861 resultados para Demographic surveys


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Aim To examine the association between the crack cocaine cessation and risky sexual behaviors. Design and setting Between June 2002 and March 2005, a sample of African-American residents of Houston, Texas who were using crack at the time of enrollment participated in a cohort study to evaluate per outreach interventions to reduce HIV risk behaviors. The sample for this study consisted of 351 women and men who completed structured surveys at baseline and at six months about socio-demographic characteristics, drug use, and sexual behaviors. Multivariate logistic regression was used to analyze the association between crack cessation and risky sexual behaviors at follow-up, while controlling for confounding characteristics. Measurements Crack cessation was defined as reporting no crack use in the 30 days prior to the follow-up interview. Possible associated factors included unprotected sex, having multiple sex partners, trading sex for money/drugs, crack use, and socio-demographic variables. Findings At the six-month follow-up interview, 21% of participants reported that they had not used crack in the previous 30 days. For women, crack cessation was significantly associated with having only one sex partner at follow-up; for men, crack cessation was significantly associated with being single, separated, or divorced at baseline, having only one sex partner at follow-up, and initiating protected sex by follow-up. Conclusion These findings support previous research indicating that crack use is associated with unprotected sex and multiple sexual partners, as men and women who ceased crack use were less likely to engage in these risky sexual behaviors. Findings demonstrate that treatment for crack use could have a meaningful effect on risky sexual behaviors and HIV/STI prevention.^

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Studies suggest that slim infants (low weight-for-height) experienced higher mortality rates than average or high weight-for-height infants (Miller and Hassanein, 1973; Hoffman, Meirik, and Bakketeig, 1984). In this study, the 1980 National Natality Survey and the National Fetal Mortality Survey were used to examine the association of weight, height and perinatal mortality. All singleton births to white married mothers, between 18 and 34 years of age and of parity less than 4, for whom both mother's and hospital questionnaires were completed in those two surveys (3796 live births and 2043 fetal deaths) were selected for analysis. Overall, low weight and height infants had excess mortality rates. However, after adjustment for low birthweight and preterm birth status, low weight and height infants had only slightly higher mortality rates than their medium or high weight and height counterparts. The current study consists of relatively well-educated white married mothers of optimal reproductive age and low parity. Therefore, lower than expected mortality rates for slim infants may be attributed to these favorable demographic factors in this sample as compared with previous studies, or because of advances in perinatal medicine, slim infants may be prevented from achieving the high mortality seen in earlier studies. ^

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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. ^

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.

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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.