The association of sedentary behaviour and physical activity with periodontal disease in NHANES 2011-2012.

AIM: Periodontal disease is one of the most prevalent oral pathologies and a major chronic disease worldwide. Lifestyle habits such as poor nutrition and smoking have been established to contribute to the development of periodontal disease, but limited research has investigated whether physical activity and sedentary lifestyle play a role. The purpose of this study is to evaluate the association between physical activity, sedentary behaviour, and periodontal disease. MATERIALS AND METHODS: We used a nationally representative data set from the National Health and Nutrition Examination Survey (NHANES) 2011-2012. We examined the association between physical activity and sedentary behaviour and periodontal disease using multivariable logistic regression models and reported odds ratios (ORs). RESULTS: Individuals with higher total physical activity, higher leisure time physical activity, and lower amount of total sedentary behaviour had lower periodontal disease prevalence. Adjusted multivariable regression models showed that higher sedentary behaviour (more than 7.5 h/day) was associated with higher odds of periodontal disease (OR = 1.17; 95% confidence interval = 1.00-1.36; p = .045). CONCLUSIONS: The findings showed that higher sedentary behaviour is associated with higher odds of periodontal disease. Future prospective longitudinal studies and strategies are needed to investigate implications further and define the magnitude of the association between physical activity and periodontal disease.

Impact of Early Reinitiation of Neuropsychiatric Medications on Agitation and Delirium in the Intensive Care Unit: A Retrospective Study.

BACKGROUND: Approximately 17% of intensive care unit (ICU) patients are prescribed at least 1 home neuropsychiatric medication (NPM). When abruptly discontinued, withdrawal symptoms may occur manifesting as agitation or delirium in the ICU setting. OBJECTIVE: To evaluate the impact of early reinitiation of NPMs. METHODS: This was a retrospective, observational cohort of adult ICU patients in a tertiary care hospital. Patients were included if admitted to the ICU and prescribed a NPM prior to arrival. Study groups were based on the timing of reinitiation of at least 50% of NPMs: ≤72 hours (early group) versus >72 hours (late group). RESULTS: The primary outcome was the proportion of patients with at least 1 agitation or delirium episode in the first 72 hours. Agitation and delirium were defined as at least 1 RASS assessment between +2 to +4 and a positive CAM-ICU assessment, respectively. A total of 300 patients were included, with 187 (62%) and 113 (38%) in the early and late groups, respectively. There was no difference in agitation or delirium (late 54 [48%] vs early 62 [33%]; adjusted odds ratio [aOR] = 1.5; 95% CI = 0.8-2.8; P = 0.193). Independent risk factors found to be associated with the primary outcome were restraints (aOR = 12.9; 95% CI = 6.9-24.0; P < 0.001) and benzodiazepines (BZDs; aOR = 2.0; 95% CI = 1.0-3.7; P = 0.038). CONCLUSIONS: After adjustment for baseline differences, there was no difference in agitation or delirium. Independent risk factors were restraint use and newly initiated BZDs.

Association Between Food Insecurity and Diet Quality Among Early Care and Education Providers in the Pennsylvania Head Start Program.

INTRODUCTION: Food insecurity affects dietary behaviors and diet quality in adults. This relationship is not widely studied among early care and education (ECE) providers, a unique population with important influences on children's dietary habits. Our study's objective was to explore how food insecurity affected diet quality and dietary behaviors among ECE providers. METHODS: We used baseline data from a cluster-randomized controlled trial (January 2019-December 2020) on 216 ECE providers under the Pennsylvania Head Start Association. We used radar plots to graph scores for the Healthy Eating Index 2015 and the Alternative Healthy Eating Index (AHEI) 2010 and fitted a multivariate regression model for diet quality measures, adjusting for covariates. RESULTS: Among the 216 participants, 31.5% were food insecure. ECE providers who were food insecure had a lower AHEI-2010 mean score (mean difference for food insecure vs food secure = -4.8; 95% CI, -7.8 to -1.7; P = .002). After adjusting for covariates, associations remained significant (mean difference = -3.9; 95% CI, -7.5 to -0.4; P = .03). Food insecure ECE providers were less likely to use nutrition labels (22.8% vs 39.1%; P = .046) and more likely to report cost as a perceived barrier to eating fruits and vegetables. CONCLUSION: We found a significant inverse association between food insecurity and the AHEI-2010 diet quality score among ECE providers after adjusting for covariates. More studies are needed to examine the effects of food insecurity on dietary behaviors of ECE providers and their response to nutrition education programs targeting their health.

