Over the next four decades, the most substantial population growth is projected to occur among individuals aged 65 and above(1). The ageing process is associated with physiological alterations that adversely affect body systems(2). Evidence supports the recommendation for higher protein intake in older adults to mitigate musculoskeletal deterioration(3). Physical activity programmes offer a valuable means of enhancing physical function in older individuals, providing a strategic setting for delivering interventions for healthy ageing(4). The aim of this investigation was to examine changes in protein intake and handgrip strength over 3 years in a population of adults attending a community exercise programme.

This is a rolling study, recruiting participants from an over 60s exercise class in the North West of the UK. Dietary intake assessed using multiple 24 hour recalls and analysed using Nutritics™ software. Grip strength was assessed using a Takei-5401 digital dynamometer. Grip strength was assessed with participants seated, maintaining a 90- degree angle at the elbow and a neutral forearm position. Mean grip strength was compared to age- and sex-matched 50th centile values(5) using a Wilcoxon Signed-Rank tests. Protein intake (g/d) was compared against calculated recommended amounts based on recommended intakes of 0.75 g/kg bodyweight(6), and higher values of 1.0 g/kg(7) and 1.2 g/kg(8) bodyweight using Wilcoxon Signed-Rank tests.

From a total of 60 participants, 20 individuals participated in year 1, 24 in year 2, and 28 in year 3. Mean grip strength in years 1, 2 and 3 was 19.7 ± 7.1 kg, 21.9 ± 7.6 kg, and 18.6 ± 6.2 kg, respectively, with no significant differences between years (p = 0.242). Mean grip strength in year 3 was significantly lower than the age- and sex-matched values (19.1 ± 7.0 kg vs. 25.0, p < 0.001, respectively). Mean daily protein intake in year 1, year 2 and year 3 was 64.5 ± 31.1 g, 64.9 ± 23.5 g and 63.7 ± 27.6 g, respectively with no significant difference between years (p = 0.472). There was no significant difference between current protein intake and calculated amounts using 0.75 g/kg bodyweight (63.7 ± 27.6 g/d vs. 48.2 ± 6.6 g/d, p = 0.064, respectively). Similarly, current intake did not significantly differ compared to calculated amounts using 1.0 g/kg bodyweight (63.7 ± 27.6 g/d vs. 64.3 ± 8.7, p= 0.469, respectively). Protein intake was significantly below the amount calculated based on 1.2 g/kg bodyweight (63.7 ± 27.6 g/d vs. 77.2 ± 10.5, p = 0.027, respectively).

Grip strength values were significantly below average for participants age and sex, and protein intake is significantly below calculated values for older adults engaging in physical activity. Future initiatives should reinforce the importance of strength training in this group, in addition to improving protein intake.

In this investigation, the effect of Ekman pumping on a quasi-geostrophic (QG) system is explored via the vertical buoyancy flux. The vertical buoyancy flux is the quantity in QG flows that is responsible for the adiabatic transfer between kinetic energy (KE) and available potential energy (APE), as well as the slow-time evolution of the mean buoyancy. Ekman pumping (or suction) is a phenomenon that arises through conservation of mass at no-slip boundaries of rotating fluid systems. Three-dimensional QG numerical simulations are run with and without Ekman pumping at the bottom boundary, as well as with and without a realistic stratification profile. Through theory and numerical experiment, it is shown that Ekman pumping drives a conversion of energy from APE to KE at small scales, and from KE to APE at large scales, even in the absence of a mean isopycnal slope. It is also shown that Ekman pumping affects the mean buoyancy by slightly weakening the stratification near the bottom boundary.

The EAT-Lancet Commission’s “Planetary Health Diet” (PHD) aims to optimise population health and environmental sustainability by promoting a plant-forward diet with animal products consumed in moderation(1). The UK’s Eatwell Guide provides recommendations for key nutrients and food groups to achieve a healthy, balanced diet; greater adherence is associated with environmental benefits(2). This secondary analysis examines the relationships between PHD adherence, food group intakes and compliance with the Eatwell Guide in UK adults.

