Harmful alcohol consumption is a major risk factor for ill-health on an individual level, a global public health challenge, and associated with workplace productivity loss. This study aimed to explore the proportion of risky drinkers in a sample of employees, investigate sociodemographic associations with risky drinking, and examine implications for intervention needs, according to recommendations from the World Health Organization (WHO).n = 3571) across sectors and branches. Risky drinking was measured with the Alcohol Use Disorders Identification Test (AUDIT). The threshold for risky drinking was set at ≥8 scores on the AUDIT. Based on WHO guidelines, risky drinkers were divided into three risk categories . The association between sociodemographic variables and risky drinking were explored with chi square tests for independence and adjusted logistic regression. The risk groups were then examined according to the WHO intervention recommendations.In a cross-sectional design, sociodemographic data were collected from Norwegian employees in 14 companies (p < .001), younger age , low education , being unmarried  and not having children . Risky drinking was most common among males without children (33.5%), males living alone (31.4%) and males aged ≤39 (26.5%). 94.6% of risky drinkers scored within the lowest risk category. Based on WHO guidelines, approximately one out of ten employees need simple advice, targeting risky drinking. In high-risk groups, one out of three employees need interventions.11.0% of the total sample reported risky drinking. Risky drinking was associated with male gender , particularly young, unmarried males without children and higher education, may be characterised as risky drinkers. This group may benefit from low-cost interventions, based on recommendations from the WHO guidelines. Harmful alcohol consumption is a major risk factor for disease, disability and mortality, and has been identified as a causal agent in more than 200 disease and injury conditions . AccordiAlcohol is by far the most used and misused psychoactive substance in the workforce and employees’ alcohol consumption is associated with productivity loss, and therefore with considerable economic costs at a societal level . A recenRisky drinking may be defined as a drinking pattern that increases the risk of social, legal, medical, occupational, domestic, and economic problems . It is, Risky drinking has been studied within different populations across countries, with prevalence estimates varying between 5.4 and 52.0% –16. In aEarly identification and intervention may be beneficial in preventing the development of alcohol problems. Knowledge on associations between sociodemographic factors and risky drinking may aid in determining which groups of employees that may need and benefit the most from early identification and interventions targeting alcohol-related problems. Some studies have demonstrated associations between risky drinking and sociodemographic variables, generally suggesting that risky drinking is more prevalent among younger individuals and males , 17, 23,The majority of the adult population is employed and employees with a risky drinking pattern constitute a much larger group than heavy drinkers . The worThe aims of the study were therefore to (a) explore the proportions of risky drinkers in a sample of Norwegian employees by utilising an internationally validated alcohol screening instrument, (b) investigate sociodemographic associations with risky drinking, and (c) examine implications for intervention needs, based on World Health Organization guidelines.n = 5) and public companies (n = 9) in Norway, employing approximately 14.353 individuals.The present study is one of several studies in the Norwegian national WIRUS-project . Other results from the WIRUS-project are published elsewhere , 30. ThiAlcohol consumption in the general Norwegian population per person per year (7.7 l) is somewhat lower compared to the rest of Europe (10.9 l) and the United States 9.2 l) [ l [2]. A4432 employees (30.9%) responded on a web-based questionnaire designed to measure alcohol consumption as well as sociodemographic variables. 3571 employees, 32.6% males and 67.4% females, responded on all items (24.9%), and thus constitute the sample in the present study. Study sample and invited sample characteristics are presented in Table Approximately seven out of ten employees were aged 40 or older and had completed a university or college education. Only 13.9% of employees lived alone, while nearly half (43.5%) of the sample was unmarried. Almost eight out of ten employees had children, while close to six out of ten had children living in their household. Approximately two out of ten employees were classified as managers, and the majority of employees were employed within public administration (75.5%) and health care services (16.6%). Information on gender and age distributions among all employees in the 14 companies (invited sample) was collected through the companies’ personnel records.Alcohol consumption was measured with the Norwegian version of the Alcohol Use Disorders Identification Test (AUDIT), developed by the WHO . The AUDThe AUDIT has been referred to as the global gold standard of alcohol screening instruments . It is dGender , living status , marital status (unmarried/married), children (having no children/having children), children in the household (having no children at home/having children at home) and work position (worker/manager) were coded as dichotomous categorical variables. Age was collapsed into categories (≤39/≥40) for application in chi square test for independence, and treated as a continuous variable in the logistic regression model. Educational level was collapsed into two categories (without/with higher education) for utilisation in chi square test for independence, and treated as a categorical variable with four levels  in the logistic regression model.Proportions of risky drinking were estimated by calculating the proportion of employees exceeding the cut off (≥8 scores) on the AUDIT, for the overall sample as well as cross-tabulated proportions for males, females and both genders according to age, educational level, living status, marital status, number of children, number of children living in the household and work position. Bivariately, a series of chi square tests for independence were applied in order to explore whether gender, age, educational level, living status, marital status, number of children, number of children living in the household and work position were significantly associated with risky drinking. Next, adjusted logistic regression was conducted to assess the influence of the sociodemographic variables on the likelihood that employees would report risky drinking. Implications for intervention needs and approaches were investigated by calculating the proportions of risky drinkers in risk levels according to sum scores on the AUDIT , and evaluating the risk level distributions in accordance with World Health Organization intervention recommendations.p < .05.All statistical analyses were performed with IBM SPSS version 24. Significant results were defined as Respondents were informed about the study’s aim, assured confidentiality and that participation was voluntary. We further collected written informed consent. The study was approved by the Regional Committee for Medical and Health Research in Norway (REK) .3179 employees (89.0%) scored within the low-risk category, while 392 employees (11.0%) had an AUDIT score equal to or above the cut off. Cross-tabulated proportions of risky drinking for males, females and both genders according to age, educational level, living status, marital status, children, children in househould and work position are presented in Table Risky drinking was found to be most widespread among males without children (33.5%), males living alone (31.4%), and males aged ≤39 (26.5%). Risky drinking was least widespread among married females (4.8%), females with children (5.2%) and females aged ≥40 (5.2%).2  = 90.34, p < .001, phi = 0.16), age  = 53.77, p < .001, phi = 0.12), educational level  = 4.34, p < .05, phi = 0.04), living status  = 32.01, p < .001, phi = 0.10), marital status  = 61.33, p < .001, phi = 0.13), children  = 126.44, p < .001, phi = 0.19), and children in household  = 36.87, p < .001, phi = 0.10). Employees’ work position was not significantly associated with risky drinking  = 2.19, p > .05, phi = .03).A series of unadjusted chi square tests for independence demonstrated statistically significant bivariate associations between risky drinking and gender  = 238.19, p < .001, indicating that the model was able to distinguish between employees who reported risky drinking and those who did not. The model explained between 6.5% (Cox and Snell R2) and 12.9% (Nagelkerke R2) of the variance in risky drinking, and correctly classified 88.8% of cases. As shown in Table p < .001), indicating that male employees were almost three times as likely as female employees to report risky drinking, adjusted for all other variables in the model. For each year of age less, the odds ratio for reporting risky drinking increased by a factor of 1.03 (p < .001), while for each decreasing unit of education, the odds of risky drinking increased by a factor of 1.17 (p < .05). With an odds ratio of 1.38 (p < .05), unmarried employees were more likely than married employees to be risky drinkers. Employees without children had a greater odds  for risky drinking compared to employees with children.The adjusted multivariate logistic regression model was statistically significant, χ2 8, n = 571 = 238There were tendencies for employees living alone and not having children in the household to have greater odds for risky drinking, compared to employees living with others and with children in the household. These associations, however, did not reach statistical significance when adjusting for all other factors in the model. Employees’ working position demonstrated neither a bivariate or a multivariate association with risky drinking.Employees’ risk level assessments for the overall sample as well as for identified at-risk groups , categorised by AUDIT sum scores and intervention recommendations, are presented in Table The aims of the present study were to explore the proportions of risky drinkers in a sample of Norwegian employees by utilising an internationally validated alcohol screening instrument, to investigate sociodemographic associations with risky drinking, and to examine implications for intervention needs based on WHO guidelines. The following main findings will be discussed: (a) Overall, approximately one out of ten employees reported risky drinking, (b) risky drinking was found to be associated with and most common among males, younger employees, employees with low education, unmarried employees and employees without children, and (c) the majority of identified risky drinkers scored within the lowest defined risk level, i.e., with moderate risk that may be addressed by means of low-cost interventions.Most comparable to our study, Halkjelsvik and Storvoll  did findStill, the present study found estimates of risky drinking (11.0%) marginally higher than what has been found in several other studies of employees, with estimates ranging from 6.0 to 8.8% –21, 23. In accordance with previous studies , 17, 23,Even though evidence on the relationship between age and alcohol consumption is somewhat inconclusive, cross-sectional studies have demonstrated lower consumption levels at older ages, and longitudinal studies have revealed decreased consumption and drinking prevalence with increasing age . Also, hIn line with similar studies , 17, theIn line with Halkjelsvik and Moan , we founThe present study has some limitations. Conducted within a cross-sectional design, we have identified associations between sociodemographic variables and risky drinking. It is, however, not possible to draw causal conclusions from these associations. Moreover, risky drinking may be influenced by a great variety of variables not measured and included in this study.n = 3571) from the Norwegian working community. The final response rate, however, was low (24.9%). Comparisons between the study sample and the invited sample (see Table p < .001), with a 4.2 percentage point overrepresentation of employees aged 40 and older. Generalisations should therefore be done with caution. Low response rates may contribute to prevalence estimates biased by non-response, and non-response bias may be a greater threat to prevalence estimates than to associations between variables [The present study was based on a relatively large sample n = 357 from theariables . Althougariables –46. HencThe study benefited from utilising the AUDIT as a measure of alcohol consumption, a widely validated tool , 35, desSociodemographic associations identified in this study do imply that in some groups, a much larger proportion, (up to one in three) may be particularly exposed to risky drinking, i.e., males, young employees, employees with low education, unmarried employees and those without children. However, identified sociodemographic correlates may not be conceived of as a check list that can inform employers about each employee’s level of alcohol risk. Knowledge of a set of significant correlates of risky drinking may, on the other hand, be directive in determining which and to what extent companies should make alcohol-preventive measures an overall priority, and for early identification purposes.In the present study, more than nine out of ten risky drinkers scored within the lowest risk category, implying that low-cost interventions (such as simple advice) on an individual and/or collective level may be serviceable and sufficient for the majority of risky drinkers. On an individual level, such interventions may be administered by the occupational health services or primary health care services. A stepped-care approach , 48 may The present study carries some implications for future research. In the research literature, it is evident that a variety of measures of alcohol consumption and thresholds for risky drinking are employed and few studies have ulitised internationally validated instruments. Such diversity and lack of standardisation makes it difficult to compare studies and assess whether observed differences are due to actual variation within populations or differences in measurement and conceptualisation. Future research should attempt at establishing more consensus on how to measure and conceptualise risky drinking.In this study we found that lower education was associated with risky drinking. This finding contradicts previous findings that generally suggests an association in the opposite direction. Hence, future research would benefit from engaging in a more thorough exploration of the association between educational level and risky drinking, e.g., by means of longitudinal studies and studies investigating possible moderators and mediators of this relationship.A considerable amount of employees (between one and three out of ten) were identified as potential risky drinkers. Being male, young, having low education, being unmarried and not having children seem to characterise employees at particular risk. However, as many as nine out of ten risky drinking employees scored within the lowest risk level. Potentially, low-cost workplace-based interventions may be a cost-effective measure to meet a major challenge that faces individual employees, employers as well as larger society.


Adolescents not only vary in their alcohol use behavior but also in their motivations for drinking. Young people living in different neighborhoods may drink for different reasons. The aims of this study were to determine if neighborhood characteristics were associated with adolescent drinking motives, and whether drinking motives mediate the relationship between neighborhood context and regular alcohol use. Data from the Scottish Health Behaviours in School-aged Children 2010 survey of students in their 4th year of secondary school were used. The study included 1119 participants who had data on neighborhood characteristics and had used alcohol in the past year. Students were asked questions about the local area where they lived, their alcohol use, and their motives for drinking alcohol, based on the Drinking Motives Questionnaire Revised Short Form (DMQR-SF). Multilevel multivariable models and structural equation models were used in this study. Coping motives showed significant variation across neighborhoods. Structural equation models showed coping motives mediated the relationships between neighborhood deprivation, living in an accessible small-town, and neighborhood-level disorder with regular alcohol use. Public health policies that improve neighborhood conditions and develop adaptive strategies, aimed at improving alcohol-free methods for young people to cope better with life’s stresses, may be particularly effective in reducing inequalities in adolescent alcohol use if targeted at small towns and areas of increased deprivation. Research has shown that adolescent alcohol consumption varies across neighborhoods ,2. AdoleDrinking motives are often regarded as the final pathway to alcohol use, which link to various drinking patterns and may mediate more distal influences ,8. CurreDrinking motives are defined as the reasons why people drink, with the assumption that people drink to obtain a desired outcome . These mInternally generated, positive reinforcement = enhancement, i.e., drinking to have fun and get drunkExternally generated, positive reinforcement = social, i.e., to better enjoy social gatheringsInternally generated, negative reinforcement = coping, i.e., to alleviate problems and worriesExternally generated, negative reinforcement = conformity, i.e., not to feel left outThe dimensions and source map onto the four motives as follows:Motives are often theorized as a potential pathway between neighborhood characteristics and alcohol use. The most common hypothesis is that in stress-inducing neighborhoods  alcohol is used to cope with the increased pressure that comes from living in such an environment ,17,18. PA review undertaken by Kuntsche et al.  examinedResearch is needed to identify sub-groups of young people who have varying drinking motives . AdditioAre characteristics of the neighborhood associated with adolescent drinking motives?If so, is there evidence that motives mediate the relationship between neighborhood conditions and adolescent alcohol use?Research questions:Survey data were collected as part of the 2010 Scottish Health Behaviour in School-aged Children (HBSC) survey, a World Health Organisation cross-national study . The 201Residential location was determined by self-report of home postcode by the pupils. Ethical approval for use of the postcode data, which is not part of the public data file, was granted by the University of St Andrews Teaching and Research Ethics Committee (reference number: MD11023). In Scotland, postcodes represent a small geographical area making it possible to geocode (assign a latitude and longitude) based on this information. Additionally, many administrative boundaries are built of postcodes; for example, Scottish data zones (DZ) and intermediate data zones (IDZs) are higher levels of geography which contain multiple postcodes. DZs (of which there are 6505) have on average 750 residents. IDZs are built up from DZ, representing 1235 regions in Scotland, containing on average 4000 residents. IDZs were developed based on administrative data and local knowledge [To be included in the analysis students had to report their home postcode and reside in an IDZ that had 5 or more survey participants (n = 1558). This allowed for adequately reliable measures of neighborhood-level social cohesion and disorder ,24,25. FDrinking motives were measured using the four factor Drinking Motives Questionnaire Revised Short Form (DMQR-SF). This questionnaire was developed and validated by Kuntsche and Kuntsche  from theImputations were carried out in cases where one item was missing on a motives scale, using the person-scale average (enhancement = 45 cases (4%); social = 20 cases (1.8%); conformity = 6 cases (0.5%); coping = 4 cases (0.4%) . CronbacAll motives were log-transformed to reduce skew and approximate a normal distribution. This was done after preliminary examination found that the residuals in the full models were not normally distributed. Descriptive statistics are reported on the motives before transformation.Weekly drinking was determined from the question: “at present how often do you drink anything alcoholic, such as beer, wine, or spirits? Try to include even those times when you only drank a small amount” Responses included frequency of consumption . Those who reported drinking any beverage type daily or weekly were coded as weekly drinkers.Neighborhood deprivation was determined by the income domain of the Scottish Index of Multiple Deprivation (SIMD) 2012, which is comprised of several indicators of income deprivation . This meData on alcohol outlet density were obtained from the Centre for Research on Environment, Society and Health at the University of Edinburgh who geocoded all premises that held a license to sell alcohol in 2012 based on postcodes. These data were used to estimate a measure of AOD using Kernel Density Estimation (KDE). This process divided Scotland into 100 × 100 m grid cells and assessed the number and proximity of outlets at a radius of the center of each cell. Outlets nearer the center were given greater weight than those further away; therefore, the value represents a proximity-weighted estimate of the density of each outlet type. Data were classified as on-trade  and off-trade  .Perceived social cohesion was measured using three questions: in the area where you live (1) you can trust people around here, (2) people say “hello” and talk to each other in the streets, and (3) it is safe for younger children to play outside. Responses ranged from “agree a lot” to “disagree a lot”, on a five-point scale. The Cronbach’s alpha of the sample at the individual level  was 0.754. Perceived disorder was measured using the same procedure. Three questions were used in this measure: in the area where you live are there (1) groups of young people who cause trouble? (2) litter, broken glass, or rubbish lying around? and (3) run-down houses or buildings? Responses ranged from “none” to “lots”, on a three-point scale. The Cronbach’s alpha at the individual level (perceived disorder) was 0.758.Neighborhood-level social cohesion and neighborhood-level disorder measures were constructed by combining individual responses within an IDZ unit. This was done using a three-level item response model  accounting for item severity and pupil’s sex as an individual-level covariate. More details can be found in Martin et al. . The relSex was included as a covariate as previous studies have found differences between boys and girls on several of the drinking motives . To testAge was not included as a covariate as all the adolescents were in the same grade and there is no hypothesized reason for drinking motives to vary due to small differences in age  examining motives as an outcome, and (2) exploring for mediation (indirect effect) of motives on alcohol use.In the first stage, associations between neighborhood characteristics and drinking motives were assessed using multilevel regression modelling. Empty models were tested to examine the variation of drinking motives across neighborhoods (IDZs). A linear model controlling for demographics and family characteristics  (Model 1) was conducted. Neighborhood characteristics were then included in a subsequent model (Model 2). Individual perceptions were adjusted for in a final model (Model 3). These analyses were conducted using runmlwin in Stata and MLWin using Markov chain Monte Carlo (MCMC) methods. These procedures do not produce point estimates, instead many iterations are run and for each evaluation a distribution is formed. From this accuracy interval estimates are produced, namely credible intervals, which can be interpreted similarly to confidence intervals. The mean of the distribution can be obtained and used as substitute for a point estimate. A p value can be derived and interpreted as the probability of the (null) hypothesis . A startAssumptions for using a linear regression model were evaluated by visual inspection of plots of residuals versus predicted values to examine for heteroskedasticity, residual Q-norm plots on the full models to test for normality, and a Global Moran’s I was calculated on the model residuals at the neighborhood-level to test for spatial autocorrelation in the model.pIn the second stage of analysis, based on findings of the previous models (where neighborhood characteristics were associated with specific motives), potential mediation of the drinking motives on the relationship between neighborhood characteristics and alcohol use were explored. Cooper et al.  lay out I) >0.95 . AnalysiI) >0.95 . The MODThe characteristics of the study sample are given in p = 0.038)) with 5.2% of variation being explained by the neighborhood in which the adolescents resided. A cross-classified model was also specified for coping motives accounting for school-level variance, which reduced the amount of variance accounted for by neighborhood to 2.9% and Bayesian DIC improved (1627.80 versus 1633.47). Enhancement motives had 1.9% of variation explained by the neighborhood in which the adolescents resided and a very small improvement in Bayesian DIC was found when including the neighborhood-level (difference = 0.48). The other two drinking motives had <1.5% of variation explained by neighborhood.Although empty models supported that coping and, to some degree, enhancement motives were the only motives to vary across neighborhoods, further models were still conducted on all four motives to examine the associations with demographic factors and perceived neighborhood conditions, as previous work has found that perceptions of neighborhoods are predictive of adolescent drinking motives .p = pp = 0.048, approximately 15% higher) compared to those in urban regions. Additionally, those residing in the least income deprived areas  and the less income deprived areas  had lower coping motives, compared to those in the most deprived areas. Those in the third category of deprivation also had reduced coping motives but this finding only neared significance (p = 0.055) when accounting for individual perceptions. Neighborhood-level disorder was positively associated with coping motives, but when adjusting for perceptions of the neighborhood this was no longer significant (p = 0.035). A 1 unit increase in perceived disorder was associated with about a 3% increase in coping motives. Including school-level variance by specifying a cross-classified model made little difference to the results  (see lly) see . Althougp = 0.030). Perceived disorder was also positively associated with enhancement motives (p = 0.039). Additionally, enhancement was positively associated with family structure, with students from single-parent families having greater enhancement motives compared to those living in two biological parent families . Conformity motives were higher for males than females  and lower in the second most income deprived neighborhood category compared to those in most deprived (p = 0.010).For social enhancement and coping motives there were few instances where neighborhood characteristics were associated with motives see . When exIn terms of residual diagnostics, Moran’s I showed no significant autocorrelation between neighborhood residuals indicating that spatial autocorrelation is not of concern in these models. The Q-norm plots see  show thaPath analysis was carried out examining coping as a potential mediator because of the significant variation across neighborhoods and the observed associations between neighborhood conditions. Neighborhood deprivation and living in an accessible small-town have previously been found to be associated with regular alcohol use among Scottish adolescents ; therefoppppp = 0.002) and the second most deprived category (p = 0.002) through coping motives to weekly drinking. The effect was also indirect for those living in an accessible small-town (p = 0.037) through coping motives to weekly drinking. Moreover, significant indirect effects were found from neighborhood-level disorder through perceptions (p = 0.022) and through coping motives  deprived neighborhoods create stress due to the physical and social conditions of the neighborhood, and alcohol is used to cope with the stress created by the environment, and (2) those residing in such neighborhoods have different strategies for coping with life’s general stresses and are more likely to use alcohol to deal with problems . BecauseNeighborhood-level disorder was associated with coping motives indirectly through perceived disorder. Moreover, perceived disorder was associated with social and enhancement motives. This is similar to findings that perceptions of violence and robberies, as an indicator of disorder, are associated with drinking to cope , highligThose living in accessible small towns had higher coping motives than their peers living in large cities. Few studies have examined the health of adolescents residing in small towns on the periphery of larger urban areas. Research in the US examined affluent suburban adolescents compared to disadvantaged urban adolescents and found that suburban youth reported significantly higher levels of substance use than urban adolescents and that anxiety levels were also higher . HoweverMediation analysis found that neighborhood deprivation and living in an accessible small-town were indirectly associated with weekly drinking through coping motives. This supports previous research that found the effects of neighborhood socio-economic status on substance use outcomes were likely to be indirect ,52. AddiDrinking motives are a concept that may aid in better targeting and designing prevention and intervention programs for at-risk adolescents ,55. The This research has several strengths. First, it examines multiple conditions of the neighborhood to determine which specific conditions may be associated with adolescent drinking motives. Second, to the best of our knowledge, this is the first study which tests for a potential mediation effect of drinking motives on the relationship between neighborhood characteristics and alcohol consumption among adolescents. However, there are several limitations to consider. This work did not account for personality traits and so further work is needed to understand how personality might impact the relationship between neighborhood conditions and alcohol use. However, altering individual intrinsic factors such as personality may be more difficult than modifying or targeting the neighborhoods where young people reside. Furthermore, this study is cross-sectional, so causation cannot be inferred. Time-series analyses and evaluation studies are needed to understand the impact of changes in the neighborhood on drinking motives and alcohol use . The datIn conclusion, of the four motives examined, only coping motives varied significantly across neighborhoods. Based on these findings, public health policies that develop adaptive strategies to improve alcohol-free methods for young people to cope better with life’s stresses may be particularly effective at reducing inequalities, if targeted at young people living in accessible small towns or areas of high neighborhood deprivation. Additionally, reduction of coping motives and regular alcohol use may be a potential side effect of improving neighborhood conditions.


