The latest medical research on Public Health

The research magnet gathers the latest research from around the web, based on your specialty area. Below you will find a sample of some of the most recent articles from reputable medical journals about public health gathered by our medical AI research bot.

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Changes in obesity and BMI among children and adolescents with selected chronic conditions during the COVID-19 pandemic.


The aim of this study was to examine COVID-19 pandemic-related changes in obesity and BMI among patients aged 5 to <20 years with selected chronic conditions.

A longitudinal study in 293,341 patients aged 5 to <20 years who were prescribed one of five medication classes (for depression, psychosis, hypertension, diabetes, or epilepsy) and who had BMI measures from January 2019 to March 2021 was conducted. Generalized estimating equations and linear mixed-effects models were used, accounting for within-child repeated measures and stratified by age, race, ethnicity, gender, and class of medication prescribed, to compare obesity and BMI z score during the pandemic (June through December 2020) versus pre-pandemic (June through December 2019).

Obesity prevalence increased from 23.8% before the pandemic to 25.5% during the pandemic; mean (SD) BMI z score increased from 0.62 (1.26) to 0.65 (1.29). Obesity prevalence during the pandemic increased at a faster rate compared with pre-pandemic among children aged 5 to <13 years (0.27% per month; 95% CI: 0.11%-0.44%) and 13 to <18 years (0.24% per month; 95% CI: 0.09%-0.40%), with the largest increases among children aged 5 to <13 years who were male (0.42% per month), Black (0.35% per month), or Hispanic (0.59% per month) or who were prescribed antihypertensives (0.28% per month).

The COVID-19 pandemic has exacerbated the obesity epidemic and widened disparities among children with selected chronic conditions. These findings highlight the importance of continuing efforts to specifically help high-risk populations who are experiencing weight gain from the pandemic.

Fostering telecompetence: A descriptive evaluation of clinical psychology predoctoral internship and postdoctoral fellowship implementation of telehealth education.


Telehealth education within clinical psychology predoctoral internships and postdoctoral fellowships has become a frequent recommendation designed to prepare future providers with evidence-informed telehealth skills that can be applied to rural populations. Unfortunately, the availability of telehealth training among internships and fellowships, as well as areas for growth, remains unclear. Thus, the current study evaluated graduate clinical psychology internship and fellowship integration of telehealth training components before and after the onset of COVID-19.

Individuals representing 74 internships and 29 fellowships completed author-created REDCap-hosted demographic and telehealth training surveys.

Before COVID-19, 2 internships and 4 fellowships reported implementing telehealth education, with a majority of materials for both types of programs being optional educational targets and generally encompassing 0-15 hours of student education. After the onset of COVID-19, 72 internships and 27 fellowships indicated implementing telehealth education, with a majority indicating materials as mandatory and encompassing between 0 and 50+ hours. Despite increases, 73.6% of internship programs and 62.1% of fellowship programs noted a desire for their students to receive additional telehealth education in the future. Integrated educational foci are discussed.

The current study demonstrated positive trends in the development of telehealth education among internships and fellowships. Nevertheless, some programs can likely benefit from additional integration of telehealth components, as well as more formal programming built around field-supported competencies and models. While work is required to further clarify field offerings, the current study provided a preliminary evaluation of internship and fellowship telehealth educational offerings.

Examining Pregnant Veterans' Acceptance and Beliefs Regarding the COVID-19 Vaccine.


Pregnant persons have received mixed messages regarding whether or not to receive COVID-19 vaccines as limited data are available regarding vaccine safety for pregnant and lactating persons and breastfeeding infants.

The aims of this study were to examine pregnant Veteran's acceptance of COVID-19 vaccines, along with perceptions and beliefs regarding vaccine safety and vaccine conspiracy beliefs.