Data from disease-free UK adults aged ≥18 years (n=452) were pooled from five cross- sectional analyses that recorded habitual dietary intake using the eNutri food frequency questionnaire, which generated nutrient and food group data(3). EAT-Lancet Index scores were calculated(4) for each participant then stratified into quartiles (Q), with the highest scores in Q4 (representing greater adherence to the PHD). Adherence to the 9 Eatwell Guide recommendations were determined for each quartile then classified as ‘very low’ (0– 2 recommendations met), ‘low’ (3–4) or ‘intermediate-to-high’ (5–9) (2). ANCOVA (adjusted for sex, age, physical activity, ethnicity, employment status, and body mass index (BMI)) compared the mean daily intakes of 17 food groups across quartiles. If significant, pairwise comparisons with Bonferroni correction were determined. P values ≤0.01 were considered significant for all.

Study participants had a mean (SD) age of 44 (19) years and a BMI of 25.7 (6.0) kg/m2 and 79.6% were female. Adherence to the Eatwell Guide was very low in Q1 and Q2, low in Q3 and intermediate-to-high in Q4 (where 5 out of the 9 recommendations were met).

Compared to Q1, higher adherence to the PHD (Q4) was associated with higher intakes of ‘fruits and vegetables’ (+408 g/d), ‘pulses’ (+25.0 g/d), ‘whole grains’(+29.2 g/d), ‘nuts and seeds’(+15.8 g/d) ‘plant-based meat alternatives’ (+14.3 g/d) and ‘plant-based dairy alternatives’ (+110 g/d) (all p≤0.001). In contrast, Q4 had lower intakes of ‘eggs’ (-17.0 g/d), ‘potatoes’(-50.5 g/d), ‘poultry’ (-38.1 g/d), ‘red meat’(-40.4 g/d), ‘processed meat’(-22.5 g/d), ‘refined grains’ (-65.0 g/d) and ‘dairy products’ (-110 g/d) relative to Q1 (all p≤0.001). Although intakes of ‘unsaturated fats and oils’ and ‘fish and other seafood’ were highest in Q4, neither was significantly different from the other quartiles.

Greater adherence to the PHD was associated with higher intakes of plant-based foods (including a two-fold higher intake in fruits and vegetables), and lower consumption of animal products, notably a five-fold lower intake of red meat. Moreover, UK adults whose diets more closely reflected the PHD also met a higher proportion of Eatwell Guide recommendations. These findings suggest that closer adherence to the PHD aligns with greater compliance to UK dietary guidelines (Eatwell Guide), reflecting a more favorable dietary pattern.

Obesity affects 1 in 8 people(1). Mobile apps offer a convenient and potentially impactful solution for weight management(2). However, knowledge of app quality and key app characteristics supporting weight loss is unclear. Most studies have focused only on popular apps(3) or certain user groups(4). The aim of this study was to review studies that evaluated the quality of weight loss apps and identify tools or methods that they used.

A systematic review was conducted to assess studies evaluating weight loss apps and identify tools or methods for quality measurement, following PRISMA guidelines(5).

Eligibility criteria included studies published within the last five years, explicitly evaluating weight loss apps, focusing on adults, and written in English from four databases: PubMed, Embase, Medline, and Web of Science. Studies were excluded if they involved non-digital weight loss interventions, evaluated other clinical patients, or were non-original research (e.g., reviews, meta-analyses, conference papers, or reports). After selecting the final included studies, reviewers extracted tools/methods to evaluate the quality of each app and synthesized the findings to identify the evaluation tools/methods used and key features of the weight loss apps.

From a total of 567 articles, we identified 13 relevant studies and 47 apps. Half of the studies were conducted in Asian countries, including China, India, Indonesia, Lebanon, and Saudi Arabia. The rest took place in individual countries across various continents, such as Australia, Europe, and North America. Apple’s iOS was the most used platform in these studies, appearing in six studies (46%), followed by Android in four studies (31%). Only one study (8%) utilized both platforms, while two studies (15%) did not specify the platform used. Out of the 13 studies, ten evaluation tools/methods were used to measure app quality: Mobile App Rating Scale (MARS) (n=4), semi-structured interview (n=2), System Usability Scale (SUS) (n=2), own-questionnaire (n=2). Other evaluation methods used less commonly were quantitative indicators (n=1), EVALAPPS (n=1), Evidence-based Strategies (EBS) Assessment (n=1), six sigma (n=1), text-mining approaches (n=1) and Taxonomy Behaviour Change Techniques (BCTs) (n=1). One study might use more than one tool/method.

Despite the growth of weight loss apps in the market, the evidence base is still limited with only 46 apps having been formally evaluated for app quality. The tools and methods used to evaluate the quality of weight loss apps are diverse. Ten common evaluation tools or methods have been identified, and MARS is the most widely utilised, following by SUS, and own-questionnaire.