Retrospective review of food insecurity screening in an outpatient stroke clinic using electronic and paper-based surveys.

Objective: To assess the feasibility of administrating an electronic and paper-based food insecurity screener among patients presenting to a stroke clinic during the study period. We aimed to ensure a consecutive sample for our retrospective analysis and evaluate the prevalence and characteristics of food insecurity in this population. Materials and methods: We conducted a retrospective review of patients with an initial telemedicine or in-person appointment to a stroke outpatient clinic between February 1 and July 31, 2021. Prior to their initial visit, patients were sent an electronic questionnaire to screen for food insecurity using the 2-item Hunger Vital Sign™ and to collect socio-demographic characteristics. Patients who were evaluated in-person were given a paper questionnaire if the electronic version was not completed upon clinic appointment. We collected data on patient demographics, screener completion rates, and the prevalence of food insecurity. The feasibility was evaluated by comparing the amount of missing data between electronic and paper-based screeners. Results: Among 406 adult stroke survivors, 365 (89.9 %) completed the food insecurity screener, with 234 (64.1 %) completing it electronically and 131 (35.9 %) by paper. Overall, 14.3 % of the stroke patients experienced food insecurity. A higher prevalence of food insecurity was observed among patients who completed paper-based compared to electronic questionnaires (21.4 % vs 10.2 %, p = 0.004). Hispanic patients were more likely to complete paper-based questionnaires (32.1 %) compared to electronic questionnaires (18.0 %, p = 0.011). Patients with a 12th grade education or less were more likely to complete paper-based (49.5 %) vs. electronic questionnaires (36.4 %, p = 0.029). Feasibility was evaluated by comparing the amount of missing data between the screener delivery modalities. A higher percentage of socio-demographic characteristics was missing in the paper-based questionnaires compared to electronic questionnaires (105.3 % vs. 14.11 %). Conclusions: Sample characteristics differ based on the mode of questionnaire delivery, suggesting that different screening modalities may be necessary to identify patients at the highest risk for food insecurity. Our study provides detailed insights into the feasibility of using electronic and paper-based screeners in a clinical setting, highlighting the importance of considering delivery methods in food insecurity assessments. It is important to note that the Spanish language electronic survey was only available during the last two months of the study, which may affect the findings regarding Hispanic patients' preference for paper surveys.

A cluster-randomized controlled trial to assess the impact of a nutrition intervention on dietary behaviors among early care and education providers: The Create Healthy Futures study.

Create Healthy Futures is a self-paced, web-based intervention on improving healthy eating behaviors among Early Care and Education (ECE) providers. We examined the impact of web-based Create Healthy Futures on diet quality measured by the Alternative Healthy Eating Index (AHEI) 2010, dietary behaviors, and related psychosocial and environmental factors among ECE providers. A cluster randomized controlled trial (CRCT) was implemented with baseline surveys administered from October 2019-January 2020, intervention implementation from April-May 2020, and post-intervention from May 2020-August 2020. Centered-based ECE programs under the Pennsylvania Head Start Association (n = 12) were recruited and randomized to intervention (n = 5) or comparison (n = 7) groups. A total of 186 ECE providers completed the post-intervention surveys (retention rate: 86.1%). At baseline, 31.5% of ECE providers were food insecure. Pre-to-post intervention demonstrated no significant within-or-between-group changes in the AHEI-2010 diet quality scores. ECE providers in the intervention group reported a significant decrease from baseline to post-intervention in the number of days eating out (aMD = -0.8, CI:-1.6, -0.1, P = 0.03). Process evaluation showed that 89.9% of the intervention group completed all online module, and 82.9% attended all of wellness session groups. Although the Create Healthy Futures intervention did not improve ECE providers' diet quality and dietary behaviors, it confirmed critical needs to provide health support to ECE providers. Future studies should employ strategies that improve access to healthy foods and nutrition education, and address social determinants of health such as food insecurity to improve diet quality and health in ECE provider population.

