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Poor sleep quality characterizes the emergency medical service (EMS) profession. Anger is particularly affected by sleep disturbance and may be related to sleep quality at both between- and within-person levels, yet this has never been examined. The current study performed a multilevel analysis of the relationship between sleep quality and anger among EMS workers.Ecological momentary assessment PARTICIPANTS: Seventy-nine EMS workers employed at an emergency medical service provider in Central New York.Participants completed 8 daily assessments that inquired about sleep quality and anger.EMS workers who typically experienced poorer sleep quality reported greater anger levels; for instance, workers who routinely experienced poor sleep quality reported anger levels that were 18%-35% higher compared to workers receiving fair sleep quality. Regardless of their typical sleep quality, days when workers experienced poorer sleep than usual was characterized by higher levels of anger: on a day when a worker experienced poorer sleep quality than usual for them, their anger levels were 5% higher on that day regardless of their typical sleep quality.EMS workers regularly experiencing poor sleep quality experience more anger. However, even workers who typically have better sleep quality experience anger elevations following poor sleep. These findings suggest that interventions targeting both between- and within-person factors impacting sleep may be important for addressing sleep quality's influence on anger in the EMS profession.

ObjectiveTo compare estimates of effect and variability resulting from standard linear regression analysis and hierarchical multilevel analysis with cross-classified multilevel analysis under various scenarios.Study design and settingWe performed a simulation study based on a data structure from an observational study in clinical mental health care. We used a Markov chain Monte Carlo approach to simulate 18 scenarios, varying sample sizes, cluster sizes, effect sizes and between group variances. For each scenario, we performed standard linear regression, multilevel regression with random intercept on patient level, multilevel regression with random intercept on nursing team level and cross-classified multilevel analysis.ResultsApplying cross-classified multilevel analyses had negligible influence on the effect estimates. However, ignoring cross-classification led to underestimation of the standard errors of the covariates at the two cross-classified levels and to invalidly narrow confidence intervals. This may lead to incorrect statistical inference. Varying sample size, cluster size, effect size and variance had no meaningful influence on these findings.ConclusionIn case of cross-classified data structures, the use of a cross-classified multilevel model helps estimating valid precision of effects, and thereby, support correct inferences.

BACKGROUND: Low-income and middle-income countries (LMICs) face a double burden of malnutrition (DBM), whereby overnutrition and undernutrition coexist within the same individual, household, or population. This analysis investigates global inequalities in household-level DBM, expressed as a stunted child with an overweight mother, and its association with economic, social, and political globalisation across country income and household wealth. METHODS: We pooled anthropometric and demographic data for 1 132 069 children (aged

Along the line that “Leave No Litter” (LNL) in protected areas is promoted globally, Hong Kong launched its LNL campaign in 2016. The success of the campaign is critically dependent on the compliance of the park visitors. Because behavioral intention is influenced by determinants of different domains, this study adopted a multilevel perspective to examine how demographic, psychological, and situational variables affected LNL intention using a voluntary response sample of 374 hikers in Hong Kong. The results indicated that attitude, perceived behavioral control, and preparedness were significant predictors of LNL intention, indicating the direct associations between them. Furthermore, preparedness mediated the effects of attitude, subjective norm, and perceived behavioral control on LNL intention. The findings of this paper may contribute to the body of knowledge on pro-environmental behavior of recreationists by providing a novel understanding of LNL intention of Hong Kong hikers. Furthermore, this study may cast light on the sustainable management of protected areas in Hong Kong as well as cities around the world.

Summary Background & aims Child growth impairments are rampant in sub-Saharan Africa. To combat this important health problem, long-term follow-up studies are needed to examine possible benefits and sustainability of various interventions designed to correct inadequate child growth. Our aim was to perform a follow-up study of children aged 60–72 months whose mothers participated in a two-armed cluster-randomized education intervention trial lasting 6 months in rural Uganda when their children were 6–8 months old with data collection at 20–24 and at 36 months. The education focused on nutrition, hygiene, and child stimulation. Methods We measured growth using anthropometry converted to z-scores according to WHO guidelines. We also included assessments of body composition using bioimpedance. We used multilevel mixed effect linear regression models with maximum likelihood method, unstructured variance-covariance structure, and the cluster as a random effect component to compare data from the intervention (receiving the education and routine health care) with the control group (receiving only routine health care). Results Of the 511 children included in the original trial, data from 166/263 (63%) and 141/248 (57%) of the children in the intervention and control group, respectively, were available for the current follow-up study. We found no significant differences in any anthropometrical z-score between the two study groups at child age of 60–72 months, except that children in the intervention group had lower (P = 0.006) weight-for-height z-score than the controls. There were no significant differences in the trajectories of z-scores or height growth velocity (cm/year) from baseline (start of original trial) to child age of 60–72 months. Neither did we detect any significant difference between the intervention and control group regarding body composition (fat mass, fat free mass, and total body water) at child age 60–72 months. Separate gender analyses had no significant impact on any of the growth or body composition findings. Conclusion In this long-term study of children participating in a randomized maternal education trial, we found no significant impact of the intervention on anthropometrical z-scores, height growth velocity or body composition. Trial registration Clinical Trials (clinical trials.gov) ClinicalTrials.gov ID NCT 02098031.

Unrest in Chile over inequalities has underscored the need to improve public hospitals. Nursing has been overlooked as a solution to quality and access concerns, and nurse staffing is poor by international standards. Using Chile's new diagnosis-related groups system and surveys of nurses and patients, we provide information to policy makers on feasibility, net costs, and estimated improved outcomes associated with increasing nursing resources in public hospitals.For this multilevel cross-sectional study, we used data from surveys of hospital nurses to measure staffing and work environments in public and private Chilean adult high-complexity hospitals, which were linked with patient satisfaction survey and discharge data from the national diagnosis-related groups database for inpatients. All adult patients on medical and surgical units whose conditions permitted and who had been hospitalised for more than 48 h were invited to participate in the patient experience survey until 50 responses were obtained in each hospital. We estimated associations between nurse staffing and work environment quality with inpatient 30-day mortality, 30-day readmission, length of stay (LOS), patient experience, and care quality using multilevel random-effects logistic regression models and zero-truncated negative binomial regression models, with clustering of patients within hospitals.We collected and analysed surveys of 1652 hospital nurses from 40 hospitals (34 public and six private), satisfaction surveys of 2013 patients, and discharge data for 761 948 inpatients. Nurse staffing was significantly related to all outcomes, including mortality, after adjusting for patient characteristics, and the work environment was related to patient experience and nurses' quality assessments. Each patient added to nurses' workloads increased mortality (odds ratio 1·04, 95% CI 1·01-1·07, p0·01), readmissions (1·02, 1·01-1·03, p0·01), and LOS (incident rate ratio 1·04, 95% CI 1·01-1·06, p0·05). Nurse workloads across hospitals varied from six to 24 patients per nurse. Patients in hospitals with 18 patients per nurse, compared with those in hospitals with eight patients per nurse, had 41% higher odds of dying, 20% higher odds of being readmitted, 41% higher odds of staying longer, and 68% lower odds of rating their hospital highly. We estimated that savings from reduced readmissions and shorter stays would exceed the costs of adding nurses by US$1·2 million and $5·4 million if the additional nurses resulted in average workloads of 12 or ten patients per nurse, respectively.Improved hospital nurse staffing in Chile was associated with lower inpatient mortality, higher patient satisfaction, fewer readmissions, and shorter hospital stays, suggesting that greater investments in nurses could return higher quality of care and greater value.Sigma Theta Tau International, University of Pennsylvania Global Engagement Fund, University of Pennsylvania School of Nursing's Center for Health Outcomes, and Policy Research and Population Research Center.For the Spanish translation of the abstract see Supplementary Materials section.

This article reports outcomes of a quasi-experimental evaluation of Success for All (SfA), a comprehensive school reform program that has recently been introduced in the Netherlands. The Response to Intervention framework is used to describe how SfA supports students at different Tiers. The effects of SfA on five reading subskills were investigated for first-grade students at risk of reading problems. 299 students from two different cohorts were involved. Multilevel analyses demonstrated a significant effect of SfA on reading comprehension (ES = +0.26) in the first cohort. For the second cohort and the other reading subskills, mostly small positive effects of SfA were found, though these effects were not statistically significant. Furthermore, the relationship between tutoring intensity and reading achievement was examined. In the second cohort, a significant negative association of tutoring intensity with word and text reading skills was found. Implementation issues that may have impacted the outcomes are discussed.

Prediction of waste production is an essential part of the design and planning of waste management systems. The quality and applicability of such predictions depend heavily on model assumptions and the structure of the collected data. Ordinarily, municipal waste generation data are organized in hierarchical structures with municipal or county levels, and multilevel models can be used to generalize linear regression by directly incorporating the structure into the model. However, small amounts of data can limit the applicability of multilevel models and provide biased estimates. To cope with this problem, Bayesian estimation is often recommended as an alternative to frequentist estimation, such as least squares or maximum likelihood estimation. This paper proposes a multilevel framework under a Bayesian approach to model municipal waste generation with hierarchical data structures. Using a real-world dataset of municipal waste generation in Denmark, the predictive accuracy of multilevel models is compared to aggregated and disaggregated Bayesian models using socio-economic external variables. Results show that Bayesian multilevel models outperform the other models in prediction accuracy, based on the leave-one-out information criterion. A comparison of the Bayesian approach with its frequentist alternative shows that the Bayesian model is more conservative in coefficient estimation, with estimates shrinking to the grand mean and broader credible intervals, in contrast with narrower confidence intervals produced by the frequentist models.

To determine how demographic, socioeconomic, and neighborhood characteristics are associated with bedtimes among US kindergarteners.Parents reported bedtimes of their children as well as personal, household, and residential characteristics via interviews in the Early Childhood Longitudinal Study-Kindergarten (ECLS-K) Class of 1998-1999. The ECLS-K links individual households to US Census tracts.A random selection of 1,280 schools and surrounding communities in the US.A random selection of 16,936 kindergarteners and their parents.The 2 outcomes were regular and latest weekday bedtimes of kindergarteners. Through a series of nested multilevel regression models, these outcomes were regressed on individual- and neighborhood-level variables, including race/ethnicity, sex, family type, household income, mother's educational attainment, neighborhood disorder, and several additional neighborhood characteristics.Models showed significant (P.05) bedtime disparities by race/ethnicity, sex, family income, and mother's educational attainment. Additionally, models tended to indicate that kindergarteners from disadvantaged neighborhoods experienced later bedtimes than children from more advantaged areas. Neighborhood characteristics accounted for a portion of racial/ethnic differences, suggesting that bedtime disparities are partly rooted in disparate environmental conditions.Reducing disparities in childhood sleep may require programs that target not only children and their parents, but also the communities in which they reside.

Objectives We described the epidemiology and healthcare exposures during a measles outbreak in London and identified factors associated with isolation on arrival to healthcare premises. Study design We conducted a cohort study including all confirmed measles cases in London residents from February 1, 2016, to June 30, 2016, and semistructured interviews with two infection prevention and control teams (IPCTs). Methods We described the outbreak and conducted a multilevel mixed-effects analysis to assess the relationship between sociodemographic and clinical factors and isolation on arrival to healthcare premises. We summarised the interviews. Results There were 182 cases, mostly aged 17–35 years (46%; 84). Excluding cases younger than one year, 76% (92/120) were unvaccinated, including two healthcare workers. The majority presented with rash (97%; 174), and 42% (70/166) required hospitalisation. Of the recorded cases, 93% of cases (164/178) had visited a healthcare setting during their infectious period (median number of visits = 2). In 33% (59/178) of the visits, the case was isolated on arrival; when not isolated, four healthcare exposures resulted in further transmission. Presenting to the hospital as opposed to a general practitioner (GP) was associated with higher odds of isolation (odds ratio = 2.23, 95% confidence interval = 1.1–4.4) when adjusted for age, gender and presenting with a cough. The IPCT identified measles training using standardised risk assessments by triage nurses in accident and emergency and intelligence regarding measles activity in the community as positive measures to prevent healthcare exposures. Conclusions We recommend opportunistic immunisation of unvaccinated young adults by GPs and that occupational health departments ensure their staff are protected against measles. Raising measles awareness in healthcare settings via training or regular sharing of current measles surveillance activity from public health to the IPCT and GP may improve triage and isolation of cases on arrival to healthcare premises.

PURPOSE: School social capital incorporates the intangible pro-social resources from social networks, including expectations and social norms, found in a school environment. School social capital may influence health behaviors such as smoking. This study examined the association of school social capital with smoking behaviors from childhood into adolescence. METHODS: We used a cohort sampled from 3 U.S. cities for the Healthy Passages Longitudinal Study of Adolescent Health. The primary outcome was cigarette smoking at grade ten (Wave 3). The primary predictor of interest was school social capital at grade five (Wave 1). We included potential covariates at the individual-, school-, and neighborhood-levels at Wave 1. To account for simultaneous clustering in schools and neighborhoods, cross-classified multilevel models (CCMM) were employed. RESULTS: After exclusions and imputations for missing variables, our final sample contained 3,968 students as constituents of 118 schools and 479 neighborhoods. With adjustment for the covariates, school social capital for grade five was negatively associated with cigarette smoking in grade ten. We estimated that a one-standard deviation increase in the school average social capital for grade five is associated with an odds ratio of 0.86 (95% Credible Interval: 0.75-0.98) for school-level smoking in grade ten. CONCLUSIONS: This study suggests that school social capital in late elementary years is associated with reduced smoking behaviors among adolescents in the United States. Influencing school social capital through enrichment of positive social norms and parent/teacher expectations may be a useful strategy to reduce adolescent smoking, with long-term implications for adult health.

Background Pre-treatment sleep disturbance has been shown to predict antidepressant treatment outcomes. How changes in sleep disturbance during acute treatment affect longitudinal outcomes, or whether continuation-phase treatment further improves sleep disturbance, is unclear. Methods We assessed sleep disturbance repeatedly in: a) 523 adults with recurrent MDD who consented to 12–14 weeks of acute-phase cognitive therapy (A-CT) and b) 241 A-CT responders at elevated risk for depression relapse/recurrence who were randomized to 8 months of continuation-phase treatment (C CT vs. fluoxetine vs. matched pill placebo) and followed protocol-treatment-free for 24 months. Trajectories of change in sleep and depression during and after A-CT were evaluated with multilevel models; individual intercepts and slopes were retained and input into Cox regression models to predict remission, recovery, relapse, and recurrence of MDD. Results Sleep disturbance improved over the course of A-CT, but most patients continued to report clinically significant sleep complaints. Response and remission were more likely in patients with less overall sleep disturbance and those with greater reduction in sleep disturbance during A-CT; these patients also achieved post-A-CT remission and recovery sooner. Sleep improvements endured throughout follow-up but were not enhanced by continuation-phase treatment. Sleep disturbance did not predict relapse or recurrence consistently. Limitations Objective sleep disturbance was not assessed. Analyses were not specifically powered to use sleep changes to predict outcomes. Conclusions Improvements in sleep disturbance during A-CT are linked to shorter times to remission and recovery, supporting consideration of monitoring and targeting sleep disturbance in adults with depression.

Objectives Plenty of studies have shown that wind velocity has an influence on airborne diseases. There is, however, no consistent conclusion found on the relationship between wind velocity and mumps, and the regional heterogeneity has been largely neglected in previous studies. This study aims to explore the association between wind velocity and mumps in Shenzhen. Study design Ecological study. Methods Sixteen subdistricts with the highest incidence rates of mumps were selected from Shenzhen city, and the multilevel distributed lag-nonlinear model was conducted to explore the relationship between mumps cases and wind velocity via the dlnm and lme4 packages of the software R 3.4.3. Results In Shenzhen, a total of 16,997 mumps cases were reported between 2013 and 2016, and the means of daily rainfall, temperature, relative humidity, and 10 min wind velocity were 5.74 mm, 23.27 °C, 76.31% and 1.87 m/s, respectively. Obvious nonlinear correlation relationships of wind velocity and mumps risk were found, where a reverse-V curved shape was shown in the exposure dimension with the logRR value of mumps peaking at 2 m/s, and the type of nonlinear correlation varying with the levels of wind velocity in lag dimension with a peak at two lag weeks. Conclusions The lag and nonlinear association between wind velocity and number of mumps cases were examined, while there was no statistically significant associations for other meteorological factors accounting for the regional heterogeneity. Results from this study indicated that public health administrators could strengthen health education in schools on ventilation management to prevent and control mumps outbreaks.

Excessive use of exclusionary school discipline with Black students is a persistent, systemic problem in U.S. schools with potential to affect students' perceptions of their school. For example, students may notice racial differences in out-of-school suspensions, which may relate to how academically engaged they feel and the extent to which they view the school's disciplinary environment as positive. The current study investigated school-level racial discipline disproportionality and observed classroom-level, positive behavior supports in relation to student perceptions of academic engagement and school disciplinary environment by fitting a series of three-level models, which included data on students (N = 17,115), classrooms (J = 310), and schools (K = 53). Two metrics of discipline disproportionality were used (i.e., the risk ratio and the risk difference) and moderation was examined through cross-level interactions. Results indicated that, regardless of race, students perceived the disciplinary environment as significantly less favorable in schools with greater racial discipline disproportionality when measured by the risk ratio, but not when measured by the risk difference. Using different disproportionality metrics in education research has important implications for policies and practices to identify and address the issue. How discipline disparities relate to the way that students perceive the disciplinary environment will likely inform intervention efforts for school psychologists.

Cold homes are associated with a range of serious health conditions as well as excess winter mortality. Despite a comparatively mild climate cold homes are a significant problem in the UK, with a recent estimate finding that over one-quarter of low-income households had been unable to adequately heat their home in winter 2022. The magnitude of cold housing in a country that benefits from a mild climate indicates indifference towards, or acceptance of, a significant minority of people living in inadequate conditions on the part of policy makers. Cold homes are therefore a source of social harm. Recent changes to the household energy price cap, the rising cost of living, the ongoing effects of the benefit cap, and below inflation uprating to social security benefits is likely to greatly exacerbate this issue. In this research we use data from the UK Household Longitudinal Study to explore whether living in a cold home causes mental health harm. We control for mental distress and housing temperature on entry to the survey in order to account for the potentially bi-directional relationship. Multilevel discrete-time event history models show that the transition into living in a home that is not suitably warm is associated with nearly double the odds of experiencing severe mental distress for those who had no mental distress at the beginning of the survey; and over three times the odds of severe mental distress for those previously on the borderline of severe mental distress. These results show the significant costs of failing to ensure that people are able to live in homes in which they are able to live comfortably by even the most basic standards. These costs will be felt not just individually, but also more broadly in terms of increased health spending and reduced working.

Stunting is a major global public health problem, associated with physical and cognitive impairments. Spatial variations in childhood stunting were observed due to changes in contextual variables from area to area, implying that geography is a crucial component in the development of strategies against childhood stunting. However, to our knowledge, there are no up-to-date studies on the distribution of childhood stunting and its determinants in Ethiopia. Thus, the aim of this study was to investigate the spatial distribution and determinants of stunting among children agedlt;5 y in Ethiopia.Geospatial and multilevel analysis of the Ethiopia Demographic and Health Survey 2019 data was done to investigate the spatial distribution and determinants of stunting among children agedlt;5 y in Ethiopia. The analysis included 5753 weighted children agedlt;5. Spatial autocorrelations analysis was done to assess the spatial dependency of stunting. Hot spot and cluster outlier analysis was used to observe the spatial clustering of stunting. Kriging interpolation was used to predict stunting in an unsampled area. A multilevel logistic regression model was fitted to identify determinants of stunting. Adjusted odds ratio with 95% confidence interval (CI) was calculated and variables having a Plt; 0.05 were declared statistically significant.The national prevalence of stunting was 36.81% (95% CI, 35.48%-38.15%), with significant spatial variations across Ethiopia. Spatial clustering of stunting was detected in the northern, northwestern, northeastern, and southwestern parts of Ethiopia. Age and sex of the child, birth interval, birth type, household wealth status, maternal education, region, and community-level illiteracy were factors significantly associated with stunting.Stunting significantly varies across Ethiopia, with the highest prevalence in Northern Ethiopia. Older age, poor family wealth, maternal illiteracy, and community illiteracy level were the significant determinants of stunting in children agedlt;5 y in this study. Policymakers should design interventions to reduce stunting among children agedlt;5 y through accessing education for women and applying economic empowerment strategies in the hot spot areas.

While substance use and mental health symptoms commonly co-occur among adolescents, few population-level studies have examined profiles of co-occurrence to inform tailored prevention and early interventions.A multilevel latent profile analysis was conducted on a representative sample of 11,994 students in 68 secondary schools to: 1) identify distinct profiles of co-occurring substance use and mental health symptoms; 2) identify types of schools based on student profiles; and 3) explore school correlates of student profiles and school types, including school climate, belonging, and safety.Five student profiles and three school types were identified. Among students, 57.6 % were in a low substance use and mental health profile, 22.5 % were in a high mental health but low substance use profile, 9.7 % were in a heavy drinking and cannabis use profile, 3.7 % were in a heavy drinking and smoking profile, and 6.5 % were in a high substance use and mental health profile. Positive school climate, belonging, and safety increased the odds of students being in the low profile, with belonging yielding larger effects among females. Among schools, 28 % had low, 57 % had moderate, and 15 % had high levels of student substance use and comorbid mental health symptoms. Rural schools were disproportionately represented in higher risk school types.The identified student substance use and mental health symptom profiles can serve as targets for tailored prevention and early interventions. Results support examining school-based interventions targeting school climate, belonging, and safety with potential benefits to both substance use and mental health.

Higher family affluence is associated with healthier behaviours in adolescents, but the strength of this association varies across countries. Differences in social mobility at the country-level, i.e. the extent to which adolescents develop a different socioeconomic status (SES) than their parents, may partially explain why the association between family affluence and adolescent health behaviours is stronger in some countries than in others. Using data from adolescents aged 11-15 years from 32 countries, participating in the 2017/2018 wave of the Health Behaviour in School-aged Children (HBSC) study (N = 185,086), we employed multilevel regression models with cross-level interactions to examine whether country-level social mobility moderates the association between family affluence and adolescent health behaviours (i.e. moderate-to-vigorous physical activity, vigorous physical activity, healthy and unhealthy foods consumption, having breakfast regularly, and weekly smoking). Higher family affluence was more strongly associated with higher levels of adolescent physical activity in countries characterized by high levels of social mobility. No cross-level interactions were found for any of the other health behaviours. Differences in social mobility at the country-level may contribute to cross-national variations in socioeconomic inequalities in adolescent physical activity. Further research can shed light on the mechanisms linking country-level social mobility to inequalities in adolescent physical activity to identify targets for policy and interventions.

In the multilevel modeling literature, contextual effect is defined as or identified by the effect of the target group-level variable while controlling for the corresponding individual-level variable. This paper extends the notion of "contextual effects" (or "neighborhood" or "school" effects) to an interaction setting, such that the effect of one explanatory variable X

Childhood underweight is a critical public health problem that needs urgent attention in developing countries like Ethiopia. Despite its variation between localities, the determinant factors and its geospatial variation have not been adequately addressed across the various regions of the country. Therefore, the aim of this study was to investigate the spatial variation and determinant factors of underweight among children under 5 y of age in Ethiopia.The total weighted samples of 5753 children aged5 y were included in this study. The data were taken from the 2019 Ethiopian Demographic and Health Survey (EDHS 2019). Arc GIS software was used to analyze geospatial variations to identify the hot- and cold spot areas of underweight in Ethiopia. A multilevel multivariable logistic regression model was used to identify the determinant factors of underweight. Excel, STATA-16, and ArcGIS software were used for the data management and analysis. In the multivariable multilevel analysis, adjusted odds ratio (aOR) with 95% confidence interval (CI) was used to declare significant determinants of underweight among children aged5 y.Among 5753 children aged5 y in Ethiopia, 21.3% were underweight during the 2019 EDHS. The distribution showed that there was a geospatial variation of underweight among children aged5 y in Ethiopia; the Global Moran's index value was 0.36 with P0.001. In multivariable multilevel analysis, the significant factors associated with underweight were the sex of the child (aOR, 1.25; 95% CI, 1.09-1.44); age of the child, with the highest odds of being underweight observed in the age group of 24 to 35 mo (aOR, 3.52; 95% CI, 2.60-4.74); wealth index, with poorer children having higher odds of being underweight (aOR, 2.25; 95% CI, 1.58-3.24); and the regions, with the highest odds of underweight was observed in Tigray (aOR, 5.63; 95% CI, 2.79-11.36) and Afar (aOR, 4.71; 95% CI, 2.33-9.51).Underweight has significant spatial variation in Ethiopia, with spatial clustering in the northern and eastern parts of the country. It is recommended that in regions like Tigray, Afar, and Somali, as well as some areas in Gambella, priority steps be taken to reduce the burden of underweight in children aged5 y. Thus, nutritional intervention programs should be strengthened and intervention strategies developed, with special emphasis on families with poor wealth index in the hotspot areas.

Depression is one of the most prevalent mental illnesses in the world. Its associated factors have been scarcely studied in the Latin American population. Our aim was to determine the contextual and individual factors associated with depressive symptoms (DS) in residents of 11 Latin American cities according to the 2019 CAF Survey (ECAF, acronym in Spanish). A multilevel analysis was performed to identify individual and contextual factors associated with DS. DS were measured by the short version of the Center for Epidemiological Studies Depression Scale (CES-D-10). Of the 10,206 participants, 42.0% had DS in the week prior to the survey. Regarding the individual factors studied, women (OR = 1.81, 95% CI: 1.65-1.99), smokers (OR = 1.30, 95% CI: 1.16-1.45), obese, junk food eaters more than twice a week, single people, and a greater number of people in the household were associated with greater probabilities of having DS. On the other hand, a secondary (OR = 0.77; 95% CI: 0.67-0.88) or superior educational level (OR = 0.58; 95% CI: 0.50-0.68) were associated as protective factors. Regarding contextual factors, higher contamination levels (OR = 1.07, 95% CI: 1.01-1.13) were associated with DS. Our study reports associations between individual and environmental factors and DS in residents of Latin America. These findings will allow the adoption of the necessary measures for decision-making and research to face this growing problem in developing countries.

Adolescents often display similar health behaviour to their peers. Peer effects on health behaviour may be influenced by the school context, and by the country of residence. According to the complex contagion theory, these effects for risky health behaviour may be different from protective health behaviour. This paper combines social network analysis and multilevel analysis to estimate the relative share of variation of risky and protective health behaviours at different levels of the population structure: individuals, peer (friendship) networks, and schools. To achieve these aims, multiple membership models are applied to estimate variations in smoking, drinking, cannabis use, and physical activity at the individual, peer, and school levels, taking into account the differences between countries. The data come from a social network survey carried out in 50 schools in six medium-sized European cities. Networks of peers were found to have similar risky health behaviour when it comes to smoking, drinking, and cannabis use. This was not true, however, for positive health behaviour, i.e. physical activity. For smoking, drinking, and cannabis use, the peer network accounted for almost half of the total behaviour variance. In comparison, the school variance was quite small for all health behaviour. The results suggest that interventions are best carried out at the peer-network level, particularly for behaviour vulnerable to complex contagion, such as smoking and cannabis use.

Background Previously published findings from a study of university students living in substance use disorder (SUD) recovery housing showed an eight-session heart rate variability biofeedback (HRVB) intervention significantly reduced craving. That study, however, uncovered pronounced inter-participant variability in craving change patterns through the course of HRVB that warranted further exploration. The purpose of the current investigation was to examine how within- and between-person factors may have differentially influenced craving changes. Methods A longitudinal multilevel modeling approach was used with time at level-1 nested within persons at level-2. Multilevel models of change were estimated to model craving trajectories and predictor relationships over time as a function of age, sex, length of abstinence, daily HRVB practice, anxiety, depression, and stress. Results A quadratic pattern of craving reductions was found, indicating that craving reductions accelerated over time for some participants. Daily HRVB practice of >12 min and older age significantly enhanced craving reductions over time. Increases in depressive symptoms attenuated the effects of HRVB on craving. The other predictors were not significantly associated with craving in this study. The true R2 for the final model indicated that 20.5% of the variance in craving was explained by older age, daily HRVB >12 min, and within-person changes in depression. Conclusions HRVB shows promise as an accessible, scalable, and cost-effective complementary anti-craving intervention. Healthcare providers may help persons recovering from SUD to better manage substance craving by the routine and strategic use of HRVB practice.

Several theories posit that cannabis and other substances are used to reduce negative affect. This daily report study considered whether variations in positive and negative affect, reported each morning, contributed to the likelihood of cannabis use later that day. We also explored whether levels of positive and negative affect reported immediately after cannabis use improved, relative to that day's morning levels. The sample included 183 men and 183 women representing heterosexual, cannabis-using couples from the community. Participants made independent, daily reports of affect and cannabis use episodes for 30 consecutive days. Using multilevel modeling, we modeled men's and women's use of cannabis on a given day as a function of morning levels of positive, hostile, and anxious affect, accounting for partner cannabis use that day, and mean levels of positive and negative affect. Men and women were more likely to use cannabis on a given day when morning positive affect was lower than typical for the person and when partner used cannabis that day. Neither hostile nor anxious affect contributed to later use of cannabis. Immediately after cannabis use, positive affect increased, and hostile and anxious affect decreased relative to that day's morning levels. The improved affect immediately after use suggests a mechanism of positive reinforcement.

This paper provides a tutorial companion for the methodological approach implemented in Huh et al. (2015) that overcame two major challenges for individual participant data (IPD) meta-analysis. Specifically, we show how to validly combine data from heterogeneous studies with varying numbers of treatment arms, and how to analyze highly-skewed count outcomes with many zeroes (e.g., alcohol and substance use outcomes) to estimate overall effect sizes. These issues have important implications for the feasibility, applicability, and interpretation of IPD meta-analysis but have received little attention thus far in the applied research literature. We present a Bayesian multilevel modeling approach for combining multi-arm trials (i.e., those with two or more treatment groups) in a distribution-appropriate IPD analysis. Illustrative data come from Project INTEGRATE, an IPD meta-analysis study of brief motivational interventions to reduce excessive alcohol use and related harm among college students. Our approach preserves the original random allocation within studies, combines within-study estimates across all studies, overcomes between-study heterogeneity in trial design (i.e., number of treatment arms) and/or study-level missing data, and derives two related treatment outcomes in a multivariate IPD meta-analysis. This methodological approach is a favorable alternative to collapsing or excluding intervention groups within multi-arm trials, making it possible to directly compare multiple treatment arms in a one-step IPD meta-analysis. To facilitate application of the method, we provide annotated computer code in R along with the example data used in this tutorial.

Background Factors associated with marijuana use in electronic nicotine delivery systems (ENDS) are largely unknown. ENDS advertising, through subtle normative cues as well as explicit and implicit messages suggesting ENDS products are socially condoned and healthier alternatives, may influence the use of marijuana in ENDS. The aim of our study was to examine the association between exposure to ENDS advertising and subsequent use of ENDS with marijuana among college students. Methods Data for this study were from waves 2 and 4 of the Marketing and Promotions across Colleges in Texas (M-PACT) study. Participants included 3720 college students (mean age = 21.4, SD = 2.3; 35.78% white; 35.7% male) across 24 colleges in Texas who completed online tobacco behavior surveys one year apart. Multilevel logistic regression was conducted to examine the association between ENDS advertising exposure at wave 2 (spring 2015) and use of marijuana in ENDS one year later at wave 4 (spring 2016), controlling for age, sex, race/ethnicity, and wave 2 sensation-seeking, impulsivity, current tobacco use, current marijuana use, and ever use of ENDS with marijuana. Use of ENDS to consume marijuana in the past six months was the outcome variable and ENDS advertising exposure was the independent variable. Results Nearly half of participants reported ever ENDS use at waves 2 and 4, and 10% used marijuana in ENDS in the past 6-months at wave 4. Multilevel logistic regression analyses indicated that for every unit increase in ENDS advertising exposure, the odds of subsequently using ENDS with marijuana one year later were 1.08 times (95% CI = 1.01–1.14) greater. Conclusions ENDS advertising uniquely contributed to the subsequent use of marijuana in an ENDS, over and above the effects of other risk factors.

Objective Sports clubs have been identified as settings where high levels of risky alcohol consumption occurs. Settings characterised by such behaviour are likely to negatively impact on levels of safety, participation and amenity. Design The study was part of a randomised control trial, designed to help community sports clubs responsibly manage the sale and consumption of alcohol; the primary outcome was reduction in alcohol consumption. This study examined the secondary effects of safety and participation. Methods A multilevel analysis examining the pathways between the alcohol intervention, risky alcohol consumption, and safety and participation was undertaken. Results It was identified that average overall risky consumption at the club level mediated the association between the intervention and increased participation; the intervention reduced overall hazardous consumption, which in turn increased participation at the club. Conclusion Interventions that target responsible alcohol management can also increase club participation. Implications for public health: Given the number of individuals involved with sports clubs, responsibly managing alcohol will also ensure that sports clubs are health promoting settings that promote community participation and engagement.

Safe and stable housing is integral to addiction recovery. Across numerous studies, recovery housing has been found to be associated with improvements in a variety of domains. Although procedures for operating some types of recovery housing have been manualized and national standards established, there are few empirical findings identifying which recovery residence characteristics may lead to improved outcomes. Using data from 330 newly admitted residents recruited from 49 sober living houses in California and re-contacted for 6- and 12-month follow-up interviews, this study examines the effects of organizational, operational, and programming characteristics on substance use, criminal justice, and employment outcomes. Results from multilevel analyses adjusting for resident demographics and length of stay indicate that organizational characteristics were associated with outcomes. Residents recruited from houses that were part of a larger organization or group of houses had increased odds of total abstinence (aOR = 3.98, p

The aim of this pilot study is to evaluate the efficacy of a resource activation (RA) program as an alternative intervention for children and adolescents with tic disorders. RA interventions focus on the strengths and abilities of the patients. This is expected to improve the patients’ perceptions regarding their own resources, which may indirectly result in a reduction of tic symptoms, impairment and comorbid conditions. A within-subject design with two phases (8 weeks diagnostic; 16 sessions treatment) was analyzed using multilevel modeling (n = 24). During the treatment phase, significant reductions of tics were found in clinical rating (Yale Global Tic Severity Scale; YGTSS), parent rating and video observation (motor tics). Moreover, an improvement was shown on most tic-related impairment and subjective burden (SB) ratings. No significant improvement was found regarding comorbid problems and self-esteem. Compared to the preceding diagnostic phase, a significant incremental treatment effect emerged in clinical rating of tic symptoms (YGTSS) and video observation (motor tics). This pilot study provides first hints that RA may represent an effective treatment for reducing tic symptoms, impairment and SB. However, further research is needed in order to establish RA as an effective treatment for tic disorders.

Background No study has examined trajectories of school-based adaptive functioning (AF) for children with developmental disabilities (DD). This is a critical gap in the literature, since AF is context dependent, and high levels of AF at school facilitate meaningful participation at school. Aims This study examined trajectories of school-based AF for 170 children with DD from age 3 to 15 years, and indicators of the early childhood home and family environment as predictors of these trajectories. Methods Multilevel modeling was used to explore trajectories of school-based AF and identify early childhood home and family predictors of these trajectories. Results Children’s school-based AF raw scores increased over time. There was significant variability in initial status and rate of change of AF. As hypothesized, higher quality mother-child interaction predicted more positive functioning. Conclusions Findings indicate the influence of the early childhood home and family environment on school-based AF over time.

Rationale Rates of adolescent pregnancy and sexually transmitted infections (STIs) in the United States remain high. Norms and beliefs about sex and the use of contraception have been identified as potential contributors to these. Objective The current study examined multi-contextual links between norms and beliefs about sex and contraception, and adolescent pregnancies and STIs. Method Hierarchical linear modeling (HLM) was used to test the study questions in the historical data from Add Health dataset (Wave I, 1994–1995, and Wave II, 1995–1996). Measures of beliefs about sex and contraception were administered to adolescents and their caregivers; pregnancies and STIs were reported by adolescents (N = 13,568; level 1). School-reported data (N = 132; level 2) included sexuality education and prevalence of pregnancies at schools. Community data included the density of family planning providers in each county. Results Adolescents negative beliefs about contraception were associated with a higher likelihood of pregnancies and STIs via their association with contraception use. The opposite effect was found for negative beliefs about sex. Parental disapproval of contraception was associated with a decreased likelihood of STIs, but with an increased likelihood of pregnancies. A greater number of pregnancies at school was associated with a greater likelihood of STIs. Unexpectedly, the number of county-level family planning providers was associated with a higher likelihood of STIs. Conclusion Adolescent individual beliefs emerged as the most salient predictors of both pregnancies and STIs.

Epilepsy is a commonly secondary disability in people with an intellectual disability (ID), affecting 22% of the ID population while 1% of general population. Surprisingly, EEG-based automated seizure detection in the ID population has not yet been sufficiently studied. The reasons are twofold. Firstly, long-term EEG recordings are few due to behavioral problems. Secondly, the annotation of EEG recordings has been proved difficult due to the complex EEG signal abnormalities caused by brain development disorders. As a result, the performance of automated seizure detection for ID people is largely unknown. In this work, we performed automated seizure detection on a retrospective dataset containing 615 h ambulatory scalp EEG from 29 participants with ID, including 91 seizures. To design a generic seizure detector for the ID people, we need to deal with three major problems: highly imbalanced data, heterogeneous dataset and difficult annotation. (1) For the imbalanced data, we used proper performance criteria (e.g., precision and recall curve) and employed a post-processing process (i.e., patient-specific detection thresholds). (2) For the heterogeneous dataset, we employed multi-domain EEG features that showed a better discriminative power in our dataset, and compared the linear and nonlinear (LDA vs. SVM with Gaussian kernel) classifiers and validated using a leave-one-out cross validation (LOOCV). (3) A stepwise EEG annotation procedure was used to improve the accuracy of annotation due to the presence of numerous seizure imitators and unclear contrast between ictal and interictal EEG activities. Results showed that LDA outperformed SVM with a clear margin of sensitivity, and achieved overall sensitivities 63.1–81.3%, a median FD/h of 1.0 and median latency of 11.5 s. Finally, we conclude that EEG signals of the ID population form a heterogeneous entity with respect to important factors: EEG discharge patterns, EEG backgrounds and EEG seizure visibility. The performance of the seizure detection varies significantly with these factors. The results presented here can serve as prior knowledge for designing a generic seizure detector for the ID patients and the non-convulsive seizure states (NCSS).

Background Parental reports are commonly used for adolescent HPV vaccination status but may be subjected to bias. Guided by the Socioecological Framework, our study explores potential multilevel factors influencing the inaccuracy of parental reports of adolescent HPV vaccination status. Methods Data from parents of 19,683 adolescents with provider-verified data were analyzed using multilevel modeling. Correlates included adolescent characteristics, parent/household factors, number of providers seen, state-level median income, and state-level HPV vaccine policy. Outcomes included inaccuracy in reporting: vaccine initiation (≥1 dose), completion (3 doses), and number of doses. Results 24% and 25% of parents reported initiation and completion inaccurately; 28% under-reported and 11% over-reported number of doses. All adolescent characteristics, parent/household factors, and number of healthcare providers seen were associated with the outcomes. Of note, compared to parents of White adolescents, parents of racial/ethnic minority adolescents were more likely to inaccurately report all outcomes (aOR ranges from 1.43 to 1.76 for initiation, 1.45–1.75 for completion, 1.98–2.05 for under-reporting, and 1.17–1.41 for over-reporting). Households with higher maternal education (aOR = 0.70, 0.92, 0.79, and 0.80) and income (aOR = 0.54, 0.62, 0.50, and 0.70) were less likely to inaccurately report initiation, report completion, under-report, and over-report, respectively. Those having seen more providers were less likely to inaccurately report initiation and completion but more likely to over-report number of vaccine doses. Discussion Being parents of females, older adolescents, and racial/ethnic minority adolescents, having lower material education, and poverty status were associated with higher odds of inaccurately reporting HPV vaccination status. These results have implications for estimates drawn from self-reports. Future research can examine sources of inaccuracies (e.g., social desirability or health literacy); they could also explore solutions (e.g., access to vaccine records) that can help parents accurately report vaccination status. State policy does not appear to have an impact on report accuracy.

The aim of the present study was to explore the role of teachers' emotional labor in explaining their enthusiasm, as perceived by their students, and the students' outcomes. Data on emotional labor from 90 high-school teachers and data on perceived teacher enthusiasm, intrinsic motivation, positive affect, and deep learning strategy from their students (N = 2019) were obtained. In order to account for the nested structure of the data and to examine the relationships between study constructs, a multilevel structural-equation modelling technique (ML-SEM) was implemented. The results at the class level showed that teacher enthusiasm fully mediated the relationship between the emotional-labor strategy of hiding feelings and student outcomes, and partially mediated the relationship between the emotional-labor strategy of faking emotions and students' positive affect. Also, faking emotions has direct and positive contribution in explaining class positive affect and intrinsic motivation.

Examining health inequalities intersectionally is gaining in popularity and recent quantitative innovations, such as the development of intersectional multilevel methods, have enabled researchers to expand the number of dimensions of inequality evaluated while avoiding many of the theoretical and methodological limitations of the conventional fixed effects approach. Yet there remains substantial uncertainty about the effects of integrating numerous additional interactions into models: will doing so reveal statistically significant interactions that were previously hidden or explain away interactions seen when fewer dimensions were considered? Furthermore, how does the multilevel approach compare empirically to the conventional approach across a range of conditions? These questions are essential to informing our understanding of population-level health inequalities. I address these gaps using data from the National Longitudinal Study of Adolescent to Adult Health by evaluating conventional and multilevel intersectional models across a range of interaction conditions (ranging from six points of interaction to more than ninety, interacting gender, race/ethnicity/immigration status, parent education, family income, and sexual identification), different model types (linear and logistic), and seven diverse dependent variables commonly examined by health researchers: body mass index, depression, general self-rated health, binge drinking, cigarette use, marijuana use, and other illegal drug use. Findings suggest that adding categories to intersectional analyses will tend to reveal new points of interaction. Stratum-level results from the multilevel approach are robust to cross-classification by school context. Conventional and multilevel approaches differ substantially when tested empirically. I conclude with a detailed consideration of the origin of these differences and provide recommendations for future scholarship of intersectional health inequalities.

Research shows that the school environment is an important social determinant of health among children and adolescents. However, we know virtually nothing of the health consequences of national education systems and policies, for example the stratification of pupils by academic ability. This study aimed to investigate if education system stratification is related to self-reported psychological and somatic health complaints of pupils aged 11 to 15, and social inequalities in such health complaints. Survey data from the Health Behaviors of School-aged Children (HBSC) survey, covering 33 countries and more than 180 000 pupils in primary and lower secondary school, were used. Multilevel models showed that education system stratification was not associated with the average levels of health complaints of pupils, but cross-level interaction effects showed that stratification moderated the relationship between social background and health complaints, such that inequalities in health complaints were smaller in countries with more stratified systems. Moreover, this moderating effect was mediated by the school learning environment and social relations in school. Specifically, social inequalities in school pressure, academic self-concept, school climate, and school satisfaction were smaller in more stratified education systems, which in turn accounted for smaller inequalities in health complaints in these countries.

Neuropsychological alterations have been identified in populations heavily exposed to metals with neurotoxic potential, such as manganese (Mn). This study examined the associations between Mn environmental exposure in school-aged children and executive functions, using structural equation modeling. Children, aged between 7 and 12 years (N = 181), were recruited from four elementary schools located in a region that is under the influence of atmospheric emissions from a ferro-manganese alloy plant in the municipality of Simões Filho, Bahia, Brazil. The following cognitive functions were evaluated: Intelligence, Inhibitory Control, Cognitive Flexibility, Verbal and Design Fluency, Verbal and Visual Working Memory and Attention. We performed structural equation modeling to identify the following executive functions latent variables: working memory, inhibitory control and cognitive flexibility. We further analyzed the relations between executive functions and Mn measured in hair (MnH) and toenails (MnTn) with linear mixed models, after controlling for co-variables. A positive effect at the individual level on working memory, inhibition control and cognitive flexibility was observed with MnTn after controlling for co-variables, but no association was found with MnH levels. However, children attending school most environmentally exposed to Mn emissions, which had the highest rate of Mn dust deposition, had the poorest scores on working memory. These findings suggest both benefits and risk of Mn on children's cognitive development.

We investigated how gender identity, sexual orientation, and race/ethnicity intersect to shape the social epidemiology of HPV vaccination initiation among U.S. college students. Cross-sectional survey data were from the National College Health Assessment (Fall, 2019-Spring, 2020; N = 65,047). We conducted an intersectional Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy by nesting participants within 36 social strata defined using gender identity, sexual orientation, and race/ethnicity. Bayesian multilevel logistic regression models with random intercepts for social strata were fit for HPV vaccination initiation. Intersectional models adjusted for the additive main effects to isolate intersectional interactions, controlling for age and geographic region. Social strata that included cisgender men, transgender women, and non-binary assigned-male-at-birth individuals and strata that included racial/ethnic minorities had a significantly lower likelihood of HPV vaccination initiation relative to strata including cisgender women and non-Hispanic White individuals, respectively, while strata including lesbian/gay and bisexual/pansexual/queer individuals had a significantly higher likelihood of HPV vaccination initiation relative to strata including heterosexual individuals. We also observed substantial between-stratum inequities in the predicted prevalence of HPV vaccination initiation, with estimates ranging from 59.2% for heterosexual, racial/ethnic minority, cisgender men to 87.1% for bisexual/pansexual/queer, racial/ethnic minority, non-binary assigned-female-at-birth individuals. That being said, the majority of the observed between-stratum variance was driven by additive rather than intersectional interaction effects and the discriminatory accuracy of intersectional stratification with respect to predicting HPV vaccination initiation was low. Collectively, our findings point to a need for more universal guidelines and clinician recommendations that promote HPV vaccine uptake for all adolescents, regardless of race/ethnicity, gender identity, sex-assigned-at-birth, or sexual orientation; however, utilizing an intersectional lens will ensure that resulting public health interventions address inequities and center the needs and experiences of multiply marginalized adolescents.

Many datasets used in the social sciences have a hierarchical structure, where lower units of aggregation are 'nested' in higher units. In many disciplines, such data are analyzed using multilevel modeling (MLM, also known as hierarchical linear modeling). However, MLM as a framework is relatively unknown in economics. Instead, economists use a range of separate econometric methods, including cluster-robust standard errors, fixed effects models, models with cross-level interactions, and estimated dependent variable models. Relying on an extensive literature review, this paper describes this methodological divide and provides a detailed comparison between MLM and 'economic methods' in their abilities to deal with three methodological challenges inherent in multilevel data ‒ clustering, omitted variables, and coefficients' heterogeneity across groups. We unfold the comparative advantages of these two methodological approaches and provide practical recommendations about which of them should be used, why, and in what settings.

The Fatality Analysis Reporting System (FARS) provides important data for studying the role of marijuana in motor vehicle crashes. However, marijuana testing data are available for only 34% of drivers in the FARS, which represents a major barrier in the use of the data.We developed a multiple imputation (MI) procedure for estimating marijuana positivity among drivers with missing marijuana test results, using a Bayesian multilevel model that allows a nonlinear association with blood alcohol concentrations (BACs), accounts for correlations among drivers in the same states, and includes both individual-level and state-level covariates. We generated 10 imputations for the missing marijuana-testing data using Markov chain Monte Carlo simulations and estimated positivity rates of marijuana in the nation and each state.Drivers who were at older age, female, using seatbelt at the time of crash, having valid license, or operating median/heavy trucks were less likely to test positive for marijuana. There was a reverse U-shaped association between BACs and positivity of marijuana, with lower positivity when BACs 0.01 g/dL or ≥0.15 g/dL. The MI data estimated a lower positivity rate of marijuana in the nation and each of the state than the observed data, with a national positivity rate of 11.7% (95% CI: 11.1, 12.4) versus 14.8% using the observed data in 2013.Our MI procedure appears to be a valid approach to addressing missing marijuana data in the FARS and may help strengthen the capacity of the FARS for monitoring the epidemic of drugged driving and understanding the role of marijuana in fatal motor vehicle crashes in the United States.

Typical of the teaching profession is the multitude of actors that comment on and evaluate teachers’ work. Previous studies indicate that teachers feel that their work is relatively underappreciated in society. Little is known about the dynamics that explain apparent variation in this feeling. Based on data from 66,593 teachers in 25 countries we study variation of Perceived Societal Appreciation (PSA). We find robust evidence that a change within countries in PISA scores predicts a within country trend in levels of PSA. In the conclusion we critically engage with contemporary OECD policies by arguing that inducing a crisis mentality about educational quality risks accomplishing the exact opposite than what one aims for.

Background Most research on mental illness stigma has involved people with psychosis; less information is available for people with affective and anxiety disorders. We aimed to compare experienced and anticipated discrimination among people with schizophrenia, and affective and anxiety disorders. Methods People with schizophrenia (n=773), affective (n=1010) and anxiety disorders (n=372) were recruited during psychiatric admission across 5 EU countries. The Discrimination and Stigma Scale (DISC-12) was used. Multivariate mixed effect logistic regression models with a random effect for hospital and country were performed to explore patient characteristics associated with experienced and anticipated discrimination. Results With anxiety disorders, there were more reports of experiences of discrimination in social life (35%), intimate relationships (23.5%), and physical healthcare (19%); in schizophrenia, in relations with neighbours (23.6%) and mental health staff (21.7%); and in affective disorders, in parental role (22.8%). In multivariate analyses, anxiety was associated with increased likelihood of experiencing discrimination in police interactions (OR=1.675; p=0.038) and physical healthcare (OR=1.816; p=0.003), and reduced likelihood when starting a family (OR=0.474; p=0.01) as compared with schizophrenia. Affective (OR=1.367; p=0.004) and anxiety disorders (OR=1.354; p=0.034) were associated with increased likelihood of concealing a diagnosis compared with schizophrenia. Limitations As patients with affective and anxiety disorders were recruited from hospital inpatient units, their experiences may not be representative of all people with these disorders. Conclusions In a sample of people receiving inpatient treatment, experienced and anticipated discrimination are perceived, at least in some life domains, as more of a burden for people with affective and anxiety disorders than those with schizophrenia.

Background Adequate infant and young child feeding during the first 1000 days of life is very essential to improve child health, survival, growth, and development through minimum dietary diversity (MDD). Hence, this study aimed to assess MDD and its multi-level factors among infants and young children aged 6–23 months in Ethiopia. Methods Ethiopian Demographic and Health Survey (EDHS-2016) data was used to identify both individual and community-level factors of dietary diversity. Weighted samples of 2,962 children were eligible and a multi-level regression model was used for the analysis. Finally, factors with a P-value of, Infant feeding; Child feeding; Diet; Children; Multilevel analysis; Ethiopia demographic and health survey.

Traffic violations, particularly drink driving, are a menace to the drivers themselves, and to other road users. Drink driving crashes often cause death or serious injury to the driver. Understanding the recidivism effect factor of drink driving is essential for designing effective countermeasures. This study is based on register-based data from the National Police Agency, Ministry of the Interior of Taiwan and monthly administrative area information from 2012 to 2015 for the entire population. Hence, this study not only focuses on the effect factor and violation differences between recidivists and non-recidivists, but discusses the entire regional characteristics effect for recidivism. The purpose of this study is to offer a comprehensive econometrical framework, using a multilevel random effect logistic model, which highlights important contributors to drink driving recidivism from regional attributes. As the study findings from our empirical results indicate, there are statistically significant differences with drink driving in administrative areas, depending on the number of report on drink driving by police, divorce rate of the population, alcohol consumption, number of community security patrol teams, number of bus trips, and level of education. The results of this study provide suggestions to the government for enhancing community security and developing public transportation, both of which can effectively decrease drink driving recidivism and improve public road safety.

Background: The use of Multilevel Models (MLM) and Generalized Estimating Equations (GEE) for analysing clustered data in the field of intellectual and developmental disability (IDD) research is still limited.\ud \ud Method: We present some important features of MLMs and GEEs: main function, assumptions, model specification and estimators, sample size and power. We provide an overview of the ways MLMs and GEEs have been used in IDD research. \ud \ud Results: While MLMs and GEEs are both appropriate for longitudinal and/or clustered data, they differ in the assumptions they impose on the data, and the inferences made. Estimators in MLMs require appropriate model specification, while GEEs are more resilient to misspecification at the expense of model complexity. Studies on sample size seem to suggest that Level 1 coefficients are robust to small samples/clusters, with any higher-level coefficients less so. MLMs have been used more frequently than GEEs in IDD research, especially for fitting developmental trajectories. \ud \ud Conclusions: Clustered data from research in the IDD field can be analysed flexibly using MLMs and GEEs. These models would be more widely used if journals required the inclusion of technical specification detail, simulation studies examined power for IDD study characteristics, and researchers developed core skills during basic studies.\ud

Background Rising numbers of visits to emergency departments (EDs), especially amongst the elderly, is a source of pressure on hospitals and on the healthcare system. This study aims to establish the determinants of ED visits in France at a territorial level with a focus on the impact of ambulatory care organisation on ED visits by older adults aged 65 years and over. Methods We use multilevel regressions to analyse how the organisation of healthcare provision at municipal and wider ‘department’ levels impacts ED utilisation by the elderly while controlling for the local demographic, socioeconomic and health context of the area in which patients live. Results ED visits vary significantly by health context and economic level of municipalities. Controlling for demand-side factors, ED rates by the elderly are lower in areas where accessibility to primary care is high, measured as availability of primary care professionals, out-of-hours care and home visits in an area. Proximity (distance) and size of ED are drivers of ED use. Conclusion High rates of ED visits are partly linked to inadequate accessibility of health services provided in ambulatory settings. Redesigning ambulatory care at local level, in particular by improving accessibility and continuity of primary and social care services for older adults could reduce ED visits and, therefore, improve the efficient use of available healthcare resources.

This study assesses the gender gap in cognitive health among older adults in India and examines the extent to which individual, household and state level characteristics contribute to the male-female difference in cognitive health. The study is based on 6548 women and men who participated in the WHO Study on Global AGEing and Adult Health conducted in six states in India during 2007–08. Multilevel ordinary least square regression was used to examine the gender difference in cognitive health, adjusting for individual, household, health behavior and state-level variables. A composite cognitive score (CCS) was calculated by combining z-scores of five individual cognitive tests. Results suggest that CCS is worse among women than among men after adjusting for individual and state level factors. The largest reduction in the gender gap in CCS was observed when adjusting for education, followed by other individual factors such as marital status, individual height, caste, religion, tobacco consumption and chronic health status. Although state level urbanization and female workforce participation rate were significantly associated with CCS, these characteristics did not contribute to the reduction of gender difference in CCS. This study extends the current knowledge of women’s disadvantage in cognitive health, demonstrating that individual level characteristics remain key determinants of gender difference in cognition among older adults in India. Importantly, this relationship holds in the context of very large cross-state variations in cognitive health and its determinants., Highlights • CCS is worse among women after adjusting for individual and state-level factors. • Individual-level characteristics remain key determinants of gender gap in CCS. • State-level characteristics did not contribute to the reduction of gender gap in CCS.

Despite the gains in cervical cancer screening, there remain persistent socio-economic, geographical, racial, and ethnic disparities. This study examines the combined effect of individual- and county-level characteristics on the use of cervical cancer screening tests such as Papanicolaou (Pap) tests in Texas.Cross-sectional study.Individual-level information was obtained from 2014-2015 Texas Behavioral Risk Factor Surveillance System (BRFSS). Using the county of residence of the study population, the BRFSS data were linked to the American Community Survey (2010-2014) and the Area Health Resources File (2015). Women aged between 21 and 65 years, with no history of hysterectomy, and residing in 47 counties in Texas were included in the study (n = 4276). Multi-level logistic regression was used to assess the independent influences of individual- and county-level covariates on receipt of a Pap test in the past 3 years.The odds of timely Pap testing were lower among women aged greater than 50 years, single women, and those with low education and income ($25,000). Black women who reside in counties with higher percentages of Hispanics (quartile 4) were less likely to be screened compared with black women living in counties with a low Hispanic population (adjusted odds ratio [OR] = 0.08 [95% confidence interval [CI]: 0.02-0.37]). County-level socio-economic status, although associated with timely screening in bivariate analysis, was not a significant predictor of screening after controlling for individual characteristics.There are significant disparities in the uptake of cervical cancer screening across Texas counties. Individual-level socio-economic disparities as well as the number of obstetric-gynecologic physicians in a county are predictors of these disparities.

Background The relative importance of individual and country-level factors influencing access to diagnosis and treatment for depression across the world is fairly unknown. Methods We analysed cross-national data from the WHO World Health Surveys. Depression diagnosis and access to health care were ascertained using a structured interview. Logistic Bayesian Multilevel analyses were performed to establish individual and country level factors associated with: (1) receiving a diagnosis and (2) accessing treatment for depression if a diagnosis was ascertained. Results The sample included 7,870 individuals from 49 countries who met ICD-10 criteria for depressive episode in the past 12 months. A third (32%) of these individuals had ever been diagnosed with depression in their lifetime. Among those diagnosed with depression, 66% reported to have ever received treatment for depression. Although individual factors were more important determinants of access to treatment for depression, country-level factors explained 27.6% of the variance in access to diagnosis and 24.1% in access to treatment. Access to treatment for depression improved with increasing country income. Female gender, better education, the presence of physical co-morbidity, more material assets, and living in urban areas were individual level determinants of better access. Limitations Data on other contextual factors was not available. Unmet need was likely underestimated, since only lifetime treatment data was available. Conclusion This study highlights major inequalities in access to a diagnosis and treatment of depression. Unlike the prevalence of depression, where contextual factors have shown to have less importance, a significant proportion of the variance in access to depression care was explained by country-level income.

Although studies have suggested that community social capital contributes to narrow income-based inequality in depression, the impacts may depend on its components. Our multilevel cross-sectional analysis of data from 42,208 men and 45,448 women aged 65 years or older living in 565 school districts in Japan found that higher community-level civic participation (i.e., average levels of group participation in the community) was positively associated with the prevalence of depressive symptoms among the low-income groups, independent of individual levels of group participation. Two other social capital components (cohesion and reciprocity) did not significantly alter the association between income and depressive symptoms., Highlights • Community social capital might be protective towards depression in older adults. • Community civic participation may enlarge the income-based gap in depression. • Considering bright and dark sides of social capital is necessary for intervention.