A clinical tool to estimate the risk of treatment-resistant schizophrenia (TRS) in people with first-episode psychosis (FEP) would inform early detection of TRS and overcome the delay of up to 5 years in starting TRS medication.

To develop and evaluate a model that could predict the risk of TRS in routine clinical practice.

We used data from two UK-based FEP cohorts (GAP and AESOP-10) to develop and internally validate a prognostic model that supports identification of patients at high-risk of TRS soon after FEP diagnosis. Using sociodemographic and clinical predictors, a model for predicting risk of TRS was developed based on penalised logistic regression, with missing data handled using multiple imputation. Internal validation was undertaken via bootstrapping, obtaining optimism-adjusted estimates of the model's performance. Interviews and focus groups with clinicians were conducted to establish clinically relevant risk thresholds and understand the acceptability and perceived utility of the model.

We included seven factors in the prediction model that are predominantly assessed in clinical practice in patients with FEP. The model predicted treatment resistance among the 1081 patients with reasonable accuracy; the model's C-statistic was 0.727 (95% CI 0.723–0.732) prior to shrinkage and 0.687 after adjustment for optimism. Calibration was good (expected/observed ratio: 0.999; calibration-in-the-large: 0.000584) after adjustment for optimism.

We developed and internally validated a prediction model with reasonably good predictive metrics. Clinicians, patients and carers were involved in the development process. External validation of the tool is needed followed by co-design methodology to support implementation in early intervention services.

To examine differences in noticing and use of nutrition information comparing jurisdictions with and without mandatory menu labelling policies and examine differences among sociodemographic groups.

Cross-sectional data from the International Food Policy Study (IFPS) online survey.

IFPS participants from Australia, Canada, Mexico, United Kingdom and USA in 2019.

Adults aged 18–99; n 19 393.

Participants in jurisdictions with mandatory policies were significantly more likely to notice and use nutrition information, order something different, eat less of their order and change restaurants compared to jurisdictions without policies. For noticed nutrition information, the differences between policy groups were greatest comparing older to younger age groups and comparing high education (difference of 10·7 %, 95 % CI 8·9, 12·6) to low education (difference of 4·1 %, 95 % CI 1·8, 6·3). For used nutrition information, differences were greatest comparing high education (difference of 4·9 %, 95 % CI 3·5, 6·4) to low education (difference of 1·8 %, 95 % CI 0·2, 3·5). Mandatory labelling was associated with an increase in ordering something different among the majority ethnicity group and a decrease among the minority ethnicity group. For changed restaurant visited, differences were greater for medium and high education compared to low education, and differences were greater for higher compared to lower income adequacy.

Participants living in jurisdictions with mandatory nutrition information in restaurants were more likely to report noticing and using nutrition information, as well as greater efforts to modify their consumption. However, the magnitudes of these differences were relatively small.

Describe how dietary intake patterns of US young adults align with the EAT-Lancet Planetary Health Diet (PHD) sustainable diet goals and identify personal, behavioural, and socio-environmental correlates of sustainable intake.

Data on past-year dietary intake were captured using a FFQ. The PHD was applied to specific food groups, and a total PHD score was calculated. Linear regression models were used to identify associations between personal, behavioural and socio-environmental factors and PHD scores.

This cross-sectional analysis uses data from the second wave of EAT 2010–2018 (Eating and Activity over Time), a population-based longitudinal study recruited in Minnesota.

Ethnically/racially diverse group of participants (n 1308) with a mean age of 22·1 (sd 2·0) years.

The mean PHD score was 4·1 (sd 1·4) on a scale of 0–14, with 14 representing the most sustainable. On average, participants consumed fewer whole grains, fish, legumes, soya, and nuts than ideal for a sustainable diet, and an excess of eggs, added sugar, and meat. The PHD score was higher for participants with higher socio-economic status (SES) and greater educational attainment. Higher home availability of healthy food (β = 0·24, P < 0·001) and less frequent fast-food consumption (β = –0·26, P < 0·001) were the strongest correlates of PHD scores.

Results suggest that a high percentage of participants may not be achieving the sustainable diet goals defined by the PHD. Reductions in meat consumption and increases in plant-based foods are necessary to increase the sustainability of US young adults’ diets.