Spatial Patterns of COVID-19 Vaccination Coverage by Social Vulnerability Index and Designated COVID-19 Vaccine Sites in Texas.

Equitable access to the COVID-19 vaccine remains a public health priority. This study explores the association between ZIP Code−Tabulation Area level Social Vulnerability Indices (SVI) and COVID-19 vaccine coverage in Texas. A mixed-effects, multivariable, random-intercept negative binomial model was used to explore the association between ZIP Code−Tabulation Area level SVI and COVID-19 vaccination coverage stratified by the availability of a designated vaccine access site. Lower COVID-19 vaccine coverage was observed in ZIP codes with the highest overall SVIs (adjusted mean difference (aMD) = −13, 95% CI, −23.8 to −2.1, p < 0.01), socioeconomic characteristics theme (aMD = −16.6, 95% CI, −27.3 to −5.7, p = 0.01) and housing and transportation theme (aMD = −18.3, 95% CI, −29.6 to −7.1, p < 0.01) compared with the ZIP codes with the lowest SVI scores. The vaccine coverage was lower in ZIP Code−Tabulation Areas with higher median percentages of Hispanics (aMD = −3.3, 95% CI, −6.5 to −0.1, p = 0.04) and Blacks (aMD = −3.7, 95% CI, −6.4 to −1, p = 0.01). SVI negatively impacted COVID-19 vaccine coverage in Texas. Access to vaccine sites did not address disparities related to vaccine coverage among minority populations. These findings are relevant to guide the distribution of COVID-19 vaccines in regions with similar demographic and geospatial characteristics.

Design for a cluster randomized controlled trial to evaluate the effects of the CATCH Healthy Smiles school-based oral health promotion intervention among elementary school children.

Background: The top two oral diseases (tooth decay and gum disease) are preventable, yet dental caries is the most common childhood disease with 68% of children entering kindergarten having tooth decay. CATCH Healthy Smiles is a coordinated school health program to prevent cavities for students in kindergarten, 1st, and 2nd grade, and is based on the framework of Coordinated Approach to Child Health (CATCH), an evidence-based coordinated school health program. CATCH has undergone several cluster-randomized controlled trials (CRCT) demonstrating sustainable long-term effectiveness in incorporating the factors surrounding children, in improving eating and physical activity behaviors, and reductions in obesity prevalence among low-income, ethnically diverse children. The aim of this paper is to describe the design of the CATCH Healthy Smiles CRCT to determine the effectiveness of an oral health school-based behavioral intervention in reducing incidence of dental caries among children. Methods: In this CRCT, 30 schools serving low-income, ethnically-diverse children in greater Houston area are recruited and randomized into intervention and comparison groups. From which, 1020 kindergarten children (n = 510 children from 15 schools for each group) will be recruited and followed through 2nd grade. The intervention consists of four components (classroom curriculum, toothbrushing routine, family outreach, and schoolwide coordinated activities) will be implemented for three years in the intervention schools, whereas the control schools will be offered free trainings and materials to implement a sun safety curriculum in the meantime. Outcome evaluation will be conducted at four time points throughout the study period, each consists of three components: dental assessment, child anthropometric measures, and parent survey. The dental assessment will use International Caries Detection and Assessment System (ICDAS) to measures the primary outcome of this study: incidence of dental caries in primary teeth as measured at the tooth surface level (dfs). The parent self-report survey measures secondary outcomes of this study, such as oral health related behavioral and psychosocial factors. A modified crude caries increment (mCCI) will be used to calculate the primary outcome of the CATCH Healthy Smiles CRCT, and a two-tailed test of the null hypothesis will be conducted to evaluate the intervention effect, while considering between- and within-cluster variances through computing the weighted-average of the mCCI ratios by cluster. Conclusion: If found to be effective, a platform for scalability, sustainability and dissemination of CATCH already exists, and opens a new line of research in school oral health. Clinical trials identifier: At ClinicalTrials.gov - NCT04632667.

