Heart rate variability (HRV) represents the activity and balance of the autonomic nervous system and its capability to react to internal and external stimuli. As a measure of general body homeostasis, HRV is linked to lifestyle factors and it is associated with morbidity and mortality. It is easily accessible by heart rate monitoring and gains interest in the era of smart watches and self-monitoring. In this review, we summarize effects of weight loss, training, and nutrition on HRV with a special focus on obesity. Besides weight reduction, effects of physical activity and dietary intervention can be monitored by parameters of HRV, including its time and frequency domain components. In the future, monitoring of HRV should be included in any weight reduction program as it provides an additional tool to analyze the effect of body weight on general health and homeostasis. HRV parameters could, for example, be monitored easily by implementation of an electrocardiogram (ECG) every two to four weeks during weight reduction period. Indices presumibly showing beneficial changes could be a reduction in heart rate and the number of premature ventricular complexes as well as an increase in standard deviation of normal-to-normal beat intervals (SDNN), just to name some.

Obesity caused by a positive energy balance is a serious health burden. Studies have shown that obesity is the major risk factor for many diseases like type 2 diabetes mellitus, coronary heart diseases, or various types of cancer. Therefore, the prevention and treatment of increased body weight are key. Different evidence-based treatment approaches considering weight history, body mass index (BMI) category, and co-morbidities are available: lifestyle intervention, formula diet, drugs, and bariatric surgery. For all treatment approaches, behaviour change techniques, reduction in energy intake, and increasing energy expenditure are required. Self-monitoring of diet and physical activity provides an effective behaviour change technique for weight management. Digital tools increase engagement rates for self-monitoring and have the potential to improve weight management. The objective of this narrative review is to summarize current available treatment approaches for obesity, to provide a selective overview of nutrition trends, and to give a scientific viewpoint for various nutrition concepts for weight loss.

Background: Despite an increasing number of smartphone applications (apps) addressing weight management, data on the effect of app-based multimodal obesity treatment approaches on weight loss is limited. This study aimed to examine the effect of a digital multimodal weight loss intervention program delivered by an app on body weight in persons with obesity. Methods: For this single-centre randomized controlled study, 168 adults with a body mass index (BMI) between 30.0 and 40.0 kg/m² without severe comorbidities were recruited in the region of Munich and randomized into two intervention groups. The ADHOC group received an app-based multimodal weight loss program from baseline on for 12 weeks plus 12 weeks of follow-up. The EXPECT group received the app-based intervention for 12 weeks after 12 weeks of “waiting” (no intervention). Anthropometric data, data on quality of life (EuroQol, EQ-5D-5L), and app usage data were collected. Results: 64.3% of study participants were women, mean age was 46.8 ± 11.0 years, and mean BMI was 34.2 ± 2.8 kg/m². The completers analysis resulted in a weight loss of 3.2 ± 3.2 kg (3.2 ± 3.0%) in the ADHOC group and 0.4 ± 2.6 kg (0.3 ± 2.6%) in the EXPECT group after 12 weeks, with a significant difference between the groups (β [95% CI] = −2.9 [−3.8; −1.9], p < 0.001). Completers in the ADHOC group showed weight maintenance after 24 weeks. The time spent on the app was associated with weight reduction (β [95% CI] = −0.10 [−0.18; −0.01], p = 0.03). Conclusions: Application of a multimodal app-based weight loss program results in moderate weight loss in persons with obesity. Trial registration: This study was registered in the German Clinical Trials Register (Registration number: DRKS00025291).

Objective: Long-term positive energy balance promotes the development of obesity, a main risk factor for type 2 diabetes mellitus (T2DM). While an association between increased resting metabolic rate (RMR) and insulin sensitivity (IS) was shown previously, the underlying mechanisms remain unclear. Aim of the mediator analysis was to investigate the role of inflammation within the association between RMR and IS. Methods: Anthropometric, clinical, and lifestyle data were collected according to standard operating procedures. RMR was measured using indirect calorimetry. Homeostasis model assessment for insulin resistance (HOMA-IR) was used as an IS parameter and C-reactive protein (CRP) was measured to represent the inflammatory status. Statistical analyses were performed using SPSS. Results: The analysis included 782 adults (517 females) with a mean age of 32.4 ± 12.0 years and a mean body mass index (BMI) of 24.6 ± 5.2 kg/m². Regression analysis indicated a significant evidence for associations between RMR and HOMA-IR (ß = 39.3 ± 7.3 kcal/d; p ≤ 0.001) and CRP and HOMA-IR (ß = 0.5 ± 0.1; p ≤ 0.001) after adjustment for fat-free mass, sex, age, and study site. Results of the mediator analysis did not support the hypothesis that CRP is a mediator for the association between RMR and HOMA-IR. These results did not change after participant stratification according to sex or BMI. Conclusion: A significant evidence for an association between RMR and IS was shown in a large cohort. However, the inflammatory status, determined via CRP levels, was not a mediator within this association.

