Effectiveness of an mHealth intervention combining a smartphone app and smart band on body composition in an overweight and obese population: Randomized controlled trial (EVIDENT 3 study)

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect

Feeding a protein-restricted diet during pregnancy in the rat induces altered gene promoter methylation in the liver of the F1 and F2 offspring [In special abstracts issue]

Background: There is evidence in humans and experimental animals for non-genomic transmission of induced phenotypes between generations. Induction of an altered phenotype in the F1 generation by feeding a protein-restricted (PR) diet to pregnant rats involves altered epigenetic regulation of specific genes. We investigated whether altered epigenetic regulation of hepatic PPARa and glucocorticoid receptor (GR) promoters induced in the F1 generation by prenatal undernutrition is passed to the F2 offspring.Methods: Rats (F0) were fed a control (18% protein) or PR (9% protein) diet throughout pregnancy and chow during lactation. F1 females were mated and fed chow throughout pregnancy and lactation. F1 and F2 offspring were fed chow. Male offspring from the F1 and F2 generations (n =6 per F0 dietary group) were killed at day 80. Methylation of the hepatic PPARa and GR promoters was determined by methylation-sensitive real-time PCR. mRNA expression was measured by real-time RT-PCR.Results: Methylation of the hepatic PPARa and GR promoters was lower (8% to 11%, p b0.05) in the F1 and F2 PR offspring. There were trends towards higher PPARa and GR expression in the PR offspring

Research Letter: is neuroticism a risk factor for postpartum depression?

Although the relationship between personality and depressive illness is complex (Shea, 2005), there is empirical evidence that some personality features such as neuroticism, harm avoidance, introversion, dependency, self-criticism or perfectionism are related to depressive illness risk (Gunderson et al. 1999). Moreover, personality traits, especially neuroticism, may explain the increased prevalence of depression among females (Goodwin & Gotlib, 2004). Few studies have explored neuroticism, extraversion and psychoticism as risk factors for depression after an event as stressful as childbirth. Pitt (1968) was the first author to report high scores on neuroticism and low scores on extraversion among postpartum depressed women. Similar results were found in a comparison of mothers with and without postpartum depressive symptoms (Dudley et al. 2001; Podolska et al. 2010). A case-control study comparing women with recurrent major depression with and without a history of postpartum depression found no personality trait differences between them; however, those with a history of postpartum depression showed higher neuroticism and psychoticism and lower extraversion than controls. These results suggested that these traits did not confer a specific risk for the postnatal onset episodes (Jones et al. 2010). Prospective studies have also studied the link between personality and postpartum depression; however, these data are not conclusive due to methodological limitations, such as sample size (Kumar & Robson, 1984; Watson et al. 1984; Areias et al. 1991; Boyce et al. 1991; Matthey et al. 2000), selection bias (Kumar & Robson, 1984; Areias et al. 1991; Boyce et al. 1991; Matthey et al. 2000), or depression assessment (self-report measures versus clinical diagnosis: Boyce et al. 1991; Matthey et al. 2000; Dudley et al. 2001; Saisto et al. 2001; Van Bussel et al. 2009) or because the authors did not take into account confounding factors such as stressful life events or social support (Watson et al. 1984; Kumar & Robson, 1984; Boyce et al. 1991; Matthey et al. 2000; Saisto et al. 2001; Verkerk et al. 2005; Van Bussel et al. 2009). (See Supplementary material, Table S1.)The aim of this paper was to extend the previous knowledge of the role of neuroticism, extroversion and psychoticism as risk factors for postpartum depression (depression symptomatology and clinical diagnosis) considering psychosocial variables in a large cohort of women from the general population.Peer Reviewe