Most research investigating sugar-sweetened beverages (SSB) and health, conducted at the individual or household level, ignores potentially important intra-household dynamics. We analysed self-reported consumption relationships between children and adults, and between children of different ages, as well as the associations between intra-household consumption, BMI and sociodemographic characteristics.

A cross-sectional analysis of survey data from Kantar Fast Moving Consumer Goods panellists in September 2017.

Great Britain.

Random sample of 603 households with children under 18 years who regularly purchase non-alcoholic beverages.

Low- or no-sugar/diet beverages dominate consumption across all age categories, particularly children under 12 years. SSB consumption increased as children became older. Children’s reported consumption of SSB and low- or no-sugar/diet beverages was positively associated with consumption by adults; a child in adolescence had over nine times the odds of consuming SSB (adjusted OR 9·55, (95 % CI 5·38, 17·00), P < 0·001), and eight times the odds of consuming low- or no-sugar/diet drinks (adjusted OR 8·12, (95 % CI 4·71, 13·97), P < 0·001), if adults did so. In households with multiple children, consumption patterns of older siblings were associated with those of the younger; notably a perfect correlation between children aged 0 and 6 years consuming SSB if siblings 13–18 years did so, and children aged 7–12 years had 22 times the odds of consuming SSB if siblings aged 13–18 years did so (OR 22·33, (95 % CI 8·60, 58·01), P < 0·001).

Multiple policies, targeting children as well as adults, such as fiscal levers and advertisement restrictions, are needed to reduce and prevent the consumption of SSB.

Psychotic experiences predict adverse health outcomes, particularly if they are persistent. However, it is unclear what distinguishes persistent from transient psychotic experiences.

In a large population-based cohort, we aimed to (a) describe the course of hallucinatory experiences from childhood to adolescence, (b) compare characteristics of youth with persistent and remittent hallucinatory experiences, and (c) examine prediction models for persistence.

Youth were assessed longitudinally for hallucinatory experiences at mean ages of 10 and 14 years (n = 3473). Multi-informant-rated mental health problems, stressful life events, self-esteem, non-verbal IQ and parental psychopathology were examined in relation to absent, persistent, remittent and incident hallucinatory experiences. We evaluated two prediction models for persistence with logistic regression and assessed discrimination using the area under the curve (AUC).

The persistence rate of hallucinatory experiences was 20.5%. Adolescents with persistent hallucinatory experiences had higher baseline levels of hallucinatory experiences, emotional and behavioural problems, as well as lower self-esteem and non-verbal IQ scores than youth with remittent hallucinatory experiences. Although the prediction model for persistence versus absence of hallucinatory experiences demonstrated excellent discriminatory power (AUC-corrected = 0.80), the prediction model for persistence versus remittance demonstrated poor accuracy (AUC-corrected = 0.61).

This study provides support for the dynamic expression of childhood hallucinatory experiences and suggests increased neurodevelopmental vulnerability in youth with persistent hallucinatory experiences. Despite the inclusion of a wide array of psychosocial parameters, a prediction model discriminated poorly between youth with persistent versus remittent hallucinatory experiences, confirming that persistent hallucinatory experiences are a complex multifactorial trait.

Online grocery shopping could improve access to healthy food, but it may not be equally accessible to all populations – especially those at higher risk for food insecurity. The current study aimed to compare the socio-demographic characteristics of families who ordered groceries online v. those who only shopped in-store.

We analysed enrollment survey and 44 weeks of individually linked grocery transaction data. We used univariate χ2 and t-tests and logistic regression to assess differences in socio-demographic characteristics between households that only shopped in-store and those that shopped online with curbside pickup (online only or online and in-store).

Two Maine supermarkets.

863 parents or caregivers of children under 18 years old enrolled in two fruit and vegetable incentive trials.

Participants had a total of 32 757 transactions. In univariate assessments, online shoppers had higher incomes (P < 0 0001), were less likely to participate in Special Supplemental Nutrition Program for Women, Infants, and Children or Supplemental Nutrition Assistance Program (SNAP; P < 0 0001) and were more likely to be female (P = 0·04). Most online shoppers were 30–39 years old, and few were 50 years or older (P = 0·003). After controlling for age, gender, race/ethnicity, number of children, number of adults, income and SNAP participation, female primary shoppers (OR = 2·75, P = 0·003), number of children (OR = 1·27, P = 0·04) and income (OR = 3·91 for 186–300 % federal poverty line (FPL) and OR = 6·92 for >300 % FPL, P < 0·0001) were significantly associated with likelihood of shopping online.

In the current study of Maine families, low-income shoppers were significantly less likely to utilise online grocery ordering with curbside pickup. Future studies could focus on elucidating barriers and developing strategies to improve access.

The National Neuropsychology Network (NNN) is a multicenter clinical research initiative funded by the National Institute of Mental Health (NIMH; R01 MH118514) to facilitate neuropsychology’s transition to contemporary psychometric assessment methods with resultant improvement in test validation and assessment efficiency.

