Neslişah R, et al. Nutr Res Pract. 2011 Apr;5(2):117-123. http://dx.doi.org/10.4162/nrp.2011.5.2.117

Purpose of Review: The prevalence of obesity continues to rise steadily. While obesity management typically relies on dietary and lifestyle modifications, individual responses to these interventions vary widely. Clinical guidelines for overweight and obesity stress the importance of personalized approaches to care. This review aims to underscore the role of precision nutrition in delivering tailored interventions for obesity management. Recent Findings: Recent technological strides have expanded our ability to detect obesity-related genetic polymorphisms, with machine learning algorithms proving pivotal in analyzing intricate genomic data. Machine learning algorithms can also predict postprandial glucose, triglyceride, and insulin levels, facilitating customized dietary interventions and ultimately leading to successful weight loss. Additionally, given that adherence to dietary recommendations is one of the key predictors of weight loss success, employing more objective methods for dietary assessment and monitoring can enhance sustained long-term compliance. Summary: Biomarkers of food intake hold promise for a more objective dietary assessment. Acknowledging the multifaceted nature of obesity, precision nutrition stands poised to transform obesity management by tailoring dietary interventions to individuals' genetic backgrounds, gut microbiota, metabolic profiles, and behavioral patterns. However, there is insufficient evidence demonstrating the superiority of precision nutrition over traditional dietary recommendations. The integration of precision nutrition into routine clinical practice requires further validation through randomized controlled trials and the accumulation of a larger body of evidence to strengthen its foundation.

The study aimed to assess and characterize the sustainability of the national diet in Turkey and its association with diet quality, dietary requirements, and sociodemographic factors. Dietary intake was assessed using 24 h recalls from the Turkey Nutrition and Health Survey 2017 (TNHS-2017) (n = 12,527). The environmental footprints were assessed with two environmental indicators: greenhouse gas emissions (GHGEs) and water footprint (WF). Diet quality was assessed using the diet quality index (DQI) and dietary diversity score (DDS). The dietary GHGEs was 3.21 ± 2.07 kg CO₂-eq/person/day and the dietary total WF was 2832 ± 1378 L/person/day. The DQI and DDS were 62.26 ± 8.28 and 6.66 ± 1.31, respectively. Total energy intake was significantly higher in the highest GHGEs and total WF tertiles (2238 ± 722 and 2383 ± 701 kcal, respectively) compared to lower GHGEs and total WF tertiles. Individuals with higher diet-related GHGEs and total WF had a higher daily intake of nutrients with the exception of the percentages of energy supplied from carbohydrates, percentages of meeting nutrients according to the recommended dietary allowance (RDA), DQI (excluding DQI total, moderation, and overall balance score), and DDS scores (p < 0.001). GHGEs and total WF value of the national diet in Turkey are lower than the world average. The results would help develop dietary guidelines to encourage sustainable dietary choices.

Aims: The aim was to determine the effect of meal glycemic load (GL) on blood glucose levels of healthy people with different body mass indexes (BMIs). Methods: Thirty healthy controls were included in this study. The participants were divided into two groups according to their BMI as normal group (BMI = 18.5–24.9 kg/m², n = 15) and overweight group (BMI = 25.0–29.9 kg/m², n = 15). Dietary assessment was done by the 24-h recall method for 3 successive days. Cases were fed by breakfasts with two different GL on consecutive days. Energy values of the test meal, adjusted to meet 25% of daily energy requirements of each case, were identical in low and high GL meal (483 kcal and 482 kcal, respectively). Finger-prick capillary blood samples were taken on 0, 15, 30, 45, 60, 90, and 120 min. Results: Average daily energy intake in normal and overweight group was found as 2514.3 ± 223.8 kcal, 2064.1 ± 521.6 kcal and 2211.4 ± 368.7 kcal, 2494.8 ± 918 kcal in males and females, respectively. Blood glucose level was increased and remained more stable in both high GL meal groups compared to low (P < 0.05). The effects of GL on BMI classified groups were also found different. High GL meal was found to be more effective for increasing blood glucose level, especially on overweight group (P < 0.05). Conclusions: The effects of GL meal were found to be different on normal and overweight individuals. The high GL meals were more effective to increase the blood glucose level than low GL meal, especially on overweight people.