Community Water Fluoridation in Focus: A Comprehensive Look at Fluoridation Levels across America.

Objective: This study reports on the number and percentage of community water systems (CWSs) meeting fluoride concentration standards set by the U.S. Department of Health and Human Services (DHHS). The study also explored changes in the population exposed to optimally fluoridated water in these systems between 2006 and 2020. Methods: This study analyzed U.S. Centers for Disease Control and Prevention data from 2006 to 2020, tabulating state-specific CWS fluoridation rates, ranking them, and calculating the percent change. Results: In 2020, 72.7% of the US population received CWS water, with 62.9% of those individuals served by a CWS system meeting DHHS fluoridation standards. This compares to 69.2% receiving CWS water in 2006 and 74.6% in 2012. The overall change in those receiving fluoridated water was 1.4%, from 61.5% in 2006 to 62.9% in 2020. State-specific percentages ranged from 8.5% in Hawaii to 100% in Washington DC in 2020 (median: 76.4%). Conclusions: Although endorsed by the American Dental Association, the percentage of individuals receiving fluoridated water did not increase substantially from 2006 to 2020, indicating that there has not been much progress toward meeting the Healthy People 2030 goal that 77.1% of Americans receive water with enough fluoride to prevent tooth decay.

Relationships between ENDS-Related Familial Factors and Oral Health among Adolescents in the United States.

The influence of familial and social environments plays a significant role in Electronic Nicotine Delivery System (ENDS) use and may contribute to poor oral health among adolescents. This study utilized the Population Assessment of Tobacco and Health (PATH) database and included youths aged 12 to 17 years who reported no history of dental health issues at baseline. Adjusted odds ratios (AOR) were used to examine the association between END-related familial factors and oral health among adolescents in the United States, with statistical significance set at p < 0.05. The sample consisted of 3892 adolescents (weighted N = 22,689,793). Parents' extremely negative reaction towards ENDS when they found their children using ENDS (AOR = 0.309) was connected to a lower risk of oral health issues. The findings suggest that clinicians and policymakers need to consider the roles of these factors when developing strategies to improve oral health outcomes.

Health Disparities Associated with Females Reporting Human Papillomavirus Infection in the United States.

Few studies provide detailed findings about the health disparities of women being told by a physician whether they have ever had a human papillomavirus (HPV) infection. This study sought to characterize the prevalence and characteristics associated with women age 18 to 59 years in the United States who report being told they were infected with HPV. This study used data from the National Health and Nutritional Examination Survey. Descriptive statistics were computed on study variables and multiple logistic regression analyses were conducted to explore the association of the study variables with the outcome variable. Sampling weights were applied to produce national estimates of prevalence. The sample consisted of 1,669 females, representative of 75,107,170 females in the United States population. Around 11.5% reported being told that they had an HPV infection, of which 60.9% were White, and 82.9% were born in the United States. White women are 2.0 times more likely to be told they have HPV than Asian women and 2.8 times more likely than Black women. United States-born women were 2.1 times more likely told they had an HPV infection than those foreign born. This study found that among U.S. women, less than 12% reported ever having been told they have had an HPV infection. Epidemiologic findings suggest gaps between ever being told of a previous infection and being diagnosed with a clinically relevant HPV infection. Despite epidemiologic data indicating higher HPV prevalence among those less educated and women of color, these groups were less likely to report ever being told they have an HPV infection than White women, and those with a college degree suggesting communication gaps among these subgroups about HPV infection that might exist. Strategies to address potential gaps in communication among these subgroups can potentially reduce the economic burden and health disparities related to HPV infection.

Artificial intelligence in dentistry: Harnessing big data to predict oral cancer survival.

BACKGROUND: Oral cancer is the sixth most prevalent cancer worldwide. Public knowledge in oral cancer risk factors and survival is limited. AIM: To come up with machine learning (ML) algorithms to predict the length of survival for individuals diagnosed with oral cancer, and to explore the most important factors that were responsible for shortening or lengthening oral cancer survival. METHODS: We used the Surveillance, Epidemiology, and End Results database from the years 1975 to 2016 that consisted of a total of 257880 cases and 94 variables. Four ML techniques in the area of artificial intelligence were applied for model training and validation. Model accuracy was evaluated using mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), R 2 and adjusted R 2. RESULTS: The most important factors predictive of oral cancer survival time were age at diagnosis, primary cancer site, tumor size and year of diagnosis. Year of diagnosis referred to the year when the tumor was first diagnosed, implying that individuals with tumors that were diagnosed in the modern era tend to have longer survival than those diagnosed in the past. The extreme gradient boosting ML algorithms showed the best performance, with the MAE equaled to 13.55, MSE 486.55 and RMSE 22.06. CONCLUSION: Using artificial intelligence, we developed a tool that can be used for oral cancer survival prediction and for medical-decision making. The finding relating to the year of diagnosis represented an important new discovery in the literature. The results of this study have implications for cancer prevention and education for the public.

Exploring the Intersection between Social Determinants of Health and Unmet Dental Care Needs Using Deep Learning.