Children get infected by SARS-CoV-2; however, compared to adults, they are far more likely to be asymptomatic shedders and have a relatively low risk of developing severe disease [1, 2]. Therefore, it has been assumed that the COVID-19 pandemic would induce little adverse health effects in children. However, concern was been raised that the COVID-19 pandemic will most likely aggravate food shortages and undernutrition among children in low- and low-medium-income countries [3]. In contrast, an online survey including 1,097 adults in Poland reported a greater degree of snacking (52%) and eating more (43%) during the nationwide quarantine due to the COVID-19 pandemic [4]. Almost 30% experienced weight gain, with a mean reported increase of 3 kg, while over 18% reported a mean weight loss of 3 kg.Data are lacking on possible effects of the pandemic in children in high-income countries. We hypothesized that the consequences of the pandemic, such as social distancing and closure of educational institutions, will affect dietary practices and related health indicators in children and their families. To explore this question, we performed a representative survey on dietary practices and health issues among German families. We designed a questionnaire with 15 questions. The questionnaire was applied in an online survey performed by the Forsa Institute for Social Research and Statistical Analysis (forsa Politik- und Sozialforschung GmbH, Berlin, Germany) during the time period of September 11–16, 2020. Standard questions on sociodemographic characteristics were included, but in order to keep the survey short, no information on migrant background was collected. Parents were advised to answer the questions in relation to the pandemic-induced changes during the preceding 6 months. During this time, the consequences of the pandemic in Germany included social distancing and reduced face-to-face meetings of people, a change to working in home office for many employees, and the at least partial closure of most day cares and schools and many sports facilities. Participants of this survey were 1,000 parents (age 20–65 years) with at least 1 child up to the age of 14 years living in the same household. The parents were selected with a systematic random method established by the Forsa Institute (forsa.ominet), considered to obtain a representative population sample.Almost two-thirds (64%) of the participating parents reported that they, or the other parent, or both, worked in home office, with equal proportions working (almost) fully or only partly in home office (Table 1). Working in the home office was more common among parents with completed higher or university education (79%) and those with high incomes (80% of those with a monthly family income of >4,500€). The proportion of parents fully working in home office increased with the size of the community they lived in (20% in communities with 500,000), whereas the child’s age was not consistently related to working in home office. Parents reported eating more often healthier diets (14%) and cooking more at home for their child (30%), with higher proportions among those who worked mostly in home office (20 and 43%, respectively). About equal numbers near 10% reported an increase or decrease of using home delivery of foods or takeout foods, respectively (Table 1). Some 27% of parents reported having gained weight since the start of the pandemic, with equal proportions among mothers and fathers, and no clear association with income, community size, or child age.An increase of children’s body weight during the pandemic was reported by 9%, with a much greater prevalence of 23% among children whose parents had a low level of school education (<10 years). An increased body weight was hardly observed among preschool children, but it occurred mostly in school-age children, particularly in the age group of 10- to 12-year-olds (19%; Table 1), with much more affected boys (24%) than girls (13%). A reduction of physical activity was reported for 38% of all children and for almost 60% of children aged 10 years and older (Table 1).Reported changes in childrens’ food habits included an increased consumption of vegetables in 14% and of fruits in 20%, with no consistent relationship to childrens’ age (Table 1), while intakes of meat and processed meats decreased by 13%. These changes appeared to result from more home preparation of meals by parents working in home office (data not shown). At the same time, there was also an increase in the consumption of salty snacks (18%), sweet snacks (20%), and soft drinks (18%), affecting clearly higher proportions of school-age children aged 10 years and older (Table 1). Boys were more likely than girls to show an increased consumption of salty snacks (20 vs. 15%), sweet snacks (22 vs. 17%), and soft drinks (12 vs. 9%), and potatoes, pasta, rice, and pizza (16 vs. 11%).These results show that the COVID-19 pandemic induces health effects that extend beyond the infection itself. Families that are more homebound due to social distancing or lockdown measures, working more from home, and reduced preschool and school attendance of their children may put more attention to the choice of foods and drinks and replace canteen and processed food by more home-cooked foods, particularly in more privileged families with higher education and income levels. At the same time, both potential increased boredom and psychosocial stress induced in parents and children, for example, due to having to combine work and childcare, the threat of job and income loss, and social isolation, may trigger increased reduced physical activity, potentially increased physically inactive screen time, and increased consumption of energy-dense snack foods and soft drinks and an increased weight gain and risk of overweight and obesity. Our data show a disturbing aggravation of socioeconomic disparity, with a 2.5 times higher...

Various studies showed that a “one size fits all” dietary recommendation for weight management is questionable. For this reason, the focus increasingly falls on personalised nutrition. Although there is no precise and uniform definition of personalised nutrition, the inclusion of genetic variants for personalised dietary recommendations is more and more favoured, whereas scientific evidence for gene-based dietary recommendations is rather limited. The purpose of this article is to provide a science-based viewpoint on gene-based personalised nutrition and weight management. Most of the studies showed no clinical evidence for gene-based personalised nutrition. The Food4Me study, e.g., investigated four different groups of personalised dietary recommendations based on dietary guidelines, and physiological, clinical, or genetic parameters, and resulted in no difference in weight loss between the levels of personalisation. Furthermore, genetic direct-to-consumer (DTC) tests are widely spread by companies. Scientific organisations clearly point out that, to date, genetic DTC tests are without scientific evidence. To date, gene-based personalised nutrition is not yet applicable for the treatment of obesity. Nevertheless, personalised dietary recommendations on the genetic landscape of a person are an innovative and promising approach for the prevention and treatment of obesity. In the future, human intervention studies are necessary to prove the clinical evidence of gene-based dietary recommendations.