Variation In Intake Research Articles

Exploring the Role of Dietary Calcium Intake in Muscle and Cardiovascular Performance Among Young Athletes

The importance of dietary calcium intake in bone metabolism has been well established; however, it is still less investigated in health-related components, especially addressing muscle performance. This study aims to compare dietary calcium intake and its relationship with cardiovascular and muscular performance in young athletes (lacrosse, Baseball, and soccer players). In this cross-sectional study, 95 participants (ages 18 to 30) participated during two visits to the Human Performance Laboratory. Participants completed body composition, lower and upper body muscle performance, cardiorespiratory protocol, and questionnaires related to dietary calcium intake. One-way ANOVA was used to determine the difference in the calcium intake between groups. The Pearson Correlation Coefficient was used to investigate the relationship between dietary calcium intake and muscle performance variables. Further, linear regression was used to assess the predictive value of calcium variables on overall muscle performance. Lacrosse players had significantly higher calcium intake than Baseball and soccer players (p < 0.05). There was a significant positive correlation between dietary calcium intake and the number of push-ups (r = 0.28; p = 0.03). CIBW and CI explained 4.3% and nearly 25% of the change in MPI, respectively (p < 0.001). This suggests the possible role of dietary calcium intake in enhancing health-related fitness components and highlights the need to explore its involvement in muscle-bone crosstalk.

Bayesian network-guided sparse regression with flexible varying effects.

In this paper, we propose Varying Effects Regression with Graph Estimation (VERGE), a novel Bayesian method for feature selection in regression. Our model has key aspects that allow it to leverage the complex structure of data sets arising from genomics or imaging studies. We distinguish between the predictors, which are the features utilized in the outcome prediction model, and the subject-level covariates, which modulate the effects of the predictors on the outcome. We construct a varying coefficients modeling framework where we infer a network among the predictor variables and utilize this network information to encourage the selection of related predictors. We employ variable selection spike-and-slab priors that enable the selection of both network-linked predictor variables and covariates that modify the predictor effects. We demonstrate through simulation studies that our method outperforms existing alternative methods in terms of both feature selection and predictive accuracy. We illustrate VERGE with an application to characterizing the influence of gut microbiome features on obesity, where we identify a set of microbial taxa and their ecological dependence relations. We allow subject-level covariates, including sex and dietary intake variables to modify the coefficients of the microbiome predictors, providing additional insight into the interplay between these factors.

Habitualness, reward and external constraints: Exploring the underlying influences of daily water intake using the Situated Assessment Method2

AbstractUnderstanding what facilitates and hinders water drinking is crucial to inform interventions for preventing underhydration. Using the Situated Assessment Method2, we extended previous research by examining what influences water drinking in daily life. We studied 213 UK adults, assessing 13 potential predictors (e.g. thirst, availability of other drinks) of their typical water intake across 10 everyday situations (e.g. during work, dinner). Participants then reported their actual water intake in these situations over three alternating days during a 1‐week follow‐up. We evaluated the variability of water intake and its influences across individuals and situations and the prospective relationship between these influences and water intake. The 13 identified predictors explained substantial proportions of variation in water intake. Factors like habitualness (e.g. subjective effort), self‐relevance (e.g. health consciousness) and immediate feedback (e.g. taste) were positively associated with water intake. However, the influence of these factors varied significantly across individuals and situations. Our results suggest that various interrelated predictors facilitate and hinder water drinking behaviour, emphasising the importance of using comprehensive behaviour theories to inform research in this domain. They also align with growing evidence that reward may regulate habitual behaviour.

