The COVID-19 Pandemic and Dental Professionals’ Infection Risk Perception: An International Survey

A global survey among dentists was used to identify the various impacts of the COVID-19 pandemic on this professional group. Special attention was given to perception and assessment of infection risk. From May to August 2020, the questionnaire was delivered in 36 countries by respective research groups and was completed by 52,491 dental professionals. The survey was designed as a cross-sectional survey based on a previously standardized questionnaire. This study focuses on the part of the questionnaire that deals with the perception of the infection risk of COVID-19 by dentists and their patients. A logistic regression model was used, which consisted of four Likert items as response options and the additional self-reported routine or emergency treatment as the dependent variable. Analysis by continent found that European and Asian dentists were particularly likely to be infected at work (OR = 1.45 95%CI = 1.02/1.84 and OR = 2.68, 95%CI = 1.45/3.22, respectively), while it was likely that Australian dentists did not feel particularly at risk due to low infection rates. Three quarters of Americans treated only emergencies during this survey period, while Europeans (64.71%) and Asians (66.67%) provided mostly routine care. This could affect the Europeans’ confidence that they would not be able to protect themselves from infections in the long-term. The COVID-19 pandemic and its impact on dental professionals’ infection risk perception is determined by the geographical origin of dentists. This study shows that, especially in high-incidence countries, infection risk perception was higher when dentists tried to provide routine dental procedures to their patients. Dental professionals can offer themselves and their patients good protection by maintaining high standards of hygiene. However, their concerns should be taken seriously and the dental professionals’ group that is of great importance for oral health care and prevention, should not be neglected in the future, even in the event of emerging pandemics

Study Protocol for an Online Questionnaire Survey on Symptoms/Signs, Protective Measures, Level of Awareness and Perception Regarding COVID-19 Outbreak among Dentists. A Global Survey

The Centres for Disease Control and Prevention and the World Health Organization have developed preparedness and prevention checklists for healthcare professionals regarding the containment of COVID-19. The aim of the present protocol is to evaluate the impact of the COVID-19 outbreak among dentists in different countries where various prevalence of the epidemic has been reported. Several research groups around the world were contacted by the central management team. The online anonymous survey will be conducted on a convenience sample of dentists working both in national health systems and in private or public clinics. In each country/area, a high (~5–20%) proportion of dentists working there will be invited to participate. The questionnaire, developed and standardized previously in Italy, has four domains: (1) personal data; (2) symptoms/signs relative to COVID-19; (3) working conditions and PPE (personal protective equipment) adopted after the infection’s outbreak; (4) knowledge and self-perceived risk of infection. The methodology of this international survey will include translation, pilot testing, and semantic adjustment of the questionnaire. The data will be entered on an Excel spreadsheet and quality checked. Completely anonymous data analyses will be performed by the central management team. This survey will give an insight into the dental profession during COVID-19 pandemic globally

The COVID-19 pandemic and its global effects on dental practice : An International survey

Objectives: A multicentre survey was designed to evaluate the impact of COVID-19 outbreak on dental practice worldwide, estimate the COVID-19 related symptoms/signs, work attitudes and behaviour and the routine use of protective measures and Personal Protective Equipment (PPE). Methods: A global survey using a standardized questionnaire with research groups from 36 countries was designed. The questionnaire was developed and pretested during April 2020 and contained three domains: 1) Personal data; 2) COVID-19 positive rate and symptoms/signs presumably related to the coronavirus; 3) Working conditions and PPE adopted after the outbreak. Countries' data were grouped by the Country Positive Rate (CPR) during the survey period and by Gross-National-Income per capita. An ordinal multinomial logistic regression model was carried out with COVID-19 self-reported rate referred by dental professionals as dependent variable to assess the association with questionnaire items. Results: A total of 52,491 questionnaires were returned with a male/female ratio of 0.63. Out of the total respondents, 7,859 dental professionals (15%) reported symptoms/signs compatible with COVID-19. More than half of the sample (n = 27,818; 53%) stated to use FFP2/N95 masks, while 21,558 (41.07%) used eye protection. In the bivariate analysis, CPR and N95/FFP2 were significantly associated (OR = 1.80 95% =5.20 95% 95% CI = 1.60/2.82 and OR CI = 1.44/18.80, respectively), while Gross-National-Income was not statistically associated with CPR (OR = 1.09 CI = 0.97/1.60). The same significant associations were observed in the multivariate analysis. Conclusions: Oral health service provision has not been significantly affected by COVID-19, although access to routine dental care was reduced due to country-specific temporary lockdown periods. While the dental profession has been identified at high-risk, the reported rates of COVID-19 for dental professionals were not significantly different to those reported for the general population in each country. These findings may help to better plan oral health care for future pandemic events

Contributions of mean and shape of blood pressure distribution to worldwide trends and variations in raised blood pressure: A pooled analysis of 1018 population-based measurement studies with 88.6 million participants