The NNN includes four clinical research sites (Emory University; Medical College of Wisconsin; University of California, Los Angeles (UCLA); University of Florida) and Pearson Clinical Assessment. Pearson Q-interactive (Q-i) is used for data capture for Pearson published tests; web-based data capture tools programmed by UCLA, which serves as the Coordinating Center, are employed for remaining measures.

NNN is acquiring item-level data from 500–10,000 patients across 47 widely used Neuropsychology (NP) tests and sharing these data via the NIMH Data Archive. Modern psychometric methods (e.g., item response theory) will specify the constructs measured by different tests and determine their positive/negative predictive power regarding diagnostic outcomes and relationships to other clinical, historical, and demographic factors. The Structured History Protocol for NP (SHiP-NP) helps standardize acquisition of relevant history and self-report data.

NNN is a proof-of-principle collaboration: by addressing logistical challenges, NNN aims to engage other clinics to create a national and ultimately an international network. The mature NNN will provide mechanisms for data aggregation enabling shared analysis and collaborative research. NNN promises ultimately to enable robust diagnostic inferences about neuropsychological test patterns and to promote the validation of novel adaptive assessment strategies that will be more efficient, more precise, and more sensitive to clinical contexts and individual/cultural differences.

To examine socio-economic inequalities in decreases in household sugar purchasing in Great Britain (GB).

Longitudinal, population-based study.

Data were obtained from the GB Kantar Fast-Moving Consumer Goods (FMCG) panel (2014–2017), a nationally representative panel study of food and beverages bought and brought into the home. We estimated changes in daily sugar purchases by occupational social grade from twenty-three food groups, using generalised estimating equations (household-level clustering).

British households who regularly reported food and beverages to the GB Kantar FMCG (n 28 033).

We found that lower social grades obtained a lower proportion of sugar from healthier foods and a greater proportion of sugar from less healthy foods and beverages. In 2014, differences in daily sugar purchased between the lowest and the highest social grades were 3·9 g/capita/d (95 % CI 2·9, 4·8) for table sugar, 2·4 g (95 % CI 1·8, 3·1) for sugar-sweetened beverages, 2·2 g (95 % CI 1·5, 2·8) for chocolate and confectionery and 1·0 g (95 % CI 0·7, 1·3) for biscuits. Conversely, the lowest social grade purchased less sugar from fruits (2·1 g (95 % CI 1·5, 2·8)) and vegetables (0·7 g (95 % CI 0·5, 0·8)) than the highest social grade. We found little evidence of change in social grade differences between 2014 and 2017. These results suggest that recent overall declines in sugar purchases are largely equally distributed across socio-economic groups.

This suggests that recent population-level policy activity to reduce sugar consumption in GB does not appear to exacerbate or reduce existing socio-economic inequalities in sugar purchasing. Low agency, population-level policies may be the best solution to improving population diet without increasing inequalities.

This is the first report on the association between trauma exposure and depression from the Advancing Understanding of RecOvery afteR traumA(AURORA) multisite longitudinal study of adverse post-traumatic neuropsychiatric sequelae (APNS) among participants seeking emergency department (ED) treatment in the aftermath of a traumatic life experience.

We focus on participants presenting at EDs after a motor vehicle collision (MVC), which characterizes most AURORA participants, and examine associations of participant socio-demographics and MVC characteristics with 8-week depression as mediated through peritraumatic symptoms and 2-week depression.

Eight-week depression prevalence was relatively high (27.8%) and associated with several MVC characteristics (being passenger v. driver; injuries to other people). Peritraumatic distress was associated with 2-week but not 8-week depression. Most of these associations held when controlling for peritraumatic symptoms and, to a lesser degree, depressive symptoms at 2-weeks post-trauma.

These observations, coupled with substantial variation in the relative strength of the mediating pathways across predictors, raises the possibility of diverse and potentially complex underlying biological and psychological processes that remain to be elucidated in more in-depth analyses of the rich and evolving AURORA database to find new targets for intervention and new tools for risk-based stratification following trauma exposure.

Brain health diplomacy aims to influence the global policy environment for brain health (i.e. dementia, depression, and other mind/brain disorders) and bridges the disciplines of global brain health, international affairs, management, law, and economics. Determinants of brain health include educational attainment, diet, access to health care, physical activity, social support, and environmental exposures, as well as chronic brain disorders and treatment. Global challenges associated with these determinants include large-scale conflicts and consequent mass migration, chemical contaminants, air quality, socioeconomic status, climate change, and global population aging. Given the rapidly advancing technological innovations impacting brain health, it is paramount to optimize the benefits and mitigate the drawbacks of such technologies.

We propose a working model of Brain health INnovation Diplomacy (BIND).

We prepared a selective review using literature searches of studies pertaining to brain health technological innovation and diplomacy.

BIND aims to improve global brain health outcomes by leveraging technological innovation, entrepreneurship, and innovation diplomacy. It acknowledges the key role that technology, entrepreneurship, and digitization play and will increasingly play in the future of brain health for individuals and societies alike. It strengthens the positive role of novel solutions, recognizes and works to manage both real and potential risks of digital platforms. It is recognition of the political, ethical, cultural, and economic influences that brain health technological innovation and entrepreneurship can have.

By creating a framework for BIND, we can use this to ensure a systematic model for the use of technology to optimize brain health.