Association of dietary intake with pneumothorax: A Mendelian randomization study

BackgroundAn association between dietary habits and lung disease has been demonstrated in previous studies. Employing Mendelian randomization, we aimed to explore how different dietary intakes relate to pneumothorax, shedding light on the interplay among gut flora, the lung-gut axis, and pneumothorax. MethodsEmploying both two-sample and multi-sample Mendelian randomization (MR) analyses, we investigated 24 dietary intake variables to establish a strong association with pneumothorax. Causal inferences were drawn using the inverse variance weighted (IVW) method. To fortify our findings, we employed a diverse array of methodologies, including Weighted Median Estimator (WME), Weighted Mode, Simple Mode, Mendelian Randomization Pleiotropy Residual Sum and Outlier (MR-PRESSO), MR-Egger regression, and LASSO. ResultsOur analysis identified genetic variants reliably predicting dietary intakes, meeting stringent criteria (p < 5 × 10−8) and demonstrating independence (r2 < 0.001). Causal-effect estimates derived from the IVW model unveiled a statistically significant association, indicating a causal correlation between pneumothorax and three dietary intakes. Specifically, heightened consumption of fresh fruit (OR = 0.196, 95%CI: 0.063–0.606, p = 0.004) and dried fruit (OR = 0.323, 95%CI: 0.114–0.911, p = 0.032) correlated with reduced pneumothorax risk, while increased processed meat intake (OR = 2.705, 95%CI: 1.026–7.128, p = 0.044) showed a positive correlation. ConclusionIn summary, our MR analysis yields robust evidence supporting a causal correlation between dietary elements and pneumothorax. This study significantly advances our comprehension of pneumothorax risk factors, protective agents, and the intricate mechanisms of the lung-gut axis.

Tea intake and non-alcoholic fatty liver disease risk: A two-sample Mendelian randomization study

BackgroundNon-alcoholic fatty liver disease (NAFLD) is a major global health problem due to its great disease and economic burdens. Tea is a popular beverage consumed by billions of people.globally owing to its health benefits. However, the evidence regarding the association between tea intake and NAFLD risk is inconsistent. ObjectiveTo examine the genetically predicted causal association between tea intake and NAFLD risk using the two-sample Mendelian randomization (MR) method. MethodsSingle‐nucleotide polymorphisms (SNPs) strongly associated with tea intake were obtained from a large dataset (N = 447,485) in the UK biobank, and summary‐level genetic data for NAFLD (2,275 cases and 375,002 controls) were collected from the FinnGen consortium. The two-sample MR method was used to investigate the causal association between tea intake and NAFLD risk. The random‐effects inverse‐variance weighted (IVW) was used as the primary approach for estimating the causal effect, and MR Egger, weighted median, simple mode, and weighted mode were used to verify the robustness of the primary results. ResultsTwenty-four valid SNPs were selected as the instrumental variables for tea intake. The IVW results indicated that tea intake was not causally associated with NAFLD risk (Odds ratio: 1.48; 95 % confidence interval: 0.64, 3.43; p = 0.364); moreover, the results from other methods were consistent with this finding. A leave-one-out analysis further demonstrated the robustness of our results. No evidence of heterogeneity, outliers, or horizontal pleiotropy was found. ConclusionOur results do not support tea intake being causally associated with a decreased risk of NAFLD.

The Effects of Restricted and Ad Libitum Milk Feeding on Growth and Health of Calves

In recent years, there has been a growing concern among consumers regarding animal welfare and their requirements, leading to an increased interest in exploring new approaches to calf rearing. Therefore, the aim of this study was to investigate the effects of milk feeding levels on the growth, feed intake, and blood variables of group-raised calves during the suckling period. Ten Holstein calves, 5 in each group, were used in the study when they were five years old. The calves were acclimated to an automated feeder during the initial 19 days of the experiment, and their initial LWs were recorded after weighing them again. The study concluded upon weaning the calves when they were sixty years old, with a total duration of 36 days The calves in the first group (G1) were provided with a total of 4 L/day of milk replacer, divided into 2 L servings in the morning and evening. Conversely, calves in the second group (G2) were allowed a maximum intake of 12 L/day of milk replacer, mimicking the natural sucking behaviour, with feedings in the morning (05:00-08:00), midday (10:00-13:00), and evening (16:00-20:00). Despite no significant differences in the LW, total and daily LW gains, and body measurements averages between of the groups, calves in G1 consumed more starter feed compared to those in G2 (P

PSX-22 Boosting techniques for prediction of dry matter intake of cattle in confinement settings and SHAP analysis on the models’ output