© The Author(s) 2018. Background: Change in the prevalence of raised blood pressure could be due to both shifts in the entire distribution of blood pressure (representing the combined effects of public health interventions and secular trends) and changes in its high-blood-pressure tail (representing successful clinical interventions to control blood pressure in the hypertensive population). Our aim was to quantify the contributions of these two phenomena to the worldwide trends in the prevalence of raised blood pressure. Methods: We pooled 1018 population-based studies with blood pressure measurements on 88.6 million participants from 1985 to 2016. We first calculated mean systolic blood pressure (SBP), mean diastolic blood pressure (DBP) and prevalence of raised blood pressure by sex and 10-year age group from 20-29 years to 70-79 years in each study, taking into account complex survey design and survey sample weights, where relevant. We used a linear mixed effect model to quantify the association between (probittransformed) prevalence of raised blood pressure and age-group- and sex-specific mean blood pressure. We calculated the contributions of change in mean SBP and DBP, and of change in the prevalence-mean association, to the change in prevalence of raised blood pressure. Results: In 2005-16, at the same level of population mean SBP and DBP, men and women in South Asia and in Central Asia, the Middle East and North Africa would have the highest prevalence of raised blood pressure, and men and women in the highincome Asia Pacific and high-income Western regions would have the lowest. In most region-sex-age groups where the prevalence of raised blood pressure declined, one half or more of the decline was due to the decline in mean blood pressure. Where prevalence of raised blood pressure has increased, the change was entirely driven by increasing mean blood pressure, offset partly by the change in the prevalence-mean association. Conclusions: Change in mean blood pressure is the main driver of the worldwide change in the prevalence of raised blood pressure, but change in the high-blood-pressure tail of the distribution has also contributed to the change in prevalence, especially in older age groups

Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

Measurement of the J/ψ pair production cross-section in pp collisions at s=13 \sqrt{s}=13 TeV

The production cross-section of J/ψ pairs is measured using a data sample of pp collisions collected by the LHCb experiment at a centre-of-mass energy of $\sqrt{s}=13$ TeV, corresponding to an integrated luminosity of 279 ±11 pb$^{−1}$. The measurement is performed for J/ψ mesons with a transverse momentum of less than 10 GeV/c in the rapidity range 2.0 < y < 4.5. The production cross-section is measured to be 15.2 ± 1.0 ± 0.9 nb. The first uncertainty is statistical, and the second is systematic. The differential cross-sections as functions of several kinematic variables of the J/ψ pair are measured and compared to theoretical predictions.The production cross-section of $J/\psi$ pairs is measured using a data sample of $pp$ collisions collected by the LHCb experiment at a centre-of-mass energy of $\sqrt{s} = 13 \,{\mathrm{TeV}}$, corresponding to an integrated luminosity of $279 \pm 11 \,{\mathrm{pb^{-1}}}$. The measurement is performed for $J/\psi$ mesons with a transverse momentum of less than $10 \,{\mathrm{GeV}}/c$ in the rapidity range $2.0<y<4.5$. The production cross-section is measured to be $15.2 \pm 1.0 \pm 0.9 \,{\mathrm{nb}}$. The first uncertainty is statistical, and the second is systematic. The differential cross-sections as functions of several kinematic variables of the $J/\psi$ pair are measured and compared to theoretical predictions

Measurement of the B0s→μ+μ− Branching Fraction and Effective Lifetime and Search for B0→μ+μ− Decays

A search for the rare decays Bs0→μ+μ- and B0→μ+μ- is performed at the LHCb experiment using data collected in pp collisions corresponding to a total integrated luminosity of 4.4  fb-1. An excess of Bs0→μ+μ- decays is observed with a significance of 7.8 standard deviations, representing the first observation of this decay in a single experiment. The branching fraction is measured to be B(Bs0→μ+μ-)=(3.0±0.6-0.2+0.3)×10-9, where the first uncertainty is statistical and the second systematic. The first measurement of the Bs0→μ+μ- effective lifetime, τ(Bs0→μ+μ-)=2.04±0.44±0.05  ps, is reported. No significant excess of B0→μ+μ- decays is found, and a 95% confidence level upper limit, B(B0→μ+μ-)<3.4×10-10, is determined. All results are in agreement with the standard model expectations.A search for the rare decays $B^0_s\to\mu^+\mu^-$ and $B^0\to\mu^+\mu^-$ is performed at the LHCb experiment using data collected in $pp$ collisions corresponding to a total integrated luminosity of 4.4 fb$^{-1}$. An excess of $B^0_s\to\mu^+\mu^-$ decays is observed with a significance of 7.8 standard deviations, representing the first observation of this decay in a single experiment. The branching fraction is measured to be ${\cal B}(B^0_s\to\mu^+\mu^-)=\left(3.0\pm 0.6^{+0.3}_{-0.2}\right)\times 10^{-9}$, where the first uncertainty is statistical and the second systematic. The first measurement of the $B^0_s\to\mu^+\mu^-$ effective lifetime, $\tau(B^0_s\to\mu^+\mu^-)=2.04\pm 0.44\pm 0.05$ ps, is reported. No significant excess of $B^0\to\mu^+\mu^-$ decays is found and a 95 % confidence level upper limit, ${\cal B}(B^0\to\mu^+\mu^-)<3.4\times 10^{-10}$, is determined. All results are in agreement with the Standard Model expectations

