Heavy alcohol use among U.S. college students is a major contributor to young adult morbidity and mortality. The aim of this study was to examine whether college alcohol policy enforcement levels predict changes in student drinking and related behaviors in a state system of public colleges and universities, following a system-wide change to a stricter policy.Students and administrators at 11 Massachusetts public colleges/universities completed surveys in 1999 (N of students = 1252), one year after the policy change, and again in 2001 (N = 1074). We calculated policy enforcement scores for each school based on the reports of deans of students, campus security chiefs, and students, and examined the correlations between perceived enforcement levels and the change in student drinking rates over the subsequent two year period, after weighting the 2001 data to adjust for demographic changes in the student body.Overall rates of any past-30-days drinking, heavy episodic drinking, and usual heavy drinking among past-30-days drinkers were all lower in 2001 compared to 1999. School-level analyses (N = 11) found deans' baseline reports of stricter enforcement were strongly correlated with subsequent declines in heavy episodic drinking . Moreover, consistently high enforcement levels across time, as reported by deans, were associated with greater declines in heavy episodic drinking. Such relationships were not found for students' and security chiefs' reports of enforcement. Marijuana use did not rise during this period of decline in heavy drinking.Study findings suggest that stronger enforcement of a stricter alcohol policy may be associated with reductions in student heavy drinking rates over time. An aggressive enforcement stance by deans may be an important element of an effective college alcohol policy. Numerous national surveys have shown that heavy alcohol use among U.S. college students is a pervasive and enduring public health problem. According to the Monitoring the Future Survey and the Harvard School of Public Health College Alcohol Study (CAS), about two in five students attending 4-year colleges in the U.S. report engaging in heavy episodic drinking, defined as >=5 drinks for males and >=4 drinks for females consumed on a single occasion during the prior two weeks ,2. The hHeavy alcohol use is a major contributor to morbidity and mortality among U.S. college students. Hingson et al.  estimateon campus were significantly and negatively correlated with the level of policy enforcement as reported by the chief of campus security at each of the schools. Interestingly, heavy drinking rates had low to moderate positive correlations  with enforcement levels reported by the dean of students at each school and by the students. We hypothesized that these positive correlations may be a reflection of deans having to discipline more students at schools with higher drinking rates, and of students who drink being more likely to encounter alcohol policy enforcement. Data for this study, however, were cross-sectional and we could not determine the temporal relationship between alcohol policy enforcement and student drinking rates.Results of that previous study  indicatesubsequent change in commonly assessed college drinking rates, i.e., any past-12-months drinking, any past-30-days drinking, recent heavy episodic drinking, usual heavy episodic drinking among drinkers, and uptake of heavy episodic drinking in college. We hypothesized that higher baseline enforcement levels would predict decreases in student drinking rates over time. We then examined how reported policy enforcement levels across the two years related to student behavior changes during the same time period. We hypothesized that schools that started with higher levels of alcohol policy enforcement in the initial year, and that reported consistently higher levels of enforcement across time, would have, on average, a greater decline in student drinking rates compared to schools that reported lower enforcement levels over time.The current study extends our previous study by examining longitudinally how student drinking and related behaviors changed over the subsequent two-year period (1999-2001), and whether reported levels of alcohol policy enforcement related to the observed changes. Specifically, we first examined how policy enforcement levels in the initial year predicted With this longitudinal study, we also had the opportunity to look at possible unintended consequences of a more restrictive alcohol policy. We examined the relationship between alcohol policy enforcement levels and change over time in student marijuana use rates, as there might be a transfer from alcohol to other types of substance use due to greater restrictions on alcohol. In addition, we examined how alcohol policy enforcement levels related to changes in rates of student drinking and driving or riding with a driver who had been drinking, since a more restrictive campus environment may result in more students choosing off-campus venues for drinking.This longitudinal study consisted of two assessments conducted two years apart (1998/1999 and 2000/2001) of the behavior and perceptions of students and administrators at 11 public colleges and universities in Massachusetts. The schools, baseline sample, and data collection instruments and method are described in detail in a previous report .th, and a second mailing during the first week of May. We chose this timing in order to avoid having spring vacation included in the prior two-week timeframe for survey responses, and to reach students before the end of the school year. Our surveys were also timed to coincide with the administration of the national CAS survey.We slightly shortened the student survey used in 1999 (Time 1 [T1]) to assess student behaviors and alcohol policy enforcement perceptions, and re-administered it in 2001 (Time 2 [T2]) at the same time of year as the 1999 survey. For both cohorts, we sent out the first mailing during the week of April 5xth student name (number determined by enrollment size of school), beginning at a random starting point, from the enrollment roll. To protect student confidentiality, the survey included no identifying information except for a numeric code identifying the school. We therefore could not link data for individual students across the two surveys. In the 2001 survey, 2,222 surveys were deliverable and 1,074 were returned completed, for a 48.3% overall response rate . This was a lower overall response rate than in 1999 (56%), mirroring a declining trend in response rates seen in the CAS across the same time period (59% to 52%)  = .79). Security chiefs' enforcement reports, however, showed more variability over time, with a more moderate correlation (ICC = .37) across data given by the same chief (n = 7). Not surprisingly, there was little consistency across the two years in deans' or security chiefs' enforcement scores when reported by different individuals. There was no difference between years in mean student enforcement scores.past-12-months drinking, (b) any past-30-days drinking, (c) any past-2-weeks heavy episodic drinking (HED) defined as >=5 drinks per occasion for males and >=4 for females [usual heavy episodic drinking (UHED) among those reporting drinking in the past 30 days, i.e., usually drinking >=5 drinks for males and >=4 drinks for females whenever they drink. In addition, we asked students whether they had ever engaged in heavy episodic drinking during their last year of high school and examined the change over time in the proportion of students who reported HED in college but who had not engaged in HED in their last year of high school ("never" for high school item and >=one occasion of past-2-weeks HED).We assessed student drinking using standard "drink" definitions  and timeframes from the CAS: (a) any  females , and (d)Finally, we also assessed any past-30-days use of marijuana and any past-30-days driving while intoxicated or riding with an intoxicated driver (DWI/RWID). All survey items came from the national CAS survey .® 9.0 software for analyses involving individual student data to correctly account for the cluster (school) sampling design in our precision estimates, and SPSS® 15.0 software for analyses involving school as the unit of analysis.We scanned student questionnaires directly into an electronic data file, and we manually entered administrator questionnaire data twice into MS Excel, compared the two files, and corrected any discrepancies. We used SUDAANWe standardized the two years' samples by applying weights derived from the T1 sample demographic profile for each school  to the T2 follow-up data for that school. We then conducted chi-square tests  to assess whether the weighted rates of interest  were significantly different between the two years. We dichotomized race into White and non-White due to small percentages in the individual non-White categories (no category had more than 5%). We also conducted stratified chi-square analyses to assess trends in drinking rates by gender, age group, and housing status.We then calculated a change score for each student behavior variable for each of the 11 schools by taking the absolute rate difference between the two years, dividing by the T1 rate, and multiplying by 100 to generate a percentage change score. The score was positive if the rate had gone up over time, and negative if the rate had gone down .m where m is the number of comparisons.To control for multiple comparisons in the subgroup analyses, we used the Benjamini-Hochberg (B-H) procedure, a sequential approach to controlling the false discovery rate  that is gaining preference over the more conservative Bonferroni correction -12. In tinitial alcohol policy enforcement levels and subsequent change in our student behavior rates of interest, we calculated correlation coefficients (Pearson's r) between T1 enforcement scores as reported by deans, security chiefs, and students, and the drinking rate change scores (N = 11). To assess how administrator-reported policy enforcement levels over time related to student drinking rate changes, we first identified the major trajectories of enforcement using hierarchical cluster analysis. Cluster analysis has previously been used to identify longitudinal trajectory profiles [® v. 15.0, using squared Euclidean distance as the measure of similarity/distance across parents and Ward's method for combining clusters [To analyze the relationship between profiles  and is aprofiles . For eacIn 1999 and 2001, the student sample was majority female and white non-Hispanic , with the vast majority of respondents (86.3%) reporting past-12-months drinking in 2001  among past-30-days drinkers declined significantly between the two survey years . In subgroup analyses, declining trends were seen among underage students  and on-campus residents  after multiple comparisons correction, but not among legal-age students (53.7% vs. 48.9%) or those living off-campus (45.1% vs. 43.7%).There was a declining trend in Uptake of HED behavior in college showed a declining trend over time . There was no such trend among off-campus residents. We found little change in past-30-days use of marijuana for the total sample, or for any subgroup examined.We found no overall difference between years in the percentage of students reporting any past-30-days DWI/RWID. However, there was an increasing trend between survey years in the percent of negative correlation coefficients for the association between T1 deans' enforcement scores and change in student drinking rates over the following two years.  (n = 5) with mean scores >=80 across time, and a "lower enforcement" group (C-LE) (n = 2) with mean scores <80. A third group not found for the deans was the "increasing enforcement group" (C-IE) (n = 2), with initial chiefs' enforcement scores <80 but increasing to a mean >80 at the second time point. As shown in Table heavy drinking may have declined, particularly among underage students and on-campus residents, for whom the school's alcohol policy may have greater impact. This apparent decline occurred despite an overall higher percentage in 2001 of students in our sample reporting heavy drinking during their last year in high school, a known risk factor for heavy drinking in college [Our study found that current  drinking rates and heavy drinking behavior among drinkers declined significantly during a period of increased restrictions on alcohol at Massachusetts public colleges and universities. While the great majority of students continued to report some drinking, study results suggest that  college -19. DuriWe were able to examine data from one school included in both our sample and the CAS sample prior to  and after (2005) our study period, allowing us to look at trends for that school both leading up to and extending beyond our study period. This school's heavy drinking rates (weighted) steadily increased through 1999 , declined in 2001 (55%), and increased again by 2005 (67%) (unpublished data). The brief interruption of the upward trend immediately following the MA Board of Higher Education policy change could be, in part, due to the stricter alcohol policy, as well as to the increased attention to underage drinking generated by the two student deaths. However, the decline between 1999 and 2001 was short-lived at this school, and possibly statewide. Over time, memories can fade and enforcement may wane, leading to drinking behaviors returning to previous or even higher than previous levels.Heavy drinking appeared to be less common over time as a usual drinking pattern among female students who drink, while there was no such change for men. Previous studies have found gender differences in both the likelihood of engaging in heavy episodic drinking, as well as the factors that increase the risk of heavy drinking in college ,20-23. Mth graders and non-college-attending young adults [uptake among on-campus and underage students, groups that are more likely to feel the impact of stricter school alcohol policy enforcement and to be affected by sanctions.College is a time of significantly increased drinking prevalence compared to the rates found among college-bound 12both alcohol and marijuana use, suggesting that demand for alcohol and marijuana may be complementary rather than substitutive [We found no evidence of a rise in marijuana use as a possible unintended consequence of stricter alcohol policy enforcement. Trend data from the CAS and Monitoring the Future studies which showed a rise in marijuana use among college students between 1993 and 1999, a time of increased restrictions on alcohol use, caused concern about students substituting marijuana and other drugs for alcohol ,25,26. Htitutive . While mAnother possible unintended consequence of a stricter college alcohol policy is that students may go off campus to drink. We found a marginally significant increase in the prevalence of past-30-days DWI/RWID behavior among on-campus but not off-campus residents. This finding may indicate that students were more likely to go off campus to drink in response to the greater restrictions. However, we did not measure community characteristics and changes in local policies which could have contributed to this trend , and thesubsequent declines in heavy drinking rates during the study follow-up period. In addition, schools with consistently high dean's enforcement scores appeared to have greater declines in past-2-weeks HED compared to schools with lower scores over time. In our previous cross-sectional study of 1999 data, however, we found that deans' enforcement scores had weak to moderate positive correlations with concurrent student drinking rates. In contrast, security chiefs' reports were strongly, and negatively, correlated with concurrent drinking rates [change over time .In examining whether stricter policy enforcement was associated with changes in school drinking rates, we found that deans' perceptions of enforcement strength in 1999 were associated with greater ng rates  but showinitiating heavy drinking in college or engaging in heavy drinking as a usual behavior.We hypothesize that the difference in our findings between the two studies may be due to the different perspectives that deans and campus security chiefs have on policy enforcement. Security chiefs are likely more knowledgeable about day-to-day enforcement activities and events, particularly those happening on evenings and weekends when students are more likely to drink. Their stricter enforcement may have a more immediate deterrent effect. On the other hand, deans may be more likely to base their enforcement perceptions on the number of students caught for violations, because they are usually charged with meting out disciplinary sanctions. In schools with more widespread drinking, deans may have more students to discipline, therefore resulting in a positive correlation between enforcement and drinking rates in a cross-sectional study. On the other hand, a more aggressive enforcement stance by deans may over time bring about changes in student perceptions and behavior, with fewer students Our previous study  found thThis longitudinal study represents an important extension of our previous cross-sectional study, allowing us to investigate the prospective relationship between alcohol policy enforcement levels and changes in rates of student drinking and associated behaviors across a statewide system of schools with a uniform alcohol policy. Our study adds to the growing body of work that suggests that environmental strategies addressing underage alcohol use can help to lower high-risk college drinking and associated behaviors -33. In pbecause of the drinking policy may confound the association between policy enforcement and student drinking rates. If a stricter alcohol policy in the MA public colleges caused more drinking students to choose alternatives  over the public colleges, thus resulting in lower drinking rates in 2001, we would expect to find lower rates of high school HED among students in 2001 compared to 1999. Instead, we found the opposite, with more students in the 2001 sample reporting HED in high school than in 1999. Finally, we did not assess other influential environmental or individual factors that may confound the relationship between enforcement measures and student drinking trends  [This study had several strengths such as a longitudinal follow-up; inclusion of the assessment of multiple perspectives of alcohol policy enforcement; the use of multi-item enforcement measures that examined a range of enforcement activities, experiences, and venues; and the evaluation of alcohol use and related outcomes, as well as potential unintended consequences of a stricter alcohol policy . Our study also had a number of limitations. The number of schools was small, limiting the power of school-level analyses; we examined only two points in time; and we relied on self-reported rather than observational measures. In addition, the student survey response rates were generally low (range 38%-54%), raising concerns about potential selection bias and inaccurate estimates of student drinking rates. In examining whether heavy drinking prevalence estimates were associated with response rates, we found low correlations in both baseline and follow-up years. We also used direct standardization of the two years' samples to control for demographic differences in our comparisons of the two time points. Of greater concern is that student self-selection into particular schools  access) ,29,34-36Future studies examining college alcohol policy enforcement should include many more schools, survey other key informants such as residence hall assistants and resident directors, include direct observation of campus enforcement practices , and chronicle other on-campus and community-wide efforts to reduce student drinking.uptake of heavy drinking in college. A unified stance among college administrators of aggressive policy enforcement and action around drinking violations, and greater awareness of and involvement in enforcement by college leaders, e.g., through giving reminders at campus events and residence meetings, may help to set a tone on campus which discourages underage and heavy drinking by students. Our study findings also suggest the need for a consistently strong enforcement stance in order for effects to appear over time. While enforcement of alcohol policies may be challenging, colleges' multi-level efforts to address student drinking, when properly implemented and consistently enforced by college staff working in unison at all levels could eventually help to lower rates of students' heavy drinking, and therefore lower the morbidity and mortality among our nation's most important resource - its young people.Our study findings suggest that an aggressive enforcement stance by deans, and other such college leaders, may be an important element of an effective college alcohol policy and be associated with reductions in student high-risk drinking rates over time, perhaps through reduced The following abbreviations were used: CAS: Harvard School of Public Health College Alcohol Study; MBHE: Massachusetts Board of Higher Education; T1: Time 1 data collection; T2: Time 2 data collection; HED: Past-2-weeks heavy episodic drinking defined as >=5 drinks in one occasion for males, >=4 for females; UHED: Usual heavy episodic drinking during the past 30 days; DWI/RWID: Driving while intoxicated/Riding with an intoxicated driver; B-H procedure: Benjamini-Hochberg procedure for controlling the false discovery rate; D-HE: Deans "higher enforcement" group; D-LE: Deans "lower enforcement group; C-HE: Campus security chiefs "higher enforcement" group; C-LE: Campus security chiefs "lower enforcement" group; C-IE: Campus security chiefs "increasing enforcement" group.The authors declare that they have no competing interests.SKH, LS, SVH, HW, and JRK participated in the conceptualization and design of the study, development of the measurement tools, and planning and review of the statistical analyses. SKH, LS, SVH, and JRK participated in the oversight of the implementation of the study, and SKH and LS performed the statistical analyses. SKH drafted the manuscript and all authors read and approved the final manuscript.


