Publications by authors named "Maryann Pentz"

The objective of this study was to use available data on the prevalence of COVID-19 risk factors in subpopulations and epidemic dynamics at the population level to estimate probabilities of severe illness and the case and infection fatality rates (CFR and IFR) stratified across subgroups representing all combinations of the risk factors age, comorbidities, obesity, and smoking status. We focus on the first year of the epidemic in Los Angeles County (LAC) (March 1, 2020-March 1, 2021), spanning three epidemic waves. A relative risk modeling approach was developed to estimate conditional effects from available marginal data.

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Background: Health disparities have emerged with the COVID-19 epidemic because the risk of exposure to infection and the prevalence of risk factors for severe outcomes given infection vary within and between populations. However, estimated epidemic quantities such as rates of severe illness and death, the case fatality rate (CFR), and infection fatality rate (IFR), are often expressed in terms of aggregated population-level estimates due to the lack of epidemiological data at the refined subpopulation level. For public health policy makers to better address the pandemic, stratified estimates are necessary to investigate the potential outcomes of policy scenarios targeting specific subpopulations.

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Objective: Emerging adulthood (ages 18-25 years) has been associated with elevated substance use. Transitional life events (TLEs) during emerging adulthood in relation to substance use are usually examined separately, rather than as a constellation. The purposes of this study were (a) to explore distinct subgroups experiencing various TLEs during emerging adulthood, (b) to identify heterogeneous trajectories of cigarette and alcohol use during emerging adulthood, and (c) to examine the association of TLEs with cigarette and alcohol use trajectories.

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The growth curve modeling (GCM) technique has been widely adopted in longitudinal studies to investigate progression over time. The simplest growth profile involves two growth factors, initial status (intercept) and growth trajectory (slope). Conventionally, all repeated measures of outcome are included as components of the growth profile, and the first measure is used to reflect the initial status.

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The risk of obesity during childhood can be significantly reduced through increased physical activity and decreased sedentary behavior. Recent technological advances have created opportunities for the real-time measurement of these behaviors. Mobile phones are ubiquitous and easy to use, and thus have the capacity to collect data from large numbers of people.

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We used latent class analysis (LCA) to identify heterogeneous subgroups with respect to behavioral obesity risk factors in a sample of 4th grade children (n = 997) residing in Southern California. Multiple dimensions assessing physical activity, eating and sedentary behavior, and weight perceptions were explored. A set of 11 latent class indicators were used in the analysis.

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One third of smokers worldwide live in China. Identifying predictors of smoking is important for prevention program development. This study explored whether the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) predict adolescent smoking in China.

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