While some studies have suggested that moderate alcohol consumption may be beneficial for rheumatoid arthritis (RA) prevention(1), the role of competing events have not been considered and may lead to misinterpretation of the magnitude of the risk between alcohol intake and RA incidence. We aimed to investigate the relationship between alcohol consumption and RA incidence when the competing risk of death is accounted for in the survival analysis.

Data from the UK Women’s Cohort Study (UKWCS), a prospective cohort study of 35,372 middleaged women established between 1995 and 1998, was used for the analyses(2). Alcohol intake was assessed at baseline by asking for the number of specified units of each type of alcoholic beverage (beer, wine, sherry, and spirits) consumed per week. Cases who developed RA were identified through linkage with Hospital Episode Statistics (HES) up to March 2019 (International Classification of Diseases, ICD-10 code M05-M06). Data linkage with the Health and Social Care Information Centre (HSCIC) allowed cause of death to be identified using ICD codes (9th/10th version). We used directed acyclic graphs, competing risk regression modelling, and subgroup analyses to examine the effect of alcohol intake on RA incidence.

Among 29,830 women linked to the HES data (666,857 person-years), 255 cases of rheumatoid arthritis were identified, with a median follow-up of 22.5 years. After adjustment for confounders, in both competing risk regression and cox proportional hazards models, regular drinking was associated with a reduced risk of RA. In the competing risk model, with occasional drinkers (less than 1 serving of alcohol per week) as the reference, the subhazard ratios (SHRs) for non-drinkers were: SHR, 0.67, 95% CI: 0.43-1.07; regular drinkers: SHR, 0.70, 95% CI: 0.53−0.94. Every additional unit of alcohol per week was associated with a 3% lower risk of rheumatoid arthritis (SHR (95% CI): 0.97(0.96−0.99)). BMI modified the linear associations between alcohol intake and risk of RA(Pinteraction=0.01). The incidence of RA in participants with a BMI < 30 kg/m2 (227 cases, 27,015 participants) was 2% lower for each additional serving of alcohol consumed per week (0.98(0.96−0.99)),no statistically significant effect was seen for alcohol in those with a BMI 30+kg/m2, though numbers were smaller in this group.

Promotion of sustainable healthy diets requires comprehensive metrics to assess environmental impact of foods consumed1. Existing food systems are failing to meet the needs of current and future generations, by operating outside several planetary boundaries. Promoting healthy diets from sustainable food systems is central to realizing the 2030 Sustainable Development Goals. Standard food composition tables do not include sustainability metrics. The aim of this work was to add UK focussed sustainability metrics to the food composition table used in myfood24.

Greenhouse gas emissions (GHGE), land and water use were added to each food item in the myfood24 UK generic and branded databases. This is recorded as per 100g of product. The values for GHGE2 takes account of factors including production method, land use management, feed used, soil and climate, processing and transport of both the product and aspects of its production e.g., fertiliser and feed. Values were weighted for UK trade statistics to reflect values for the UK food supply. Land use and freshwater withdrawals were also added.

Exploration of the sustainability metrics in the myfood24 database by food category show, as expected, that meat (1.5 kg CO2eq, SD 1.4), fish (1.8 kg CO2eq, SD 1.0) and dairy (1.3 kg CO2eq, SD 0.8) plus dried herbs/spices (1.4 kg CO2eq, SD 1.2) have the highest GHGE per 100g. In the meat category, beef and lamb had GHGE ∼3.8 kg CO2eq with pork and chicken having lower values ∼1.0 kg CO2eq. Plant based protein sources had much lower GHGE per 100g, with pulses at 0.3 CO2eq (SD 0.2) and nuts at 0.2 CO2eq (SD 0.2). Land use was by far the highest per 100g for lamb (63 m2year/day, SD 18) with beef next at 8 m2year/day (SD 4). Chocolate (5 m2year/day, SD 2) was the sixth highest food category for land use. Drinks, vegetables, fruit and potatoes had the lowest land use values. Regarding water use, seafood per 100g had high values at 484l/day (SD 167), followed by nuts (218l/day, SD 172), lamb (171l/day, SD 36) and rice (164l/day SD 42). Drinks, potatoes and breads had the lowest land use values per 100g.

Through addition of sustainability metrics to food and nutrient composition databases we can measure the impact of food intake in relation to both nutrients and sustainability. This linked data will help us to understand how to adapt our diets to be healthier and better for the planet.

It is common for individuals to seek information online when facing health and nutritional problems, particularly those with lower education level and nutritional knowledge(1). One way to access such information is through search engines, with Google being the most popular, currently used by 92% of the world’s population, with an average of 85.59 billion monthly visits(2). Google Trends is a tool provided by Google, freely accessible, allowing users to observe patterns in internet searches(3). The aim of this study is to identify patterns to predict trends related to weight loss at specific times.