Pregnant Veterans were asked whether they had been offered the COVID-19 vaccine during pregnancy, and whether they chose to accept or refuse it. Additional questions focused on perceptions of COVID-19 vaccine safety and endorsements of vaccine knowledge and conspiracy beliefs. Logistic regression was utilized to examine predictors of acceptance of a vaccine during pregnancy.

Overall, 72 pregnant Veterans were offered a COVID-19 vaccine during pregnancy; over two-thirds (69%) opted not to receive a vaccine. Reasons for not receiving a vaccine included potential effects on the baby (64%), side effects for oneself (30%), and immunity from a past COVID-19 infection (12%). Those who received a vaccine had significantly greater vaccine knowledge and less belief in vaccine conspiracy theories. Greater knowledge of vaccines in general (aOR: 1.78; 95% CI: 1.2-2.6) and lower beliefs in vaccine conspiracies (aOR: 0.76; 95% CI: 0.6-0.9) were the strongest predictors of acceptance of a COVID-19 vaccine during pregnancy.

Our study provides important insights regarding pregnant Veterans' decisions to accept the COVID-19 vaccine, and reasons why they may choose not to accept the vaccine. Given the high endorsement of vaccine conspiracy beliefs, trusted healthcare providers should have ongoing, open discussions about vaccine conspiracy beliefs and provide additional information to dispel these beliefs.

Effects of Intimate Partner Violence During COVID-19 and Pandemic-Related Stress on the Mental and Physical Health of Women Veterans.


Little is known about women veterans' intimate partner violence (IPV) experiences during the COVID-19 pandemic or the impacts of pandemic-related stress on their mental and physical health.

To identify IPV experiences among women veterans prior to and during the pandemic, pandemic-related stressors, and examine their respective contributions to mental and physical health.

We assessed IPV (CTS-2), PTSD (PCL-5), depression (CESD), anxiety (DASS-A), physical health (PHQ-15), and physical health-related quality of life (SF-12) prior to the pandemic (June 2016-December 2016/January 2017) and during the pandemic study period (March 2020-December 2020/January 2021). We assessed pandemic-related stressors (EPII) during the pandemic study period.

Over a third (38.7%) of participants experienced IPV during the pandemic study period (psychological: 35.9%, physical: 9.9%, sexual: 4.2%). Overall rates, frequency, and severity of IPV experience did not significantly differ between the pre-pandemic and pandemic study periods. Few participants tested positive for COVID-19 (4.2%); however, most participants reported experiencing pandemic-related stressors across life domains (e.g., social activities: 88%, physical health: 80.3%, emotional health: 68.3%). IPV during the pandemic and pandemic-related stressors were both associated with greater PTSD and depressive symptoms. Pandemic-related stressors were associated with worse anxiety and physical health symptoms. Neither IPV during the pandemic nor pandemic-related stressors were associated with physical health-related quality of life.

IPV experiences during the pandemic were common among women veterans, as were pandemic-related stressors. Although IPV did not increase in the context of COVID-19, IPV experiences during the pandemic and pandemic-related stressors were linked with poorer mental and physical health.

Impact of COVID-19 on the patient referral pattern and conversion rate in the university versus private facial plastic surgery centers.


To compare the number of referrals and conversion rate between the pandemic and pre-pandemic period.

The number of referrals and conversion rate between the 10-month pandemic (March-December 2020) and pre-pandemic (March-December 2019) were evaluated in the two university (mainly non-cosmetic) and private (mainly cosmetic) facial plastic surgery centers. Demographics and monthly number and type (cosmetic and non-cosmetic) of the referrals and surgeries were recorded from the both and cosmetic facial injections (botulinum toxin and filler) and the source of referrals (web- and non-web-based) from the private center. The conversion rate was a ratio of the number of the surgeries to the number of referrals.

