Gestational Diabetes Mellitus (GDM) increases risks for type 2 diabetes and weight management is recommended to reduce the risk. Conventional dietary recommendations (energy-restricted, low fat) have limited success in women with previous GDM. The effect of lowering Glycaemic Index (GI) in managing glycaemic variables and body weight in women post-GDM is unknown. To evaluate the effects of conventional dietary recommendations administered with and without additional low-GI education, in the management of glucose tolerance and body weight in Asian women with previous GDM. Seventy seven Asian, non-diabetic women with previous GDM, between 20- 40y were randomised into Conventional healthy dietary recommendation (CHDR) and low GI (LGI) groups. CHDR received conventional dietary recommendations only (energy restricted, low in fat and refined sugars, high-fibre). LGI group received advice on lowering GI in addition. Fasting and 2-h post-load blood glucose after 75 g oral glucose tolerance test (2HPP) were measured at baseline and 6 months after intervention. Anthropometry and dietary intake were assessed at baseline, three and six months after intervention. The study is registered at the Malaysian National Medical Research Register (NMRR) with Research ID: 5183. After 6 months, significant reductions in body weight, BMI and waist-to-hip ratio were observed only in LGI group (P<0.05). Mean BMI changes were significantly different between groups (LGI vs. CHDR: -0.6 vs. 0 kg/m2, P= 0.03). More subjects achieved weight loss ≥5% in LGI compared to CHDR group (33% vs. 8%, P=0.01). Changes in 2HPP were significantly different between groups (LGI vs. CHDR: median (IQR): -0.2(2.8) vs. +0.8 (2.0) mmol/L, P=0.025). Subjects with baseline fasting insulin≥2 μIU/ml had greater 2HPP reductions in LGI group compared to those in the CHDR group (−1.9±0.42 vs. +1.31±1.4 mmol/L, P<0.001). After 6 months, LGI group diets showed significantly lower GI (57±5 vs. 64±6, P<0.001), GL (122±33 vs. 142±35, P=0.04) and higher fibre content (17±4 vs.13±4 g, P<0.001). Caloric intakes were comparable between groups. In women post-GDM, lowering GI of healthy diets resulted in significant improvements in glucose tolerance and body weight reduction as compared to conventional low-fat diets with similar energy prescription.

Personalized nutrition is an approach that tailors nutrition advice to individuals based on an individual’s genetic information. Despite interest among scholars, the impact of this approach on lifestyle habits and health has not been adequately explored. Hence, a systematic review of randomized trials reporting on the effects of personalized nutrition on dietary, physical activity, and health outcomes was conducted. A systematic search of seven electronic databases and a manual search resulted in identifying nine relevant trials. Cochrane’s Risk of Bias was used to determine the trials’ methodological quality. Although the trials were of moderate to high quality, the findings did not show consistent benefits of personalized nutrition in improving dietary, behavioral, or health outcomes. There was also a lack of evidence from regions other than North America and Europe or among individuals with diseases, affecting the generalizability of the results. Furthermore, the complex relationship between genes, interventions, and outcomes may also have contributed to the scarcity of positive findings. We have suggested several areas for improvement for future trials regarding personalized nutrition.

Plant-Based Alternative Products (PBAPs) to meat and dairy are increasingly available. Their relative nutritional quality in comparison to animal-based homologs is poorly documented. To characterize and evaluate the plant-based alternatives available on the market in Spain in comparison to animal products in terms of their nutritional composition and profile, and degree of processing. Nutritional information for PBAPs and homologs were obtained from the Spanish 'Veggie base', branded food composition database. Five PBAPs categories (cheese, dairy products, eggs, meat, and fish, n = 922) were compared to animal-based processed (n = 922) and unprocessed (n = 381) homologs, using the modified version of the Food Standard Agency Nutrient Profiling System (FSAm-NPS score) and NOVA classification criteria. Compared to processed or unprocessed animal food, PBAPs contain significantly higher sugar, salt, and fiber. PBAPs for fish, seafood, and meat were lower in protein and saturated fatty acids. Overall, 68% of PBAPs, 43% of processed and 75% of unprocessed animal-homologs had Nutri-Score ratings of A or B (most healthy). About 17% of PBAPs, 35% of processed and 13% of unprocessed animal-based food were in Nutri-Score categories D or E (least healthy). Dairy, fish, and meat alternatives had lower FSAm-NPS scores (most healthy), while cheese alternatives scored higher (least healthy) than animal-based homologs. Unprocessed fish and meat were healthier than similar PBAPs based on FSAm-NPS criteria. Approximately 37% of PBAPs and 72% of processed animal-based products were ultra-processed food (NOVA group 4). Within the ultra-processed food group, Nutri-Score varied widely. Most PBAPs had better nutrient profile than animal-based homologs. However, cheese, fish and meats PBAPs had poorer nutrient profile and were more processed. Given the high degree of processing and variable nutritional profile, PBAPs require a multi-dimensional evaluation of their health impact.

Dietary patterns can produce an environmental impact. Changes in people's diet, such as the increased consumption of ultra-processed food (UPF) can not only influence human health but also environment sustainability. Assessment of the impact of 2-year changes in UPF consumption on greenhouse gas emissions and water, energy and land use. A 2-year longitudinal study after a dietary intervention including 5879 participants from a Southern European population between the ages of 55-75 years with metabolic syndrome. Food intake was assessed using a validated 143-item food frequency questionnaire, which allowed classifying foods according to the NOVA system. In addition, sociodemographic data, Mediterranean diet adherence, and physical activity were obtained from validated questionnaires. Greenhouse gas emissions, water, energy and land use were calculated by means of the Agribalyse® 3.0.1 database of environmental impact indicators for food items. Changes in UPF consumption during a 2-year period were analyzed. Statistical analyses were conducted using computed General Linear Models. Participants with major reductions in their UPF consumption reduced their impact by -0.6 kg of CO₂eq and -5.3 MJ of energy. Water use was the only factor that increased as the percentage of UPF was reduced. Low consumption of ultra-processed foods may contribute to environmental sustainability. The processing level of the consumed food should be considered not only for nutritional advice on health but also for environmental protection. ISRCTN, ISRCTN89898870. Registered 05 September 2013, http://www.isrctn.com/ISRCTN89898870.

Biomarkers of aging serve as important outcome measures in longevity-promoting interventions. However, there is limited consensus on which specific biomarkers are most appropriate for human intervention studies. This work aimed to address this need by establishing an expert consensus on biomarkers of aging for use in intervention studies via the Delphi method. A 3-round Delphi study was conducted using an online platform. In Round 1, expert panel members provided suggestions for candidate biomarkers of aging. In Rounds 2 and 3, they voted on 500 initial statements (yes/no) relating to 20 biomarkers of aging. Panel members could abstain from voting on biomarkers outside their expertise. Consensus was reached when there was ≥70% agreement on a statement/biomarker. Of the 460 international panel members invited to participate, 116 completed Round 1, 87 completed Round 2, and 60 completed Round 3. Across the 3 rounds, 14 biomarkers met consensus that spanned physiological (eg, insulin-like growth factor 1, growth-differentiating factor-15), inflammatory (eg, high sensitivity C-reactive protein, interleukin-6), functional (eg, muscle mass, muscle strength, hand grip strength, Timed-Up-and-Go, gait speed, standing balance test, frailty index, cognitive health, blood pressure), and epigenetic (eg, DNA methylation/epigenetic clocks) domains. Expert consensus identified 14 potential biomarkers of aging which may be used as outcome measures in intervention studies. Future aging research should identify which combination of these biomarkers has the greatest utility.