Malnutrition is a major public health and development concern in the developing world and in poor communities within these regions. Understanding the nature and determinants of socioeconomic inequality in malnutrition is essential in contemplating the health of populations in developing countries and in targeting resources appropriately to raise the health of the poor and most vulnerable groups.This paper uses a concentration index to summarize inequality in children's height-for-age z-scores in Ghana across the entire socioeconomic distribution and decomposes this inequality into different contributing factors. Data is used from the Ghana 2003 Demographic and Health Survey.The results show that malnutrition is related to poverty, maternal education, health care and family planning and regional characteristics. Socioeconomic inequality in malnutrition is mainly associated with poverty, health care use and regional disparities. Although average malnutrition is higher using the new growth standards recently released by the World Health Organization, socioeconomic inequality and the associated factors are robust to the change of reference population.Child malnutrition in Ghana is a multisectoral problem. The factors associated with average malnutrition rates are not necessarily the same as those associated with socioeconomic inequality in malnutrition. In the developing world, an estimated 230 million (39%) children under the age of five are chronically malnourished and about 54% of deaths among children younger than 5 are associated with malnutrition . MalnutrChronic malnutrition is usually measured in terms of growth retardation. It is widely accepted that children across the world have much the same growth potential, at least to seven years of age. Environmental factors, diseases, inadequate diet, and the handicaps of poverty appear to be far more important than genetic predisposition in producing deviations from the reference. These conditions, in turn, are closely linked to overall standards of living and the ability of populations to meet their basic needs. Therefore, the assessment of growth not only serves as one of the best global indicators of children's nutritional status, but also provides an indirect measurement of the quality of life of an entire population -13.Large scale development programs such as the Millennium Development Goals (MDGs) have also emphasized the importance of the under-fives' nutritional status as indicators for evaluating progress . When aiAgainst this background, Ghana provides an interesting case study. The country experienced remarkable gains in health from the immediate post independence era. Life expectancy improved over the years and the prevention of a range of communicable diseases improved child survival and development. However in the last decade despite increasing investments in health, Ghana has not achieved target health outcomes. There has been no significant change in Ghana's under-five and infant mortality rates between 1993 and 2003. In the last couple of years, under-five mortality was actually slightly increasing. Life expectancy has also fallen from 57 years in 2000 to 56 years in 2005 . Ghana'sMalnutrition in Ghana has been most prevalent under the form of Protein Energy Malnutrition (PEM), which causes growth retardation and underweight. About 54% of all deaths beyond early infancy were associated with PEM, making this the single greatest cause of child mortality in Ghana .A paradigm shift in Ghanaian health policy has been taking place in 2006. The theme for the new health policy in Ghana was 'Creating Wealth through Health". One of the fundamental hypotheses of this policy was that improving health and nutritional status of the population would lead to improved productivity, economic development and wealth creation . Since tFrom the existing evidence it is clear that childhood malnutrition is associated with a number of socioeconomic and environmental characteristics such as poverty, parents' education/occupation, sanitation, rural/urban residence and access to health care services. Also demographic factors such as the child's age and sex, birth interval and mother's age at birth have been linked with malnutrition ,5,22-26.Further, this paper contributes to the literature by delivering evidence on the determinants of malnutrition and socioeconomic inequality in Ghana using the new child growth standards population that has recently been released by the World Health Organization (WHO) . This reThe results are useful from a policy perspective as they can be used in setting policies to reduce malnutrition and the excessive burden on the poor. The results of this study are particularly relevant for Ghanaian policy makers, but can also be generalized to other settings in the sense that they show that malnutrition is associated with a broad range of factors and that the factors related to average malnutrition are not necessarily the same as those related to socioeconomic inequality in malnutrition.Nutritional status was measured by height-for-age z-scores. An overview of other nutritional indices and why height-for-age is the most suited for this kind of analysis is provided in . A heighy). This facilitates interpretation since it has a positive mean and is increasing in malnutrition .yi is linearly modelledIf  showed ty, xk, Ck is the concentration index of xk (with respect to socioeconomic status) and GCε is the generalized concentration index of the residuals. The latter term reflects the socioeconomic inequality in height-for-age that is left unexplained by the model and is calculated as where μ is the mean of As the DHS data have a hierarchical structure, with children nested in households and households nested within communities, we have also considered using multilevel models to estimate the associations of variables with childhood malnutrition (see e.g. ). AllowiAll estimation takes account of sample weights (provided with the DHS data). Statistical inference on the decomposition results is obtained through bootstrapping with 3000 replications. The bootstrap procedure takes into account the dependence of observations within clusters.Data is used from the 2003 Ghana Demographic Health Survey (DHS) and are restricted to children under the age of 5. Anthropometric measures are missing for 12.3% of children in this age group. The final sample contains information on 3061 children. We did examine possible selection problems due to the high proportion of missing observations. A logit model explaining the selection in the sample and a Heckman sample selection model (using different exclusion restrictions) were used to check for this . Both teThe nutritional status of a child is specified to be a linear function of child-level characteristics such as age, sex, duration of breastfeeding, size at birth; maternal characteristics such as education, mother's age at birth, birth interval, marital status, use of health services, occupation and finally household-level characteristics such as wealth, type of toilet facility, access to safe water, number of under-five children in the household, region and urbanization. We preferred not to include information on the type of toilet and water source into the wealth indicator, as these variables can be expected to have a direct relation with children's growth apart from being correlated with household socioeconomic status .The explanatory variables are described in the last column of Table No information on mother's nutritional status was included in the set of explanatory variables. Since about 10% of women in the dataset were pregnant at the time of interview, their BMI did not provide an accurate measure of their nutritional status. Furthermore, BMI reflects current nutritional status and may not be relevant for children born 5 years prior to the interview. Inclusion of mother's height-for-age had no significant effect on results.In the 2003 DHS data for Ghana, 36% of children under the age of 5 are stunted. Stunting is defined as height-for-age being below minus 2 SD from the median of the reference population. The concentration index for stunting in children under the age of 5 was -0.12 (SD = 0.016). This negative value implies that poor children had a higher probability of being stunted than their better off peers. Using the older NCHS reference study showed a lower prevalence of stunting (29%) and slightly higher socioeconomic inequality .Figure Figure The regression coefficients and their significance are shown in the first column of Table Malnutrition increased with the child's age in a non-linear way. Children who were very small at birth had a higher probability to be stunted than children with normal size. Male children were more prone to malnutrition than their female peers. Long duration of breastfeeding is associated with higher malnutrition.With respect to maternal characteristics, the existence of a short birth interval was significantly increasing malnutrition. Children of women that accessed health services more frequently were less prone to being malnourished. Maternal occupation showed no clear effect. Maternal education and household wealth showed a significant association with childhood malnutrition. The presence of two or more under-five children in the household was negatively associated with the child's nutritional status. Sanitation variables however had no significant association on malnutrition. As compared to the Northern region all regions were associated with lower malnutrition, especially the Accra region. The high regional disparities in malnutrition are further illustrated in Figure Table age>12 months The contribution of the error term only amounted to about 6%, meaning that the decomposition model functioned well in explaining socioeconomic inequality in malnutrition.Wealth accounted for the major part (31%) of socioeconomic inequality. This part of socioeconomic inequality reflects the direct contribution of wealth. The remainder is the wealth-related inequality in malnutrition through other factors. Important contributors were regional variables (23%) and the use of health care services (18%). The age of the child was contributing negatively to socioeconomic inequality (-8%). This means that the combined effect of its coefficient and its distribution by wealth was lowering socioeconomic inequality in malnutrition. Older children were more likely to be stunted and were more prevalent in higher wealth quintiles. The latter is reflected by the positive and significant C of the variable Using the older NCHS reference population gave very similar regression and decomposition results are therefore not discussed (results are available upon request.).Relative to other Sub-Saharan countries, Ghana appeared to have a rather low level of average stunting, combined with relatively high socioeconomic inequality in stunting. The use of the new WHO child growth standards yielded a higher average stunting rate as compared to the older NCHS reference group.  found thMalnutrition in Ghanaian children rises with the age of the child, which is confirmed by other studies ,25,32. TShort birth intervals and the presence of two or more under-five children in the household, affected childhood growth negatively by placing a heavy burden on the mother's reproductive and nutritional resources, and by increasing competition for the scarce resources within the household . ChildreMaternal education was significantly lowering childhood malnutrition. This may reflect education generating the necessary income to purchase food. However, although education is often suggested to be a measure of social status, the coefficient stayed significant after controlling for household wealth and living conditions. A high level of maternal education could also lower childhood malnutrition through other pathways such as increased awareness of healthy behaviour, sanitation practices and a more equitable sharing of household resources in favour of the children ,5,49.Sanitation in terms of having a toilet and access to safe water did not significantly affect malnutrition.  also repThe higher levels of malnutrition of the population living in the northern regions of Ghana have already been observed more than a decade ago . This reThe high socioeconomic inequality in childhood malnutrition is -apart from wealth itself-mainly associated with regional characteristics and use of health care services. Wealth was responsible for about one third of the socioeconomic inequality in malnutrition. This means that poorer children were more likely to be malnourished, mainly because of their poverty. The regional contribution results from the fact that poorer children are more likely to live in regions with disadvantageous characteristics. Given the strong regional associations with malnutrition, after controlling for a broad range of socioeconomic and demographic covariates, there must be other important regional aspects. The regional inequality in Ghana originates from both geographical and historical reasons. Much of the North is characterized by lower rainfall, savannah vegetation, periods of severe drought and remote and inaccessible location. Further, the colonial dispensation ensured that northern Ghana was a labor reserve for the southern mines and forest economy and the post-colonial failed to break the established pattern .Health services use was also responsible for a substantial proportion of socioeconomic inequality in malnutrition. This derives from the combined effect of the positive associations between health services use and childhood growth and the unequal use across socioeconomic groups. The reason for the lower health care use amongst the poor may be due to several barriers including the cost of care, cost of transportation and lower awareness on health promoting behavior . User feThe negative contribution of age comes from the combined facts that older children are more likely to be malnourished and at the same time more prevalent in the richer wealth quintiles. The latter could be related to higher child and infant mortality rates amongst poorer households that cause the proportion of older children to be lower among poor households as compared to richer households.Combining the results from the analysis on the determinants of malnutrition and socioeconomic inequality demonstrates that variables that are associated with average malnutrition are not necessarily also related to socioeconomic inequality. Although bio-demographic variables such as a risky birth interval, size at birth, duration of breastfeeding and the sex of the child are quite strongly associated with a child's nutritional status, they do not contribute to socioeconomic inequality in malnutrition. This is because of their relatively equal distribution across socioeconomic groups. Other variables such as urban/rural location, having a toilet, access to clean water and maternal occupation are very unequally distributed across socioeconomic groups, but still do not contribute to socioeconomic inequality in malnutrition because they are not significantly associated with malnutrition. A third group of variables such as regions, health care use and wealth are both very strongly related to average and socioeconomic inequality in malnutrition.There exist some limitations of this study. First, DHS only collects information on the recent food consumption of the youngest child under three years of age living with the mother. Restricting the sample to these children would substantially reduce the number of observations. However, the analysis was also conducted on this sub sample, using food consumption as one of the determinants of malnutrition . SinThe regression results show that malnutrition is associated with a broad range of factors. However in Ghana it often falls through the cracks since it has no institutional home. Tackling malnutrition therefore calls for a shared vision and should be viewed and addressed in a broader context . TherefoThe results also suggest that factors strongly associated with average malnutrition are not necessarily also contributing to socioeconomic inequality in malnutrition. The distinction between these groups of variables can be quite important, as it suggests that policies trying to reduce average malnutrition rates can be different from those aiming at lowering socioeconomic inequality in malnutrition. If equity goals are to be achieved, health policies in Ghana should further be directed at strategies/interventions to reduce poverty and to improve the use of health care and family planning services among the poorer population groups. Furthermore, regional disparities should further be tackled to narrow the gap in malnutrition between the poor and the rich. A starting point could be for policy makers to include under-five malnutrition differentials to set criteria to guide resource allocation to regions. Moreover, the strong regional contributions to socioeconomic inequality, even after controlling for other factors such as household wealth and education, bring forward the issue of geographical targeting. Further targeting public programs towards the central and northern regions would substantially reduce socioeconomic inequality in malnutrition and is administratively easier than targeting the poor. The latter argument is relevant for Ghana, where pro-poor policies (redistribution schemes and exemption policies) are not having the aimed effect because of problems in identifying the poor ,56. GeogWith respect to Ghana, regional averages should be interpreted with caution as there is large heterogeneity between districts in each region and indeed among socio-economic groups within districts. In this case, polices aimed at reducing child malnutrition based on regional averages may lead to under coverage of those in need.  exposes EVDP was responsible for the study design, analysis, interpretation of the data and writing of the paper. ARH and NS contributed to formulating the study design, interpreting the data and revising the manuscript. CJA contributed to the writing of the paper and revising the manuscript. JV provided guidance to the work and commented on the manuscript. All authors approved the final version of the paper.


