Lifecourse Educational Trajectories and Hypertension in Midlife: An Application of Sequence Analysis.

BACKGROUND: Higher educational attainment predicts lower hypertension. Yet, associations between nontraditional educational trajectories (eg, interrupted degree programs) and hypertension are less well understood, particularly among structurally marginalized groups who are more likely to experience these non-traditional trajectories. METHODS: In National Longitudinal Survey of Youth 1979 cohort data (N = 6 317), we used sequence and cluster analyses to identify groups of similar educational sequences-characterized by timing and type of terminal credential-that participants followed from age 14-48 years. Using logistic regression, we estimated associations between the resulting 10 educational sequences and hypertension at age 50. We evaluated effect modification by individual-level indicators of structural marginalization (race, gender, race and gender, and childhood socioeconomic status [cSES]). RESULTS: Compared to terminal high school (HS) diploma completed at traditional age, terminal GED (OR: 1.32; 95%CI: 1.04, 1.66) or Associate degree after

Association of Social Support With Functional Outcomes in Older Adults Who Live Alone.

Importance: Older adults who live alone are at risk for poor health outcomes. Whether social support mitigates the risk of living alone, particularly when facing a sudden change in health, has not been adequately reported. Objective: To assess if identifiable support buffers the vulnerability of a health shock while living alone. Design, Setting, and Participants: In this longitudinal, prospective, nationally representative cohort study from the Health and Retirement Study (enrollment March 2006 to April 2015), 4772 community-dwelling older adults 65 years or older who lived alone in the community and could complete activities of daily living (ADLs) and instrumental ADLs independently were followed up biennially through April 2018. Statistical analysis was completed from May 2020 to March 2021. Exposures: Identifiable support (ie, can the participant identify a relative/friend who could help with personal care if needed), health shock (ie, hospitalization, new diagnosis of cancer, stroke, heart attack), and interaction (multiplicative and additive) between the 2 exposures. Main Outcomes and Measures: The primary outcomes were incident ADL dependency, prolonged nursing home stay (≥30 days), and death. Results: Of 4772 older adults (median [IQR] age, 73 [68-81] years; 3398 [71%] women) who lived alone, at baseline, 1813 (38%) could not identify support, and 3013 (63%) experienced a health shock during the study. Support was associated with a lower risk of a prolonged nursing home stay at 2 years (predicted probability, 6.7% vs 5.2%; P = .002). Absent a health shock, support was not associated with a prolonged nursing home stay (predicted probability over 2 years, 1.9% vs 1.4%; P = .21). However, in the presence of a health shock, support was associated with a lower risk of a prolonged nursing home stay (predicted probability over 2 years, 14.2% vs 10.9%; P = .002). Support was not associated with incident ADL dependence or death. Conclusions and Relevance: In this longitudinal cohort study among older adults who live alone, identifiable support was associated with a lower risk of a prolonged nursing home stay in the setting of a health shock.

Understanding the benefits of different types and timing of education for mental health: A sequence analysis approach.

OBJECTIVES: Individuals increasingly experience delays or interruptions in schooling; we evaluate the association between these non-traditional education trajectories and mental health. METHODS: Using year-by-year education data for 7,501 National Longitudinal Survey of Youth 1979 participants, ages 14-48 (262,535 person-years of education data), we applied sequence analysis and a clustering algorithm to identify educational trajectory groups, incorporating both type and timing to credential. Linear regression models, adjusted for early-life confounders, evaluated relationships between educational trajectories and mental health component scores (MCS) from the 12-item short form instrument at age 50. We evaluated effect modification by race, gender, and race by gender. RESULTS: We identified 24 distinct educational trajectories based on highest credential and educational timing. Compared to high school (HS) diplomas, < HS (beta=-3.41, 95%CI:-4.74,-2.07) and general educational development credentials (GEDs) predicted poorer MCS (beta=-2.07,95%CI:-3.16,-0.98). The following educational trajectories predicted better MCS: some college immediately after High School (beta=1.52, 95%CI:0.68,2.37), Associate degrees after long interruptions (beta=1.73, 95%CI:0.27,3.19), and graduate school soon after Bachelor's completion (beta=1.13, 95%CI:0.21,2.06). Compared to White men, Black women especially benefited from educational credentials higher than HS in predicting MCS. CONCLUSIONS: Both type and timing of educational credential predicted mental health. Black women's mental higher especially benefited from higher educational credentials.

Estimating the impact of violent events on transmission in Ebola virus disease outbreak, Democratic Republic of the Congo, 2018-2019.

INTRODUCTION: As of April 2019, the current Ebola virus disease (EVD) outbreak in the Democratic Republic of the Congo (DRC) is occurring in a longstanding conflict zone and has become the second largest EVD outbreak in history. It is suspected that after violent events occur, EVD transmission will increase; however, empirical studies to understand the impact of violence on transmission are lacking. Here, we use spatial and temporal trends of EVD case counts to compare transmission rates between health zones that have versus have not experienced recent violent events during the outbreak. METHODS: We collected daily EVD case counts from DRC Ministry of Health. A time-varying indicator of recent violence in each health zone was derived from events documented in the WHO situation reports. We used the Wallinga-Teunis technique to estimate the reproduction number R for each case by day per zone in the 2018-2019 outbreak. We fit an exponentially decaying curve to estimates of R overall and by health zone, for comparison to past outbreaks. RESULTS: As of 16 April 2019, the mean overall R for the entire outbreak was 1.11. We found evidence of an increase in the estimated transmission rates in health zones with recently reported violent events versus those without (p = 0.008). The average R was estimated as between 0.61 and 0.86 in regions not affected by recent violent events, and between 1.01 and 1.07 in zones affected by violent events within the last 21 days, leading to an increase in R between 0.17 and 0.53. Within zones with recent violent events, the mean estimated quenching rate was lower than for all past outbreaks except the 2013-2016 West African outbreak. CONCLUSION: The difference in the estimated transmission rates between zones affected by recent violent events suggests that violent events are contributing to increased transmission and the ongoing nature of this outbreak.

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration.