Changes in Food Insecurity Among Individuals Using a Telehealth and Nutrition Platform: Longitudinal Study.

BACKGROUND: Food insecurity is a complex public health problem affecting many individuals in the United States. Digital health interventions that promote behavior change and provide access to affordable and healthy food may help to alleviate food insecurity. OBJECTIVE: The aim of this study was to characterize food-insecure users of Foodsmart, a telehealth and nutrition platform with meal planning, food ordering, nutrition education, budgeting, and grocery discount features, and to evaluate changes in diet and food insecurity. METHODS: We retrospectively analyzed data collected from 4595 adults who used the Foodsmart platform between February and October 2021. Participants self-reported their diet, demographics, biometrics, and food insecurity status in a 56-item questionnaire. Participants were reported to be food insecure if they answered "sometimes" or "often" to the question "How often does the food you buy not last and you don't have money to get more?" from the United States Department of Agriculture's Household Food Security survey. We examined baseline characteristics of participants by food insecurity status, associations between characteristics and baseline food insecurity, and changes in diet quality and food insecurity status. To evaluate potential causes of reversing food insecurity, the use of 6 Foodsmart features was compared between food-insecure participants who achieved food security versus food-insecure participants who remained food insecure, based on their last response to the food insecurity question. RESULTS: We found that 16% (742/4595) of participants were food insecure at baseline. Participants who were food insecure at baseline were more likely to be obese, to have at least one chronic condition, to have a lower diet quality, to cook less frequently at home, to think healthy food is too expensive, and less likely to order takeout or eat at a restaurant. Among participants who were food insecure at baseline, 61% (451/742) improved their nutrition and 29% (217/742) responded that they were food secure at follow-up, with an increasing percentage achieving food security with longer enrollment time. Using a multivariable logistic regression model, we found that age, diabetes, prediabetes, BMI categories, and diet quality at baseline were statistically significantly associated with the likelihood of being food insecure at baseline. Among those who were food insecure at baseline, there was a higher relative proportion of participants who achieved food security and used the "deals" (28.6% higher), "CookItNow" (36.4% higher), and "telenutrition" (27.5% higher) features compared to those who remained food insecure. CONCLUSIONS: This study assesses the characteristics of individuals enrolled on the Foodsmart platform who answered the food insecurity question. We found that a significant number of participants who were food insecure at enrollment achieved food security. This finding shows that telehealth and nutrition platforms may potentially help users improve household food security.

Blood Pressure Control in Individuals With Hypertension Who Used a Digital, Personalized Nutrition Platform: Longitudinal Study.

BACKGROUND: While there is a strong association between adhering to a healthy dietary pattern and reductions in blood pressure, adherence remains low. New technologies aimed to help facilitate behavior change may have an effect on reducing blood pressure among individuals with hypertension. OBJECTIVE: This study aims to evaluate characteristics of participants with stage 2 hypertension who used Foodsmart and to assess changes in systolic blood pressure (SBP) and diastolic blood pressure (DBP). METHODS: We analyzed demographic, dietary, and clinical characteristics collected from 11,934 adults with at least two blood pressure readings who used the Foodsmart platform. Stage 2 hypertension was defined as SBP ≥140 mmHg or DBP ≥90 mmHg. We calculated mean changes in blood pressure among participants with stage 2 hypertension and stratified by length of follow-up and the covariates associated with achieving blood pressure levels below stage 2 hypertension. We compared changes in diet quality and weight between participants with stage 2 hypertension at baseline who achieved stage 1 hypertension or below and those who did not. RESULTS: We found that 10.63% (1269/11,934) of participants had stage 2 hypertension at baseline. Among Foodsmart participants with stage 2 hypertension at baseline, SBP and DBP decreased, on average, by 5.7 and 4.0 mmHg, respectively; 33.02% (419/1269) of participants with stage 2 hypertension at baseline achieved blood pressure levels below stage 2 hypertension (SBP <140 mmHg and DBP <90 mmHg). Using a multivariable ordinal logistic regression model, changes in Nutriscore (P=.001) and weight (P=.04) were statistically significantly associated with changes in blood pressure categories for users with stage 2 hypertension at baseline. Using a multivariable logistic regression model, we found that baseline Nutriscore, change in Nutriscore, and change in weight were associated with greater likelihood of users with stage 2 hypertension at baseline achieving a lower blood pressure category. CONCLUSIONS: This study evaluated changes in SBP and DBP among users (with hypertension) of the Foodsmart platform and found that those with stage 2 hypertension, on average, improved their blood pressure levels over time.