Despite these concerns, little is known about whether the use of polycarbonate food or beverage containers actually contributes to BPA body burden in people. A new study of human exposure to BPA from drinking containers now shows that study participants’ urinary concentrations of the molecule increased by two-thirds after they used polycarbonate drinking bottles for 1 week Rodent studies have associated prenatal and neonatal exposure to BPA with early onset of sexual maturation, reproductive tract lesions, and altered development of the mammary gland, among other reproductive abnormalities. However, limited information is available on human health effects. Nevertheless, human exposure to BPA is widespread: the chemical was detected in the urine of more than 92% of the participants aged 6 years and older in the 2003–2004 National Health and Nutrition Examination Study (NHANES).Not all polycarbonate plastics contain BPA, but nearly three-quarters of the BPA used in the United States in 2003 went into the manufacture of this one material. The hard, nearly shatterproof plastic is widely used in drinking bottles, baby bottles, and non-food uses ranging from eyeglasses to labware. Earlier studies of polycarbonate drinking containers containing BPA have shown that under normal use—washing, rinsing, and exposure to high temperatures or to alkali or acid solutions—the plastic can degrade and release small amounts of the constituent chemical.BPA is believed to be rapidly metabolized and eliminated. Therefore, in the current study, 77 college students aged 18–22 underwent a weeklong “washout” to minimize any preexisting BPA load that could have arisen from the use of polycarbonate drinking bottles. During the washout, participants were instructed to drink any cold beverages only from stainless steel bottles and to avoid drinking water from the polycarbonate dispensers in the college dining halls. After the washout, the group switched to drinking cold drinks only from 2 new researcher-provided polycarbonate bottles for 1 week. Exposure to other BPA sources was not controlled; thus, the study yielded a conservative estimate of the potential for BPA exposure via polycarbonate drinking bottles.Comparison of urine samples collected throughout the study showed that after using polycarbonate bottles for 1 week, participant’s mean urinary BPA concentrations increased by more than two-thirds to 2.1 μg/L, compared with the mean of 2.6 μg/L observed in the NHANES 2003–2004 study. The authors anticipate higher urinary BPA concentrations would result from drinking hot beverages stored in the same bottles.


Six state groupings were identified: North Central and New England with the highest consumption and heavy drinking levels; Middle Atlantic, Pacific and South Coast with moderate drinking levels; and Dry South with the lowest drinking levels. Analyses of relationships between beer and spirits series for states within groups as compared to those in different groups failed to clearly indicate group cohesiveness.US state alcohol consumption patterns and trends are examined in order to identify groups of states with similar drinking habits or cultures. Rates of heavy drinking and current abstention and  Factors that may underlie or influence drinking culture include a state’s demographic make-up in terms of age, gender and race/ethnicity groups, the distribution of socio-economic characteristics such as educational attainment, income and wealth, a state’s mix of religions with differing perspectives on alcohol use, degree of urbanicity, state alcohol policies and regulatory regimes, the structure of the alcoholic beverage market in terms of wholesale and retail distribution networks, historical and cultural practices related to drinking (or not drinking) various alcoholic beverages, the size and importance of alcoholic beverage production industries both historically and currently, exposure to advertising for alcohol products and potentially other factors. Yet, clearly some of these aspects of drinking culture are shared across states, particularly those in geographic proximity to one another, and other aspects may be shared across states with similar populations throughout the country. Therefore, one would expect that drinking cultures and markets would not be defined by state borders in most cases. Media markets too may help create cultural sub-groups that cover multiple states or even market-related areas potentially spread across many parts of the country. Relative proportions of the various demographic and market-demarcated sub-groups, along with geographic proximity, should define the degree of shared drinking cultures between states. Thus, states may share similarities in terms of certain beverage types or drinking patterns but may be divergent on other beverages or trends. It is also relevant regarding drinking culture, to consider commonalities reflected in trends over time.per capita consumption and percentage of heavy drinkers and a relatively low abstention rate. Alternative definitions of “wetness” in terms of alcohol policy and alcohol availability could also be applied and future studies should address how these are related to the drinking outcome-based definition of wetness. Early work utilizing data from the first National Alcohol Survey (NAS) conducted in 1964 using nine Census-defined regions found the Northeast, North Central and Pacific regions to be Wet and the South, Mountain and West North Central states to be Dry [per capita consumption.Past research has generally focused on characterizing Wet and Dry regions of the US. In these studies and the current analysis “wetness” is determined by consumption patterns with Wet areas having a relatively high o be Dry . In thesper capita apparent consumption [Survey measures of consumption volume have been found to be highly correlated with sumption  and survsumption . Some hasumption . This masumption . Religiosumption .Survey-based models of the determinants and consequences of alcohol use typically utilize regional control variables to capture unmeasured aspects of drinking culture . Most USper capita apparent alcohol consumption. This paper aims to categorize the US states into regional groups based on the wetness of recent drinking patterns and to evaluate whether these groupings represent linked drinking cultures over time through pair-wise analyses of trends in per capita apparent consumption of beer and spirits within and outside of these regional groupings.No studies have specifically tried to group states empirically based on drinking pattern and alcohol sales data. Much more state-specific data is now available to fine tune these characterizations and to begin to empirically define state groupings in terms of shared drinking culture. Measures characterizing drinking culture in this study focus on the percentage of the population drinking five or more (5+) drinks in a day in the past month, drinking at all in the past month and 2.2.1.Survey estimates for each state are taken from synthetic state-level estimates for the 2005–2006 combined samples from the National Survey on Drug Use and Health (NSDUH) of past month 5+ drinks in a day and past month drinking among those aged 12 and older and other age sub-groups. These published estimates were used because to prevent identification, the public use files for this survey do not include geographic identifiers . The NSDPer capita (aged 15 and older) apparent alcohol consumption data for 1950 to 2002 and for 2005 are estimates from the Alcohol Research Group (ARG) state alcohol per capita ethanol database. Tax and sales based estimates of per capita apparent consumption of beer, wine, spirits and total ethanol for 1950 to 2005 are calculated using %ABV conversions developed by ARG and population estimates are from the US Census Bureau [s Bureau –13.2.2.per capita apparent consumption of alcohol. Also considered were the past month 5+/4+ binge measure taken form the 2007 BRFSS survey and the past year abstention rate in the 2005–2006 NSDUH surveys. The NSDUH estimates are seen as more reliable than the BRFSS estimates due to higher response rates and especially higher reported volumes of drinking, implying better coverage of alcohol sales [Per capita apparent consumption figures are generally seen as the most reliable estimates of overall drinking, not being subject to non-response and self-report biases. However, an exception to this rule is states with large cross-border and/or tourist sales relative to their populations, particularly, Nevada, Alaska, Hawaii, District of Columbia, New Hampshire and Delaware. Correlations between reporting 5+ drinks in a day in the last month and monthly drinkers in the 2005–6 NSDUH, 2005 per capita apparent consumption and 5+/4+ drinks in a day monthly based on the 2007 BRFSS were also calculated to determine the degree to which these measures indicated similar rankings of states. The percentage of past month drinkers reporting having 5+ drinks in any day in the past month in the 2005–6 NSDUH was also calculated to illustrate the prevalence of heavy drinking among drinkers. Based primarily on inspecting the proportion of heavy drinkers and per capita apparent consumption of alcohol, but also considering the other measures, states were generally characterized as Wet, Moderate or Dry. States within these categories were then grouped according to geographic proximity with some exceptions made in order keep the number of groups relatively small and to include nearly all states in some group. For example, Utah was grouped with the other Dry states that form a geographically contiguous group in the South and the Moderate states in the South were grouped together although they do not all share borders.State groupings were created based on geographic proximity and primarily on the estimate, from the NSDUH 2005–2006 combined sample, of the percentage of those 12 and older drinking 5+ drinks in a day on any day in the past month, as well as from the 2005 ol sales . Per capper capita apparent consumption by beverage type were examined to give an indication of whether alcohol consumption trends within the state groupings appear to move together and to have similar levels and general trends. To establish whether relationships between states within a resultant regional grouping where stronger and more common than those with states outside of the groupings, Granger Causality tests [per capita beer consumption in Ohio) to predict the current value of another series . These tests incorporated two lagged values and a 0.05 significance level was used for rejecting the null hypothesis of no relationship. The proportion of significant relationships (in either or both directions) between states within a group was then compared to the proportion with states outside of the group to determine the relative degree to which beverage series trends were more closely related within regional groups.Following the grouping, based on cross-sectional results, data on trends in ty tests  were estty tests  between 3.WetNorth Central- Alaska, Colorado, Illinois, Iowa, Kansas, Michigan, Minnesota, Montana, Missouri, Ohio, Nebraska, North Dakota, South Dakota, Wisconsin, WyomingNew England- Maine, Massachusetts, New Hampshire, Rhode Island, VermontModerateMiddle Atlantic- Connecticut, Delaware, Maryland, New Jersey, New York, PennsylvaniaPacific- California, Hawaii, Idaho, Nevada, Oregon, WashingtonSouth Coast- Arizona, Florida, Louisiana, New Mexico, South Carolina, TexasDryDry South- Alabama, Arkansas, Georgia, Indiana, Kentucky, Mississippi, North Carolina, Oklahoma, Tennessee, Utah, Virginia, West VirginiaSix state groups were identified by consideration of the