Fine Scale Replicable Risk Mapping in an Informal Settlement: A Case Study of Mathare, Nairobi.

Slums and informal settlements continue to pose considerable health challenges, mostly associated with the unavailability of basic amenities and proper waste management. While mapping where risks occur, such as the location of features associated with disease is obviously beneficial, the spatial data required is frequently not available, especially on a continuous basis. In this paper, we employ a robust, cost-effective, and efficient means of monitoring for these types of environments, using the Mathare SIS in Kenya as an illustration. We show how spatial videos can be used to capture microenvironments around homes or other key features such as toilets and water points, to show localized environmental risks such as standing water and mud. We also show the utility of this approach to capture longitudinal change. The objective of this paper is to illustrate how this method can map changes in the spatial variability of health risks in a challenging environment.

Examining Social Vulnerability and the Association With COVID-19 Incidence in Harris County, Texas.

Studies have investigated the association between social vulnerability and SARS-CoV-2 incidence. However, few studies have examined small geographic units such as census tracts, examined geographic regions with large numbers of Hispanic and Black populations, controlled for testing rates, and incorporated stay-at-home measures into their analyses. Understanding the relationship between social vulnerability and SARS-CoV-2 incidence is critical to understanding the interplay between social determinants and implementing risk mitigation guidelines to curtail the spread of infectious diseases. The objective of this study was to examine the relationship between CDC's Social Vulnerability Index (SVI) and SARS-CoV-2 incidence while controlling for testing rates and the proportion of those who stayed completely at home among 783 Harris County, Texas census tracts. SARS-CoV-2 incidence data were collected between May 15 and October 1, 2020. The SVI and its themes were the primary exposures. Median percent time at home was used as a covariate to measure the effect of staying at home on the association between social vulnerability and SARS-CoV-2 incidence. Data were analyzed using Kruskal Wallis and negative binomial regressions (NBR) controlling for testing rates and staying at home. Results showed that a unit increase in the SVI score and the SVI themes were associated with significant increases in SARS-CoV-2 incidence. The incidence risk ratio (IRR) was 1.090 (95% CI, 1.082, 1.098) for the overall SVI; 1.107 (95% CI, 1.098, 1.115) for minority status/language; 1.090 (95% CI, 1.083, 1.098) for socioeconomic; 1.060 (95% CI, 1.050, 1.071) for household composition/disability, and 1.057 (95% CI, 1.047, 1.066) for housing type/transportation. When controlling for stay-at-home, the association between SVI themes and SARS-CoV-2 incidence remained significant. In the NBR model that included all four SVI themes, only the socioeconomic and minority status/language themes remained significantly associated with SARS-CoV-2 incidence. Community-level infections were not explained by a communities' inability to stay at home. These findings suggest that community-level social vulnerability, such as socioeconomic status, language barriers, use of public transportation, and housing density may play a role in the risk of SARS-CoV-2 infection regardless of the ability of some communities to stay at home because of the need to work or other reasons.

Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality.

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic's onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient's encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death.

Spatial Video Health Risk Mapping in Informal Settlements: Correcting GPS Error.

Informal settlements pose a continuing health concern. While spatial methodologies have proven to be valuable tools to support health interventions, several factors limit their widespread use in these challenging environments. One such technology, spatial video, has been used for fine-scale contextualized mapping. In this paper, we address one of the limitations of the technique: the global positioning system (GPS) coordinate error. More specifically, we show how spatial video coordinate streams can be corrected and synced back to the original video to facilitate risk mapping. Past spatial video collections for the Mathare informal settlement of Kenya are used as an illustration as these data had been previously discarded because of excessive GPS error. This paper will describe the bespoke software that makes these corrections possible, and then will go on to investigate patterns in the coordinate error.