Data were extracted from Google Trends over the past 20 years, from 2004 to 2024, using the keywords “weight loss” and “diet.” In Google Trends, users may input a keyword consisting of words or phrases that are relevant to the chosen issue or cases. The duration of time that users wish to examine can be specified. Furthermore, users can explore geographical regions or search worldwide. Figures generated represent search interest based on the highest points on the graph for specific regions and times. The popularity of search terms is relative and depends on the category: search term or topic. Data is normalised and presented on a scale from 0-100, where each point on the graph is divided by the highest point, or 100. A value of 100 indicates peak popularity, 50 indicates half popularity, and 0 indicates insufficient data for the term.

Over the past 20 years, there has been an increasing trend in searches for websites using the keyword “weight loss,” with an average interest score of 31. This differs from the keyword “diet,” which has shown a tendency towards stagnation in popularity, although it briefly peaked with a score of 100 in early 2014 and has an average interest score of 53. Both keywords exhibit similar search patterns, reaching their highest peaks each year in January and lowest points in December.

For the keyword “weight loss,” the most searches were from South Africa (100), Romania (96), and Vietnam (91), while the lowest were from Italy (4), Japan (5), and the Netherlands (9). For the keyword “diet,” the most searches were from Poland (100), Kuwait (87), and Greece (85), while the lowest were from Japan (2), Thailand (7), and France (11). Users also searched for other related topics or queries including ozempic and intermitten fasting.

Our data indicates a consistent increasing trend in searches for weight loss over the last 20 years via Google Trends. New Year resolutions may be linked to peak searches which occur in January. While this data may prove useful for researchers and policymakers, further validation of its validity and reliability is necessary.

Optimal nutrition during infancy and early childhood is crucial for promoting healthy growth, development, and overall well-being(1). Concerns arise regarding commercially available Food Products for Infants and Young Children (FIYC) due to potential imbalances in sugar, salt, fat content, and inappropriate promotion. The World Health Organization’s (WHO) Nutrient and Promotion Profile Model (NPPM) assesses the nutritional quality and promotional practices of commercial baby foods for children under 36 months. This study evaluates and compares the compliance of FIYC products in the UK and Kyrgyzstan with the NPPM guidelines.

This study evaluated the compliance of FIYC products in the UK and Kyrgyzstan with the WHO’s NPPM guidelines. Data on commercially available FIYC products for children aged 6-36 months were collected from both countries (UK: n = 469 products, 21 brands; Kyrgyzstan: n = 203 products, 20 brands). The NPPM website was utilized to assess nutritional composition (energy, sugar, protein, salt) against WHO guidelines and evaluate labelling information (ingredient lists, nutrient/health/marketing claims, breastfeeding recommendations) for adherence to NPPM criteria(2). Data analysis for comparison across the two countries employed SPSS v29.

Analysis of 672 FIYC products using the NPPM website revealed distinctly different compositions between the UK (n = 469) and Kyrgyzstan (n = 203). The UK dataset contained a higher proportion of meals (38%) compared to fruits and vegetables (30%). Conversely, Kyrgyzstan had a higher percentage of fruits and vegetables (52%) and cereals (26%). Nutrient assessments displayed varying pass rates. Pass rates for products in the model were higher for the UK compared to Kyrgyzstan for energy density (75% vs. 47%), total fat (98% vs. 67%), and sodium (69% vs. 10%). However, Kyrgyzstan had a higher protein pass rate (96% vs. 94%). Regarding sugars, the UK achieved a 50% pass rate for total sugar compared to only 7% in Kyrgyzstan, with free sugar addition pass rates of 81% and 73% respectively. Promotion assessments revealed a similar compliance for the lower age recommendation (from 6 months) (85% UK, 76% Kyrgyzstan). However, all products failed the total marketing, health, and promotional claims evaluation. Breastfeeding instruction compliance was also low, with only 5% (UK) and 35% (Kyrgyzstan) passing.

In conclusion, the study identified both strengths and weaknesses in FIYC product compositions and nutritional profiles across the UK and Kyrgyzstan. However, more work is needed in adhering to marketing, health claims, and breastfeeding instruction guidelines in both countries. Stronger policies to improve FIYC are needed across the WHO European Region promoting child health and reducing future disease risk.

Measuring dietary intake accurately is essential in establishing relationships between food consumption patterns and non-communicable diseases. Researchers are now using online tools to replace traditional methods1. New technologies provide a more flexible approach and are generally preferred by study participants. However, it is not known whether the underlying databases are reliable. Weight loss app energy calculations vary considerably compared to weighed food records2. The aim of this work was to review the quality and compare the content of online food composition tables including those linked to assessment tools.

We undertook a Google search supplemented by expert knowledge to identify online food composition tables in the English language. Databases were either stand-alone online food and drink databases or associated with dietary assessment tools. Databases found were accessed; and we conducted a review of their features. Information on numbers and types of foods, their origin, nutrients and completeness of datasets were extracted using a standardised approach.

Twenty-two online food composition databases were reviewed from around the world. 12 (55%) of the databases were associated with dietary assessment software and 9 (41%) solely used an API to link with other systems. Numbers of food items included in the databases ranged from 18 million (‘myfitnesspal’) to 600 (‘FoodDB’). The largest databases generally used crowd sourced data.