Exposure to natural environments and the adoption of specific cognitive strategies are each claimed to have a direct influence on executive mental functioning. Here we manipulate both factors to help determine whether they draw on common cognitive resources. Three experiments investigated links between environmental effects (nature vs. urban video tours) and strategic effects . Each experiment used a pretest-posttest design and assessed executive mental functioning using a backward digit span task and Raven's progressive matrices. Experiment 1 manipulated participants' cognitive strategy through explicit instructions in order to establish a link between cognitive strategy and executive mental functioning. Experiment 2 used a pair of 10-min video tours  to examine the relationship between environmental exposure and executive mental function on the same tasks, replicating previous findings with the backward digit span task and extended them to a new task . In Experiment 3, these two manipulations were combined to explore the relations between them. The results showed that the nature video tour attenuated the influence of task instructions relative to the urban video tour. An interaction between environmental video exposure and cognitive strategy was found, in that effects of cognitive strategy on executive function were smaller in the nature video condition than in the urban video condition. This suggests that brief exposure to nature had a direct positive influence on executive mental functioning. The past decade has seen considerable interest in the relations between the natural environment and human cognition  hypothesizing that interactions with nature restore or improve functioning of goal-directed attention mechanisms. But there are other theories worth noting as well. The biophilia hypothesis  or an active one . In object categorization, a passive strategy is linked to results that are based on family resemblance and global characteristics of stimuli, whereas an active strategy is linked to feature- and rule-based groupings of stimuli. Whether these results are beneficial or harmful to overall performance depends on the task constructed by the experimenter . This research hints that an active strategy, relative to a passive strategy, leads to greater involvement of central cognitive control. This is consistent with Smilek et al.  and then seeing whether the environment and cognitive strategy have interactive influences on digit span memory. This is the heart of additive factors logic  direct influences of instructional strategies on executive functioning have been claimed  to replicate previous findings between a relationship between environmental exposure and executive mental function  were randomly assigned to active or passive conditions. The active and passive instructions were modified for the present tasks from those used in Smilek et al.  × 2  × 2  mixed experimental design, with instruction as the between-groups factor and phase and task as the within-groups factors. Ethical approval was granted by the University of British Columbia Behavioral Research Ethics Board for all studies in this paper (Certificate H14-00769) and all individuals gave informed consent in writing prior to participating in the study. All participants were recruited from the Department of Psychology human subject pool in return for extra course credit. In Experiment 1, 30 participants aged 18 to 30 years  to generalize the findings and (b) to test for possible differences in the way executive functions are required for each task. A backward digit span task was adapted from the Wechsler Adult Intelligence Scale Third Edition  software using the Psychophysics Toolbox . This was followed by a posttest backward digit span task, which was identical in design to the pretest, with 14 new trials. After the backward digit span was completed, the condition specific instructions for the Raven's task were shown. The participant then completed the posttest Raven's task, which was also identical in design to its pretest counterpart, with 12 different matrices shown.z-scores to compare performance across the two tasks and in combination. These z-scores were derived by subtracting the group mean for each task from the participant's raw score for that task, and then dividing this difference by the group standard deviation for the same task. Mixed design analyses of variance (ANOVA) were used to analyze the influences of the three factors  on the z-scores. In addition, analyses of covariance (ANCOVA) were conducted, using pre-scores as a covariate, in order to control for potential baseline differences in performance between the two strategy conditions. These results only strengthened our conclusions in each experiment and so we report the ANOVA results in the body of the paper for simplicity and the ANCOVA results in the Appendix A.3 .Because the raw scores of the two tasks were based on different scales , we used r(58) = 0.46, p < 0.001, supporting the hypothesis that there was significant overlap in the mental functions being tested in the two tasks.The raw scores in the digit span and Raven task are shown in Table F = 5.480, p = 0.027, F = 20.508, p < 0.001, F = 5.373, p = 0.028, F = 24.45, p < 0.001, F = 4.205, p = 0.040, F = 5.373, p = 0.028, p > 0.30.The mixed-design ANOVA of the standardized scores indicated that the active instruction strategy led to generally better performance than the passive instruction strategy, active approach led to an increase in performance, whereas instructing participants to take a passive approach reduced performance. The novel contribution of these findings is that this is the first time that passive-active instructions have been shown to directly influence backward digit span and Raven's Matrices, tasks that are tailored to make heavy demands on central executive processes. Specifically, active strategy instructions led to gains in performance, whereas passive strategy instructions led to performance decrements. A second novel contribution was finding that the influence of instructions were stronger for the backward digit span task than for Raven's matrices.The main finding was that instructing participants to take an Here we repeated the pre-post design, but instead of inserting an instructional manipulation we invited participants to view a brief video of a nature tour through Banff National Park or an urban tour of the city of Barcelona.M = 21.10 years, SD = 3.54) were randomly assigned to either a nature video group, an urban video group, or a no video group. After completing Experiment 1, we used G*Power  × 2  × 2  mixed experimental design, with video as the between-groups factor and phase and task as the within-groups factors. Ninety participants aged 17 to 45 years  and a 10-min segment of a Barcelona tour video was shown in the urban condition (https://www.youtube.com/watch?v=clW7aV0vVAY). These videos were selected because they each had numerous characteristics attributed to each of these two conditions in past research  and because a video simulates the walking experience better than still photos. Both videos were shown in full screen mode, with the sound disabled. As with any comparison between environments, there were many differences to note. For example, there was a constant text banner in the lower left portion of the urban video but not in the nature video, consistent with the differences in text found in typical urban and natural settings. The videos were taken from different continents  and the spacing and duration of camera cuts and pans clearly differed as well. Our goal was simply to see if these constellation of differences led to differences in executive functioning, as has been previously reported for different environments that vary on many of these dimensions as well. Finally, we note that in the no video condition participants moved directly from pre-testing to post-testing after a short break of 2–3 min, whereas each video took at least 10 min in the environment conditions .A 10-min segment from a YouTube video of a Banff National Park tour was shown in the nature condition  = 21.728, p = 0.001, three between-group conditions in this experiment.The raw scores in the digit span and Raven task are shown in Table three video conditions were entered into the ANOVA model, p > 0.17, but it approached significance when the urban video and no video data were combined into a single group for comparison with the nature video condition, F = 3.570, p = 0.062, p-values Bonferroni corrected: digit span t(29) = 3.47, p < 0.01; Ravens t(29) = 3.36, p < 0.01), whereas the no video group showed the least improvement overall , and the urban video group was mixed  = 0.128, p = 1.0, and some improvement in the Raven's task, t(29) = 2.29, p = 0.06). When we examined each of the two tasks separately, the improvement in the digit span task following the nature video was significantly greater than for the urban and no video conditions, F = 6.23, p = 0.01, F = 1.647, p > 0.30, p > 0.30.The two-way interaction of video x phase was not significant when all In summary, participants viewing the nature video improved in their task performance from pretest to posttest more than participants who viewed either an urban video or no video. This finding is consistent with previous tests of attention restoration theory Berto, . The novThe experiment tested environmental exposure via brief video tours in combination with strategy instructions. The goal was to determine whether the effects seen in Experiments 1 and 2 influenced the same or different cognitive mechanisms, using additive factors logic  were given the tasks, instructions, and videos used in the previous experiments. Half the participants in each video condition were randomly assigned to receive the active instructions, and the rest were assigned to receive the passive instructions. Because we were looking for a possible three-way interaction between strategy x video x phase in this experiment, we again increased the sample in each of the two instructional conditions to n = 40.The design of this experiment was a 2  × 2  × 2  × 2  mixed experimental design, with video and instruction as between-groups factors and phase and task as the within-groups factors. Eighty participants aged 18–63 years . However, there was a significant interaction of strategy x phase, F = 22.903, p = 0.001, t(76) = 2.57, p < 0.01] and they generally declined from pretest to posttest when given the