Posttraumatic stress symptoms (PTSS) are common following traumatic stress exposure (TSE). Identification of individuals with PTSS risk in the early aftermath of TSE is important to enable targeted administration of preventive interventions. In this study, we used baseline survey data from two prospective cohort studies to identify the most influential predictors of substantial PTSS.

Self-identifying black and white American women and men (n = 1546) presenting to one of 16 emergency departments (EDs) within 24 h of motor vehicle collision (MVC) TSE were enrolled. Individuals with substantial PTSS (⩾33, Impact of Events Scale – Revised) 6 months after MVC were identified via follow-up questionnaire. Sociodemographic, pain, general health, event, and psychological/cognitive characteristics were collected in the ED and used in prediction modeling. Ensemble learning methods and Monte Carlo cross-validation were used for feature selection and to determine prediction accuracy. External validation was performed on a hold-out sample (30% of total sample).

Twenty-five percent (n = 394) of individuals reported PTSS 6 months following MVC. Regularized linear regression was the top performing learning method. The top 30 factors together showed good reliability in predicting PTSS in the external sample (Area under the curve = 0.79 ± 0.002). Top predictors included acute pain severity, recovery expectations, socioeconomic status, self-reported race, and psychological symptoms.

These analyses add to a growing literature indicating that influential predictors of PTSS can be identified and risk for future PTSS estimated from characteristics easily available/assessable at the time of ED presentation following TSE.

To examine associations of household crop diversity with school-aged child dietary diversity in Vietnam and Ethiopia and mechanisms underlying these associations.

We created a child diet diversity score (DDS) using data on seven food groups consumed in the last 24 h. Generalised estimating equations were used to model associations of household-level crop diversity, measured as a count of crop species richness (CSR) and of plant crop nutritional functional richness (CNFR), with DDS. We examined effect modification by household wealth and subsistence orientation, and mediation by the farm’s market orientation.

Two survey years of longitudinal data from the Young Lives cohort.

Children (aged 5 years in 2006 and 8 years in 2009) from rural farming households in Ethiopia (n 1012) and Vietnam (n 1083).

There was a small, positive association between household CNFR and DDS in Ethiopia (CNFR–DDS, β = 0·13; (95 % CI 0·07, 0·19)), but not in Vietnam. Associations of crop diversity and child diet diversity were strongest among poor households in Ethiopia and among subsistence-oriented households in Vietnam. Agricultural earnings positively mediated the crop diversity–diet diversity association in Ethiopia.

Children from households that are poorer and those that rely more on their own agricultural production for food may benefit most from increased crop diversity.

To determine the usefulness of adjusting antibiotic use (AU) by prevalence of bacterial isolates as an alternative method for risk adjustment beyond hospital characteristics.

Retrospective, observational, cross-sectional study.

Hospitals in the southeastern United States.

AU in days of therapy per 1,000 patient days and microbiologic data from 2015 and 2016 were collected from 26 hospitals. The prevalences of Pseudomonas aeruginosa, extended-spectrum β-lactamase (ESBL)–producing bacteria, methicillin-resistant Staphylococcus aureus (MRSA), and vancomycin-resistant enterococci (VRE) were calculated and compared to the average prevalence of all hospitals in the network. This proportion was used to calculate the adjusted AU (a-AU) for various categories of antimicrobials. For example, a-AU of antipseudomonal β-lactams (APBL) was the AU of APBL divided by (prevalence of P. aeruginosa at that hospital divided by the average prevalence of P. aeruginosa). Hospitals were categorized by bed size and ranked by AU and a-AU, and the rankings were compared.

Most hospitals in 2015 and 2016, respectively, moved ≥2 positions in the ranking using a-AU of APBL (15 of 24, 63%; 22 of 26, 85%), carbapenems (14 of 23, 61%; 22 of 25; 88%), anti-MRSA agents (13 of 23, 57%; 18 of 26, 69%), and anti-VRE agents (18 of 24, 75%; 15 of 26, 58%). Use of a-AU resulted in a shift in quartile of hospital ranking for 50% of APBL agents, 57% of carbapenems, 35% of anti-MRSA agents, and 75% of anti-VRE agents in 2015 and 50% of APBL agents, 28% of carbapenems, 50% of anti-MRSA agents, and 58% of anti-VRE agents in 2016.