Abstract Measurement of individual dry matter intake (DMI) is critical to improving the management of the beef herd and is necessary to determine the feed efficiency of individual cattle. Combining machine learning models and proxies for DMI (e.g., water intake, body weight, climatic variables) has the potential to replace the need for dedicated feed intake equipment. It would also open the possibility of measuring DMI in situations like grazing where quantifying DMI directly is not possible. In this study, we examined the relationship between DMI, animal variables and environmental variables. In this study, we developed and tested machine learning models based boosting techniques to develop approaches to predict DMI in cattle, using the same data we have previously published results from Random Forest techniques in the past. The dataset included both bulls and steers. The developed models include both regular boosting regression models and random effects boosting models. The regular boosting technique models such as gradient boosting regression, light gradient boosting regression, extreme gradient boosting regression. Similarly, random effects boosting machine learning model Gaussian process boosting (GPBoost) was developed to consider the random effects associated with the intake behavior of the animals. The extreme gradient boosting model outperformed other regular boosting regression models with a r2 of 0.81 and 0.48 on training and testing datasets respectively. However, it does not consider the random effects associated with the longitudinal nature of the animal intake and weather variables and prone to overfitting. GPBoost model variants were tested and developed to avoid overfitting and to incorporate a random effects model, which we propose as the overall best performing model. The GPBoost generalized well on the training and testing datasets with r2 scores of 0.55 and 0.54 respectively. To further understand the model’s performance on the unseen dataset, we used SHAP analysis on the GPBoost. The SHAP analysis revealed that water intake, full body weight and age of the animals contributed significantly to predicting unseen data.

188 Prediction of individual grazing beef cattle dry matter intake

Abstract Estimation of individual dry matter intake (DMI) of pastured beef cattle is critical to grassland management, genetic improvement of efficiency, and increasing the sustainability of animal agriculture. Currently, the only way to measure individual DMI of grazing cattle is through expensive, labor intensive, and spatially demanding research protocol. Very few options for assessment of individual DMI of grazing animals exist for cattle producers. We have developed a machine learning approach to predicting individual DMI of pastured beef cattle that requires only body weight (BW), water intake, and open-source climate variables. Training data were collected in Wardensville, WV at the West Virginia University Research, Outreach, and Education Center. Crossbred steers (n = 32) were phenotyped for Residual Feed Intake (RFI) in the barn. Animals were split into four groups of two low RFI and two high RFI. After a grazing acclimation period, animal groups were rotationally grazed concurrently through 0.05 ha plots for 7 d. Daily BW and water intake data were collected throughout the experiment using an RFID-equipped front-end scale and metered waterers. Beginning on d 2, animals were provided a bolus of Cr2O3 (10 g) at 0700 and 1900 h. Beginning on d 5, fecal samples were collected from each animal at 0700 and 1900 h. Samples were analyzed for Cr2O3 content and used in conjunction with forage digestibility from paired clipped samples to generate individual intakes. These data were used as ground truth data to assess model performance. We used our Repeated Measures Random Forest (RMRF) model to predict individual DMI of animals using daily BW, water intake, and climate variables. Intakes estimated by RMRF were compared with intakes estimated by NASEM equations. Our model outperformed NASEM predictions by 70%, indicating that our method achieves better results than the current most efficient approach. Though iterative model improvements will be made (collection of more training data, collection of more diverse training data, and use of first-differenced, moving average, and seasonally adjusted variables), our work demonstrates a novel, efficient method for researchers and producers to more accurately estimate DMI of individual pastured beef cattle.

