Long-term metabolic fate and mortality in obesity without metabolic syndrome

Food addiction and the physical and mental health status of adults with overweight and obesity

Background

Overweight and obesity now affect more than a third of the world's population. They are strongly associated with somatic diseases, in particular increasing the risk of many metabolic and cardiovascular diseases, but also with mental disorders. In particular, there is a strong association between obesity and depression. As a result, more attention is paid to the neurobiological, behavioural, and psychological mechanisms involved in eating. One of these is food addiction (FA). Research comparing lifestyle elements, physical and mental health problems of excess body weight and individuals with FA is limited and has focused on younger people, mainly students. There is also a lack of studies that relate actual metabolic parameters to FA. To better understand the problem of FA also in older adults, it is important to understand the specific relationships between these variables.

Methods

A cross-sectional survey was conducted with 172 adults with overweight and obesity (82% female) aged 23-85 years. The mean age of all subjects was M = 59.97 years (SD = 11.93), the mean BMI was M = 32.05 kg/m2 (SD = 4.84), and the mean body fat was M = 39.12% (SD = 6.48). The following questionnaires were used: Food Frequency Questionnaire-6 (FFQ-6), Global Physical Activity Questionnaire (GPAQ), Three Factor Eating Questionnaire-R18 (TFEQ-R18), Yale Food Addiction Scale 2. 0 (YFAS 2.0), Zung Self-Rating Depression Scale (SDS). Body composition, anthropometry, fasting glucose, lipid profile, and blood pressure were measured.

Results

A total of 22.7% of participants with overweight and obesity had symptoms of depression according to the SDS, and 18.6% met the criteria for FA according to YFAS 2.0. FA was statistically significantly more common among people up to 50 years. BMI, body fat mass, diastolic blood pressure and sedentary behaviour were statistically significantly higher in people with FA symptoms. Those who were sedentary for 301-450 min per day were significantly more likely to have depressive symptoms, and those who were sedentary for more than 450 min per day were significantly more likely to have FA symptoms.

Conclusions

Our findings complement the current literature on FA, particularly in older adults and metabolic parameters, and suggest further research directions. Although our cross-sectional study design does not allow causal interpretations, increasing physical activity appears to be particularly important in the management of people with overweight or obesity and FA. This may be even more important than for people with depression alone, but future research is needed to explore these relationships further.

Association of obesity with cardiovascular disease in the absence of traditional risk factors

BACKGROUND

The association between obesity and cardiovascular disease (CVD) in people without traditional CVD risk factors is unclear. This study aimed to investigate the association of obesity with CVD and its subtypes in people without traditional CVD risk factors.

METHODS

Based on the Kailuan cohort study, the included participants were divided into different groups according to levels of body mass index (BMI) and waist height ratio (WHtR), respectively. Multivariate Cox proportional hazard models were used to evaluate the associations.

RESULTS

This study included 31,955 participants [men 63.99%; mean age (48.14 ± 3.33) years]. During a median follow-up period of 12.97 (interquartile range: 12.68-13.17) years, 1298 cases of CVD were observed. Compared with the normal BMI group, the hazard ratios (HRs) for CVD, stroke, and myocardial infarction (MI) in the BMI obese group were 1.31 (95% confidence interval [CI] 1.11-1.55), 1.21 (95%CI 1.01-1.46), 1.62 (95%CI 1.13-2.33), respectively. Compared with the WHtR non-obese group, the HRs for CVD, stroke, and MI in the obese group were 1.25(95%CI 1.11-1.41), 1.18 (95%CI 1.03-1.34), 1.57 (95%CI 1.18-2.09), respectively. There was an interaction between age and WHtR (P for interaction was 0.043). The association between WHtR and CVD was stronger in people under 60 years old, with a HR of 1.44 (95%CI 1.24-1.67).

CONCLUSION

We found that obesity increased the risk of CVD in people without traditional CVD risk factors. The association of WHtR with CVD was stronger in people under 60 years old.