The a-AU considerably changes how hospitals compare among each other within a network. Adjusting AU by microbiological burden allows for a more balanced comparison among hospitals with variable baseline rates of resistant bacteria.

Social and economic changes associated with new roads can bring about rapid nutritional transitions. To study this process, we: (1) describe trends in adult overweight and obesity (OW/OB) among rural Afro-Ecuadorians over time and across a gradient of community remoteness from the nearest commercial centre; (2) examine the relationship between male and female adult OW/OB and factors associated with market integration such as changing livelihoods and (3) examine the co-occurrence of adult OW/OB and under-five stunting and anaemia.

Adult anthropometry was collected through serial case–control studies repeated over a decade across twenty-eight communities. At the same time, anthropometry and Hb were measured for all children under 5 years of age in every community.

Northern coastal Ecuador.

Adults (n 1665) and children under 5 years of age (n 2618).

From 2003 and 2013, OW/OB increased from 25·1 % to 44·8 % among men and 59·9 % to 70·2 % among women. The inverse relationship between remoteness and OW/OB in men was attenuated when adjusting for urban employment, suggesting that livelihoods mediated the remoteness–OW/OB relationship. No such relationship was observed among women. Communities with a higher prevalence of male OW/OB also had a greater prevalence of stunting, but not anaemia, in children under 5 years of age.

The association between male OW/OB and child stunting at the community level, but not the household level, suggests that changing food environments, rather than household- or individual-level factors, drove these trends. A closer examination of changing socio-economic structures and food environments in communities undergoing rapid development could help mitigate future public health burdens.

To determine the association between livestock ownership and Hb concentration of women of child-bearing age (WCBA) and preschool-aged children in Sub-Saharan Africa (SSA).

A prospective analysis of publicly available cross-sectional data, using linear and logistic regressions controlling for potential confounders.

Twenty-eight countries in SSA.

162 305 WCBA and 118 607 children aged 6–59 months.

More than half of WCBA (62·5 %) and children (58 %) belonged to households that owned livestock. The average altitude-adjusted blood Hb concentration for WCBA and children was 12.23 and 10·24 g/dL, respectively. In adjusted models, higher number of livestock owned was associated with lower Hb concentration for children but not for WCBA. The magnitude of the association for children was small, with one additional unit of livestock owned reducing Hb concentration by 0·001 g/dL. Higher numbers of cattle, cows and bulls, sheep, and goats were associated with lower Hb concentration for both groups. The number of certain categories of livestock owned was associated with the consumption of relevant foods by children. There was no association between the consumption of animal-source foods and Hb concentration or between livestock ownership and diarrhoeal diseases or fever among children.

Livestock ownership in SSA had a net negative association with the Hb concentration of children and no association with that of WCBA. The results highlight the need for research aimed at clarifying the mechanisms linking livestock ownership and nutritional status, and identifying entry points for leveraging livestock ownership to improve the health of women and children in SSA.

The goal of the present study was to use a methodology that accurately and reliably describes the availability, price and quality of healthy foods at both the store and community levels using the Nutrition Environment Measures Survey in Stores (NEMS-S), to propose a spatial methodology for integrating these store and community data into measures for defining objective food access.

Two hundred and sixty-five retail food stores in and within 2 miles (3·2 km) of Flint, Michigan, USA, were mapped using ArcGIS mapping software.

A survey based on the validated NEMS-S was conducted at each retail food store. Scores were assigned to each store based on a modified version of the NEMS-S scoring system and linked to the mapped locations of stores. Neighbourhood characteristics (race and socio-economic distress) were appended to each store. Finally, spatial and kernel density analyses were run on the mapped store scores to obtain healthy food density metrics.

Regression analyses revealed that neighbourhoods with higher socio-economic distress had significantly lower dairy sub-scores compared with their lower-distress counterparts (β coefficient=−1·3; P=0·04). Additionally, supermarkets were present only in neighbourhoods with <60 % African-American population and low socio-economic distress. Two areas in Flint had an overall NEMS-S score of 0.

By identifying areas with poor access to healthy foods via a validated metric, this research can be used help local government and organizations target interventions to high-need areas. Furthermore, the methodology used for the survey and the mapping exercise can be replicated in other cities to provide comparable results.