28 Integrating homeostasis in practical mineral supplementation recommendations

Abstract A long-established objective in ruminant nutrition is an accurate supply of the 4 main trace metal nutrients Zn, Cu, Mn, and Fe, respecting bioavailability, nutritional interactions, and nutrient tolerance. Although, current dietary supplementation practices, justified by the multiple uncertainties of trace metal supply, results in dietary levels that widely exceed nutritional guidelines. Additionally, reference feeding recommendations are defined assuming fixed and highly conservative uptake coefficients, an approach that disregards the opportunity, and limitations, of absorptive regulation, the main homeostatic mechanism of these nutrients. Mitigating deficiency risks by generous supplementation can result in a generally overlooked risk, exceeding tolerable trace metal availability. Complete nutrient balance studies have recently described the overwhelming homeostatic downregulation of trace metals at dietary levels that are not uncommon in practice. This finding calls for a novel approach to define supplementation that resolves this conundrum of trace metal adequacy. This approach integrated 3 elements: a stochastic analysis of native dietary supply; a stochastic analysis of net nutrient requirements; and the identification of the upper and lower boundaries of homeostatic regulation for these 4 nutrients in the bovine species. This last, aims to resolve the main limitation of current dietary guidelines, using the potential maximum uptake rates in homeostatic upregulation, and the minimum uptake rates achievable by downregulation, instead of assuming fixed uptake rates. As result, this approach delivers dietary supply ranges of adequate supply, instead of a minimum dietary level to meet dietary adequacy. The probability distribution of nutrient supply was determined by dry-matter intake variability, diversity in dietary composition, and variability of nutrient occurrence in feedstuffs. The probability distribution of net nutrient requirements was defined by the variability of the components of a classic factorial requirement approach applied to different animal conditions. A maximum apparent absorption efficiency was determined to define lower supply boundaries using published datasets. Upper boundaries were defined as the dietary supply level beyond which apparent absorption empirically has shown to exceed net requirements. As expected, this risk-based approach resulted in much lower supplementation recommendations than current reference models. However, it supports the value of preventive supplementation of Zn and Cu to growing and lactating animals, and Cu to non-lactating non-growing cows. This assessment also indicates merit in Mn supplementation to growing bovines. Furthermore, it confirms that under all circumstances native dietary Fe meets nutritional needs, but it also illustrates a tolerance risk to native Fe supply under multiple productive scenarios. Most interestingly, this analysis illustrates the risk of exceeding trace metal tolerance boundaries with common levels of supplementation under common conditions. This approach offers a novel perspective to trace metal supplementation, pointing at an opportunity to improve nutritional adequacy by reconsidering supplementation practices.

The Analysis of Factors Related to Anemia Levels in Adolescent Girls

The impact on teenagers, if they experience anemia, is that it disrupts their ability to learn, reduces their physical exercise ability and body fitness, reduces individual work capacity, reduces the body's immune function, and reduces the ability to regulate body temperature. This research aimed to analyze factors related to anemia in adolescent girls. The research method used quantitative with a cross-sectional approach. The population in the study were all 50 Adolescents who were checked for Hb in March and had moderate anemia. The sample was 44 respondents taken by purposive sampling technique. The instrument used a questionnaire to determine the length of the menstrual period, nutritional status, knowledge, and iron intake. The research used an ordinal distribution used an ordinal regression test. The research results showed that the variable length of menstruation was 0.879 with p=0.348 (&gt; 0.05), the nutritional status variable was 0.231 with p=0.631 (&gt;0.05), the knowledge level variable was 4.407 with p=0.021 (&gt;0.05) and the nutritional intake variable was 11.575 with p=0.001 (&lt;0.05). This meant that the level of knowledge and nutritional intake was related to the level of anemia. Meanwhile, the length of menstruation and nutritional status were not related to the level of anemia. For future researchers, it is expected to provide interventions related to knowledge including individual or group counseling as well as providing a healthy lunch menu program to increase iron intake in adolescents.

A narrative review of factors affecting the welfare of dairy cows in larger Australasian pasture-based production systems

