), obese individuals (OR=2.0; 95%CI: 1.53–2.74), and those with ≥2 comorbidities (OR=2.22; 95%CI: 1.71–2.89) were more likely to experience prolonged hospitalization. In the second wave, he likelihood of extended hospital stays was higher among individuals aged ≥60 years (OR=2.04; 95%CI: 1.58–2.62) and those with ≥2 comorbidities (OR=1.77; 95%CI: 1.29–2.41). In the third wave, prolonged hospitalization was more frequent among older adults (OR=1.89; 95%CI: 1.65–2.17,), individuals with 5–9 symptoms (OR=1.52; 95%CI: 1.20–1.92), obese individuals (OR=2.2; 95%CI: 1.78–2.73), and those with comorbidities (OR=1.45; 95%CI: 1.22–1.72 and OR=2.0; 95%CI: 1.69–2.45). In conclusion, we identified variations in hospitalization patterns across the pandemic waves, although the differences were relatively subtle. These variations likely reflect gradual shifts in the risk factors associated with prolonged hospital stays. Our findings highlight t the importance of implementing targeted public health interventions, particularly those designed to reduce disease severity and improve clinical outcomes among vulnerable populations at greater risk of extended hospitalization.

Work ability during the COVID-19 pandemic: A cross-sectional study in a low-income urban setting in Brazil

by Ana Paula Cândido Oliveira, Daniela Alencar Vieira, Cristiane Wanderley Cardoso, Tereza Magalhães, Rosangela Oliveira Anjos, Eduardo José Farias Borges Reis, Kionna Oliveira Bernardes Santos, Guilherme Sousa Ribeiro

Work ability is a subjective concept that reflects the balance between an individual’s perception of the physical, mental, and social demands of work and their competence and resources to meet those demands. The COVID-19 crisis significantly impacted health, work, and socioeconomic conditions worldwide. However, few studies have examined work ability in disadvantaged urban communities during this period. To analyze factors associated with work ability within the context of social vulnerability during the COVID-19 pandemic, we conducted a cross-sectional study in a low-income neighborhood in Salvador, Brazil, between February and June 2022. Sociodemographic, health, and labor data were collected, and work ability was assessed using the Work Ability Index (WAI), a widely used tool for evaluating work ability. Multivariable analyses based on a hierarchical model were run to investigate factors associated with low WAI scores. The study included 292 workers aged ≥16 years (59.6% women; median age 41 years). Most workers (84.6%) were classified as having adequate work ability based on their WAI scores. Multivariable analyses found that inadequate work ability was more frequent among women (prevalence ratio [PR]: 1.89, 95% confidence interval [CI]: 1.02-3.48), individuals who self-rated their health as moderate/good (PR: 5.91; 95% CI: 1.45-24.05) or poor/very poor (PR: 21.62; 95% CI: 5.14-90.91) compared to those with excellent/very good health, and those reporting diabetes (PR: 2.1; 95% CI: 1.13-3.9). Working >40 hours per week (PR: 0.47; 95% CI: 0.28-0.96) was negatively associated with inadequate work ability, suggesting that individuals with adequate work ability may be selected for longer working hours. A history of COVID-19 was not associated with inadequate work ability. These findings suggest that targeted interventions to improve work ability in low-income communities should prioritize women and workers with chronic health conditions, such as diabetes.

Monitoring emerging pathogens using negative nucleic acid test results from endemic pathogens in pig populations: Application to porcine enteric coronaviruses

by Ana Paula Serafini Poeta Silva, Guilherme Arruda Cezar, Edison Sousa Magalhães, Kinath Rupasinghe, Srijita Chandra, Gustavo S. Silva, Marcelo Almeida, Bret Crim, Eric Burrough, Phillip Gauger, Christopher Siepker, Marta Mainenti, Michael Zeller, Rodger G. Main, Mary Thurn, Paulo Fioravante, Cesar Corzo, Albert Rovira, Hemant Naikare, Rob McGaughey, Franco Matias Ferreyra, Jamie Retallick, Jordan Gebhardt, Angela Pillatzki, Jon Greseth, Darren Kersey, Travis Clement, Jane Christopher-Hennings, Melanie Prarat, Ashley Johnson, Dennis Summers, Craig Bowen, Kenitra Hendrix, Joseph Boyle, Daniel Correia Lima Linhares, Giovani Trevisan

This study evaluated the use of endemic enteric coronaviruses polymerase chain reaction (PCR)-negative testing results as an alternative approach to detect the emergence of animal health threats with similar clinical diseases presentation. This retrospective study, conducted in the United States, used PCR-negative testing results from porcine samples tested at six veterinary diagnostic laboratories. As a proof of concept, the database was first searched for transmissible gastroenteritis virus (TGEV) negative submissions between January 1^st, 2010, through April 29^th, 2013, when the first porcine epidemic diarrhea virus (PEDV) case was diagnosed. Secondly, TGEV- and PEDV-negative submissions were used to detect the porcine delta coronavirus (PDCoV) emergence in 2014. Lastly, encountered best detection algorithms were implemented to prospectively monitor the 2023 enteric coronavirus-negative submissions. Time series (weekly TGEV-negative counts) and Seasonal Autoregressive-Integrated Moving-Average (SARIMA) were used to control for outliers, trends, and seasonality. The SARIMA’s fitted and residuals were then subjected to anomaly detection algorithms (EARS, EWMA, CUSUM, Farrington) to identify alarms, defined as weeks of higher TGEV-negativity than what was predicted by models preceding the PEDV emergence. The best-performing detection algorithms had the lowest false alarms (number of alarms detected during the baseline) and highest time to detect (number of weeks between the first alarm and PEDV emergence). The best-performing detection algorithms were CUSUM, EWMA, and Farrington flexible using SARIMA fitted values, having a lower false alarm rate and identified alarms 4 to 17 weeks before PEDV and PDCoV emergences. No alarms were identified in the 2023 enteric negative testing results. The negative-based monitoring system functioned in the case of PEDV propagating epidemic and in the presence of a concurrent propagating epidemic with the PDCoV emergence. It demonstrated its applicability as an additional tool for diagnostic data monitoring of emergent pathogens having similar clinical disease as the monitored endemic pathogens.