passive instructions . These results imply that viewing a nature video plays a buffering role against cognitive strategies, modulating both the strong positive (for active instructions) and negative (for passive instructions) influences of adopting a particular cognitive strategy. No effects involving measure were significant in this experiment, p > 0.24.The raw scores in the digit span and Raven task are shown in Table The main aim of this study was to test a central tenet of attention restoration theory, namely, that exposure to a natural vs. urban environment has a direct positive influence on executive mental function  the influence of task instructions relative to the urban video tour. As such, these findings provide strong support for one of the main tenets of attention restoration theory, namely, that brief exposure to nature influences executive mental functions directly rather than via another motivational or strategic route.While this study does not rule out other potential mechanisms that very well could also be at play, such as stress reduction, motivation, and perceptual fluency, the results support the view that at least some of the positive cognitive effects derived from viewing nature involved changes to the executive control of attention. As such, these data provide compelling support for attention restoration theory and its hypothesized mechanism for the cognitive benefits of nature, which are influences on the executive control of attention .not theoretically linked to central executive functioning. One example might be a pop-out visual search, such as was tested in Smilek et al.  and controlled processing (meaning with conscious effort). The prevailing view in the literature on environmental effects is that they occur outside of the awareness of participants . JE and MB assisted in the theoretical question, experimental design of the study, and in the writing of this paper. Otherwise all data collection, data analysis, and writing were overseen by SB. This research was supported by a Discovery Grant to JE, from the Natural Sciences and Engineering Research Council of Canada.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


In the original article, there was an error. In the Abstract, the number of participants was mistakenly listed as “One hundred and thirty-two toddlers,” an outdated number from a previous version of this paper, instead of “One hundred and seventy-six” (176).Abstract:A correction has been made to the “Joint engagement with a speaker is one cue children may use to establish that an interaction is relevant to them and worthy of attention. People on pre-recorded video cannot engage contingently with a viewer in shared experiences, possibly leading to deficits in learning from video relative to learning from responsive face-to-face encounters. One hundred and seventy-six toddlers (24 and 30 months old) were offered referential social cues disambiguating a novel word's meaning in one of four conditions: responsive live (a speaker was present and engaged with children); unresponsive video (a speaker on video looked at the camera and smiled at scripted times); unresponsive live , and responsive video . Children of both ages reliably learned the word in the responsive live condition, and older children (30 months) learned in the unresponsive live condition. Neither group learned in the responsive or unresponsive video conditions. The results show that the addition of communicative social cues to the video presentation via video chat was not sufficient to support learning in this case. Rather, toddlers' transfer and generalization of words presented on video chat may depend on other contextual factors, such as co-viewers who scaffold their learning. Live, responsive video as implemented in this and prior studies is compared, with implications for the use of video chat via the Internet with young children.”The authors apologize for this error and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.


Escherichia coli (DEC) prevalence among pediatric patients with diarrhea at the Costa Rican National Children’s Hospital-Social Security Service . DEC variations with respect to rainfall, presence of coinfections, and DEC antimicrobial resistance were also investigated.This study aimed to estimate diarrheagenic E. coli (EAEC) [n = 189 (31%)], enteropathogenic E. coli (EPEC) [n = 145 (24%)] and enteroinvasive E. coli (EIEC) [n = 91 (15%)]. A reduction in the probability of EAEC gastroenteritis was detected as rainfall rose above 200 mm/mo. . Coinfections were observed mainly between EPEC and Campylobacter spp. (10%). Antimicrobial resistance occurred in 0.6%, 29%, and 42% of DEC for ciprofloxacin, trimethoprim/sulfamethoxazole, and ampicillin, respectively.A retrospective observational study from January 2008 to December 2016 was conducted. A total of 12 247 gastroenteritis records were analyzed. Annual DEC prevalence ranged from 2.7% (2008) to 9.0% (2013). The most prevalent pathotypes were enteroaggregative  Annually, diarrheal diseases account for more than two million deaths worldwide. Of these, more than half a million correspond to children under 5 years of age . DiarrheEscherichia coli (DEC), identifying six well-known pathotypes: Enteropathogenic E. coli (EPEC), enterotoxigenic E. coli (ETEC), shiga-toxin producing E. coli (STEC), enteroinvasive E. coli (EIEC), enteroaggregative E. coli (EAEC), and diffusely adherent E. coli (DAEC). Moreover, infections provoked by mixed pathotypes of E. coli (MPEC) can be identified when genes belonging to different pathotypes are concurrently found in a given strain. In Costa Rica, a previous study showed a predominant circulation of EPEC and EIEC between 2005 and 2007  and were selected for further analysis.χ2 = 84.2; p < 0.0001). Notably, 2013 showed a nearly 3-fold increase in DEC prevalence (9.0%) with respect to 2008, whereupon prevalence decreased to 3.6% (n = 68) by 2016.DEC cases and prevalence were distributed as follows: . Significant differences in prevalence were observed throughout the study period (Log-linear regression (LR), . EAEC was the most frequent pathotype identified [31% (n = 189)], followed by EPEC [24% (n = 145)], EIEC [15% (n = 91)], ETEC [11% (n = 70)], DAEC [9% (n = 54)], STEC [8% (n = 46)], and MPEC [2% (n = 14)] . This interaction had a sigmoidal pattern, as shown in Fig. Rainfall records depicted two well-defined seasons (dry and rainy), as well as noticeable variations in monthly rainfall averages between the years Fig. a. The inWe also estimated the infection probability for each pathotype. Among the pathotypes investigated, only the EAEC infection probability and monthly rainfall was significant Fig. .Fig. 3DECampylobacter coinfection was the most prevalent .Coinfections were found across most pathotypes, except for MPEC, and the global prevalence was estimated at 11% (n = 64). Frequency of co-infections ranged between pathotypes . EPEC-Antimicrobial susceptibility to ampicillin (AMP), trimethoprim/sulfamethoxazole (TMP/STX) and ciprofloxacin (CIP) differed among DEC pathotypes. Approximately 25-30% of EPEC, ETEC, STEC and EIEC isolates showed resistance to AMP, whereas this proportion increased to 50% for MPEC, 54% for EAEC, and 77% for DAEC. TMP/STX resistance was found in 16% of EPEC and ETEC, 23.3% of STEC and EIEC, 33.9% of EAEC, 40% of MPEC, and 60% of DAEC. A generalized susceptibility to CIP was found across all DEC pathotypes. Over a span of 9 years, only one STEC isolate showed resistance to all three antimicrobials.To estimate the burden of DEC gastroenteritis, we analyzed more than 46 906 laboratory records, of which only 26% n = 12 247) fulfilled the inclusion criteria. DEC was identified in 609 (5.0%) of these samples. A similar study found DEC in 7.44% of cases in children under 5 years of age , whilst  247 fulfRegarding STEC, its prevalence remained low over the span of this study. Nonetheless, its association with large outbreaks, hemolytic uremic syndrome (HUS) and the high mortality rates emphasize the relevance of this pathotype for public health , 25. To E. coli is well-documented and makes this bacterium a classic indicator of fecal contamination in water sources [The ubiquity of  sources . DEC pre sources –30. By vCampylobacter spp. was the most prevalent pathogen (4%) co-infecting pediatric patients in this study, which were predominantly associated with EPEC (10% of the cases) and ETEC (6% of the cases). The coinfection between EPEC and Campylobacter was also found at similar rates in a multicenter study in Europe, using a multiplex PCR-based approach [We found 11% of coinfections between DEC and other enteropathogens. Changes in gut microbiota induced by DEC infection and the potential interaction with other pathogens have been reviewed elsewhere . Campyloapproach .We found different antimicrobial susceptibility patterns among DEC pathotypes. Notably, 54% of EAEC isolates were mono-resistant to AMP, 34% to TMP/STX, and 33% showed resistance to both. Resistance to multiple antimicrobials is a major concern in EAEC , consideFor more than a decade, DEC has been investigated in stool specimens via molecular methods at the HNN-CCSS. Through this work, we are now aware of the local distribution, prevalence, antimicrobial resistance, and the interactions between each DEC pathotype and rainfall for most of this period.Since March 2017, a syndromic multiplex PCR is part of the routine tests performed directly on diarrheic stool specimens for the simultaneous detection of multiple pathogens. This novel molecular approach will improve diagnostic efficiency through reduced turnaround times and an extended coverage of agents targeted in a single assay, thereby enabling a timely management and the instauration of appropriate antimicrobial therapy when warranted. The overall impact of this strategy will require an exhaustive review, for which this study establishes a reference against which future research can draw upon to determine the influence of technical innovation on the epidemiological profile of infectious gastroenteritis at the HNN-CCSS.It is possible that a minor fraction of data may be missing due to the retrospective nature of this study. Additionally, this is a hospital and laboratory-based study only. Consequently, it does not include all children diagnosed with DEC gastroenteritis in the central region of Costa Rica. It is likely that the actual DEC pediatric disease was greater than depicted in this study.