‘myfood24’ had the largest total number of variables (n = 326) and ‘Carbs and Cals’ and ‘Nutracheck’ only had 8 nutrient variables. The source of food composition data is not clear for all of the datasets. 7 of the databases explicitly include the UK and 3 the US generic food tables, often in addition to branded data. Most databases do not state how they are checked for accuracy or completeness. Where databases state how missing data is infilled only ‘myfood24’ considers both macro and micronutrients. Eight of the databases were only relevant for one country, and 13 tools reported having food data for a range of countries. In addition to nutrients some databases also include non-nutrient phytochemicals, allergens or sustainability metrics. Food images were often used to assist with portion size estimation, although some tools only used general pictures or pictures that did not reflect the food. Searching for food items varied in accuracy and some systems allowed barcode scanning.

Online food composition databases allow for much greater differentiation of foods, including branded items compared to traditional tables. They range considerably in size and quality. Care should be taken to ensure databases underlying online assessment tools are reliable with limited missing data to ensure the application of such databases to research does not produce misleading results.

With the rising rates of non-communicable diseases in Nigeria, there is need to understand the links between diet and health using an accurate and efficient dietary assessment method. The new online dietary assessment tool comprising a database of local Nigerian and West African diets, myfood24 West Africa (1), was piloted in a healthy adult population in Nigeria.

Participants were staff of Michael Okpara University of Agriculture Umudike, Abia State in southeast Nigeria, at least 18 years, not pregnant, not had childbirth in the last 3 months, and not diagnosed with diabetes. A pre-recorded video demonstration of food recording with myfood24 was sent to participants. One-day 24-hour recall was self-recorded by either participants or by the researcher on behalf of the participants. Participants who used myfood24 on their own completed the usability questionnaire to rate their agreement with system usability statements and provided feedback on the system.

179 adults were recruited for the study and a total of 1345 food/drink entries were made with a median number of 7 (IQR: 5, 9) food/drink entry per day per participant. Foods from our new West African food database contributed to 60-82% of the energy and nutrient intake. Mean energy intake was 1844 (SD 781) kcal; with energy coming from 28% fat, 63% CHO, and 9% protein. 53 (30%) participants used myfood24 on their own, with a mean age of 38.5±8.7 years. There was no significant difference in the energy intake (p = 0.67) and body mass index (p = 0.82) of participants who used myfood24 on their own and those who did not. 39 out of 53 participants completed the user questionnaire. The mean system usability score was 74 (95% CI 65, 83), indicating a good usability. Participants found the tool easy to use and estimate portion sizes of local foods; it was educative showing levels of macronutrient consumed; and more efficient than manual recording of foods but some participants commented that a few local foods were missing.

myfood24 will support research investigation of relationships between diets and health in Nigeria. There is also now an offline function removing reliance on WiFi. Feedback from participants will inform future updates of the database.

There is no regular, routine measurement of food and nutrient intake undertaken regionally in the UK. This makes evaluation of local public health interventions challenging. Consumers want to be more sustainable in what they are eating. Social media penetration in the UK is 90%(1), with ∼47m people using Facebook, a potential route to study recruitment. Nutritional analysis software with accurate underpinning food composition and sustainability data could enable quick and easy large scale data collection. This study aimed to collect diet and sustainability measures using online tools and to test the feasibility of using social media to obtain a large, regionally focused sample in a short time.

We undertook a rapid, time limited, regional (Yorkshire and Humber) food and nutrient tracking survey ‘One day: Diet in Yorkshire and Humber’ for use with policy makers(2). A Facebook (FB) boost approach was used to recruit a regional sample of adults. Participants completed a brief online demographic survey and used myfood24® to give a detailed measure of their food intake for the previous day. myfood24® generic and branded databases were used(3) which include sustainability metrics.

The FB posts were boosted for 21 days and reached 76.9k individuals. Just under £1,000 was spent on 3 FB boosts and 1,428 participants completed the questionnaire. 673 participants also completed the one-day diet diary. Hull, Barnsley and Doncaster had the highest rates of overweight and obesity in the region. Overall nutrient values recorded were similar to national survey data for older women. Intakes of fibre (mean 18g, SD 11) and iron (mean 9.6mg, SD 5.0) were low. For the first time, measures of sustainability from the diet were calculated from myfood24®.

The mean greenhouse gas emissions (GHGE) were 5.9(kg CO2 eq/day) (95% CI 5.6, 6.1); land use 9.0 (m2year/day) (95% CI 7.6, 10.3) and water use 582 (l/day) (95% CI 551, 611). Regression analysis showed that for each additional 100kcal consumed there was a significant increase in GHGE of 0.9 (kg CO2 eq/day) (95% CI 0.8, 1.1). Land and water use were also significantly increased with increasing energy intake. Adjusting for total energy, protein intake was positively associated with all 3 metrics. Carbohydrate was inversely associated with GHGE and land use. However, fat intake was not associated with any of the sustainability measures. Portions of fruit and vegetables consumed were positively associated with water use only.

Diet is clearly linked to sustainability. The mean GHGE from diet is equivalent to driving an average car ∼22km/day. We successfully recruited a large sample in a short timeframe using FB. Participants were able to use online tools to report food intakes. This data is relevant to local and national policy makers to monitor and evaluate public health programmes.