variables mentioned in Methods, as shown in per capita apparent consumption estimates but residents’ drinking in surveys clearly fits with the New England group. Alaska also has a relatively high tourist/visitor impact and being geographically separated from the contiguous mainland states it is difficult to place its drinking culture in this environment. per capita apparent consumption for 2005 and the percentage of the population 18 and older reporting past month 5+/4+ days in the 2007 BRFSS survey. The states are listed in descending order by the past month 5+ percentages for those 12 and older in the 2005–6 NSDUH. Considering the regional groupings using the group name variable in terms of the ordering by 5+ percentages shows the groups to make sense in terms of this ordering. The US average is included for reference and all but one (Alaska) of the North Central states and all but one (Maine) of the New England states are seen to be above this average. These are the two groups of states represented as Wet. The Dry South states, seen as the Dry group, are all found below the US average. The three middle groups, Pacific, Middle Atlantic and South Coast are more distributed both above and below and are generally categorized as Moderate in terms of wetness.The District of Columbia was not grouped due to unique characteristics but if a complete grouping is necessary for analytic purposes it would be included in the Middle Atlantic group. The District of Columbia is situated between Maryland in the Middle Atlantic and Virginia in the Dry South but has much higher alcohol consumption than both and differs in many ways, reflecting its unique features. Other states were also difficult to clearly classify. Nevada has increased in the number residents relative to visitors recently and now fits better into the Pacific region while Utah’s drinking pattern fits the Dry South although its drinking culture may not be closely linked to the other member states due to geographic and cultural separation. New Hampshire is another special case where out-of-state buyers inflate per capita apparent consumption illustrates a general but far from complete agreement  survey measures of drinking patterns and e states . These ce states  and to c05–7 surve states . The natFuture studies at the individual-level should utilize and compare the efficacy of these two nested groupings to evaluate differences in drinking patterns, attitudes towards alcohol, and alcohol-related problems and outcomes in US surveys offering detailed measures of these constructs such as the National Alcohol Survey (NAS) and the National Epidemiologic Survey of Alcohol Related Conditions (NESARC). These groups should also be valuable for defining pooled models and matched control groups for cross-section time-series analyses of alcohol policy effectiveness and in estimating relationships between alcohol use measures and mortality or other outcomes in aggregate analyses at the US state level. Tests of the homogeneity of state time-series relationships between alcohol sales and specific mortality causes within and across these groups should also be undertaken to further evaluate group cohesiveness.per capita apparent consumption of alcohol, while a large group of mostly Southern states are found to stand out as relatively low on these measures. The groups incorporate a variety of differing alcohol availability policies and tax levels suggesting the importance of exploring cultural factors such as religion and religious involvement [This paper updates the analyses of US drinking regions last considered over 20 years ago by Alcohol Research Group scientists ,2. The aolvement ,22, raceolvement –25 and molvement . These folvement  and the olvement , as appe


Despite the relatively low recorded alcohol consumption level, the Baltic countries  and neighbouring Finland suffer from similar harmful consequences related to the use of alcoholic beverages, including socio-economic inequalities in alcohol related mortality. Comparative evidence is needed to understand harmful drinking patterns and to implement preventive alcohol policies also in the Baltic countries. This study compared heavy and binge drinking by sex, age, education, urbanisation and marital status in the Baltic countries and Finland.The data were nationally representative postal surveys conducted in Estonia (n = 6271), Latvia (n = 6106), Lithuania (n = 7966) and Finland (n = 15764) during 1994–2002. The criterion for heavy drinking was at least 15 portions weekly among men, and at least five among women, and for binge drinking at least six portions per one occasion.Heavy drinking was more common among younger participants in all countries, and in Latvia among the less-educated. Among Finnish men, and among women from all countries except Latvia, the better-educated were more often heavy drinkers. In Latvia and Finland, urban men, and in all countries, urban women, were more often heavy drinkers. Heavy drinking was more common among non-married Lithuanian and Finnish men, and Finnish women. Binge drinking was more common among less-educated Estonian and Latvian men, and among younger and less-educated women in all countries.Our results support the continued power of traditional drinking habits in the North Eastern part of Europe. In the future the target groups for prevention of excessive drinking should also include young and less-educated women in all four countries studied. Despite the relatively low recorded alcohol consumption level ,2, the BIn the Baltic countries heavy alcohol use is recognised as a social problem , and theLittle evidence is, however, available on changes in the sociodemographic patterning of heavy drinking in the 1990s and early 2000s in the Baltic countries, although mortality studies suggest that this will likely become an important issue in the near future -13. SuchThe Finbalt Health Monitor data  allow haThis study aims to compare the patterning of heavy drinking and binge drinking by key sociodemographic determinants, i.e. sex, age, education, urbanisation, marital status and ethnicity in Estonia, Latvia, Lithuania and Finland in 1994–2002. More specifically, the aims are to examine:1) What is the overall sociodemographic patterning of heavy drinking in these four countries from 1994–2002?2) What kind of changes occurred from 1994–2002 in the sociodemographic patterning of heavy drinking in these four countries?3) What is the overall sociodemographic patterning of binge drinking in these four countries from 2000–2002?Data were collected from nationally representative cross-sectional postal surveys from the Finbalt Health Monitor project in 1994, 1996, 1998, 2000 and 2002 in Estonia, Lithuania and Finland. Lithuanian data on weekly alcohol consumption has been available since 1996. In Latvia, surveys were carried out since 1998. The national surveys have been accepted by respective ethics committees. In Estonia by the Tallinn Medical Research Ethics Committee, in Lithuania by the Lithuanian Bioethics Committtee, in Latvia the Ethical commitee of Riga Stradins university and in Finland by the ethical Committee of the Public Health Institute. In all the countries the covering letter of the questionnaire is formulated in a way that a respondent provides an informed consent by returning the questionnaire.The methodology and questionnaires of the surveys have been standardised . The datIn Estonia, Lithuania and Finland, the questionnaire measured education as the total number of years of education. In Latvia, the questionnaire measured education according to four standard educational levels. In all four countries, the level of urbanisation was based on the administrative classification of the respondent's address. Ethnic origin was dichotomized as 'natives' and 'non-natives'. In the Baltic countries, 'non-natives' comprised mainly Russians.  or bottles of the following drinks have you consumed during the last week (7 days)? If you have not had any, mark 0, i. medium strong or strong beer __ bottles, ii. free-mixed highballs __ bottles, iii. strong alcohol, spirits __ restaurant portions (4 cl.), iv. wine or equivalent __ glasses. In Finland an additional beverage, 'cider or other light wine', was included with 'wine' in our analysis. In Lithuania, the consumption of 'free-mixed highballs' was not asked. Empty responses were included in the 0 consumption category. Distribution of weekly alcohol consumption was skewed to the right in all countries (skewness 4.95–9.03), indicating that the proportion of non-drinkers and moderate drinkers was substantial.Because of this type of data we decided to categorize our respondents into high and low alcohol consumption groups by using comparable criteria for all the countries involved. The feasible cutt-off point was found to be at least 15 portions per week among men, and at least five portions per week among women. It is inevitable that higher consumption group may contain both heavy occasional and moderate frequent consumption, however, in this paper it is called heavy drinkers.  of medium-strong beer . Overall estimates for mean annual pure alcohol consumption in the study period were 2.7 litres per capita in Estonia years 1994–2002), 2.9 in Latvia years 1998–2002), 2.7 in Lithuania (years 1996–2002) and 4.4 in Finland (years 1994–2002). Compared to official consumption statistics [–2002, 2.94–2002, The analysis was carried out in three phases. In the first phase, we examined sociodemographic differences in heavy drinking cross-sectionally in order to include all relevant factors with sufficient detail and statistical power. Logistic regression analysis was used; all models were fitted separately for each country among men and women, and the main effects were included in their assumed temporal order. The effect of age was added first, followed by education, urbanisation and marital status. Interactions between education and each sociodemographic factor were included separately into the mutually adjusted main effects model. , and the criterion for a statistically significant effect was In the second phase, we examined the changes over time in the sociodemographic differences in heavy drinking. Again logistic regression analysis was used. The effect of study year was added first, followed by age , education, urbanisation  and marital status (dichotomous). Models consisting of each explanatory variable were also examined. We assessed changes over time in the associations by including interactions between study year and each sociodemographic factor separately into the mutually adjusted main effects model. The differences between study years are presented in Additional files In the third phase, binge drinking was examined with logistic regression analysis. The effect of age was added first, followed by education, urbanisation and marital status. Interactions between education and each sociodemographic factor were included separately into the mutually adjusted main effects model. , suggesting that the educational gradient was steepest in 1998. No consistent change occurred, however, in the gradient over time (data not shown).Heavy drinking was more common in Finland than in the Baltic countries among both men and women . In younger age groups educational differences were less marked. In Latvian women, the educational gradient was steepest in the age group of 34–39 years. The educational gradient was, however, basically similar to that presented in Additional File P < 0.05). (data not shown)The educational gradient was steepest among Finnish men and women aged 49–64 years, and the interaction of education and age was statistically significant (P < 0.001). In Latvian men, the age gradient was steeper among