Erosive tooth wear and wedge-shaped defects in 1996 and 2006: cross- sectional surveys of Swiss army recruits.

The purpose of this study was to determine the prevalence and possible etiological factors of erosive tooth wear and wedge-shaped defects in Swiss Army recruits and compare the findings with those of an analogous study conducted in 1996. In 2006, 621 recruits between 18 and 25 years of age (1996: 417 recruits; ages 19 to 25) were examined for erosive tooth wear and wedge-shaped defects. Additional data was acquired using a questionnaire about personal details, education, dentitions subjective condition, oral hygiene, eating and drinking habits, medications used, and general medical problems. In 2006, 60.1% of those examined exhibited occlusal erosive tooth wear not involving the dentin (1996: 82.0%) and 23.0% involving the dentin (1996: 30.7%). Vestibular erosive tooth wear without dentin involvement was seen in 7.7% in 2006 vs. 14.4% in 1996. Vestibular erosive tooth wear with dentin involvement was rare in both years (0.5%). Oral erosive tooth wear lacking exposed dentin was also rare in those years, although more teeth were affected in 2006 (2.1%) than in 1996 (0.7%). The examinations in 2006 found one or more initial wedge-shaped lesions in 8.5% of the recruits, while 20.4% of the study participants exhibited such in 1996. In 1996, 53% consumed acidic foods and beverages more than 5 times/day; in 2006, 83.9% did so. In neither study did multivariate regression analyses show any significant correlations between occurrence and location of erosive tooth wear and wedge-shaped defects and various other parameters, e.g., eating and hygiene habits, or dentin hyper-sensitivity. Despite a significant increase in consumption of acidic products between 1996 and 2006, the latter study found both fewer erosive tooth wear and fewer wedge-shaped defects (i.e., fewer non-carious lesions.).

Does the use of mobile devices (tablets and smartphones) affect survey quality and choice behaviour in web surveys?

Web surveys are becoming increasingly popular in survey research including stated preference surveys. Compared with face-to-face, telephone and mail surveys, web surveys may contain a different and new source of measurement error and bias: the type of device that respondents use to answer the survey questions. This is the first study that tests whether the use of mobile devices, tablets or smartphones, affects survey characteristics and stated preferences in a web-based choice experiment. The web survey on expanding renewable energy production in Germany was carried out with 3182 respondents, of which 12% used a mobile device. Propensity score matching is used to account for selection bias in the use of mobile devices for survey completion. We find that mobile device users spent more time than desktop/laptop users to answer the survey. Yet, desktop/laptop users and mobile device users do not differ in acquiescence tendency as an indicator of extreme response patterns. For mobile device users only, we find a negative correlation between screen size and interview length and a positive correlation between screen size and acquiescence tendency. In the choice experiment data, we do not find significant differences in the tendency to choose the status quo option and scale between both subsamples. However, some of the estimates of implicit prices differ, albeit not in a unidirectional fashion. Model results for mobile device users indicate a U-shaped relationship between error variance and screen size. Together, the results suggest that using mobile devices is not detrimental to survey quality.

Training primary care physicians to offer their patients faecal occult blood testing and colonoscopy for colorectal cancer screening on an equal basis: a pilot intervention with before-after and parallel group surveys.

OBJECTIVES Primary care physicians (PCPs) should prescribe faecal immunochemical testing (FIT) or colonoscopy for colorectal cancer screening based on their patient's values and preferences. However, there are wide variations between PCPs in the screening method prescribed. The objective was to assess the impact of an educational intervention on PCPs' intent to offer FIT or colonoscopy on an equal basis. DESIGN Survey before and after training seminars, with a parallel comparison through a mailed survey to PCPs not attending the training seminars. SETTING All PCPs in the canton of Vaud, Switzerland. PARTICIPANTS Of 592 eligible PCPs, 133 (22%) attended a seminar and 106 (80%) filled both surveys. 109 (24%) PCPs who did not attend the seminars returned the mailed survey. INTERVENTION A 2 h-long interactive seminar targeting PCP knowledge, skills and attitudes regarding offering a choice of colorectal cancer (CRC) screening options. OUTCOME MEASURES The primary outcome was PCP intention of having their patients screened with FIT and colonoscopy in equal proportions (between 40% and 60% each). Secondary outcomes were the perceived role of PCPs in screening decisions (from paternalistic to informed decision-making) and correct answer to a clinical vignette. RESULTS Before the seminars, 8% of PCPs reported that they had equal proportions of their patients screened for CRC by FIT and colonoscopy; after the seminar, 33% foresaw having their patients screened in equal proportions (p<0.001). Among those not attending, there was no change (13% vs 14%, p=0.8). Of those attending, there was no change in their perceived role in screening decisions, while the proportion responding correctly to a clinical vignette increased (88-99%, p<0.001). CONCLUSIONS An interactive training seminar increased the proportion of physicians with the intention to prescribe FIT and colonoscopy in equal proportions.

Tobacco use and related psychosocial risk factors among youth in urban India: Assessment of Project MYTRI follow-up surveys

Project MYTRI (Mobilizing Youth for Tobacco-Related Initiatives in India) was a large 2-year randomized school-based trial with a goal to reduce and prevent tobacco use among students in 6th and 8th grades in Delhi and Chennai in India (n=32 schools). Baseline analyses in 2004 showed that 6th grade students reported more tobacco use than 8 th grade students, opposite of what is typically observed in developed countries like the US. The present study aims to study differences in tobacco use and psychosocial risk factors between the 6th grade cohort and 8th grade cohort, in a compliant sub-sample of control students that were present at all 3 surveys from 2004-06. Both in 2004 and 2005, 6th grade cohort reported significantly greater prevalence of ever use of all tobacco products (cigarettes, bidis, chewing tobacco, any tobacco). These significant differences in ever use of any tobacco between cohorts were maintained by gender, city and socioeconomic status. The 6th grade cohort also reported significantly greater prevalence of current use of tobacco products (cigarettes, chewing tobacco, any tobacco) in 2004. Similar findings were observed for psychosocial risk factors for tobacco use, where the 6th grade cohort scored higher risk than 8th grade cohort on scales for intentions to smoke or chew tobacco and susceptibility to smoke or chew tobacco in 2004 and 2005, and for knowledge of health effects of tobacco in all three years.^ The evidence of early initiation of tobacco use in our 6th grade cohort in India indicates the need to target prevention programs and other tobacco control measures from a younger age in this setting. With increasing proportions of total deaths and lost DALYs in India being attributable to chronic diseases, addressing tobacco use among younger cohorts is even more critical. Increase in tobacco use among youth is a cause for concern with respect to future burden of chronic disease and tobacco-related mortality in many developing countries. Similarly, epidemiological studies that aim to predict future death and disease burden due to tobacco should address the early age at initiation and increasing prevalence rates among younger populations. ^

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.

Benthos fauna in the North Sea from 2 surveys in 1986 and 1987

During two surveys in the North Sea, in summer 1986 and in winter 1987, larger epibenthos was collected with a 2 m beam trawl. The distributions of the species were checked for average linkage by means of the JACCARD-index cluster analysis. In summer two main clusters can be recognized. These are situated to the north and to the south of the Dogger Bank. In winter two main clusters may be recognized as well, but these clusters divide the North Sea into a western and an eastern part. We conclude, that these differences of epibenthos characteristics are correlated with seasonal changes in water body distributions.