Practice and attitude differences in physician cigarette use: A study of prevalence, physicians' role, and smoking policy awareness in Dubai, UAE

The use of tobacco products ruins the health of millions of people around the world. On average, tobacco users die nearly seven years earlier than non-tobacco users. n1 Cigarette smoking is a particular concern in the developing countries of the Middle East and Gulf Cooperation Council (GCC) region where smoking prevalence is expected to increase. This is due to the tobacco industry's vigorous commercial and marketing activities. n3 Smoking prevalence among physicians is considered to be an effective indicator of a society's readiness to identify the smoking epidemic and its related health diseases. n4 There is a lack of detailed data on the smoking prevalence among healthcare professionals, particularly physicians, in the United Arab Emirates (UAE). This cross sectional study is the first to address smoking practices among physicians working at the Department of Health and Medical Services (DOHMS); in Dubai, UAE. ^ This study describes the cigarette smoking prevalence among DOHMS Physicians, physician attitudes towards tobacco use and tobacco bans; physician attitudes towards smoking cessation techniques (among smokers and non-smokers); and physician awareness of official anti-smoking policies. Data for the study was collected through the use of an adapted WHO standardized questionnaire, the Global Health Professionals Survey. The questionnaire was administered by the researcher to physicians (n=288) at their work place. Date was analyzed using the SPSS analytic software program. ^ Twelve percent of DOHMS physicians smoked cigarettes. Regardless of smoking status, the majority supported a tobacco ban in hospitals and public places, and a ban on tobacco advertising. There is a significant relationship between physician smoking status and discussing risks of tobacco use (p < 0.05). Non-smoking physicians reported spending more time with patients discussing hazards of smoking (p < 0.01). Non-smokers reported providing more counseling than their smoking colleagues. The majority of DOHMS physicians (63%) reported a lack of knowledge about 5As/ 5Rs. The majority of physicians also reported they are aware of hospital smoking policies that restrict smoking. Regardless of physician smoking status, DOHMS physicians are not very actively involved in smoking cessation activities. This cross sectional study is the first to address smoking programs, policies, and practices among physicians in Dubai, UAE. Findings support the need for increased physical smoking cessation training as well as the development of smoking cessation programs for tobacco control, and programs with a focus on physician participation in reducing tobacco and cigarette use among the general population.^

Survey analysis on dental infection control & occupational safety from India---1999 & 2010

The objective was to study knowledge, attitudes, practice (KAP) and needs regarding infection control measures using two cross-sectional surveys from 1999 and 2010 conducted in India. Both data collection instruments had only about 35 comparable variables in common. In 1999, there were 456 respondents (dentists) who completed a self-administered survey instrument compared to 272 respondents in 2010. Both the 1999 and 2010 samples were mutually independent with no overlap, had regional differences, and therefore, were not completely comparable for changes in KAP over time. While almost all respondents from both surveys felt that education in dental safety was needed and wanted mandatory dental safety curriculum in dental schools, severe inadequacies in dental safety knowledge, protection against immunizable diseases, and practice of universal precaution were noted. Data from the study demonstrated that there is a substantial opportunity to improve the knowledge, attitude and practice of dental infection control and occupational safety in India. Few respondents (27%) reported that the infectious disease status of a patient is always known and a significant number reported that they had the right to refuse care for patients of known infectious disease status. This indicates that Stigma in treating HIV/AIDS patients remains a concern, which in turn suggests that a stronger focus on educating dentists about dental safety and on stigma and infectious disease is needed. Information obtained from this study could be utilized for developing policies oriented towards increasing dental safety educational efforts, in both dental schools as curriculum, and for practicing dentists through professional updates or continuing dental education.^