On the basis of current growth trajectories, pasture-based dairies of the future are likely to be bigger, have higher stocking rates and feed more concentrate to cows. This review uses the five-domains framework to consider risks to the welfare of dairy cows in these larger intensified pasture-based production systems. The factors considered in this review can be broadly categorised as (1) emerging welfare risks that can be managed, (2) emerging welfare risks that require research to be managed, or (3) persisting and/or exacerbated welfare risks. First, large herds could be subject to welfare risks associated with more stock per labour unit, longer milking times and longer distances walked to and from the dairy. To counter this, the time that cows in large herds spend off pasture can be reduced by splitting the herd into several more manageable groups, and animal-monitoring technologies can help identify health challenges with a reduced stockperson to animal ratio. Cow body condition and productivity can be maintained at high stocking rates by improving pasture production and feeding a higher proportion of concentrate. The risk of ruminal acidosis may then be reduced by appropriate transition feeding regimes and rumen buffers. Second, ensuring social stability and reducing competition may become difficult as herd sizes increase and feeding becomes more intensive. The resulting variability in feed intake, increased agonistic behaviour and social stress present emerging risks to cow welfare. Research is needed to better understand the social behaviour of cows in large intensive pasture-based herds, and how the design of the pre-milking area, the feeding pad and pasture feeding regimes (i.e. quantity and timing of pasture allocation) can improve accessibility for more vulnerable animals. Finally, intensive pasture-based dairies of the future will continue to face welfare challenges relating to lameness, mastitis and cull-cow management, whereas risks due to environmental exposure may be exacerbated by the removal of shelterbelts to facilitate irrigation. These require continued efforts in research (e.g. ways of incorporating shelter into intensive grazing systems), development (e.g. pathway to market for aged beef) and extension (e.g. improved record keeping and benchmarking of lameness and mastitis).

Evaluating the effect of green tea intake on cardiovascular diseases: A Mendelian randomization study in European and East Asian populations.

Previous research shows that more than 70% of cardiovascular diseases (CVDs) are attributed to modifiable risk factors. Here, we investigated relationship between consumption of green tea in European and East Asian populations and risk of CVDs using Mendelian randomization (MR). Instrumental variables for green tea intake were obtained from genome-wide association studies (GWASs) of 64,949 Europeans and 152,653 East Asians. GWASs for CVDs were derived from UK BioBank and BioBank Japan projects. The main method selected for MR analysis was either the inverse variance weighted (IVW) or Wald ratio, depending on the quantity of single nucleotide polymorphisms. Furthermore, we performed sensitivity analyses to confirm the reliability of the findings. Based on the results of IVW, there is no causal relationship between consumption of green tea and risk of 4 CVDs among Europeans (atrial fibrillation: OR = 1.000, 95% CI: 0.995-1.005, P = .910; heart failure: OR = 1.003, 95% CI: 0.994-1.012, P = .542; ischemic stroke: OR = 1.002, 95% CI: 0.993-1.011, P = .690; coronary artery disease: OR = 1.001, 95% CI: 0.996-1.007, P = .677). Sensitivity analyses and supplementary MR analyses also verify the robustness of the findings. Likewise, there was no correlation between the consumption of green tea and the occurrence of CVDs in East Asians. The consumption of green tea is not associated with a reduced risk of CVDs in populations from Europe and East Asia. This means that those who are trying to reduce their risk of CVDs by drinking more green tea may not benefit from doing so.

Variability in Gut Microbiota Composition and Dietary Intake Before and After a Health Screening Colonoscopy

Variability in Gut Microbiota Composition and Dietary Intake Before and After a Health Screening Colonoscopy

Diet, Protein, Iron and Vitamin C Intake on Anemia Status of Adolescent Girls

Background: Anemia is a condition of the body in which the level of Hemoglobin (Hb) in the blood is below normal. Anemia in adolescents has an impact on decreased concentration, memory, and brain performance in adolescents, as well as stunted physical growth, first menstruation, decreased immunity and learning achievement. Objective to find out whether there is a relationship between diet, protein intake, iron intake and vitamin C intake on the anemia status of adolescent girl Methods: This research was conducted in May 2023. This type of research is a descriptive study with a cross-sectional research design. The sample size in this study was 70 respondents. The data for this research were taken by direct interviews using a questionnaire and a 3 × 24 hour Recall form with the results of Univariate and Bivariate data Results: The results of the study with univariate analysis showed that 4 students (5.7%) had anemia status. A good diet was 85.7%, protein intake was insufficient by 88.6%, iron intake was insufficient by 87.1%, and vitamin C intake was insufficient by 97.1%. The results of the cross-table analysis showed that female students with anemia had a poor diet of 75%, protein intake was 100%, iron intake was 100% insufficient, and vitamin C intake was insufficient by 100%. Conclusion: Bivariate analysis shows an F change value of 0.000 (&lt;0.05) meaning there is a significant relationship between the variables of diet, protein intake, iron intake and vitamin C intake on the anemia status of young women, and this relationship shows an R value: 0.603 meaning a relationship between the independent variables and the dependent variable is strong.