Changes in Glycemic Control Among Individuals With Diabetes Who Used a Personalized Digital Nutrition Platform: Longitudinal Study.

BACKGROUND: Diabetes-related costs are the highest across all chronic conditions in the United States, with type 2 diabetes accounting for up to 95% of all cases of diabetes. A healthy diet is strongly associated with lowering glycated hemoglobin A1c (HbA1c) levels among individuals with diabetes, which can help curtail other health complications. Digital health platforms can offer critical support for improving diet and glycemic control among individuals with diabetes. Less is known about the characteristics of people with diabetes who use digital health platforms (specifically, a platform that integrates personalized healthy meal plans and food ordering) and changes in their HbA1c levels. OBJECTIVE: The aim of this study is to characterize Foodsmart users with diabetes and evaluate the longitudinal impact of Foodsmart-a personalized digital nutrition platform with meal planning, food ordering, and nutrition education features-on changes in HbA1c levels. METHODS: We retrospectively analyzed data collected from 643 adults with at least two self-reported HbA1c entries in the Foodsmart platform between January 2016 and June 2021. Participants self-reported their HbA1c levels, height, weight, health conditions, and diet in a 53-item food frequency questionnaire. Diabetes was defined as HbA1c ≥6.5%. We analyzed distributions of characteristics by baseline diabetes status and examined the association of characteristics with the likelihood of having diabetes at baseline. To evaluate the change in HbA1c levels among Foodsmart users, we calculated mean changes (absolute and percent) in HbA1c among participants with diabetes and by length of follow-up. We also compared changes in HbA1c and weight between participants with diabetes at baseline who achieved a normal HbA1c level and those who did not. RESULTS: We found that 43.5% (280/643) of the participants with at least two HbA1c level entries had diabetes at baseline. Participants with diabetes at baseline were more likely to be male, have a higher weight and BMI, report high blood pressure, and have a poorer diet in comparison to participants without diabetes. Using a multivariable logistic regression model, we found that being male and obese were statistically significantly associated with baseline diabetes. Among participants with diabetes at baseline, HbA1c was reduced, on average, by 0.46%. In addition, 21.4% (60/280) of participants with diabetes achieved a normal HbA1c level (<6.5%) in their last HbA1c level entry; this percentage increased with longer follow-up time (39% [7/18] at >24 months). In a sensitivity analysis, users with an HbA1c ≥7.0% at baseline had an average absolute change of -0.62% and 31.2% (62/199) of these participants achieved HbA1c levels of less than 7.0%. CONCLUSIONS: This study assessed characteristics of individuals enrolled on the Foodsmart platform with HbA1c levels and found that users with diabetes had lower HbA1c levels over time and a sizable percentage of participants were successful in achieving normal levels.

Evaluating the Impact of a Digital Nutrition Platform on Cholesterol Levels in Users With Dyslipidemia: Longitudinal Study.

