The Cost of Drug Use in Adolescence: Young People, Money and Substance Abuse.

It is now common for young people in full-time compulsory education to hold part-time jobs. However, whilst the 1990s experienced a rise in illicit drug use particularly among young people and an increase in the level of interest for identifying factors associated with drug use, little attention has been paid to the influence of the money young people have to spend and its potential links with drug use. Four thousand five hundred and twenty-four young people living in Northern Ireland completed a questionnaire in school year 10 (aged 13/14 years). The findings suggested there was a positive association between the amount of money (and its source) young people received and higher rates of drug use. The study concludes that money, and how it is spent by young people, may be an important factor for consideration when investigating drug use during adolescence. The findings may help inform drug prevention strategies particularly through advice on money management, and taking responsibility for their own money.

A Debriefing Session with a Nutritionist Can Improve Dietary Assessment Using Food Diaries.

The objective of the current study was to evaluate the effect of a debriefing call on nutrient intake estimates using two 3-d food diaries among women participating in the Women's Health and Interview Study (WISH) Diet Validation Study. Subjects were 207 women with complete data and six 24-h recalls (24-HR) by telephone over 8 mo followed by two 3-d food diaries during the next 4 mo. Nutrient intake was assessed using the food diaries before and after a debriefing session by telephone. The purpose of the debriefing call was to obtain more detailed information on the types and amounts of fat in the diet. However, due to the ubiquitous nature of fat in the diet, the debriefing involved providing more specific detail on many aspects of the diet. There was a significant difference in macronutrient and micronutrient intake estimates after the debriefing. Estimates of protein, carbohydrate, and fiber intake were significantly higher and total fat, monounsaturated fat, saturated fat, vitamin A, vitamin C, -tocopherol, folic acid, and calcium intake were significantly lower after the debriefing (P <0.05). The limits of agreement between the food diaries before and after the debriefing were especially large for total fat intake, which could be under- or overestimated by 15 g/d. The debriefing call improved attenuation coefficients associated with measurement error for vitamin C, folic acid, iron, tocopherol, vitamin A, and calcium estimates. A hypothetical relative risk (RR) = 2.0 could be attenuated to 1.16 for folic acid intake assessed without a debriefing but to only 1.61 with a debriefing. Depending on the nutrients of interest, the inclusion of a debriefing can reduce the potential attenuation of RR in studies evaluating diet disease associations.

Prediction of adipose tissue composition using Raman spectroscopy: average properties and individual fatty acids.

Abstract: Raman spectroscopy has been used for the first time to predict the FA composition of unextracted adipose tissue of pork, beef, lamb, and chicken. It was found that the bulk unsaturation parameters could be predicted successfully [R-2 = 0.97, root mean square error of prediction (RMSEP) = 4.6% of 4 sigma], with cis unsaturation, which accounted for the majority of the unsaturation, giving similar correlations. The combined abundance of all measured PUFA (>= 2 double bonds per chain) was also well predicted with R-2 = 0.97 and RMSEP = 4.0% of 4 sigma. Trans unsaturation was not as well modeled (R-2 = 0.52, RMSEP = 18% of 4 sigma); this reduced prediction ability can be attributed to the low levels of trans FA found in adipose tissue (0.035 times the cis unsaturation level). For the individual FA, the average partial least squares (PLS) regression coefficient of the 18 most abundant FA (relative abundances ranging from 0.1 to 38.6% of the total FA content) was R-2 = 0.73; the average RMSEP = 11.9% of 4 sigma. Regression coefficients and prediction errors for the five most abundant FA were all better than the average value (in some cases as low as RMSEP = 4.7% of 4 sigma). Cross-correlation between the abundances of the minor FA and more abundant acids could be determined by principal component analysis methods, and the resulting groups of correlated compounds were also well-predicted using PLS. The accuracy of the prediction of individual FA was at least as good as other spectroscopic methods, and the extremely straightforward sampling method meant that very rapid analysis of samples at ambient temperature was easily achieved. This work shows that Raman profiling of hundreds of samples per day is easily achievable with an automated sampling system.

A critical evaluation of Raman spectroscopy for the analysis of lipids: fatty acid methyl esters.

The work presented here is aimed at determining the potential and limitations of Raman spectroscopy for fat analysis by carrying out a systematic investigation of C-4-C-24 FAME. These provide a simple, well-characterized set of compounds in which the effect of making incremental changes can be studied over a wide range of chain lengths and degrees of unsaturation. The effect of temperature on the spectra was investigated over much larger ranges than would normally be encountered in real analytical measurements. It was found that for liquid FAME the best internal standard band was the carbonyl stretching vibration nu(C = O), whose position is affected by changes in sample chain length and physical state; in the samples studied here, it was found to lie between 1729 and 1748 cm(-1). Further, molar unsaturation could be correlated with the ratio of the nu(C = O) to either nu(C = C) or delta(H-C = ) with R-2 > 0.995. Chain length was correlated with the delta(CH2)(tw)/nu(C = O) ratio, (where "tw" indicates twisting) but separate plots for odd- and even-numbered carbon chains were necessary to obtain R-2 > 0.99 for liquid samples. Combining the odd- ani even-numbered carbon chain data in a single plot reduced the correlation to R-2 = 0.94-0.96, depending on the band ratios used. For molal unsaturation the band ratio that correlated linearly with unsaturation (R-2 > 0.99) was nu(C = C)/delta(CH2)(SC) (where "sc" indicates scissoring). Other band ratios show much more complex behavior with changes in chemical and physical structure. This complex behavior results from the fact that the bands do not arise from simple vibrations of small, discrete regions of the molecules but are due to complex motions of large sections of the FAME so that making incremental changes in structure does not necessarily lead to simple incremental changes in spectra.

Multivariate prediction of clarified butter composition using Raman spectroscopy

Raman spectroscopy has been used to predict the abundance of the FA in clarified butterfat that was obtained from dairy cows fed a range of levels of rapeseed oil in their diet. Partial least squares regression of the Raman spectra against FA compositions obtained by GC showed good prediction for the five major (abundance >5%) FA with R-2=0.74-0.92 and a root mean SE of prediction (RMSEP) that was 5-7% of the mean. In general, the prediction accuracy fell with decreasing abundance in the sample, but the RMSEP was 1.25%. The Raman method has the best prediction ability for unsaturated FA (R-2=0.85-0.92), and in particular trans unsaturated FA (best-predicted FA was 18:1 tDelta9). This enhancement was attributed to the isolation of the unsaturated modes from the saturated modes and the significantly higher spectral response of unsaturated bonds compared with saturated bonds. Raman spectra of the melted butter samples could also be used to predict bulk parameters calculated from standard analyzes, such as iodine value (R-2=0.80) and solid fat content at low temperature (R-2=0.87). For solid fat contents determined at higher temperatures, the prediction ability was significantly reduced (R-2=0.42), and this decrease in performance was attributed to the smaller range of values in solid fat content at the higher temperatures. Finally, although the prediction errors for the abundances of each of the FA in a given sample are much larger with Raman than with full GC analysis, the accuracy is acceptably high for quality control applications. This, combined with the fact that Raman spectra can be obtained with no sample preparation and with 60-s data collection times, means that high-throughput, on-line Raman analysis of butter samples should be possible.