Internet sex among non-gay identifying men who have sex with men

The aim of this study was to examine the role of the Internet in Internal Homonegativity (IH) among Non gay identifying men who have sex with men (NGI-MSM). This study at University of Texas School of Public Health (UTSPH) had a mixed method research design and consisted of men 18 years of age and older who were residents of the US and Canada. The data were collected using an online survey called 'Men's Sexual Health Survey' which was developed in collaboration with Boston University School of Public Health and Denver Public Health. These surveys were administered in English, which took 30-minutes to complete, and were placed on gay oriented websites and chat rooms. 141 participants were presented with the module relating to IH. A Principal Component Analysis with varimax rotation on the nine questions that asked the participants about their feelings about gay men produced three factors of IH identified as (1) public identification as gay; (2) perception of stigma associated with being gay; and (3) social comfort with gay men. The factors significantly correlated with age, grade completed in school, income, openness about being gay and socializing with gay people, meeting partners online, dating on the Internet, attitude toward condom usage, alcohol and drug use before sex and having unprotected sex with Internet partners. These findings point toward the role of the Internet in determining IH and sexual behavior. Despite the risks, the Internet's popularity and outreach in NGI-MSM makes it an effective medium to spread public health programs.^

ATTITUDES AND PRACTICES OF GENETIC COUNSELORS IN PROVIDING PREDICTIVE TESTING TO MINORS AT RISK FOR LI-FRAUMENI SYNDROME

Li- Fraumeni Syndrome (LFS) is a rare autosomal dominant hereditary cancer syndrome caused by mutations in the TP53 gene that predisposes individuals to a wide variety of cancers, including breast cancer, soft tissue sarcomas, osteosarcomas, brain tumors, and adrenocortical carcinomas. Individuals found to carry germline mutations in TP53 have a 90% lifetime cancer risk, with a 20% chance to develop cancer under the age of 20. Despite the significant risk of childhood cancer, predictive testing for unaffected minors at risk for LFS historically has not been recommended, largely due to the lack of available and effective screening for the types of cancers involved. A recently developed screening protocol suggests an advantage to identifying and screening children at risk for LFS and we therefore hypothesized that this alongside with the availability of new screening modalities may substantiate a shift in recommendations for predictive genetic testing in minors at risk for LFS. We aimed to describe current screening recommendations that genetic counselors provide to this population as well as explore factors that may have influenced genetic counselors attitude and practice in regards to this issue. An online survey was emailed to members of the National Society of Genetic Counselors (NSGC) and the Canadian Association of Genetic Counsellors (CAGC). Of an estimated 1000 eligible participants, 172 completed surveys that were analyzed. Genetic counselors in this study were more likely to support predictive genetic testing for this population as the minor aged (p

Booster Breaks in the workplace: Effects on employee stress

The current study examined the effects of a 15-minute daily physical activity break on the stress levels of white collar employees. An innovative group physical activity program, the Booster Break, was implemented in two worksites, both located in a large metropolitan area. One hundred sixteen participants were randomly assigned to one of three conditions; 43 participants were assigned to the Booster Break condition, 40 participants were assigned to an individual, computer-based physical activity condition, and 32 were assigned to a no-physical activity control condition. Self-report and objective measures were taken at baseline and after the completion of the intervention. There were no significant differences among conditions in perceived stress or blood pressure after the intervention. However, the data showed trends in the direction predicted with a decrease in perceived stress among Booster Break (change in perceived stress = -0.1) and computer prompt participants (change in perceived stress = -0.2) and an increase in perceived stress among the control group (change in perceived stress = 0.2). More research is recommended to fully understand the effects of worksite physical activity on stress.^

Predicting smokeless tobacco cessation in a blue -collar population

The use of smokeless tobacco products is undergoing an alarming resurgence in the United States. Several national surveys have reported a higher prevalence of use among those employed in blue-collar occupations. National objectives now target this group for health promotion programs which reduce the health risks associated with tobacco use.^ Drawn from a larger data set measuring health behaviors, this cross-sectional study tested the applicability of two related theories, the Theory of Reasoned Action (TRA) and the Theory of Planned Behavior (TPB), to smokeless tobacco (SLT) cessation in a blue-collar population of gas pipeline workers. In order to understand the determinants of SLT cessation, measures were obtained of demographic and normative characteristics of the population and specific constructs. Attitude toward the act of quitting (AACT) and subjective norm (SN) are constructs common to both models, perceived behavioral control (PBC) is unique to the TPB, and the number of past quit attempts is not contained in either model. In addition, a self-reported measure was taken of SLT use at two-month follow-up.^ The study population was comprised of all male SLT users who were field employees in a large gas pipeline company with gas compressor stations extending from Texas to the Canadian border. At baseline, 199 employees responded to the SLT portion of the survey, 118 completed some portion of the two-month follow-up, and 101 could be matched across time.^ As hypothesized, significant correlations were found between constructs antecedent to AACT and SN, although crossover effects occurred. Significant differences were found between SLT cessation intenders and non-intenders with regard to their personal and normative beliefs about quitting as well as their outcome expectancies and motivation to comply with others' beliefs. These differences occurred in the expected direction, with the mean intender score consistently higher than that of the non-intender.^ Contrary to hypothesis, AACT predicted intention to quit but SN did not. However, confirmatory of the TPB, PBC, operationalized as self-efficacy, independently contributed to the prediction of intention. Statistically significant relationships were not found between intention, perceived behavioral control, their interactive effects, and use behavior at two-month follow-up. The introduction of number of quit attempts into the logistic regression model resulted in insignificant findings for independent and interactive effects.^ The findings from this study are discussed in relation to their implications for program development and practice, especially within the worksite. In order to confirm and extend the findings of this investigation, recommendations for future research are also discussed. ^