Individual variability and consistency of post-exercise energy and macronutrient intake, appetite sensations, and food reward in healthy adults

Limited evidence is available about the variability of appetitive responses within individuals after an acute bout of exercise. The present study aimed to assess the consistency and individual variability of post-exercise appetitive responses in healthy individuals. Twenty participants (10 females, 23.9 ± 4.1 years, 22.5 ± 2.0 kg m−2) joined the laboratory to perform four sessions separated by a minimum of 5 days: i) a control session with a rest period before and an ad libitum lunch (REST), and ii) three identical exercise sessions (EX) with a 30-min moderate-intensity (60–70% of predicted maximal heart rate) walking bout ending 25 min before the ad libitum lunch. Subjective appetite sensations were assessed before and after the meal at regular intervals, and satiety quotients were calculated. Food reward was assessed by the Leeds Food Preference Questionnaire before and after lunch. For each EX session, the difference with the REST session was calculated (Δ = EX – REST). Energy and macronutrient intake were consistent in response to exercise (all intraclass correlation coefficients (ICC) > 0.8) while results showed that post-exercise subjective appetite sensations and satiety quotients varied across the three EX sessions (almost all ICC < 0.7). Food reward was overall consistent in response to exercise before the test meal but not after. When considering the changes (Δ), the results showed no or poor consistency for most of the appetitive outcomes. To conclude, energy and macronutrient intake, as well as pre-meal food reward, are consistent after exercise in healthy individuals, while subjective appetite sensations are not stable within individuals across the sessions. Regarding the variations from REST to EX sessions, the results suggest that the individual changes observed are only random day-to-day variations.

Computing levels of nutrient inadequacy from household consumption and expenditure surveys: A case study

This paper presents an approach to estimate the between-subject variability in nutrient intake (through the coefficient of variation [CV]) and a method to estimate the prevalence of nutrient inadequacy (PoNI) (for eight micronutrients) using household consumption and expenditure survey (HCES) data. Prevalence values are compared to individual-level estimates derived using the National-Cancer-Institute method. Data come from the 2015 Bangladesh Integrated-Household-Survey, which conducted a household-level 7-day recall (7DR) and two rounds of individual-level 24-hour recall (24HR), filled by one respondent on behalf of all members, for the same rural households. The PoNI values based on 7DR are lower than those calculated from 24HR data, due to the larger average intake estimates from 7DR data. After controlling for differences in average intake estimates and adjusting household-level data for random measurement errors, the PoNI values from 7DR and 24HR data are remarkably close. This highlights the potential use of HCES data (conducted according to international agreed standards) for estimating the level of between-subject variability in usual nutrient intake in a population. The CVs from HCES could be used to compute the PoNI using average intake estimates from individual-level data; and the inadequacy of global nutrient supply using Supply and Utilization Accounts data.

Effect of monensin and/or probiotics on feed intake, apparent digestibility, ruminal, serum and urinary variables, and nitrogen balance of steers

The objective of the present study was to evaluate the association of Bacillus toyonensis, Saccharomyces cerevisiae var. boulardii, and sodium monensin on feed intake, apparent digestibility, ruminal, urinary, and serum variables in the diet of steers. Four Angus × Nellore crossbred steers, with 403.0 ± 75.5 kg of BW, rumen cannulated and housed individually were used. The animals were submitted to a 4 ×4 Latin square design, receiving the following treatments: monensin only (MO); monensin + B. toyonensis (MBT); monensin + S. cerevisiae boulardii (MSB); and B. toyonensis + S. cerevisiae boulardii (BTSB). Treatments with monensin (MO, MBT and MSB) presented lower DM intake than BTSB, but similar apparent digestibility between treatments. No difference was observed between treatments for ruminal pH, but BTSB presented higher NH3-N concentration than MBT and MSB and did not differ from MO. All concentrations in the blood serum and urinary variables were found within the physiological range or close to normal, and no difference was observed in the retained nitrogen. The BTSB treatment showed potential as a feed additive for cattle, by controlling rumen pH and similar concentrations of NH3-N, total SCFA, and retained nitrogen to MO treatment, but when probiotics were combined with monensin no beneficial effect was observed under the studied conditions.