Alcohol consumption among Indigenous Australians can involve a stop-start pattern of drinking, with consumption well above recommended guidelines on each occasion. Such intermittent drinking patterns can make screening for risky drinking difficult. This study evaluates the ability of several short alcohol screening tools, contained in the Grog Survey Application, to detect short- or long-term risky drinking as defined by Australian guidelines. Tested tools include a modification of Alcohol Use Disorders Identification Test-Consumption (AUDIT-Cm).Alcohol consumption was assessed in current drinkers in the past year (n = 184) using AUDIT-Cm and using the last four drinking occasions (Finnish method). Sensitivity and specificity were assessed relative to the Finnish method, for how AUDIT-Cm score , and how subsets of AUDIT-Cm questions  were able to determine short- or long-term risk from drinking. Responses to AUDIT-Cm were used to calculate the average standard drinks consumed per day, and the frequency at which more than four standard drinks were consumed on single occasions. Finally, shorter versions of the Finnish method  were compared to the full Finnish method, by examining the percentage of variance retained by shorter versions.2 = 0.997).AUDIT-Cm has a high sensitivity in detecting at-risk drinking compared with the Finnish method . The combination of AUDIT-1m and AUDIT-2m was able to classify the drinking risk status for all but four individuals in the same way as the Finnish method did. For the Finnish method, two drinking sessions to calculate drinks per drinking occasion, and four to calculate frequency resulted in nearly identical estimates to data on all four of the most recent drinking occasions  contains supplementary material, which is available to authorized users. There are similarities in patterns of alcohol consumption in Indigenous peoples in Australia and other colonised countries  –3. AlcohIn survey settings, standard approaches, such as quantity-frequency or graduated quantity-frequency can be difficult to apply in populations with stop-start drinking patterns , 6. In cThe Finnish method for assessing consumption  asks aboThe first three consumption items of the Alcohol Use Disorders Identification Test (AUDIT-C) form one of the most commonly used screening tools globally . AUDIT-CAlthough AUDIT-C has been studied in Indigenous Australians more than other available screening tools , no valiTo help Indigenous Australians describe their drinking, we developed and evaluated a tablet computer-based application to assess and record alcohol consumption . The GroUsing a clinical interview performed by an Aboriginal health worker as a reference standard, the Grog Survey App performed well in measuring risky drinking  . The AppWhile the Grog Survey App provides an acceptable  and valiUsing data from the larger study on the development and evaluation of the Grog Survey App, we now evaluate the ability of short alcohol screening tools, contained within the App survey, to detect short-term or long-term risky drinking as defined by Australian NHMRC guidelines . The anaStudy methods were designed by investigators in consultation with the Aboriginal Drug and Alcohol Council of South Australia; the Aboriginal Drug and Alcohol Network, representing Aboriginal alcohol and other drug workers in New South Wales (NSW); and the Aboriginal Health Council of South Australia (AHCSA), the peak body for ACCHSs in South Australia. Ethical approval was obtained from ACHSA and from Metro South Health Human Research Ethics Committee in Queensland.Stratified convenience sampling was used—we aimed to recruit: 20 non-drinkers, 40 non-dependent drinkers and 40 dependent drinkers in each of two state. Aboriginal field research assistants set up participants on iPads to complete the survey App. Research assistants recruited based on observation/anecdotal knowledge of the drinking category that potential participants would be in. Then at the end of each day all iPads were synchronised to the University of Sydney encrypted server and the App dashboard provided an update of the number of people in each category, to inform the next days’ recruitment efforts. Participants were classified as non-drinkers by the survey App if they reported not consuming alcohol in the preceding 12 months. To classify dependent and non-dependent drinkers, participants were asked on the survey App to rate the frequency of three alcohol dependence criteria (ICD-11) , 18. Parr = 0.8, and ɑ = .05 a sample size of 46 is required . Greater sizes were sought to try to allow analysis of differences between urban and remote sites, and because of anticipated challenges in ensuring complete data collection. In urban Queensland (QLD), recruitment was based in an Indigenous primary health care service and surrounding community (August–November 2016). In South Australia (SA), recruitment centred on a regional ACCHS and a remote Aboriginal community controlled drug and alcohol day centre . Individuals were eligible for inclusion if they self-identified as being Aboriginal or Torres Strait Islander and were 16 years or older. Exclusion criteria included obvious intoxication. Non-drinkers  were excluded from analyses in the current paper.Most of the analyses involved in validating  and shorAll survey items were delivered using the ‘Grog Survey App’. Broadly, the App presents questions on demographics, alcohol consumption (10 items), alcohol dependence (3 items based on ICD-11 ), harms The App includes: culturally appropriate questioning style and gender-specific voice and images; ‘translation’ to colloquial English and (for audio) to the local Indigenous language (Pitjantjatjara); interactive visual approaches to estimate quantity of drinking; images of specific brands of alcohol, rather than abstract description of alcohol type (e.g. ‘spirits’); images of commercial and make-shift drinking containers (e.g. empty soft drink bottles); option to estimate consumption based on the individual’s share of what the group drank; key time points to explain time references for communities that do not routinely use calendars  . In thisFinnish methodParticipants reported on their four most recent drinking occasions in the last 12 months. Participants reported when these occasions occurred, and how much alcohol they consumed on each. Rather than report on standard drinks, participants selected pictures of the alcohol product consumed, the container they drank from, and how full the container was with alcohol [Modifications of AUDIT-CAs described elsewhere [After asking whether individuals consumed any alcohol at all in the past 12 months, the Finnish method and AUDIT-1m were each asked independently to estimate frequency of drinking. Australian standard drinks (10 g ethanol) consumed on each of the last four drinking occasions were estimated using a visual and interactive approach on the App, and responses to AUDIT-2m were derived from this. The frequency at which participants consumed at levels associated with risk of short-term harms  was asked using a modified, visual form of AUDIT-3 . Similarly, for AUDIT-2m, in order to mimic the performance of this test when delivered using response categories, the mid-point of the first four response categories was used to calculate the average drinks consumed per drinking occasion for those responses. As there is no upper bound for the top category (10 + drinks), 10 standard drinks was used.Short-term risk was estimated by the combination of AUDIT-1m and AUDIT-2m if participants consumed more than four standard drinks per occasion and had consumed alcohol at least once in the last 12 months. Similarly, participants were classed as being at short-term risk by AUDIT-3mV if they indicated drinking more than four drinks on an occasion at least once in the past year.Long-term risk was estimated with the AUDIT-1m and AUDIT-2m by multiplying the frequency of drinking (mid-point of response category of AUDIT-1m) by the average standard drinks per day (mid-point of response category for AUDIT-2m). Long-term risk was estimated with the