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) and Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic (2004-2012)

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2007

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2008

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2005

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Clupea harengus (Norwegian spring spawning herring) from acoustic and trawl surveys in the North-East Atlantic in May 2006

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Spatially explicit estimates of length and biomass of Micromesistius poutassou (Blue Whiting) from acoustic and trawl surveys in the North-East Atlantic in May 2011

Acoustic estimates of herring and blue whiting abundance were obtained during the surveys using the Simrad ER60 scientific echosounder. The allocation of NASC-values to herring, blue whiting and other acoustic targets were based on the composition of the trawl catches and the appearance of echo recordings. To estimate the abundance, the allocated NASC -values were averaged for ICES-squares (0.5° latitude by 1° longitude). For each statistical square, the unit area density of fish (rA) in number per square nautical mile (N*nm-2) was calculated using standard equations (Foote et al., 1987; Toresen et al., 1998). To estimate the total abundance of fish, the unit area abundance for each statistical square was multiplied by the number of square nautical miles in each statistical square and then summed for all the statistical squares within defined subareas and over the total area. Biomass estimation was calculated by multiplying abundance in numbers by the average weight of the fish in each statistical square then summing all squares within defined subareas and over the total area. The Norwegian BEAM soft-ware (Totland and Godø 2001) was used to make estimates of total biomass.

Seagrass and associated benthic community data derived from field surveys at Low Isles, Great Barrier Reef, conducted July-August, 1997

The distribution of seagrass and associated benthic communities on the reef and lagoon of Low Isles, Great Barrier Reef, was mapped between the 29 July and 29 August 1997. For this survey, observers walked or free-dived at survey points positioned approximately 50 m apart along a series of transects. Visual estimates of above-ground seagrass biomass and % cover of each benthos and substrate type were recorded at each survey point. A differential handheld global positioning system (GPS) was used to locate each survey point (accuracy ±3m). A total of 349 benthic survey points were examined. To assist with mapping meadow/habitat type boundaries, an additional 177 field points were assessed and a georeferenced 1:12,000 aerial photograph (26th August 1997) was used as a secondary source of information. Bathymetric data (elevation below Mean Sea Level) measured at each point assessed and from Ellison (1997) supplemented information used to determine boundaries, particularly in the subtidal lagoon. 127.8 ±29.6 hectares was mapped. Seagrass and associated benthic community data was derived by haphazardly placing 3 quadrats (0.25m**2) at each survey point. Seagrass above ground biomass (standing crop, grams dry weight (g DW m**-2)) was determined within each quadrat using a non-destructive visual estimates of biomass technique and the seagrass species present identified. In addition, the cover of all benthos was measured within each of the 3 quadrats using a systematic 5 point method. For each quadrat, frequency of occurrence for each benthic category was converted to a percentage of the total number of points (5 per quadrat). Data are presented as the average of the 3 quadrats at each point. Polygons of discrete seagrass meadow/habitat type boundaries were created using the on-screen digitising functions of ArcGIS (ESRI Inc.), differentiated on the basis of colour, texture, and the geomorphic and geographical context. The resulting seagrass and benthic cover data of each survey point and for each seagrass meadow/habitat type was linked to GPS coordinates, saved as an ArcMap point and polygon shapefile, respectively, and projected to Universal Transverse Mercator WGS84 Zone 55 South.