BACKGROUND: A strong association exists between consuming a healthy diet and lowering cholesterol levels among individuals with high cholesterol. However, implementing and sustaining a healthy diet in the real world is a major challenge. Digital technologies are at the forefront of changing dietary behavior on a massive scale, as they can reach broad populations. There is a lack of evidence that has examined the benefit of a digital nutrition intervention, especially one that incorporates nutrition education, meal planning, and food ordering, on cholesterol levels among individuals with dyslipidemia. OBJECTIVE: The aim of this observational longitudinal study was to examine the characteristics of people with dyslipidemia, determine how their status changed over time, and evaluate the changes in total cholesterol, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-HDL-C, and triglycerides among individuals with elevated lipids who used Foodsmart, a digital nutrition platform that integrates education, meal planning, and food ordering. METHODS: We included 653 adults who used Foodsmart between January 2015 and February 2021, and reported a lipid marker twice. Participants self-reported age, gender, weight, and usual dietary intake in a 53-item food frequency questionnaire, and lipid values could be provided at any time. Dyslipidemia was defined as total cholesterol ≥200 mg/dL, HDL-C ≤40 mg/dL, LDL-C ≥130 mg/dL, or triglycerides ≥150 mg/dL. We retrospectively analyzed distributions of user characteristics and their associations with the likelihood of returning to normal lipid levels. We calculated the mean changes and percent changes in lipid markers among users with elevated lipids. RESULTS: In our total sample, 54.1% (353/653) of participants had dyslipidemia at baseline. Participants with dyslipidemia at baseline were more likely to be older, be male, and have a higher weight and BMI compared with participants who had normal lipid levels. We found that 36.3% (128/353) of participants who had dyslipidemia at baseline improved their lipid levels to normal by the end of follow-up. Using multivariate logistic regression, we found that baseline obesity (odds ratio [OR] 2.57, 95% CI 1.25-5.29; P=.01) and Nutriscore (OR 1.04, 95% CI 1.00-1.09; P=.04) were directly associated with achieving normal lipid levels. Participants with elevated lipid levels saw improvements as follows: HDL-C increased by 38.5%, total cholesterol decreased by 6.8%, cholesterol ratio decreased by 20.9%, LDL-C decreased by 12.9%, non-HDL-C decreased by 7.8%, and triglycerides decreased by 10.8%. CONCLUSIONS: This study characterized users of the Foodsmart platform who had dyslipidemia and found that users with elevated lipid levels showed improvements in the levels over time.

Sustaining weight loss among adults with obesity using a digital meal planning and food purchasing platform for 12, 24, and 36 months: a longitudinal study.

BACKGROUND: Previous studies have shown that lifestyle changes, such as diet and exercise, can lead to weight loss, resulting in dramatic improvements in overall health and chronic disease risk. However, while many traditional dieting, food tracking and weight loss coaching programs result in short-term weight loss, there is less evidence of their effectiveness on sustaining weight loss over time. METHODS: We conducted a retrospective analysis of 1,740 adults with obesity who used Foodsmart, a digital personalized dietary assessment, meal planning and food purchasing platform. Participants reported age, gender, at least three measures of weight, and their diet using a food frequency questionnaire. We defined sustained weight loss as participants who lost 5 % of initial weight between their first and second reported weights and lost weight or maintained weight between second and third reported weights. A healthy eating score, Nutriscore, was calculated to assess overall diet quality. We used multivariate logistic regression models to examine the association between user characteristics and odds of sustained weight loss. RESULTS: Over a median of 25 months, the mean (standard deviation) change in weight among participants was - 6.2 (19.8) pounds. In total, 39.3 % (684/1,740) of participants lost at least 5 % of their initial weight, and 22.4 % percent (389/1,740) of participants sustained weight loss. In the fully-adjusted logistic regression model, we found that obesity class 2 (odds ratio, OR: 1.69, 95 % confidence interval, CI: 1.27-2.24, P < 0.001), obesity class 3 (OR: 2.23, 95 % CI: 1.68-2.97, P < 0.001), baseline diet quality (OR: 1.06, 95 % CI: 1.02-1.09, P < 0.001), and greater change in diet quality (OR: 1.10, 95 % CI: 1.07-1.14, P < 0.001) were significantly associated with sustained weight loss. CONCLUSIONS: This study characterized and demonstrated the utility of Foodsmart, a digital platform that gives personalized nutrition recommendations and meal planning tools, in sustained weight reduction among users with obesity.