non-natives than among natives, and the interaction between ethnicity and age was statistically significant (P < 0.05). In Estonian men, the educational gradient was observed only among non-natives, where heavy drinking was most common among the low-educated. This educational difference in non-native Estonian men was statistically non-significant but the statistical significance of interaction between ethnicity and education was P < 0.05. (data not shown)Heavy drinking was more common among the non-natives than the native Estonian women. The mutually adjusted odds ratio was 1.40 (1.07–1.83), and the effect of ethnicity was statistically significant  than among natives.We found that the sociodemographic patterning of heavy drinking was more consistent among women than among men. Heavy drinking was also more common among younger, better-educated and urban men and women in Estonia, Lithuania and Finland. There were no major changes over time in this patterning. Binge drinking was more common among less-educated Estonian and Latvian men and among younger and less-educated women in all countries. In Latvia, both heavy drinking and binge drinking were more common among the less-educated.According to the estimated coverage rates of this study, underrreporting was likely to be substantial -particularly in the Baltic countries. Research into heavy drinking is compromised when alcohol consumption of the majority of respondents falls within the limits of moderate drinking  in populIt has been argued that in the Baltic countries lay people may respond to alcohol surveys in a way they expect the authorities would like them to do -29. AnotSociodemographic differences were more pronounced among women, especially with regard to binge drinking. The use of six portions per one occasion may better indicate excessive use of alcohol among women as studies suggest that simple questions on alcohol consumption are likely to underestimate gender differences in the prevalence of heavier drinking . HoweverAs with other comparative studies , age wasThe Finnish experience shows that drinking habits may change within a relatively short period of time . We alsoThe educational gradient was consistent among men in Latvia, and to some extent in Estonia: the less-educated were more often heavier drinkers. This is in accordance with other surveys ,35 and fExplanations for excessive drinking among the less-educated in Latvia include low price as well as illegal production and sale of alcohol . HoweverIn general, urban people in all four countries tended to drink more. In Finland in particular, the differences were consistent, which agrees with previous evidence . As otheThe association of marital status with drinking was generally expected, as drinking is more common among the non-married. This was the case in Finland especially, but the association was less consistent in the Baltic countries, partly due to low statistical power of the analyses. Our data provided slight support, however, to the assumption that non-married-, and particularly divorced men are a risk group in the Baltic transition economies. For women, smaller-than-expected differences between marital status groups in the Baltic countries may be partly due to parenthood, which has been associated with women's drinking elsewhere  but coulIn Estonia non-native women drank more often than did the natives, which partly contrasts with an earlier survey , but agrWe found no major changes over time in the sociodemographic patterning of heavy drinking, which may suggest that the years 1994–2002 were a period of relative stabilisation in the re-independent Baltic countries after the major shock effects of the economic transition after the collapse of the Soviet regime in the early 1990s. The possible contribution of drinking habits to the increasing educational differences in mortality  and the In short, our study on Estonia, Latvia, Lithuania and Finland supports the continued power of traditional drinking habits in this part of North Eastern Europe. Thus heavy drinking and binge drinking is still much more common among men than women. However, in the future young and less-educated women should be included as a new target group for prevention of excessive drinking in all four countries studied.The author(s) declare that they have no competing interests.All authors participated in the design of the study and writing the manuscript. VH performed the statistical analysis and drafted the first versions. All authors have read and approved the final draft of the paper.The pre-publication history for this paper can be accessed here:Basic characteristics of the study material.Click here for fileConsumption of alcohol beverages in 1994–2002 .Click here for fileHeavy drinking: Consumption of at least 15 alcohol portions per weekamong men by sociodemographic variables in 1994 (excl. Lithuania), 1996, 1998, 2000 and 2002. Unadjusted (unadj.) and mutually adjusted for all other terms in the model (adj) odds ratios (OR) and their 95% confidence intervals (CI).Click here for fileHeavy drinking: Consumption of at least 5 alcohol portions per weekamong women by sociodemographic variables in 1994 (excl. Lithuania), 1996, 1998, 2000 and 2002. Unadjusted (unadj.) and mutually adjusted for all other terms in the model (adj) odds ratios (OR) and their 95% confidence intervals (CI).Click here for fileBinge drinking among men (at least once a week) by sociodemographicvariables in 2000 and 2002. Unadjusted (unadj.) and mutually adjusted for all other terms in the model (adj) odds ratios (OR) and their 95% confidence intervals (CI).Click here for fileBinge drinking among women (at least once a month) bysociodemographic variables in 2000 and 2002. Unadjusted (unadj.) and mutually adjusted for all other terms in the model (adj) odds ratios (OR) and their 95% confidence intervals (CI).Click here for file


Binge drinking is a leading cause of preventable death and results in employee absenteeism and lost productivity. Knowledge about the prevalence of binge drinking among employees of different occupations is limited.We assessed the prevalence of binge drinking  by primary occupation using data from the 2004–2005 North Dakota Behavioral Risk Factor Surveillance System. We used logistic regression to assess the association between binge drinking and primary occupation.Overall, 24.1%  of North Dakota workers reported binge drinking. The prevalence was highest among farm or ranch employees , food or drink servers , and farm or ranch owners . The prevalence was lowest among health care workers . Compared with health care workers, the adjusted odds of binge drinking were highest among farm or ranch employees , food or drink servers , and farm or ranch owners . Health insurance coverage was lowest among employees in occupations with the highest prevalence of binge drinking.We found occupational differences in the prevalence of binge drinking among employees in North Dakota. Many occupational categories had a high prevalence of binge drinking. We recommend the implementation of both employer-sponsored and population-based interventions to reduce binge drinking among North Dakota workers, particularly because employees in occupations with the highest rates of binge drinking had the lowest rates of health insurance coverage. Excessive drinking, including high per-occasion alcohol consumption  and high average daily alcohol consumption, is the third leading cause of preventable death in the United States . In 2001Work-related consequences of binge drinking include unintentional injuries, elevated health care costs, poor job performance, and absenteeism as a result of alcohol-induced hangover or other alcohol-related problems -16. FurtNorth Dakota consistently has one of the highest rates of binge drinking in the nation . The purThe Behavioral Risk Factor Surveillance System (BRFSS) is an ongoing, state-based, random-digit–dialed telephone survey coordinated by the Centers for Disease Control and Prevention (CDC). The survey uses a disproportionate stratified sampling method and is conducted annually by all states . InformaTo our knowledge, North Dakota is the only state that collects information on occupation and binge drinking using the BRFSS. The BRFSS survey assesses employment status with the following question: "Are you currently: employed for wages, self-employed, out of work for more than 1 year, out of work for less than 1 year, a homemaker, a student, retired, or unable to work?" We defined people as "employed" if they reported their employment status as either "employed for wages" or "self-employed." Respondents not meeting criteria for being employed were defined as "not employed."The North Dakota BRFSS began collecting information on occupation in 2004. Data on primary occupation were collected using the following question: "Which of the following most accurately describes the type of work or business you currently work in most often?" Occupational categories selected from the largest known employment categories in the state included state government employee, other government employee, farmer or rancher , other farm or ranch worker , manufacturing, health care, food or drink server , wholesale or retail sales, financial sales, and other. We defined "workers" as all employed respondents who selected one of nine occupation responses or the "other" occupation response. Employed respondents who did not provide their occupation were excluded from all occupation-related subanalyses.We defined binge drinkers as adults who had consumed alcohol during the previous month and who answered "one" or a higher number to the following question: "Considering all types of alcoholic beverages, how many times during the past 30 days did you have five or more drinks on an occasion?" We defined frequent binge drinkers as those who reported binge drinking three or more times during the previous 30 days; we reported this number of frequent binge drinkers as a proportion of total binge drinking workers. Nonbinge drinkers were defined as either respondents who had not drunk alcohol during the previous 30 days  or respondents who had drunk alcohol during the previous 30 days but who did not binge drink.We also assessed health insurance coverage and usage among binge drinkers. We defined "having health care" as a yes response to the following question: "Do you have any kind of health care coverage, including health insurance, prepaid plans such as HMOs, or government plans such as Medicare?" Inability to access a doctor was defined as any respondent answering no to the following question: "Was there a time in the past 12 months when you needed to see a doctor but could not because of the cost?" .We calculated both the crude and age group– and sex-standardized prevalence of binge drinking by occupation; we standardized the prevalence of binge drinking for age group and sex covariates to the North Dakota adult population aged 18 years or older to remove the effects of these factors on the prevalence of binge drinking by occupation in North Dakota . We usedA total of 7055 North Dakota adults aged 18 years or older participated in the BRFSS for 2004–2005. The total response rate was 62% in 2004 and 58% in 2005. On weighted analysis, 67.5% of North Dakotans were employed, and 93.8% of those who were employed provided information about their primary occupation. Of those who gave information on their occupation, 66.2% were classified into one of nine occupations, and the remaining 33.8% were classified as "other."Overall, 19.8% of all North Dakota adults reported binge drinking on at least one occasion during the previous 30 days . The preAmong employed respondents, the prevalence of binge