Background Accurate dietary assessment is needed in studies that include analysis of nutritional intake. Image-based dietary assessment apps have gained in popularity for assessing diet, which may ease researcher and participant burden compared to traditional pen-to-paper methods. However, few studies report the validity of these apps for use in research. Keenoa is a smartphone image-based dietary assessment app that recognizes and identifies food items using artificial intelligence and permits real-time editing of food journals. Objective This study aimed to assess the relative validity of an image-based dietary assessment app — Keenoa — against a 3-day food diary (3DFD) and to test its usability in a sample of healthy Canadian adults. Methods We recruited 102 participants to complete two 3-day food records. For 2 weeks, on 2 non-consecutive days and 1 weekend day, in random order, participants completed a traditional pen-to-paper 3DFD and the Keenoa app. At the end of the study, participants completed the System Usability Scale. The nutrient analyses of the 3DFD and Keenoa data before (Keenoa-participant) and after they were reviewed by dietitians (Keenoa-dietitian) were analyzed using analysis of variance. Multiple tests, including the Pearson coefficient, cross-classification, kappa score, % difference, paired t test, and Bland-Altman test, were performed to analyze the validity of Keenoa (Keenoa-dietitian). Results The study was completed by 72 subjects. Most variables were significantly different between Keenoa-participant and Keenoa-dietitian (P<.05) except for energy, protein, carbohydrates, fiber, vitamin B1, vitamin B12, vitamin C, vitamin D, and potassium. Significant differences in total energy, protein, carbohydrates, % fat, saturated fatty acids, iron, and potassium were found between the 3DFD and Keenoa-dietitian data (P<.05). The Pearson correlation coefficients between the Keenoa-dietitian and 3DFD ranged from .04 to .51. Differences between the mean intakes assessed by the 3DFD and Keenoa-dietitian were within 10% except for vitamin D (misclassification rate=33.8%). The majority of nutrients were within an acceptable range of agreement in the Bland-Altman analysis; no agreements were seen for total energy, protein, carbohydrates, fat (%), saturated fatty acids, iron, potassium, and sodium (P<.05). According to the System Usability Scale, 34.2% of the participants preferred using Keenoa, while 9.6% preferred the 3DFD. Conclusions The Keenoa app provides acceptable relative validity for some nutrients compared to the 3DFD. However, the average intake of some nutrients, including energy, protein, carbohydrates, % fat, saturated fatty acids, and iron, differed from the average obtained using the 3DFD. These findings highlight the importance of verifying data entries of participants before proceeding with nutrient analysis. Overall, Keenoa showed better validity at the group level than the individual level, suggesting it can be used when focusing on the dietary intake of the general population. Further research is recommended with larger sample sizes and objective dietary assessment approaches.

PCA analysis identified 15 of 32 PPAQ questions that were related to increased physical activity in pregnant women, but only walking and pedometer steps were associated with GWG. Our analysis supports daily walking as the preferred PA for achieving a healthy rate of GWG.

he obesity epidemic affects all health professionals, including the obstetrical community, as women who exceed their gestational weight gains (GWG) increase their risk of pregnancy complications. 1 The concept of a "fit pregnancy" is emerging as women are trying to achieve optimal health outcomes for their unborn child and for themselves. 2 Women can attain a "fit pregnancy" with an appropriate GWG by balancing energy intake (EI) with energy expenditure (EE). Currently there exist dietary, 1,3,4 exercise 5,6 and GWG 1,7 guidelines for pregnant women. Nutritional requirements during pregnancy are based on Dietary Reference Intakes (DRI) recommended by the Institute of Medicine (IOM). 1 Recently the IOM adopted the World Health Organization (WHO) GWG recommendations, which state that women aim for total weight or weekly weight gains based on their pre-pregnancy BMI (PP-BMI). 7 Joint SOGC/ CSEP Clinical Practice Guidelines encourage women to exercise if they have no contraindications. 5 Currently there exist Canadian step recommendations for youth, adults and older adults, but none for pregnant women. 8,9 Despite recommendations, research shows that obstetricians seldom recommend PA, 2,10 but rather participation is influenced by family members. 10-12 When health care providers do promote appropriate GWG by discussing weight goals, PA, and reviewing nutritional requirements during pregnancy, women who receive advice are more likely to target appropriate weight gains. 13 However, intervention trials have not been uniformly successful. 14-18 Research for pregnant women has focused on the strict exercise routines, not daily PA as it relates to EE. 19 Daily PA can be addressed by quantifying total steps taken per day and by using validated questionnaires. 19 To date, one Canadian study has assessed PA patterns during pregnancy, citing walking as the most frequently performed type of PA during pregnancy, 20 but no study has examined the impact of PA on gestational weight gain. The objectives of this study were to: 1) measure daily EI, PA and weekly GWG to observe whether pregnant women were meeting public health recommendations, 2) explore the impact of health care provider advice on PA and GWG, and 3) determine behaviours associated with recommended weekly GWG.

Modeling the relationship using hierarchical models suggests that PP-BMI, prepartum PA, and EI differentially impact GWG, IBW, and PPWR.

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