The impact of home, work, and church environments on fat intake over time among rural residents: a longitudinal observational study

Optimizing an mHealth Intervention to Change Food Purchasing Behaviors for Cancer Prevention: Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

Dietary intake is a powerful modifiable factor that influences cancer risk; however, most US adults do not adhere to dietary guidelines for cancer prevention. One promising pathway for improving dietary adherence is targeting grocery shopping habits. Interventions might facilitate healthy grocery choices, with a combination of mHealth and traditional methods, by promoting the salience of dietary goals while shopping, enhancing motivation to make dietary changes, and increasing household support for healthy food purchasing.

OBJECTIVE

This pilot study will assess feasibility and acceptability of intervention components designed to improve adherence to dietary guidelines for cancer prevention (preliminary aim). The primary aim of the study is to quantify the effect of each intervention component, individually and in combination, on dietary intake (primary aim) and grocery store food purchases (exploratory aim). Mediation analyses will be conducted to understand the mechanisms of action (goal salience, motivation, and household support-secondary aims). The overarching goal is to optimize an mHealth intervention to be tested in a future fully powered clinical trial.

METHODS

The study enrolled adults (N=62) with low adherence to dietary recommendations for cancer prevention. In a 20-week program, all participants attend a nutrition education workshop and receive weekly educational messages through an app. A factorial design is used to test 4 intervention components: (1) location-triggered messages: educational messages are delivered when arriving at grocery stores; (2) reflections on the benefits of change: content is added to messages to encourage reflection on anticipated benefits of healthy eating, and participants attend an additional workshop session and 3 coach calls on this topic; (3) coach monitoring: food purchases are monitored digitally by a coach who sends personalized weekly app messages and conducts 3 coaching calls that focus on feedback about purchases; and (4) household support: another adult in the household receives messages designed to elicit support for healthy food purchasing, and support is addressed in 3 coach calls and an extra workshop session attended by the index participant and household member. Assessments are completed at weeks 0, 10, and 20 using self-report measures, as well as objective capture of grocery data from the point of purchase using store loyalty accounts.

RESULTS

The National Cancer Institute funded this study (R21CA252933) on July 7, 2020. Participant recruitment began in the spring of 2021 and concluded with the successful enrollment of 62 participants. Data collection is expected to be completed in the summer of 2022, and results are expected to be disseminated in the summer of 2023.

CONCLUSIONS

The results of this study will inform the development of scalable interventions to lower cancer risk via changes in dietary intake.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04947150; https://clinicaltrials.gov/ct2/show/NCT04947150.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/39669.

Rural Family Medicine Clinicians' Motivations to Participate in a Pragmatic Obesity Trial

PURPOSE

To understand the motivations of rural-practicing primary care clinicians who participate in an intensive multiyear pragmatic randomized behavioral obesity intervention trial, Rural Engagement in Primary Care for Optimizing Weight Reduction (RE-POWER).

METHODS

Structured interviews were conducted with 21 family medicine clinicians who were study leads at participating rural practices. Themes emerged through an analysis of transcripts and interview notes by using the constant comparative method.

RESULTS

The analysis revealed 3 main themes. First, primary care clinicians participated in RE-POWER because it provided a concrete plan to address their recurring clinical care need for effective obesity treatment and management. Second, participation offered help to frustrated physicians who felt a deep professional duty to care for all their patients' problems but were dissatisfied with current obesity management. Third, participation was also attractive to rural primary care clinicians because it provided a visible and sustainable way to demonstrate their commitment to improving the health of patients and the broader community.

CONCLUSIONS

Our findings show that clinicians are motivated to try solutions for a clinical problem-in this case obesity-when that clinical problem is also closely connected to a particularly frustrating area of clinical care that challenges their professional identity. Our data suggest that a motivation to close the gap between ideal and real practice can become such a high priority that clinicians are sometimes willing to try potential solutions, such as engagement in research, that they otherwise would not consider.

Meal analysis for understanding eating behavior: meal- and participant-specific predictors for the variance in energy and macronutrient intake

Background

Meals differ in their nutritional content. This variation has not been fully addressed despite its potential contribution in understanding eating behavior. The aim of this study was to investigate the between-meal and between-individual variance in energy and macronutrient intake as a measure of variation in intake and the meal type-specific relative importance of predictors of these intake variations.

Methods

Energy and macronutrient intake were derived from three 24 h dietary recalls in an EPIC-Potsdam sub-cohort of 814 German adults. Intra-class correlation was calculated for participants and meal type. Predictors of intake were assessed using meal type-specific multilevel regression models in a structural equation modeling framework at intake and participant levels using the Pratt Index. The importance of the predictor energy misreporting was assessed in sensitivity analyses on 682 participants. 95% confidence intervals were calculated based on 1000 bootstrap samples.