drinking varied by occupation, ranging from 13.2% among health care workers to 45.3% among farm or ranch employees . OverallFarm or ranch employees, food or drink servers, farm or ranch owners, manufacturing employees, employees who selected "other" occupation, wholesale or retail sales employees, and other government employees had significantly higher odds of binge drinking compared with health care workers . We founMore than one-third  of binge drinking workers reported frequent binge drinking (three or more binge drinking occasions during the past 30 days) (data not shown). Among binge drinkers, the prevalence of frequent binge drinking was generally more common among participants in occupations that also had a high prevalence of binge drinking . For exaAmong workers who reported binge drinking, 81.3% had some form of health care coverage , and occExcessive alcohol consumption, including binge drinking, has enormous implications for business and the economy. Lost productivity accounts for approximately three-quarters of the costs of excessive drinking in the United States . In thisTo our knowledge, this is the first population-based study to examine the relationship between binge drinking and occupation. Although no other study has focused on binge drinking, other studies support our findings that people in certain occupational groups  have higher rates of alcohol-related diagnoses compared with people in other occupational groups  -27. FurtAlthough we did not establish a temporal relationship between work and binge drinking, binge drinking among workers can negatively affect the employer, regardless of when the binge drinking occurs. Binge drinking is associated with adverse occupational outcomes ,12,28, aIt was impossible to establish a causal association between occupation and binge drinking during this cross-sectional study. Furthermore, even after controlling for established risk factors for binge drinking, some occupation-specific differences in binge drinking are probably due to characteristics of employees in certain occupations rather than the occupations themselves. Examples of key factors that we could not assess included familial country of origin, religious affiliation, history of alcohol use before employment, and coworker attitudes toward risk-taking behaviors .Employment in certain occupations may be a risk factor for binge drinking. Mandell et al found a cause-and-effect relationship between occupation and alcohol dependence , which mThis study has some limitations. Our prevalence estimates of binge drinking are probably conservative, because alcohol use is typically underreported by respondents  and becaWe recommend the aggressive implementation of effective population-based policy interventions to reduce excessive drinking, because binge drinking was common among most occupational groups and because a substantial proportion of workers in some occupations with particularly high rates of binge drinking were most likely to lack health insurance or report cost as a barrier to health care. Examples of effective policy interventions include increasing alcohol excise taxes, limiting the density of alcohol outlets and hours of sale, and enforcing laws prohibiting the sale of alcohol to people already intoxicated -35. EmplAlthough many employed people might lack access to worksite health programs, the majority of workers in this analysis reported having health insurance coverage, and only one-tenth of workers reported that cost was a barrier to accessing health care. The U.S. Preventive Services Task Force recommends routine screening and brief counseling interventions (SBI) in primary-care settings for alcohol "misuse"  . In cont


As compared to the distribution patternof distinct monoclonal antibody-defined cytokeratins in the normal adult thymus, CKmodulation was evidenced in the three situations studied. During thymus ontogeny,both cytokeratins of simple lining epithelia, as CK8 and CK18, as well as the CK1/CK10pair , were expressed since earlystages of thymus development. They were located in the central region of thymic lobulespreceding the cortical-medullary distinctions. This differed from what had beenpreviously shown for mouse thymus ontogeny, revealing that the interspecific diversityin the distribution pattern of thymic cytokeratins occurred early in fetal life. Amodulation of CK expression was also detected when hamster thymic epithelial cells(TEC) were led to grow in culture, with a down-regulation of CK19 contrasting with anenhancement of CK18 expression. This diverged from the maintenance of the in situpattern when human TEC were cultured. Last, in vivo hydrocortisone treatment, knownto increase the numbers of KL1+ cells in the mouse thymus medulla, promoted a corticalexpression of the CK1/CK10 pair in the hamster thymus. Taken together, our findingsdemonstrate a continuous plasticity of the thymic epithelium, at least regardingcytokeratin expression, and enlarge the concept of interspecific diversity of intrathymicCK distribution in conditions as morphogenesis, in vitro system, and responsiveness toglucocorticoid hormone treatment.Cytokeratin (CK) expression was investigated, by means of immunocytochemistry, inthe hamster thymic epithelium during ontogeny, as well as in primary cultures andupon glucocorticoid hormone treatment


The application of low-voltage direct electrical current (DEC) has been studied in animals and humans for the ablation of anal condylomata, oesophageal cancer and Kaposi's sarcoma. Twenty milliamps of DEC passed through multiple 6 cm x 1 cm, flat-plate longitudinal electrodes into the squamous mucosa of the oesophagus of healthy dogs for periods ranging from 10 min to 2 h resulted in denudation and necrosis of the oesophageal mucosa at the site of application of the current. In humans, the application of DEC to two patients with benign anal condyloma acuminata, three patients with inoperable obstructing oesophageal cancer and one patient with disseminated Kaposi sarcoma resulted in striking necrosis of tumour tissue that was confirmed by macroscopic and microscopic studies. These initial findings imply promising therapeutic potential for the use of DEC as a simple, effective, safe, low-cost alternative for ablation of neoplasia.


We sought to determine predictors of drinking the month before and after beginning college, as well as changes in drinking between these two periods among adjudicated students. We conducted these analyses to inform individual and university-wide approaches to addressing underage drinking, particularly among the heaviest drinkers.The sample consisted of 143 students entering college, adjudicated during their first semester, and interviewed during the same semester. The sample consisted of 43% women. Drinking data were collected through the Time-Line Follow-Back interview.The average number of drinking days (DD) during the first month of college was 7.0 (SD = 4.7), the average number of drinks per drinking day (DDD) was 7.4 (SD = 3.4), and the average volume of standard drink units consumed during this month was 56.3 (SD = 51.2). Students had volunteered for a two-year college facilitation study, and had been invited to participate after receiving a citation for violating university alcohol policies. Analyses consisted of nine backward elimination regression analyses with nine variables entered as predictors (one was a control variable). Age of first intoxication was related to every dependent measure. Men had a higher August DDD, September DDD, and September volume than women. Roommate drinking level was associated with September DDD and September volume. Out-of-state students had a lower August volume than in-state students. High school rank was inversely related to September drinking days. SAT score, declared major status, and fraternity/sorority status were not related to drinking according to these multivariate analyses.Results suggest that approaches to underage drinking for adjudicated students may need to be tailored according to age of first intoxication. Results also suggest the drinking level of the heaviest drinking roommate may moderate individual level interventions. Further, interventions applied to an entire dorm room may prove efficacious. Results also suggest that high school rank, rather than SAT scores, should be used as college entry criteria to yield a drier incoming class. Results may not generalize to non-adjudicated students. Heavy drinking by college students negatively impact themselves and those around them . Negative impacts for heavy drinkers include impaired academic performance  personalMany universities have disciplinary sanctions and/or fines for students observed drinking on campus . This grA promising line of research for college students in general, consists of the study of specific events and transitions in the context of college drinking . NeighboWe have collected drinking data using the Time-Line Follow-Back  inquirinFirst Offenders of the University's Alcohol and Drug Policy were invited to participate in the College Facilitation 3 Study. This study is a large randomized trial of College Facilitation. College Facilitation consists of 18 planned telephone contacts once a month during the academic year for a total of two calendar years. The tone of the calls is non-confrontational, supportive, and empathic. College Facilitation is designed to reduce drinks per drinking day, to reduce peak drinking levels, and to reduce the frequency of drinking related consequences within the context of helping the student get the most out of college, both academically and as a well-rounded person. The College Facilitation protocol is based on the Extended Case Monitoring protocol ,14 whichThis research was carried out in compliance with the Helsinki Declaration and is approved by the Institutional Review Boards of the Pacific Institute for Research and Evaluation and the university where the study was conducted. After providing documented informed consent, students completed an interview that included closed-ended questions, open-ended questions, surveys, and the semi-structured Time-Line Follow-Back. We closed participant recruitment in September 2007 with a sample of 374. This analysis focuses on Freshmen recruited during the Fall 2005 and 2006 semesters. During the course of recruitment approximately 20 adjudicated students had less than two heavy drinking days in the last 28 days, and were therefore ineligible. Approximately 16 students that were eligible were not interested in participating in the study. One student was underage when recruited, and s/he was not interested in the study after s/he turned 18.All but 16 of the 143 freshmen in the sample had at least 28 days of data following the opening of the dorms. The duration of the data for the other 16 ranged from 23 to 27 days, and their drinking volume and number of drinking days were prorated to make up for the shorter assessment window. Participants for the results presented here consist of college students beginning their first semester of college and interviewed between September 26, 2005 and December 19, 2005 or between September 25, 2006 and December 7, 2006 (inclusive). Dormitories opened on Saturday September 3, 2005 and September 2, 2006. We operationalized the first month of college as the first 28 days starting with the opening of the dormitories.  