Diet and health inequalities: Connecting with vulnerable groups to address food insecurity-the DIO food project.

The current cost-of-living crisis is disproportionately affecting families experiencing poverty and is likely to be amplifying existing dietary inequalities and challenges, such as food insecurity (FI). Government policies designed to address diet inequality in the UK have historically had minimal impact on population diet and health and may have even widened existing inequalities. Therefore, the effect of nutrition policies on those experiencing FI in the context of the current cost-of-living crisis needs to be better understood.

Supermarket top-up of Healthy Start vouchers increases fruit and vegetable purchases in low-income households.

Stark, widening health and income inequalities in the United Kingdom underpin the need for increased support for low-income families to access affordable and nutritious foods. Using anonymised supermarket loyalty card transaction records, this study aimed to assess how an additional Healthy Start voucher (HSV) top-up of £2, redeemable only against fruit and vegetables (FVs), was associated with FV purchases among at-risk households. Transaction and redemption records from 150 loyalty card-holding households, living in northern England, who had engaged with the top-up scheme, were analysed to assess the potential overall population impact.

Objectively measuring the association between the built environment and physical activity: a systematic review and reporting framework.

Background: Objective measures of built environment and physical activity provide the opportunity to directly compare their relationship across different populations and spatial contexts. This systematic review synthesises the current body of knowledge and knowledge gaps around the impact of objectively measured built environment metrics on physical activity levels in adults (≥ 18 years). Additionally, this review aims to address the need for improved quality of methodological reporting to evaluate studies and improve inter-study comparability though the creation of a reporting framework.

Impact on purchasing behaviour of implementing 'junk free checkouts': A pre-post study.

In 2015, Tesco Express convenience stores implemented a healthy checkouts initiative; products high in fat, salt or sugar were removed from in-queue areas. We compare purchasing of less healthy foods before and after its introduction. Tesco provided store-level sales data (n = 1151) for Express stores in England over two 8-week periods, May-July 2014 and 2015.

Exploring the Geographic Variation in Fruit and Vegetable Purchasing Behaviour Using Supermarket Transaction Data.

The existence of dietary inequalities is well-known. Dietary behaviours are impacted by the food environment and are thus likely to follow a spatial pattern. Using 12 months of transaction records for around 50,000 'primary' supermarket loyalty card holders, this study explores fruit and vegetable purchasing at the neighbourhood level across the city of Leeds, England.

Predicting Food Safety Compliance for Informed Food Outlet Inspections: A Machine Learning Approach.

Consumer food environments have transformed dramatically in the last decade. Food outlet prevalence has increased, and people are eating food outside the home more than ever before. Despite these developments, national spending on food control has reduced.

Characterisation of Temporal Patterns in Step Count Behaviour from Smartphone App Data: An Unsupervised Machine Learning Approach.

The increasing ubiquity of smartphone data, with greater spatial and temporal coverage than achieved by traditional study designs, have the potential to provide insight into habitual physical activity patterns. This study implements and evaluates the utility of both K-means clustering and agglomerative hierarchical clustering methods in identifying weekly and yearlong physical activity behaviour trends. Characterising the demographics and choice of activity type within the identified clusters of behaviour.

A systematic review of supermarket automated electronic sales data for population dietary surveillance.

Context: Most dietary assessment methods are limited by self-report biases, how long they take for participants to complete, and cost of time for dietitians to extract content. Electronically recorded, supermarket-obtained transactions are an objective measure of food purchases, with reduced bias and improved timeliness and scale.

Objective: The use, breadth, context, and utility of electronic purchase records for dietary research is assessed and discussed in this systematic review.

Socio-demographic determinants of physical activity and app usage from smartphone data.

The increasing ubiquity of smartphones provides a potential new data source to capture physical activity behaviours. Though not designed as a research tool, these secondary data have the potential to capture a large population over a more extensive spatial area and with longer temporality than current methods afford. This paper uses one such secondary data source from a commercial app designed to incentivise activity.

A comparison of time to event analysis methods, using weight status and breast cancer as a case study.

Survival analysis with cohort study data has been traditionally performed using Cox proportional hazards models. Random survival forests (RSFs), a machine learning method, now present an alternative method. Using the UK Women's Cohort Study (n = 34,493) we evaluate two methods: a Cox model and an RSF, to investigate the association between Body Mass Index and time to breast cancer incidence.

Understanding Barriers to Novel Data Linkages: Topic Modeling of the Results of the LifeInfo Survey.