The goals of this study were to develop a risk prediction model in unmet dental care needs and to explore the intersection between social determinants of health and unmet dental care needs in the United States. Data from the 2016 Medical Expenditure Panel Survey were used for this study. A chi-squared test was used to examine the difference in social determinants of health between those with and without unmet dental needs. Machine learning was used to determine top predictors of unmet dental care needs and to build a risk prediction model to identify those with unmet dental care needs. Age was the most important predictor of unmet dental care needs. Other important predictors included income, family size, educational level, unmet medical needs, and emergency room visit charges. The risk prediction model of unmet dental care needs attained an accuracy of 82.6%, sensitivity of 77.8%, specificity of 87.4%, precision of 82.9%, and area under the curve of 0.918. Social determinants of health have a strong relationship with unmet dental care needs. The application of deep learning in artificial intelligence represents a significant innovation in dentistry and enables a major advancement in our understanding of unmet dental care needs on an individual level that has never been done before. This study presents promising findings and the results are expected to be useful in risk assessment of unmet dental care needs and can guide targeted intervention in the general population of the United States.

Social Network Analysis of COVID-19 Sentiments: Application of Artificial Intelligence.

BACKGROUND: The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic. OBJECTIVE: The aim of this study is to analyze discussions on Twitter related to COVID-19 and to investigate the sentiments toward COVID-19. METHODS: This study applied machine learning methods in the field of artificial intelligence to analyze data collected from Twitter. Using tweets originating exclusively in the United States and written in English during the 1-month period from March 20 to April 19, 2020, the study examined COVID-19-related discussions. Social network and sentiment analyses were also conducted to determine the social network of dominant topics and whether the tweets expressed positive, neutral, or negative sentiments. Geographic analysis of the tweets was also conducted. RESULTS: There were a total of 14,180,603 likes, 863,411 replies, 3,087,812 retweets, and 641,381 mentions in tweets during the study timeframe. Out of 902,138 tweets analyzed, sentiment analysis classified 434,254 (48.2%) tweets as having a positive sentiment, 187,042 (20.7%) as neutral, and 280,842 (31.1%) as negative. The study identified 5 dominant themes among COVID-19-related tweets: health care environment, emotional support, business economy, social change, and psychological stress. Alaska, Wyoming, New Mexico, Pennsylvania, and Florida were the states expressing the most negative sentiment while Vermont, North Dakota, Utah, Colorado, Tennessee, and North Carolina conveyed the most positive sentiment. CONCLUSIONS: This study identified 5 prevalent themes of COVID-19 discussion with sentiments ranging from positive to negative. These themes and sentiments can clarify the public's response to COVID-19 and help officials navigate the pandemic.

Health and dental care expenditures in the United States from 1996 to 2016.

INTRODUCTION: As total health and dental care expenditures in the United States continue to rise, healthcare disparities for low to middle-income Americans creates an imperative to analyze existing expenditures. This study examined health and dental care expenditures in the United States from 1996 to 2016 and explored trends in spending across various population subgroups. METHODS: Using data collected by the Medical Expenditure Panel Survey, this study examined health and dental care expenditures in the United States from 1996 to 2016. Trends in spending were displayed graphically and spending across subgroups examined. All expenditures were adjusted for inflation or deflation to the 2016 dollar. RESULTS: Both total health and dental expenditures increased between 1996 and 2016 with total healthcare expenditures increasing from $838.33 billion in 1996 to $1.62 trillion in 2016, a 1.9-fold increase. Despite an overall increase, total expenditures slowed between 2004 and 2012 with the exception of the older adult population. Over the study period, expenditures increased across all groups with the greatest increases seen in older adult health and dental care. The per capita geriatric dental care expenditure increased 59% while the per capita geriatric healthcare expenditure increased 50% across the two decades. For the overall US population, the per capita dental care expenditure increased 27% while the per capita healthcare expenditure increased 60% over the two decades. All groups except the uninsured experienced increased dental care expenditure over the study period. CONCLUSIONS: Healthcare spending is not inherently bad since it brings benefits while exacting costs. Our findings indicate that while there were increases in both health and dental care expenditures from 1996 to 2016, these increases were non-uniform both across population subgroups and time. Further research to understand these trends in detail will be helpful to develop strategies to address health and dental care disparities and to maximize resource utilization.

Neonatal invasive Streptococcus gallolyticus subsp. pasteurianus infection with delayed central nervous system complications.

Group D streptococci are known to cause newborn septicemia and meningitis, but the Streptococcus bovis group strains rarely cause serious neonatal infections in Korea. Central nervous system (CNS) complications of neonatal S. bovis group infection have rarely been reported. In adults, S. bovis group strains cause bacteremia and endocarditis, and are associated with gastrointestinal malignancy. However, only a few studies have reported meningitis and septicemia in infants. Here, we describe a case of bacteremia and meningitis due to Streptococcus gallolyticus subsp. pasteurianus with a delayed CNS complication in an infant. A 28-day-old male infant was admitted to the hospital with a 1-day history of fever. Cultures of blood, cerebrospinal fluid, and urine showed the presence of S. bovis group strain-S. gallolyticus subsp. pasteurianus. He was discharged after 21 days of intravenous ampicillin and cefotaxime administration. Two weeks later, he was readmitted with a fever and short episodes of tonic-clonic movements. Brain magnetic resonance imaging showed marked bilateral frontal subdural effusion. He was discharged after 31 days of antibiotic therapy, and no neurological sequelae were observed at the 9-month follow-up. In conclusion, we present a rare case of neonatal S. gallolyticus subsp. pasteurianus infection causing urinary tract infection, septicemia, meningitis, and delayed CNS complications. This case emphasizes the need for physicians to be aware of S. bovis infection in infants.