Weight Reduction Through a Digital Nutrition and Food Purchasing Platform Among Users With Obesity: Longitudinal Study.

BACKGROUND: Digital nutrition apps that monitor or provide recommendations on diet have been found to be effective in behavior change and weight reduction among individuals with obesity. However, there is less evidence on how integration of personalized nutrition recommendations and changing the food purchasing environment through online meal planning and grocery delivery, meal kits, and grocery incentives impacts weight loss among individuals with obesity. OBJECTIVE: The objective of this observational longitudinal study was to examine weight loss and predictors of weight loss among individuals with obesity who are users of a digital nutrition platform that integrates tools to provide nutrition recommendations and changes in the food purchasing environment grounded in behavioral theory. METHODS: We included 8977 adults with obesity who used the digital Foodsmart platform, created by Zipongo, Inc, DBA Foodsmart between January 2013 and April 2020. We retrospectively analyzed user characteristics and their associations with weight loss. Participants reported age, gender, height, at least 2 measures of weight, and usual dietary intake. Healthy Diet Score, a score to measure overall diet quality, was calculated based on responses to a food frequency questionnaire. We used paired t tests to compare differences in baseline and final weights and baseline and final Healthy Diet Scores. We used univariate and multivariate logistic regression models to estimate odds ratios and 95% CI of achieving 5% weight loss by gender, age, baseline BMI, Healthy Diet Score, change in Healthy Diet Score, and duration of enrollment. We conducted stratified analyses to examine mean percent weight change by enrollment duration and gender, age, baseline BMI, and change in Healthy Diet Score. RESULTS: Over a median (IQR) of 9.9 (0.03-54.7) months of enrollment, 59% of participants lost weight. Of the participants who used the Foodsmart platform for at least 24 months, 33.3% achieved 5% weight loss. In the fully adjusted logistic regression model, we found that baseline BMI (OR 1.02, 95% CI 1.02-1.03; P<.001), baseline Healthy Diet Score (OR 1.06, 95% CI 1.05-1.08; P<.001), greater change in Healthy Diet Score (OR 1.12, 95% CI 1.11-1.14; P<.001), and enrollment length (OR 1.28, 95% CI 1.23-1.32; P<.001) were all significantly associated with higher odds of achieving at least 5% weight loss. CONCLUSIONS: This study found that a digital app that provides personalized nutrition recommendations and change in one's food purchasing environment appears to be successful in meaningfully reducing weight among individuals with obesity.

A 40-Day Journey to Better Health: Utilizing the DanielFast to Improve Health Outcomes in Urban Church-Based Settings.

Background: As the costs associated with obesity increase, it is vital to evaluate the effectiveness of chronic disease prevention among underserved groups, particularly in urban settings. This research study evaluated Philadelphia area Keystone First members and church participants enrolled in a group health education program to determine the impact of the Daniel Fast on physical health and the adoption of healthy behaviors. Methods: Participants attended six-weekly health education sessions in two participating churches, and were provided with a digital healthy eating platform. Results: There was a statistically significant decrease from baseline to post assessment for weight, waist circumference and cholesterol. Participants reported a significant improvement in their overall well-being, social and physical functioning, vitality and mental health. Conclusion: Results of this study demonstrate that dietary recommendations and comprehensive group health education delivered in churches and reinforced on a digital platform can improve physical health, knowledge and psychosocial outcomes.

Prospective health care: the second transformation of medicine.

Emerging scientific technologies provide rich sources of predictive biomarkers, which could transform health care. Identification of causal biomarkers will enable the development of tools to quantify risk and anticipate disease. Accurate health risk analysis is rapidly becoming feasible, so health care can become rational, preventive and personalized.