Background: Novel consumer and lifestyle data, such as those collected by supermarket loyalty cards or mobile phone exercise tracking apps, offer numerous benefits for researchers seeking to understand diet- and exercise-related risk factors for diseases. However, limited research has addressed public attitudes toward linking these data with individual health records for research purposes. Data linkage, combining data from multiple sources, provides the opportunity to enhance preexisting data sets to gain new insights.

Dietary Patterns Derived from UK Supermarket Transaction Data with Nutrient and Socioeconomic Profiles.

Poor diet is a leading cause of death in the United Kingdom (UK) and around the world. Methods to collect quality dietary information at scale for population research are time consuming, expensive and biased. Novel data sources offer potential to overcome these challenges and better understand population dietary patterns.

The impact of body mass index on breast cancer incidence among women at increased risk: an observational study from the International Breast Intervention Studies.

Background: We investigated the association between body mass index (BMI) and breast cancer risk in women at increased risk of breast cancer receiving tamoxifen or anastrozole compared with placebo using data from the International Breast Cancer Intervention Studies [IBIS-I (tamoxifen) and IBIS-II (anastrozole)].

Methods: Baseline BMI was calculated from nurse assessed height and weight measurements for premenopausal (n = 3138) and postmenopausal (n = 3731) women in IBIS-I and postmenopausal women in IBIS-II (n = 3787). The primary endpoint was any breast cancer event (invasive and ductal carcinoma in situ).

Food safety vulnerability: Neighbourhood determinants of non-compliant establishments in England and Wales.

This paper utilises logistic regression to identify ecological determinants of non-compliant food outlets in England and Wales. We consider socio-demographic, urbanness and business type features to better define vulnerable populations based on the characteristics of the area within which they live. We find a clear gradient of association between deprivation and non-compliance, with outlets in the most deprived areas 25% less likely (OR = 0.

Rapid, quantitative therapeutic screening for Alzheimer's enzymes enabled by optimal signal transduction with transistors.

We show that commercially sourced n-channel silicon field-effect transistors (nFETs) operating above their threshold voltage with closed loop feedback to maintain a constant channel current allow a pH readout resolution of (7.2 ± 0.3) × 10 at a bandwidth of 10 Hz, or ≈3-fold better than the open loop operation commonly employed by integrated ion-sensitive field-effect transistors (ISFETs).

Evidence from big data in obesity research: international case studies.

Background/objective: Obesity is thought to be the product of over 100 different factors, interacting as a complex system over multiple levels. Understanding the drivers of obesity requires considerable data, which are challenging, costly and time-consuming to collect through traditional means. Use of 'big data' presents a potential solution to this challenge.

Relationship of the Frequency, Distribution, and Content of Meals/Snacks to Glycaemic Control in Gestational Diabetes: The myfood24 GDM Pilot Study.

This study examines nutritional intakes in Gestational diabetes mellitus piloting the myfood24 tool, to explore frequency of meals/snacks, and daily distribution of calories and carbohydrates in relation to glycaemic control. A total of 200 women aged 20-43 years were recruited into this prospective observational study between February 2015 and February 2016. Diet was assessed using myfood24, a novel online 24-h dietary recall tool.

Validation of the Oxford WebQ Online 24-Hour Dietary Questionnaire Using Biomarkers.

The Oxford WebQ is an online 24-hour dietary questionnaire that is appropriate for repeated administration in large-scale prospective studies, including the UK Biobank study and the Million Women Study. We compared the performance of the Oxford WebQ and a traditional interviewer-administered multiple-pass 24-hour dietary recall against biomarkers for protein, potassium, and total sugar intake and total energy expenditure estimated by accelerometry. We recruited 160 participants in London, United Kingdom, between 2014 and 2016 and measured their biomarker levels at 3 nonconsecutive time points.

Can big data solve a big problem? Reporting the obesity data landscape in line with the Foresight obesity system map.

Background: Obesity research at a population level is multifaceted and complex. This has been characterised in the UK by the Foresight obesity systems map, identifying over 100 variables, across seven domain areas which are thought to influence energy balance, and subsequent obesity. Availability of data to consider the whole obesity system is traditionally lacking.

Exploring the Feasibility of Use of An Online Dietary Assessment Tool (myfood24) in Women with Gestational Diabetes.

myfood24 is an online 24 hr dietary recall tool developed for nutritional epidemiological research. Its clinical application has been unexplored. This mixed methods study explores the feasibility and usability of myfood24 as a food record in a clinical population, women with gestational diabetes (GDM).