AUDIT-3mV by multiplying five standard drinks (as this question asked about drinking 5 + drinks) by the mid-point of the frequency response selected for that level of drinking. We then compared the risk classifications of these two short forms to classifications made by the Finnish method in a sensitivity and specificity analysis (with the Finnish method as a reference standard). In order to calculate the sensitivity and specificity of the AUDIT-Cm, the table function, from base R, and the ‘epi.tests’ function, from the epiR package, were used together. A cross-tabulation of risk status was produced which compared risk status derived from responses to the AUDIT-Cm with responses derived from the Finnish method. This cross-tabulation was then supplied to the ‘epi.tests’ function in order to obtain sensitivity, specificity and their respective confidence intervals.r) to demonstrate accuracy of shorter versions of the Finnish method in comparison to the full Finnish method, which uses the last four drinking occasions. We examined use of smaller numbers of drinking occasions  to estimate the average number of standard drinks per occasion, and the frequency of occasions. Correlations were squared in order to calculate r2 (the percentage of variance retained) by the shorter versions.Finally, we used Pearson correlations (SD = 13.4). Of these, 28 (15.2%) were from regional areas, 66 from remote (35.9%) and 90 from urban centres (48.9%). Most  had completed high school up to at least Year 10.Participants were 184 Aboriginal and Torres Strait Islander peoples who had consumed alcohol in the past 12 months  found a high number  of drinkers were at risk from their drinking in the past year . A very similar number of drinkers  were classified as at risk based on their total AUDIT-Cm scores . In keeping with this, responses to AUDIT-2m show that most drinkers (77.7%) consumed 10 or more standard drinks per drinking occasion . AUDIT-Cm only disagreed with the Finnish method on the risk status of four participants.Subsets of items from the AUDIT-Cm were used to classify participants into NHMRC short- and long-term risk categories. Together, AUDIT-1m and AUDIT-2m identified almost two-thirds of drinkers  as being at short-term risk from drinking at least once a month and a quarter  of drinkers as being at long-term risk from their drinking. AUDIT-3mV identified 95 (51.6%) participants as being at short-term risk from their drinking (5 + drinks per occasion) at least once per month and classified four participants at long-term risk . In order to exclude the possibility that this was due to reporting where participants gave identical answers for each occasion, we excluded cases with zero variation in amounts consumed between occasions. Similar results were obtained .Using two drinking sessions to calculate drinking intensity (drinks per drinking occasion) and four to calculate frequency resulted in estimates that were nearly identical to those obtained when collecting data on all four of the most recent drinking occasions . But when they do drink they tend to consume large quantities. More than three-quarters (77.7%) of our subjects reported 10 or more Australian standard drinks on drinking occasions. While the current study over-sampled likely dependent drinkers, this pattern of infrequent heavy drinking occasions has been reported elsewhere for Indigenous Australians in several studies [.4%). ButThe combination of AUDIT-1m and AUDIT-2m detected a little over two-thirds of the drinkers who were identified as being at short-term risk from their drinking (using the Finnish Method as a reference standard) . Adding AUDIT-3mV only slightly increased the sensitivity . Accordingly, AUDIT-3mV may offer limited benefit in communities where there is typically a high number of drinks consumed per drinking occasion.usual frequency of a drinking behaviour. It is less surprising that AUDIT-3mV performed poorly at detecting people who were at long term-risk from their drinking , as the threshold of AUDIT-3mV (5 + drinks per occasion) is considerably higher than the Australian threshold for long-term risk (2 + drinks per day). Also, the relatively low frequency of drinking among this population results in a lower average consumption per day.AUDIT-3 has been proposed as a single item screening tool for some populations . HoweverAUDIT-3mV was asked using a visual representation of the drinking threshold. In at least one other study  such a vWe found that simply asking in detail about the quantity consumed on the last two occasions and about the timing of the last two drinking occasions was as good as asking about both quantity and timing for the last four drinking occasions (98.6% % of the variance was explained). Even the quantity from the last occasion and the timing of the last two occasions explained 95.9% of the variance explained by the full Finnish method. In keeping with this, Gregson and Stacey  found th2 = 0.997).Any approach to estimating drinking can be difficult when drinking is stop-start (e.g. a person from dry community comes to town for 2 weeks and drinks daily while there), and the last two occasions approach has the potential to be inaccurate if the timing of those occasions is not typical of usual drinking frequency , 26. In One important difference with our method of assessment that was not present in past studies , 25, 26 AUDIT-1m and AUDIT-3mV were asked as part of the larger questionnaire, and not in their standard order. We cannot assume that these questions will behave the same way if administered as standalone items. This requires further investigation.The last four occasions (Finnish) method has been used as the reference standard because it was well correlated when compared with a clinical interview conducted by an Aboriginal health professional . HoweverHere AUDIT-2m  was derived from a visual approach, tailored to each individual to estimate consumption. This may have increased its accuracy over an approach where the client or interviewer is required to convert drinking to standard drinks. In a clinical or survey setting accuracy relies on the client and/or interviewer understanding standard drink sizes and being comfortable with arithmetic for conversion. Visual aids are likely to be needed to assist in this process. Furthermore, the App considered sharing of drinks, which is sometimes overlooked in a clinical setting , 28, resIt is not clear how generalisable these study findings would be to other indigenous populations beyond the study regions. The current sample over-sampled likely dependent drinkers. It also was conducted in relatively under-privileged regions , and respondents might be more prone to all-or-nothing drinking than a higher socio-economic status region. Further research is needed using a representative sample from two or more Indigenous Australian communities, to re-test these survey approaches and to describe the local prevalence of different drinking patterns (Additional file We are unable to provide the raw participant-level data used in the reported analyses. Data was collected from small Australian Aboriginal communities and we do not have ethical clearance to release these datasets. Complete code used for the analyses presented are available in Additional file Screening for risky drinking is difficult to do in any population, but there can be added challenges in Indigenous, culturally diverse or disadvantaged populations. The combination of AUDIT-1m and AUDIT-2m may be a superior short screening tool, relative to AUDIT-3mV, in groups where intermittent and high per occasion drinking is common. Asking about quantity consumed on the last two occasions and the timing of the last four occasions appears less time consuming than the full Finnish method, but still retains the majority of its accuracy. In populations with high rates of short-term risk from drinking, a respectful discussion about drinking and education on how to reduce risk from drinking may be helpful for any individual who says that they drink.Additional file 1. Complete code for the analyses presented in this study.