Effects of Acacia mearnsii De Wild. extract and monensin on intake, digestibility, and ruminal variables of lambs

Effects of Acacia mearnsii De Wild. extract and monensin on intake, digestibility, and ruminal variables of lambs

Feasibility of using simple diet self-assessment tool (SDSAT) to establish trajectory of dietary intake for patients undergoing chemotherapy.

e13805 Background: Chemotherapy is often accompanied by impaired dietary intake, which is associated with poor clinical outcomes without effective intervention. Predicting dietary changes during chemotherapy enables early nutritional support, but the dynamic pattern and interindividual variability in dietary intake during chemotherapy remain unclear. Our aim was thus to assess the feasibility of using the Simple Diet Self-Assessment Tool (SDSAT) to establish dietary intake trajectories in patients receiving chemotherapy. Methods: This study used data from an ongoing, prospective cohort study (Patient-Reported Outcome Management Including Surveillance and Intervention in Nutritional Group) of patients receiving chemotherapy in 2021 and 2022. Diet was assessed using the SDSAT once before the treatment and at least three times during one chemotherapy cycle. We applied a group-based trajectory model to identify trajectories of dietary intake. The 24-hour dietary recall (24HR) was used to verify the validity of energy and protein intake estimated by SDSAT; compliance with SDSAT was also assessed. Results: Five trajectory groups were identified for food intake based on 217 entries by 56 patients. The compliance rate accounted for 81.11% for ≥4 cumulative responses per cycle. The agreement between the SDSAT score and the dietary energy and protein intake estimated from 24HR was high (κ: 0.888–1.0, P&lt;0.001). Groups 1 and 2 had significantly lower dietary energy/protein intake than Groups 4 and 5 (P&lt;0.001) but with distinct dietary patterns. Group 4 was the most common dietary trajectory (35.10%). Furthermore, Groups 1, 2, and 3 had significantly weaker handgrip strength (OR: 1.12, 95% CI: 1.02–1.22, P=0.016) compared with Groups 4 and 5. Conclusions: SDSAT was feasible to establish dietary trajectories during one chemotherapy cycle. Longitudinal analysis highlights the interindividual differences in dietary intake patterns among patients receiving chemotherapy and may help to inform proactive and individually tailored nutritional interventions.

Effects of a culturally tailored low-glycaemic index dietary educational intervention on reducing cardiometabolic risk among Chinese adults with obesity: a randomized controlled trial.

An assessor-blinded randomized controlled trial was conducted to assess the effect of a culturally tailored low-glycaemic index (GI) dietary educational intervention on body mass index and cardiometabolic risks for Chinese people with obesity in Hong Kong. A total of 166 Chinese adults in Hong Kong with obesity were randomized to the intervention group (n = 83) or the control group (n = 83). The intervention group received the culturally sensitive low-GI dietary educational intervention based on the health belief model, consisting of an educational booklet, one individual interactive educational session, and three follow-up telephone calls. The control group received general advice on a healthy diet, including a pamphlet, one individual education session, and three follow-up telephone calls. Outcome measures included body mass index, cardiometabolic risk factors, dietary intake variables, and sense of satiety. Data collection was conducted at baseline and post-intervention at 12 weeks. A generalized estimating equation model was used to compare the difference in changes in outcome variables between groups. Compared with the control group, the intervention group exhibited a significant reduction in dietary glycaemic load (β = -6.963, P = 0.026) at post-intervention. No significant effects were found on other outcomes. A 12-week culturally tailored and health belief model-based low-GI dietary educational intervention significantly reduced the dietary glycaemic load and showed the feasibility of the low-GI dietary intervention in Chinese adults in Hong Kong with obesity. A longer intervention period and follow-up might be required to achieve improvements in reducing cardiometabolic risk factors in people with obesity. ClinicalTrials.gov: NCT04152213.