Effects of differential measurement error in self-reported diet in longitudinal lifestyle intervention studies

Culturally Adapted Lifestyle Intervention for South Asian Adults With Cardiovascular Risk Factors: The SAHELI Randomized Clinical Trial

Importance

South Asian adults in the US experience excess cardiovascular disease (CVD) compared with other racial and ethnic groups. The effectiveness and reach of guideline-recommended lifestyle interventions have not been evaluated in this population.

Objective

To evaluate whether a culturally adapted, group lifestyle intervention will improve CVD risk factors more effectively than written health education materials among US South Asian adults.

Design, Setting, and Participants

This single-blind randomized clinical trial was conducted from March 6, 2018, to February 11, 2023 at community sites in the Chicago, Illinois, metropolitan area. South Asian adults aged 18 to 65 years who were overweight or obese, had no history of CVD events, and had at least 1 additional CVD risk factor (hypertension, dyslipidemia, prediabetes, or diabetes) were eligible for inclusion.

Intervention

A 16-week, culturally adapted, group-based lifestyle intervention led by community health coaches. Lifestyle modification counseling was delivered in English, Gujarati, Hindi, and Urdu. Participants tracked their diet and physical activity (PA) and received 4 optional group maintenance sessions between months 5 and 11 of follow-up. The intervention was delivered in person prior to the onset of the COVID-19 pandemic and via videoconference starting in March 2020. The control group received written health education materials, delivered monthly.

Main Outcomes and Measures

Primary outcomes were the between-group differences in CVD risk factor changes from baseline to 12 months, including weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), glycated hemoglobin (HbA1c), and total cholesterol, estimated using multivariate mixed-effects regression models. Secondary outcomes were self-reported diet quality, PA, and self-efficacy, estimated using univariate mixed-effects regression models.

Results

Among 549 randomized participants, 318 (57.9%) were women, and mean (SD) participant age was 49.2 (9.5) years. Mean differences in CVD risk factor changes from baseline to 12 months in the intervention vs control group were calculated for weight (mean difference, -0.07 kg; 95% CI, -0.55 to 0.42), SBP (mean difference, 0.47 mm Hg; 95% CI, -1.85 to 2.79), DBP (mean difference, 0.44 mm Hg; 95% CI, -1.06 to 1.95), cholesterol (mean difference, -2.47 mg/dL; 95% CI, -8.51 to 3.57), and HbA1c (mean difference, -0.07%; 95% CI -0.20% to 0.07%). Intervention participation was associated with greater improvements in dietary quality, PA, and self-efficacy than control.

Conclusions and Relevance

In the SAHELI randomized clinical trial, a culturally adapted, group lifestyle intervention was not more effective than written health education materials for CVD risk factor reduction among US South Asian adults, but the intervention was associated with small improvements in self-reported health behaviors. Effective CVD prevention interventions for this elevated-risk population require further investigation.

Trial Registration

ClinicalTrials.gov Identifier: NCT03336255.

Comparison of metrics for assessing face washing behaviour for trachoma control

There is currently no single, easy-to-use, reliable indicator to assess whether a face has been washed with soap in the context of trachoma elimination. This study aimed to compare survey report, script-based pictorial recall and facial cleanliness indicators as alternatives to structured observation for measuring face washing behaviour. This method validation study was nested in the Stronger-SAFE trial, Oromia Region, Ethiopia. Structured observation was conducted in randomly selected households for three hours from dawn. The primary caregiver in each household participated in a survey to capture (self)-reported behaviour and/or script-based pictorial recall, a routine-based diary activity to covertly capture information on face washing behaviour of themself and any children aged 1-12. Children 4-12 years old directly participated in the survey and pictorial recall in a subset of households. The facial cleanliness of children aged 1-12 was assessed qualitatively and using the quantitative Personal Hygiene Assessment Tool (qPHAT). Prevalence estimates, sensitivity, specificity and predictive values were computed for each behavioural indicator with observation data as the gold standard. The appropriateness of script-based pictorial recall was assessed using baseline and 3-month follow-up data. Baseline data were collected from 204 households in 68 clusters. Survey estimates of face washing and face washing with soap among caregivers and children were 32% to 60% and 5% to 31% higher than observed behaviour, respectively. Face washing prevalence estimates from pictorial recall were lower than survey estimates and comparable with observations for some face washing with soap indicators (0.3% to 13% higher than observations). Specificity of pictorial recall indicators was high (85% to 99%), but the sensitivity was low (0% to 67%), resulting in a low positive predictive value for all indicators. Both qualitative facial cleanliness indicators and qPHAT scores were poorly correlated with observed face washing earlier that morning. Pictorial recall overestimated face washing with soap among both caregivers and children following intervention delivery but not at baseline. Survey (self)-reported data on face washing is highly inaccurate. Script-based pictorial recall does not correctly classify those who wash their face with soap, and is subject to differential bias following intervention exposure, and facial cleanliness is a poor indicator of recent face washing in settings where faces become rapidly dirty again after washing. Alternatives to structured observation cannot be recommended to monitor the effectiveness of face washing interventions in community settings. Trial Registration ISRCTN registry ISRCTN40760473, https://doi.org/10.1186/ISRCTN40760473.

Navigating healthier beverage consumption in adolescents using the "R-Ma Bot" chatbot: A usability and evaluation study

Objective

This pilot study aimed to evaluate the usability and effectiveness of a behavior change technique (BCT)-based chatbot developed to promote healthier beverage consumption among adolescents.