Risk factors of acute malnutrition in Bangladesh are well documented. However, due to regional variations in prevalence of acute malnutrition, it is important to explore the risk factors specific to the region, for designing and implementing public health interventions.A mixed-method matched case-control study was conducted in the Kurigram district of Bangladesh. Community perspectives on causes of acute malnutrition were collected from 75 purposively selected caregivers through interviews, focus group discussions and informal group discussions. The data was analysed manually by coding and sub-coding according to different themes. Caregivers of 52 malnourished and 95 well-nourished children matched in age group and sex with the malnourished children, were interviewed using a structured questionnaire. The conditional logistic regression analysis was performed to identify the risk factors of acute malnutrition.Caregivers perceived inappropriate feeding practice as a major cause of acute malnutrition whereas birth order , number of family members , illness in the last 2 weeks  and access to hygienic latrine  were also associated with acute malnutrition among children under five in Kurigram.Community awareness on infant feeding practices and family planning, management of childhood illness and access to hygienic latrine facilities should be prioritised to prevent acute malnutrition in the northern districts. According to World Health Organization (WHO) nearly 20 million children are suffering from acute malnutrition and more than 70% of the world’s children with wasting live in Asia, most in south-central Asia [Childhood acute malnutrition, in the form of wasting defined by weight-for-height ral Asia . Levels ral Asia .The causal path of acute malnutrition is very complex, whereby biological, cultural and socio-economic factors are interrelated. As described by the UNICEF casual framework, the causes of malnutrition are divided into immediate, underlying and basic causes; inadequate dietary intake and disease are the immediate causes; household food insecurity, inadequate care and poor sanitation and hygiene practice are underlying causes; other socio-economic characteristics are classed as basic causes of malnutrition in developing countries . NutritiAlthough the main factors contributing to malnutrition in Bangladesh are well documented, the factors varies by region and over time. The purpose of this study is to identify risk factors of acute malnutrition in the Kurigram District of northern Bangladesh and assist policy makers in designing and targeting preventive intervention projects addressing the main factors specific to this area.A mixed-method study was conducted from July 2013 to June 2014 in three Unions of Kurigram District, situated in the northern region of Bangladesh. Initially, 18 caregivers of children aged under five years were interviewed, six focus group discussions (FGDs) with a total of 42 women, and an informal group discussion (iFGDs) with 15 people residing in the study area were conducted to explore community perception of the causes of acute malnutrition. All participants of the qualitative study were selected purposively (i.e. not randomly) from the community awareness session of Terre des hommes (Tdh), who had received health messages on exclusive and continued breast feeding, appropriate complementary feeding, correct handwashing practice, safe drinking water, hygienic latrines, delaying age at marriage, and family planning methods, or from the outdoor waiting area of Tdh primary clinic in Kurigram but were not beneficiaries of the Tdh community health programme, based on their availability, interest to participate in the study and was a caregiver of under-five year old child [n = 52) enrolled in the community management of acute malnutrition (CMAM) project of Tdh during February 2014 to May 2014 were selected as cases, and 95 children from the same neighbourhood of the cases were selected as controls with a ratio of 1: 2 between case and control. Initially controls were listed based on the information provided by the caregivers of malnourished children, and selected after household visits. If more than two controls were identified, controls with minimum age difference with case were selected. However, for nine cases only one control was identified. All caregivers selected, participated in the study.Following the qualitative study, a matched case-control study was conducted to identify the risk factors of acute malnutrition among children aged 6–59 months. Cases were defined as children with WHZ < − 2SD and/or MUAC < 125 mm, and controls were children with WHZ ≥ − 2SD and MUAC ≥ 125 mm who were residing in the same neighbourhood as the cases. The cases and controls were matched in two age groups, i.e. either 6 to 23 months or 24 to 59 months, and by sex. All the children  with precision of 100 g. Height or length was measured using locally manufactured height measurement boards to the nearest mm by Monitoring Assistants. All measurements were made in line with the WHO standard protocols . All groSome variables were categorised for more specification. Age of the child was categorised into two groups, i.e. 6–23 months and 24–60 months considering the higher likelihood of younger children becoming malnourished. Birth order of the child was categorised as first child and not first child since culturally preference is given to the first child. Parents’ education was categorised as illiterate and literate, where a person unable to read and write was considered illiterate. In order to explore taboos related to feeding practice, a series of questions were asked to caregivers of both cases and controls based on the findings of qualitative study. The responses were then analysed into two categories as family who believed in food taboos and who did not. The household water source was classified as improved only if it was a tube-well with platform. Similarly, sanitary latrine with water-sealed pan was classified as a hygienic latrine. Household food security was measured by household food insecurity access scale (HFIAS) ), household hunger scale (HHS) and food consumption score (FCS) –13. HousThe quantitative data was analysed using STATA 12 . Bivariaz-score than children without acute malnutrition. However, there was not enough evidence of a difference in mean height-for-age z-score (Table n = 8) was the first child compared with 41.0% (n = 39) among controls  were never breastfed, 91 (87%) were immediately put to breast after birth, and 84 (93%) were continuing breastfeeding.The importance of exclusive breast feeding and continued breast feeding along with timely introduction of family foods was widely shared by the caregivers. One of the breast-feeding mother mentioned that, “p = 0.31) based on the HFAIS scale  had minimum adequate meal frequency and only 9 (8%) had a minimum acceptable diet in line with WHO’s recommended infant and young child feeding practice. As a possible reason the findings of qualitative study indicated that caregivers were unfamiliar with the concept of a diversified diet. Moreover, knowledge of nutritious food varied greatly among this group. Caregivers informed that they prepared meals using available resources and due to a lack of money they were unable to buy meat and other food items from the market. Most of the caregivers shared their concern about child’s lack of appetite. It was observed that in most cases children were served the same food at breakfast and lunch. The poor infant and young child feeding practice could also be linked to food insecurity as children with acute malnutrition were more likely from food insecure households compared with children without acute malnutrition . However, there was not enough evidence of difference in proportion of caregivers who believe in food taboos between case and control group . Fever (63%) and diarrhoea (16%) were the most frequent illnesses reported. The findings were similar to the perception of the caregivers as illness was attributed as a cause of the child’s poor nutritional condition. According to the caregivers, respiratory illnesses such as cough, pneumonia, asthma and skin diseases were common in winter, while dysentery and chicken pox were common in summer. Fever and diarrhoea were reported in both seasons. Newborn illnesses were attributed to the effect of an “evil eye”, i.e. cursed by a malevolent glare, and the remedy was a priest or a traditional healer. Quoting a mother “My child was not able to feed at my breast so everyone said that a spirit has attacked him. So I consulted a priest who gave me an amulet for 7 days which made no difference”.Most of the children with acute malnutrition were suffering from illness in the last 2 weeks compared with children without acute malnutrition, and the association was statistically significant .Caregivers of well-nourished children recognised that an unclean environment in the home and poor hand washing practices were causes of malnutrition. During the FGDs with caregivers of children, it emerged that tube-wells were the main sources of water. However, caregivers consumed water without any purification. Of concern also was that some households had no latrines and even households with toilets did not have sealed latrines. Hand washing practice was also very poor with very few reporting hand washing with soap after defecation or cleaning a child. Though there was not enough evidence of an association with household water source and purification of water with acute malnutrition, the children were less likely to be malnourished if the household had a sanitary latrine (OR 0.34, 95% CI 0.12, 0.95; The findings of the multivariate conditional logistics regression analysis suggest that birth order, number of family members, illness in the last 2 weeks and household toilet facility are associated with nutritional status of the children Table . A childThe results of the multivariate logistic regression indicate that illness in the last 2 weeks and number of family members are the risk factors of acute malnutrition while being the first child and household access to a hygienic latrine prevents acute malnutrition for children enrolled in a community-based programme in Kurigram. Our qualitative study also revealed that inappropriate feeding practice is perceived as one of the major causes of acute malnutrition by the caregivers of the children.Black et al. in the Lancet 2008 mentioned diseases as one of the immediate causes of acute malnutrition . The relConsidering the numerous health benefits associated with hygiene, Black et al. identified an unhealthy household environment as an underlying cause of acute malnutrition . The relFamily size has been documented as a risk factor of malnutrition in several studies in Ethiopia, Pakistan, India, and Malaysia –21. The From 6 months up to 2 years of age and beyond, along with breastfeeding, infants should receive nutritionally adequate and safe complementary foods to meet their evolving and increasing nutritional requirements . HoweverThe study was conducted as part of a community-based programme which could be considered a strength as only few studies were conducted to explore risk factors of acute malnutrition based on children enrolled in a community programme. The mixed-method approach to evaluate the association between acute malnutrition to other exposures quantitatively and understand community perspective and practice which influence child nutritional status qualitatively could also be considered a strength. The study relied on children enrolled in the community programme and matched controls based on the information provided by the community workers and caregivers could be argued as a limitation. The small sample size of the study is another limitation in generalizing the findings. Although caregivers from both Tdh intervention and non-intervention areas were recruited for the qualitative part of the study, Tdh’s behaviour change activities may have influenced the community perception. A longitudinal study following children overtime would have been a better study design in establishing the casual path. However, with limited resources and as part of the monitoring and evaluation activities a case-control study was considered most suitable. In order to minimize biases, experienced staff of Tdh’s Monitoring and Evaluation team were trained and assigned for data collection and anthropometric measurement.The risk factors identified for acute malnutrition in Kurigram can be useful for designing community-based preventive activities. Community awareness activities can be strengthened to improve awareness on appropriate infant and young child feeding practices and benefits of a small family. Interventions to increase coverage and access to hygienic latrines need to be considered by the local government and the non-governmental organisations. Increasing care seeking from the Community Clinic will be useful—this will need a two-pronged intervention—improving the quality of services in the clinic and ensuring that caregivers seek care early for the sick child. The causal framework of acute malnutrition is complex and needs multi-sectoral preventive interventions to improve nutrition status of children.