The Definition and Prevalence of Obesity and Metabolic Syndrome: Correlative Clinical Evaluation Based on Phenotypes

Increase in the prevalence of obesity has become a major worldwide health problem in adults as well as among children and adolescents. In the last four decades, studies have revealed that the significant increase in the prevalence of obesity has become a pandemic. Obesity is the result of complex interactions between biological, genetic, environmental, and behavioral factors. Indeed, almost all of the children suffering from obesity in early childhood face with being overweight or obese in adolescence. Different phenotypes have different risk factors in the clinical evaluation of obesity. Individuals suffering from metabolically unhealthy obesity (MUO) are at an excess risk of developing cardiovascular diseases (CVDs), several cancer types, and metabolic syndrome (MetS), whereas the metabolically healthy obesity (MHO) phenotype has a high risk of all-cause mortality and cardiometabolic events but not MetS. While most obese individuals have the MUO phenotype, the frequency of the MHO phenotype is at most 10-20%. Over time, approximately three-quarters of obese individuals transform from MHO to MUO. Total adiposity and truncal subcutaneous fat accumulation during adolescence are positively and independently associated with atherosclerosis in adulthood. Obesity, in general, causes a large reduction in life expectancy. However, the mortality rate of morbid obesity is greater among younger than older adults. Insulin resistance (IR) develops with the central accumulation of body fat. MHO patients are insulin-sensitive like healthy normal-weight individuals and have lower visceral fat content and cardiovascular consequences than do the majority of MUO patients. MetS includes clustering of abdominal obesity, dyslipidemia, hyperglycemia, and hypertension. The average incidence of MetS is 3%, with a 1.5-fold increase in the risk of death from all causes in these patients. If lifestyle modifications, dietary habits, and pharmacotherapy do not provide any benefit, then bariatric surgery is recommended to reduce weight and improve comorbid diseases. However, obesity treatment should be continuous in obese patients by monitoring the accompanying diseases and their consequences. In addition to sodium-glucose co-transporter-2 (SGLT2) inhibitors, the long-acting glucagon-like peptide-1 (GLP-1) receptor agonist reduces the mean body weight. However, caloric restriction provides more favorable improvement in body composition than does treatment with the GLP-1 receptor (GLP1R) agonist alone. Combination therapy with orlistat and phentermine are the US Food and Drug Administration (FDA)-approved anti-obesity drugs. Recombinant leptin and synthetic melanocortin-4-receptor agonists are used in rarely occurring, monogenic obesity, which is due to loss of function in the leptin-melanocortin pathway.

Association of body weight change with all-cause and cause-specific mortality: A nationwide population-based study

AIMS

Weight gain and loss increase the risk of all-cause mortality. This study explored the association of short-term weight change with all-cause and cause-specific mortality in middle-aged to older people.

METHODS

This was a 8.4-year retrospective cohort study of 645,260 adults aged 40 to 80 who underwent health checkups twice within a 2-year interval between January 2009 and December 2012. Cox analyses were used to analyze the association between short-term weight change and all-cause and cause-specific mortality.

RESULTS

Weight gain and loss were associated with an increased risk of all-cause mortality: the hazard ratios were 2.05 (95% confidence interval [CI], 1.93-2.16), 1.21 (95% CI, 1.16-1.25), 1.12 (95% CI 1.08-1.17), and 1.60 (95% CI, 1.49-1.70) for the severe weight loss, moderate weight loss, moderate weight gain, and severe weight gain groups, respectively. This U-shaped association was also seen between weight change and cause-specific mortality. Within the weight loss group, those who regained weight after two years had a reduced mortality risk.

CONCLUSIONS

In a middle-aged and elderly population, weight gain or loss of more than 3% during a 2-year interval was related to an elevated risk of all-cause and cause-specific mortality.

Effects of short-term exposure to gaseous pollutants on metabolic health indicators of patients with metabolic syndrome in Northwest China

Currently few studies have explored the relationship between exposure to gaseous pollutants and metabolic health indicators in patients, especially in patients with metabolic syndrome (Mets). This study collected 15,520 patients with Mets in a prospective cohort of nearly 50,000 people with 7 years of follow-up from 2011 to 2017, and matched air pollutants and meteorological data during the same period. The mixed effects model was used to analyze the relationship between different short exposure windows (1-week, 1-month, 2-month, and 3-month) of gaseous pollutants (SO2, NO2, and O3) and the metabolic health indicators of patients after controlled the confounding factors. Stratified analysis was performed by demographic characteristics and behavioral factors. The effects of gaseous pollutants on patients with different Met components were also analyzed. The results showed that the short-term exposure to SO2, NO2, and O3 had a certain effect on the metabolic health indicators of patients with Mets in different exposure windows, and with the extension of the exposure window period, the effects increased. The stratified analysis showed that gender, age, and life behaviors might modify these detrimental effects. In addition, the effects of gaseous pollutants on metabolic health indicators in G4 and G7 were more obvious than other Met components, and the effects of gaseous pollutants on the level of LDL-C were found to be statistically significant in most components. Therefore, patients with Mets should pay more attention to the influence of gaseous pollutants to take appropriate protection to reduce potential health risk.