The number of referrals declined by 7.7% in the private center which was significantly higher for the non-cosmetic (26%) than the cosmetic (0.5%) referrals. It was 32% in the university center. The private center conversion rate significantly (P < 0.001) decreased for both the cosmetic (60%) and non-cosmetic (82%) procedures. It was not significantly different between the cosmetic (65%) and non-cosmetic (58%) procedures in the university center. However, the number of cosmetic facial injections (11%) and the web-based referral source (4%) increased. The recovery was better for the number of referrals (better in the private center) than the conversion rate.

The fall in the conversion rate was statistically significant in the private center. While the number of referrals recovered to almost the pre-pandemic level, the conversion rates, despite recovery, remained at a lower level at the end.

A prospective observational study of post-COVID-19 chronic fatigue syndrome following the first pandemic wave in Germany and biomarkers associated with symptom severity.


A subset of patients has long-lasting symptoms after mild to moderate Coronavirus disease 2019 (COVID-19). In a prospective observational cohort st...

Antiviral efficacy of favipiravir against Zika and SARS-CoV-2 viruses in non-human primates.


The COVID-19 pandemic has exemplified that rigorous evaluation in large animal models is key for translation from promising in vitro results to suc...

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy.


The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to exam...

Psychological impact on dental students and professionals in a Lima population during COVID-19s wave: a study with predictive models.


Peru was the country with the highest COVID-19 case fatality rate worldwide during second wave of infection, with dentists and pre-professional stu...

Glucocorticoids' treatment impairs the medium-term immunogenic response to SARS-CoV-2 mRNA vaccines in Systemic Lupus Erythematosus patients.


Limited data exists on SARS-CoV-2 sustained-response to vaccine in patients with rheumatic diseases. This study aims to evaluate neutralizing antib...

The role of electrolyte imbalances in predicting the severity of COVID-19 in the hospitalized patients: a cross-sectional study.


Coronavirus disease 2019 (COVID-19) can be fatal in severe cases. Accordingly, predicting the severity and prognosis of the disease is valuable. Th...

The Mann-Kendall-Sneyers test to identify the change points of COVID-19 time series in the United States.


One critical variable in the time series analysis is the change point, which is the point where an abrupt change occurs in chronologically ordered observations. Existing parametric models for change point detection, such as the linear regression model and the Bayesian model, require that observations are normally distributed and that the trend line cannot have extreme variability. To overcome the limitations of the parametric model, we apply a nonparametric method, the Mann-Kendall-Sneyers (MKS) test, to change point detection for the state-level COVID-19 case time series data of the United States in the early outbreak of the pandemic.

The MKS test is implemented for change point detection. The forward sequence and the backward sequence are calculated based on the new weekly cases between March 22, 2020 and January 31, 2021 for each of the 50 states. Points of intersection between the two sequences falling within the 95% confidence intervals are identified as the change points. The results are compared with two other change point detection methods, the pruned exact linear time (PELT) method and the regression-based method. Also, an open-access tool by Microsoft Excel is developed to facilitate the model implementation.

By applying the MKS test to COVID-19 cases in the United States, we have identified that 30 states (60.0%) have at least one change point within the 95% confidence intervals. Of these states, 26 states have one change point, 4 states (i.e., LA, OH, VA, and WA) have two change points, and one state (GA) has three change points. Additionally, most downward changes appear in the Northeastern states (e.g., CT, MA, NJ, NY) at the first development stage (March 23 through May 31, 2020); most upward changes appear in the Western states (e.g., AZ, CA, CO, NM, WA, WY) and the Midwestern states (e.g., IL, IN, MI, MN, OH, WI) at the third development stage (November 19, 2020 through January 31, 2021).

This study is among the first to explore the potential of the MKS test applied for change point detection of COVID-19 cases. The MKS test is characterized by several advantages, including high computational efficiency, easy implementation, the ability to identify the change of direction, and no assumption for data distribution. However, due to its conservative nature in change point detection and moderate agreement with other methods, we recommend using the MKS test primarily for initial pattern identification and data pruning, especially in large data. With modification, the method can be further applied to other health data, such as injuries, disabilities, and mortalities.