Methods

The Read and Manage your health roBot ("R-Ma Bot"), designed with 13 BCTs, was tested with 42 adolescents (13 men, 29 women, mean age 15.0 ± 0.7) for 2 weeks. Usability was assessed after the 2-week intervention using a chatbot usability questionnaire, recruitment, retention, participation, and engagement. Scores above 70 out of 100 were considered high usability. Qualitative data from open-ended questions were collected for evaluation. Effectiveness was measured by changes in knowledge, use and impact of nutrition labels, and weekly consumption of sugar, sodium, and caffeine from carbonated and/or energy drinks before and after the 2-week intervention.

Results

The score of R-Ma Bot's usability averaged 74.7, with participants addressing it useful, friendly, and easy to use, though they suggested improving unnatural conversation flow. All participants engaged with the chatbot for at least 13 out of 14 days, with over half using it daily for the entire period. After intervention, awareness of nutrition labels increased from 64.3% to 92.9%, and nonreaders decreased from 42.9% to 16.7%. Weekly sugar intake from beverages significantly decreased by 60%, from 13.1 ± 20.1 mg to 7.9 ± 12.8 mg.

Conclusions

R-Ma Bot's high usability contributed to high retention and behavioral changes, significantly reduced sugar consumption from beverages and improved awareness of nutrition labels. We suggest integrating strategies that enhance knowledge, motivation, and opportunities through BCTs with youth-friendly design elements in the development of interventions for adolescents.

Mitigating underreported error in food frequency questionnaire data using a supervised machine learning method and error adjustment algorithm

BACKGROUND

Food frequency questionnaires (FFQs) are one of the most useful tools for studying and understanding diet-disease relationships. However, because FFQs are self-reported data, they are susceptible to response bias, social desirability bias, and misclassification. Currently, several methods have been created to combat these issues by modelling the measurement error in diet-disease relationships.

METHOD

In this paper, a novel machine learning method is proposed to adjust for measurement error found in misreported data by using a random forest (RF) classifier to label the responses in the FFQ based on the input dataset and creating an algorithm that adjusts the measurement error. We demonstrate this method by addressing underreporting in selected FFQ responses.

RESULT

According to the results, we have high model accuracies ranging from 78% to 92% in participant collected data and 88% in simulated data.

CONCLUSION

This shows that our proposed method of using a RF classifier and an error adjustment algorithm is efficient to correct most of the underreported entries in the FFQ dataset and could be used independent of diet-disease models. This could help nutrition researchers and other experts to use dietary data estimated by FFQs with less measurement error and create models from the data with minimal noise.

Perspective: Council for Responsible Nutrition Science in Session. Optimizing Health with Nutrition-Opportunities, Gaps, and the Future

Achieving optimal health is an aspirational goal for the population, yet the definition of health remains unclear. The role of nutrition in health has evolved beyond correcting malnutrition and specific deficiencies and has begun to focus more on achieving and maintaining 'optimal' health through nutrition. As such, the Council for Responsible Nutrition held its October 2022 Science in Session conference to advance this concept. Here, we summarize and discuss the findings of their Optimizing Health through Nutrition - Opportunities and Challenges workshop, including several gaps that need to be addressed to advance progress in the field. Defining and evaluating various indices of optimal health will require overcoming these key gaps. For example, there is a strong need to develop better biomarkers of nutrient status, including more accurate markers of food intake, as well as biomarkers of optimal health that account for maintaining resilience-the ability to recover from or respond to stressors without loss to physical and cognitive performance. In addition, there is a need to identify factors that drive individualized responses to nutrition, including genotype, metabotypes, and the gut microbiome, and to realize the opportunity of precision nutrition for optimal health. This review outlines hallmarks of resilience, provides current examples of nutritional factors to optimize cognitive and performance resilience, and gives an overview of various genetic, metabolic, and microbiome determinants of individualized responses.

Risk of Type 2 Diabetes Among Individuals with Excess Weight: Weight Trajectory Effects

PURPOSE OF REVIEW

Increased risk of type 2 diabetes mellitus (T2D) among individuals with overweight or obesity is well-established; however, questions remain about the temporal dynamics of weight change (gain or loss) on the natural course of T2D in this at-risk population. Existing epidemiologic evidence is limited to studies that discretely sample and assess excess weight and T2D risk at different ages with limited follow-up, yet changes in weight may have time-varying and possibly non-linear effects on T2D risk. Predicting the impact of weight change on the risk of T2D is key to informing primary prevention. We critically review the relationship between weight change, trajectory groups (i.e., distinct weight change patterns), and T2D risk among individuals with excess weight in recently published T2D prevention randomized controlled trials (RCTs) and longitudinal cohort studies.

RECENT FINDINGS

Overall, weight trajectory groups have been shown to differ by age of onset, sex, and patterns of insulin resistance or beta-cell function biomarkers. Lifestyle (diet and physical activity), pharmacological, and surgical interventions can modify an individual's weight trajectory. Adolescence is a critical etiologically relevant window during which onset of excess weight may be associated with higher risk of T2D. Changes in insulin resistance and beta-cell function biomarkers are distinct but related correlates of weight trajectory groups that evolve contemporaneously over time. These multi-trajectory markers are differentially associated with T2D risk. T2D risk may differ by the age of onset and duration of excess body weight, and the type of weight loss intervention. A better understanding of the changes in weight, insulin sensitivity, and beta-cell function as distinct but related correlates of T2D risk that evolve contemporaneously over time has important implications for designing and targeting primary prevention efforts.