We used an integer number of weeks to control for the variation in drinking during the week . We operThe eight hypothesized predictor variables can be grouped into pre-collegiate and collegiate variables. Pre-collegiate variables, in turn, can be grouped into demographics , academic variables , and drinking history (age of first intoxication). Collegiate variables include fraternity status, whether the student has declared a major, and the heaviest drinking status of the student's roommate(s). These variables can also be used to describe the sample of 143. The sample consisted of 43% women. (The incoming class of 2006 was 56% women.) The average age of first intoxication was 15.7 (SD = 1.4). Age of first intoxication ranged from 12 to 18 years old. The average high school rank was the 70th percentile . The mean SAT score was 1130 (SD = 120) out of a possible 1600 points, and 29% of the students were in-state residents. Sixty nine percent of the students had declared a major. Eight percent were fraternity/sorority members or pledges. All participants had at least one roommate. Participants were asked whether their roommate was a heavy, moderate, or light drinker, or abstainer. If a student had more than one roommate, the heaviest drinking roommate was counted. Five percent reported that their heaviest drinking roommate was an abstainer, 18% reported a light drinker, 64% reported a moderate drinker, and 13% reported that their heaviest drinking roommate was a heavy drinker. We also included one control variable: 39% of the participants were written up during the September window. (None of the participants were written up during the August window.) Most (61%) were written up after the windows of drinking data presented here. All of the data presented were based on self-report. Participants were compensated $25 for their participation in the baseline assessment.An examination of the distributional characteristics of the drinking variables revealed that these variables approximated the normal distribution, in contrast to DDD and DD observed in clinical samples . Paired The eight predictor variables and one control variable were entered into a backward stepwise regression analysis for each of the nine dependent variables. Age of first intoxication was related to every dependent measure. Men had a higher August DDD, September DDD, and September volume than women. Roommate drinking level was associated with September DDD and September volume. Out of state students had a lower August volume than in-state students. Out of state students showed a marginally significant increase in volume, relative to in-state students. High school rank was inversely related to September drinking days (better grades less drinking). High school rank was marginally inversely related to September volume. High school rank was marginally related to a decrease in drinking days. On the other hand, SAT score, declared major status, and fraternity/sorority status were not related to drinking according to these multivariate analyses . If the students were cited for violating university policy in September (as opposed to later in the first semester) the students were marginally likely to have a greater August volume, and were drinking on more days in September.  were first intoxicated almost a year younger on average than in-state students  indicating that residency does predict August volume when age of first intoxication is taking into account through the multivariate analysis.The reductions in drinking volume and DDD from August to September were initially surprising, given the literature's focus on problematic alcohol use during college. Future research should investigate whether this finding is specific to adjudicated students or generalizes to Freshmen in general. While some studies ,20 have The reductions in drinking volume and DDD from August to September suggest that parents ,22 shareWhile high school rank and SAT scores are correlated with each other, only high school rank is related to September drinking in this sample. SAT scores reflect academic aptitude and high school rank reflects actual academic performance. The regression results suggest that high school rank would be a useful university eligibility criterion that could also lead to a drier student population, whereas SAT scores are not a useful criterion in this regard.Students with an earlier first intoxication had greater drinking levels in August and September than students with a later first intoxication. However, students with an earlier first intoxication showed decreases in drinking from August to September, while students with a later intoxication showed increases in drinking during this time period. There is a convergence in drinking behavior across the sample as indicated by the constriction in variance (a reduction in variability) across drinking days and volume. Access to alcohol may vary widely across the participants in August  but will be more uniform in September since most if not all the Freshmen lived in the dorms. For students with an earlier age of first intoxication the supervision of a residence hall advisor may reflect a healthier environment than the one they left. For students with a later age of intoxication, the college environment may reflect a less structured environment than the one they left. Figure There are a number of caveats and limitations with the present findings. These results may not generalize to all universities. Reflecting the demographics of this university (with 27% minority students) coupled with the risk for heavy drinking among minority students, minorities were not well represented in this sample (4%). All of the data (including drinking data) are self-report. Most of the predictor variables utilized in these analyses may be conceptualized as demographic variables. Variables such as alcohol expectancies and decisional balance, known to be related to drinking variables, were not examined. Further, the analyses do not examine potential moderators . The null finding regarding fraternity/sorority status should be treated with caution. Only 8% of the sample consisted of members or pledges, so we had insufficient statistical power to detect a difference on this variable. Further, since we recruited students early on, they may have not had the opportunity to pledge or join fraternities and sororities. While representative of both sexes, the sample is not representative of minorities. While the roommate's drinking was a predictor, we are unable to tease out selection versus socialization. We did not ask if the participant knew, or drank with, their roommate before beginning college.This study has policy, prevention, and intervention implications. Results suggest that approaches to underage drinking for adjudicated students may need to be tailored according to age of first intoxication. Results also suggest the drinking level of the heaviest drinking roommate may moderate individual level interventions. Further, interventions applied to an entire dorm room may prove efficacious. Results also suggest that high school rank, rather than SAT scores, should be used as college entry criteria to yield a drier incoming class. Age of first intoxication predicted all nine dependent measures, and is an important possible point for prevention efforts, and an important variable in college drinking research. Sex is an important variable in college drinking research, especially in regard to drinks per drinking day.1stIntox: age of first intoxication, DD: drinking days, DDD: drinks per drinking day, HS: high school, M: mean, SAT: Scholastic Aptitude Test, SD: standard deviation, Vol: volume.The authors declare that they have no competing interests.HRJ recruited, interviewed and administered surveys to participants, entered data, and provided substantial input on the manuscript. WHZ is the PI of the NIAAA grant, has overall primary oversight of the day to day operations of this project, conducted the statistical analyses, wrote the first draft of the manuscript, and was responsible for the editing of the final draft. DDG has primary oversight of HRJ and provided substantial input on the manuscript. RLS assisted with conceptualizing the design of the overall study, assisted with finalizing the statistical plan of the overall study, and provided substantial input on the manuscript. WBT and JEL provide the college facilitation telephone contacts and provided substantial input on the manuscript. FCC was the liaison to the Vice President of Student Affairs, and provided substantial input on the manuscript. All authors read and approved the final manuscript.


Plasmodium falciparum. However, screening of Haitian refugees in Jamaica in 2004, by microscopic examination, identified P. falciparum, P. vivax, and P. malariae. PCR confirmed the P. malariae and P. falciparum but not P. vivax infections. DNA sequencing and rRNA gene sequences showed transmission of P. malariae. This report confirms that P. malariae is still being transmitted in Haiti.Since 1963, reported malaria transmission in Haiti has been restricted to  Plasmodium malariae and 1 P. vivax) were reported  of the 869 million persons live in areas where ecologic conditions have been propitious for the transmission of malaria  was chosen by the Ministry of Health for inclusion in this aspect of the study. These samples included 30 P. falciparum. P. malaria, or P. vivax by using either the single-round PCR protocol of Padley et al.  were sent to the Heath Protection Agency, Malaria Reference Laboratory, London School of Hygiene and Tropical Medicine, for species confirmation by PCR. DNA was extracted from 105 filter-paper blood spots and tested for DNA from P. vivax were found with PCR. The absence of P. vivax was verified by species-specific real-time PCR, as described by de Monbrison et al. .Four P. malariae rRNA gene sequences in GenBank, and to that of P. brasilianum that had been isolated from a monkey in French Guiana  by using the program T-Coffee (http://ca.expasy.org/tools/#translate). The alignment produced is presented in the P. malariae rRNA gene sequences in GenBank and with that of the indistinguishable simian parasite, P. brasilianum  because the population is immunologically naive and the competent vector,


T cell progenitors derive from the bone marrow but must migrate via bloodstream to the thymus in order to differentiate. The mechanism by which the thymus recruits progenitors from the blood is unknown. It is known, however, that there are receptive and refractory periods for progenitor recruitment and that when cells are imported, they enter the thymus through post-capillary venules. Therefore, recruitment is an active process temporally and spatially regulated. In order to characterize the mechanism of recruitment, we evaluated vascular signals known to regulate leukocyte extravasation, with respect to their intrathymic location and temporal fluctuations. We find that CD34, MECA79, VCAM-1, ICAM-1 and VAP-1 are all expressed in thymic blood vessels. MECA79 and VAP-1 appear to be specific for post-capillary venules, while ICAM-1 and VCAM-1 are also found on intrathymic stromal cells. MAdCAM is also expressed in the thymus, but is not associated with vascular tissues. Only MECA79 is upregulated during recruitment peaks, suggesting a role for this molecule in the periodicity of recruitment. Together, these studies reveal potential roles for l-selectin ligands, VCAM-1, ICAM-1 and VAP-1 in progenitor recruitment to the thymus, and implicate the presence of other periodic signals, such as chemokines and cytokines, that cooperate to execute this essential function.


The presence in the thymus of hemopoietic cells other than thymocytes has been known formany years, but the extent of the hemopoietic activity of the thymus and the possiblefunctional implications have only recently begun to receive much attention. This reviewsummarizes the literature in this field, especially in the light of current cytokine andthymic-factor knowledge, and includes clinical relevance where possible.