Measurements of prompt charm production cross-sections in pp collisions at s=5 \sqrt{s}=5 TeV

Production cross-sections of prompt charm mesons are measured using data from $pp$ collisions at the LHC at a centre-of-mass energy of $5\,$TeV. The data sample corresponds to an integrated luminosity of $8.60\pm0.33\,$pb$^{-1}$ collected by the LHCb experiment. The production cross-sections of $D^0$, $D^+$, $D_s^+$, and $D^{*+}$ mesons are measured in bins of charm meson transverse momentum, $p_{\text{T}}$, and rapidity, $y$. They cover the rapidity range $2.0 < y < 4.5$ and transverse momentum ranges $0 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D^0$ and $D^+$ and $1 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D_s^+$ and $D^{*+}$ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of $1 < p_{\text{T}} < 8\, \text{GeV}/c$ are determined to be \begin{equation*} \sigma(pp\rightarrow D^0 X) = 1190 \pm 3 \pm 64\,\mu\text{b} \end{equation*} \begin{equation*} \sigma(pp\rightarrow D^+ X) = 456 \pm 3 \pm 34\,\mu\text{b} \end{equation*} \begin{equation*} \sigma(pp\rightarrow D_s^+ X) = 195 \pm 4 \pm 19\,\mu\text{b} \end{equation*} \begin{equation*} \sigma(pp\rightarrow D^{*+} X)= 467 \pm 6 \pm 40\,\mu\text{b} \end{equation*} where the uncertainties are statistical and systematic, respectively.Production cross-sections of prompt charm mesons are measured using data from pp collisions at the LHC at a centre-of-mass energy of 5 TeV. The data sample corresponds to an integrated luminosity of 8.60 ± 0.33 pb$^{−1}$ collected by the LHCb experiment. The production cross-sections of D$^{0}$, D$^{+}$, D$_{s}^{+}$ , and D$^{∗+}$ mesons are measured in bins of charm meson transverse momentum, p$_{T}$, and rapidity, y. They cover the rapidity range 2.0 < y < 4.5 and transverse momentum ranges 0 < p$_{T}$ < 10 GeV/c for D$^{0}$ and D$^{+}$ and 1 < p$_{T}$ < 10 GeV/c for D$_{s}^{+}$ and D$^{∗+}$ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of 1 < p$_{T}$ < 8 GeV/c are determined to be $\begin{array}{l}\sigma \left( pp\to {D}^0X\right)=1004\pm 3\pm 54\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}^{+}X\right)=402\pm 2\pm 30\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}_s^{+}X\right)=170\pm 4\pm 16\mu \mathrm{b},\\ {}\sigma \left( pp\to {D}^{\ast +}X\right)=421\pm 5\pm 36\mu \mathrm{b},\end{array}$ where the uncertainties are statistical and systematic, respectively.Production cross-sections of prompt charm mesons are measured using data from $pp$ collisions at the LHC at a centre-of-mass energy of $5\,$TeV. The data sample corresponds to an integrated luminosity of $8.60\pm0.33\,$pb$^{-1}$ collected by the LHCb experiment. The production cross-sections of $D^0$, $D^+$, $D_s^+$, and $D^{*+}$ mesons are measured in bins of charm meson transverse momentum, $p_{\text{T}}$, and rapidity, $y$. They cover the rapidity range $2.0<y<4.5$ and transverse momentum ranges $0 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D^0$ and $D^+$ and $1 < p_{\text{T}} < 10\, \text{GeV}/c$ for $D_s^+$ and $D^{*+}$ mesons. The inclusive cross-sections for the four mesons, including charge-conjugate states, within the range of $1 < p_{\text{T}} < 8\, \text{GeV}/c$ are determined to be \sigma(pp\rightarrow D^0 X) = 1004 \pm 3 \pm 54\,\mu\text{b} \sigma(pp\rightarrow D^+ X) = 402 \pm 2 \pm 30\,\mu\text{b} \sigma(pp\rightarrow D_s^+ X) = 170 \pm 4 \pm 16\,\mu\text{b} \sigma(pp\rightarrow D^{*+} X)= 421 \pm 5 \pm 36\,\mu\text{b} where the uncertainties are statistical and systematic, respectively