Ten years of experience in the prevention of mother-to-child human immunodeficiency virus transmission in a university teaching hospital.

PURPOSE: Administration of antiretroviral drugs to mothers and infants significantly decreases mother-to-child human immunodeficiency virus (HIV) transmission; cesarean sections and discouraging breastfeeding further decreases this risk. The present study confirmed the HIV status of babies born to mothers infected with HIV and describes the characteristics of babies and mothers who received preventive treatment. METHODS: This study retrospectively analyzed medical records of nine infants and their mothers positive for HIV who gave birth at Korea University Ansan Hospital, between June 1, 2003, and May 31, 2013. Maternal parameters, including HIV diagnosis date, CD4+ count, and HIV ribonucleic acid (RNA) copy number, were analyzed. Infant growth and development, HIV RNA copy number, and HIV antigen/antibody test results were analyzed. RESULTS: Eight HIV-positive mothers delivered nine babies; all the infants received antiretroviral therapy. Three (37.5%) and five mothers (62.5%) were administered single- and multidrug therapy, respectively. Intravenous zidovudine was administered to four infants (50%) at birth. Breastfeeding was discouraged for all the infants. All the infants were negative for HIV, although two were lost to follow-up. Third trimester maternal viral copy numbers were less than 1,000 copies/mL with a median CD4+ count of 325/µL (92-729/µL). Among the nine infants, two were preterm (22.2%) and three had low birth weights (33.3%). CONCLUSION: This study concludes that prophylactic antiretroviral therapy, scheduled cesarean section, and prohibition of breastfeeding considerably decrease mother-to-child HIV transmission. Because the number of infants infected via mother-to-child transmission may be increasing, studies in additional regions using more variables are necessary.

Estrogen therapy for experimental intracerebral hemorrhage in rats.

OBJECT: The aims of this study were to determine the following: whether there are sex differences in intracerebral hemorrhage (ICH) induced brain injury in rats, whether delayed administration of 17beta-estradiol can reduce ICH-induced brain damage, and whether these effects are estrogen receptor (ER)-dependent. METHODS: Male and female Sprague-Dawley rats received an infusion of 100 microl autologous whole blood into the right basal ganglia. Twenty-four hours later the rats were killed. The effects of 17beta-estradiol on ICH-induced brain injury were examined by measuring brain edema and neurological deficits. Both ER-alpha and hemeoxygenase (HO)-1 were investigated through Western blot and immunohistochemical analysis. Brain edema was significantly less severe in female compared with that in male rats. The ER antagonist ICI 182,780 exacerbated ICH-induced brain edema in female but not in male rats, indicating that ER-alpha activation during ICH is protective in female rats. Administration of exogenous 17beta-estradiol in male, but not in female, rats significantly attenuated brain edema, neurological deficits, and ICH-induced changes in HO-1 when given 2 hours after hemorrhage. The effects of exogenous 17beta-estradiol occurred through an ER-independent mechanism. CONCLUSIONS: Results in this study indicate that 17beta-estradiol could be a potential therapeutic agent for ICH.

Holo-transferrin and thrombin can interact to cause brain damage.

BACKGROUND AND PURPOSE: Previous studies have suggested that delayed release of hemoglobin degradation products, particularly iron, is involved in intracerebral hemorrhage (ICH)-induced brain injury. However, a recent study found evidence of iron-induced brain injury soon after ICH. This study, therefore, examined whether another iron-containing component of blood, holo-transferrin (holo-Tf), might also induce brain injury either alone or in combination with thrombin, another factor involved in early ICH-induced brain injury. METHODS: Male Sprague-Dawley rats received an intracerebral infusion of holo-Tf, apo (noniron-loaded)-Tf, thrombin, or a combination of Tf with thrombin into the right basal ganglia. The rats were euthanized 24 hours later for measurement of brain edema and assessment of DNA damage (single- and double-strand breaks and 8-hydroxyl-2'-deoxyguanosine immunohistochemistry). Iron distribution was examined histochemically. RESULTS: Holo-Tf, apo-Tf, and the dose of thrombin used (1 U) all failed to induce brain edema when administered alone. However, the combination of holo-Tf with thrombin (but not apo-Tf with thrombin) caused brain edema, DNA damage, and intracellular iron accumulation in the ipsilateral basal ganglia. CONCLUSIONS: These results suggest that in addition to hemoglobin-bound iron, Tf-bound iron may contribute to ICH-induced brain injury and that thrombin may contribute to the latter by facilitating cellular iron uptake.