Results

Differences between meal types explain a large proportion of the variation in intake (intra-class correlation: 39% for energy, 25% for carbohydrates, 47% for protein, and 33% for fat). Between-participant variation in intake was much lower, with a maximum of 3% for carbohydrate and fat. Place of meal was the most important intake-level predictor of energy and macronutrient intake (Pratt Index of up to 65%). Week/weekend day was important in the breakfast meal, and prior interval (hours passed since last meal) was important for the afternoon snack and dinner. On the participant level, sex was the most important predictor, with Pratt Index of up to 95 and 59% in the main and in the sensitivity analysis, respectively. Energy misreporting was especially important at the afternoon snack, accounting for up to 69% of the explained variance.

Conclusions

The meal type explains the highest variation in energy and macronutrient intakes. We identified key predictors of variation in the intake and in the participant levels. These findings suggest that successful dietary modification efforts should focus on improving specific meals.

Electronic supplementary material

The online version of this article (10.1186/s12937-019-0440-8) contains supplementary material, which is available to authorized users.

Meal and habitual dietary networks identified through Semiparametric Gaussian Copula Graphical Models in a German adult population

Gaussian graphical models (GGMs) are exploratory methods that can be applied to construct networks of food intake. Such networks were constructed for meal-structured data, elucidating how foods are consumed in relation to each other at meal level. Meal-specific networks were compared with habitual dietary networks using data from an EPIC-Potsdam sub-cohort study. Three 24-hour dietary recalls were collected cross-sectionally from 815 adults in 2010-2012. Food intake was averaged to obtain the habitual intake. GGMs were applied to four main meals and habitual intakes of 39 food groups to generate meal-specific and habitual dietary networks, respectively. Communities and centrality were detected in the dietary networks to facilitate interpretation. The breakfast network revealed five communities of food groups with other vegetables, sauces, bread, margarine, and sugar & confectionery as central food groups. The lunch and afternoon snacks networks showed higher variability in food consumption and six communities were detected in each of these meal networks. Among the central food groups detected in both of these meal networks were potatoes, red meat, other vegetables, and bread. Two dinner networks were identified with five communities and other vegetables as a central food group. Partial correlations at meals were stronger than on the habitual level. The meal-specific dietary networks were only partly reflected in the habitual dietary network with a decreasing percentage: 64.3% for dinner, 50.0% for breakfast, 36.2% for lunch, and 33.3% for afternoon snack. The method of GGM yielded dietary networks that describe combinations of foods at the respective meals. Analysing food consumption on the habitual level did not exactly reflect meal level intake. Therefore, interpretation of habitual networks should be done carefully. Meal networks can help understand dietary habits, however, GGMs warrant validation in other populations.

Association of self-care status with some relevant factors in middle-aged women in their early menopausal stage

BACKGROUND

Through self-care, people can solve their health-related problems through increasing their awareness and correcting their lifestyles.

OBJECTIVES

To determine the association of self-care status with some relevant factors in Kashanian middle-aged women in their early menopausal stage.

METHODS

This is a cross-sectional study on 351 women in the age range of 45-60 years. Women were selected based on cluster sampling method from the individuals at health-care centers in Kashan, Iran. Researcher-constructed questionnaire on self-care was used. The validity and the reliability of the questionnaire were calculated. The information gathering method was questionnaire completion by the study participants or interview with them. Collected data were analyzed with SPSS 16 software. T-test, ANOVA, Spearman correlation, and linear regression analysis were applied.

RESULTS

The mean (±standard deviation) of the self-care score was 108.14 ± 20.43. Self-care scores were weak in 13.92%, intermediate in 71.02%, and good in 15.06%. Regression analysis showed that the mean of self-care was significantly higher in those with higher educational level of women's (P = 0.045) and their spouses (P = 0.001). Women who were covered by insurance also showed higher self-care; in addition, there was no significant relationship between self-care and participants' job, spouses' jobs, marital status, marital satisfaction, economic satisfaction, number of children, number of households, and type of accommodation (P > 0.05).

CONCLUSION

The results indicate that self-care is inadequate and that the level of education of couples and insurance coverage has a positive effect on the level of self-care in postmenopausal women. To promote self-care in old age, education and empowerment can be considered.

Development and Testing of the Church Environment Audit Tool

OBJECTIVES

In this paper, we describe development and reliability testing of a novel tool to evaluate the physical environment of faith-based settings pertaining to opportunities for physical activity (PA) and healthy eating (HE).

METHODS

Tool development was a multistage process including a review of similar tools, stakeholder review, expert feedback, and pilot testing. Final tool sections included indoor opportunities for PA, outdoor opportunities for PA, food preparation equipment, kitchen type, food for purchase, beverages for purchase, and media. Two independent audits were completed at 54 churches. Interrater reliability (IRR) was determined with Kappa and percent agreement.

RESULTS

Of 218 items, 102 were assessed for IRR and 116 could not be assessed because they were not present at enough churches. Percent agreement for all 102 items was over 80%. For 42 items, the sample was too homogeneous to assess Kappa. Forty-six of the remaining items had Kappas greater than 0.60 (25 items 0.80-1.00; 21 items 0.60-0.79), indicating substantial to almost perfect agreement.

CONCLUSIONS

The tool proved reliable and efficient for assessing church environments and identifying potential intervention points. Future work can focus on applications within faith-based partnerships to understand how church environments influence diverse health outcomes.