Impact of obesity and diet on brain structure and function: a gut-brain-body crosstalk

Sex difference in the association between BMI and cognitive impairment in Chinese older adults

BACKGROUND

The association between body mass index (BMI) and cognitive impairment (CI) has been the subject of extensive research, yet the precise dose-response effects remain undefined.

METHODS

Older adults were selected from the 2011/2012 survey at baseline and the new recruits from the 2014 and 2018 waves of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). Multiple logistic regression models were used to evaluate the association between BMI categories and CI, and Restricted Cubic Spline (RCS) was used to explore the nonlinear relationship between BMI and CI.

RESULTS

The study included 29,380 older adults aged from 65 to 117 years, with an average age of 82 years. Of these, 13,465 were men, and 5359 exhibited cognitive impairment. The logistic model indicated that in female participants, being underweight was positively correlated with CI (OR:1.32; 95%CI 1.20-1.46), whereas being overweight was inversely correlated with CI (OR:0.86; 95%CI 0.75-0.99), and we didn't find any association between BMI category and CI in male participants. RCS modeling revealed a U-shaped relationship between BMI and CI. When stratified by sex, men exhibited a similar trend, with the lowest risk at a BMI of 22.774 kg/ m2, while women had the lowest risk of CI at a BMI of 24.817 kg/ m2.

LIMITATION

This was a cross-sectional study, it cannot provide information on causal relationships.

CONCLUSION

A U-shaped relationship was observed between BMI and CI in older adults, more pronounced in the male population, suggesting that male older adults may need to manage their BMI more rigorously.

Emerging role of the host microbiome in neuropsychiatric disorders: overview and future directions

The human body harbors a diverse ecosystem of microorganisms, including bacteria, viruses, and fungi, collectively known as the microbiota. Current research is increasingly focusing on the potential association between the microbiota and various neuropsychiatric disorders. The microbiota resides in various parts of the body, such as the oral cavity, nasal passages, lungs, gut, skin, bladder, and vagina. The gut microbiota in the gastrointestinal tract has received particular attention due to its high abundance and its potential role in psychiatric and neurodegenerative disorders. However, the microbiota presents in other body tissues, though less abundant, also plays crucial role in immune system and human homeostasis, thus influencing the development and progression of neuropsychiatric disorders. For example, oral microbiota imbalance and associated periodontitis might increase the risk for neuropsychiatric disorders. Additionally, studies using the postmortem brain samples have detected the widespread presence of oral bacteria in the brains of patients with Alzheimer's disease. This article provides an overview of the emerging role of the host microbiota in neuropsychiatric disorders and discusses future directions, such as underlying biological mechanisms, reliable biomarkers associated with the host microbiota, and microbiota-targeted interventions, for research in this field.

The Influence of Obesity on Cognitive Functioning Among Healthcare Professionals: A Comprehensive Analysis

Background Excessive body fat, or obesity, is a worldwide epidemic and a major contributor to the development of dementia. Aim The research aimed to determine how obesity affected healthcare professionals' memory performance. Materials and Method A total of 474 participants (both male and female) were recruited in this study by random sampling method from three different health institutions. Participants were categorized into overweight, normal weight, and obese groups based on their body mass index (BMI) as per the WHO guidelines and for body fat participants. The memory function test was done using the Gilewski MJ scale. General frequency of forgetting, mnemonic usage, retrospective functioning, and seriousness of forgetting were measured and compared across the BMI and %body fat groups. Results The percentage of body fat of males and females was 38.19% and 42.26%. Statistically, a significant difference (p<0.05) was observed among the male and female BMI and percentage of body fat. The results showed that there was a significant difference between memory scale parameters and percentage BMI. Statistically, a significant difference was observed in the level of general frequency of forgetting among participants with different percentages of BMI (p<0.05). Similar, results were also observed in the level of seriousness of forgetting, retrospective functioning, and mnemonics usage with different % BMI (p<0.05). The findings showed a positive correlation between BMI and %body fat on the scale of general frequency of forgetting and seriousness of forgetting whereas, a negative correlation was observed on the scale of retrospective functioning and mnemonics usage. Conclusion Memory loss is one of the disorders that obesity is linked to more frequently. A focus on keeping a healthy weight may help prevent the development of future diseases.

Obesity Impairs Cognitive Function with No Effects on Anxiety-like Behaviour in Zebrafish

Over the last decade, the zebrafish has emerged as an important model organism for behavioural studies and neurological disorders, as well as for the study of metabolic diseases. This makes zebrafish an alternative model for studying the effects of energy disruption and nutritional quality on a wide range of behavioural aspects. Here, we used the zebrafish model to study how obesity induced by overfeeding regulates emotional and cognitive processes. Two groups of fish (n = 24 per group) were fed at 2% (CTRL) and 8% (overfeeding-induced obesity, OIO) for 8 weeks and tested for anxiety-like behaviour using the novel tank diving test (NTDT). Fish were first tested using a short-term memory test (STM) and then trained for four days for a long-term memory test (LTM). At the end of the experiment, fish were euthanised for biometric sampling, total lipid content, and triglyceride analysis. In addition, brains (eight per treatment) were dissected for HPLC determination of monoamines. Overfeeding induced faster growth and obesity, as indicated by increased total lipid content. OIO had no effect on anxiety-like behaviour. Animals were then tested for cognitive function (learning and memory) using the aversive learning test in Zantiks AD units. Results show that both OIO and CTRL animals were able to associate the aversive stimulus with the conditioned stimulus (conditioned learning), but OIO impaired STM regardless of fish sex, revealing the effects of obesity on cognitive processes in zebrafish. Obese fish did not show a deficiency in monoaminergic transmission, as revealed by quantification of total brain levels of dopamine and serotonin and their metabolites. This provides a reliable protocol for assessing the effect of metabolic disease on cognitive and behavioural function, supporting zebrafish as a model for behavioural and cognitive neuroscience.

The Concept of Healthy Behaviours in Obesity May Have Unintended Consequences

Obesity has become a global epidemic, representing a major health crisis, with a significant impact both in human and financial terms. Obesity was originally seen as a condition, not a disease, which was considered self-inflicted. Thus, it was understandable that a simplistic approach, such as eat less and move more was proposed to manage obesity. Over the last 25 years, the perception of obesity has been gradually changing and the awareness has risen that it is a disease in its own right and not just a precipitating factor for type 2 diabetes, non-alcoholic fatty liver disease (NAFLD), etc. Creation of a comprehensive algorithm for the management of obesity needs to be informed by an in-depth understanding of the issues impacting the provision of treatment. Promotion of healthy behaviours is essential to help the population become healthier, but these are not obesity treatment strategies. Twenty percent of patients with obesity may respond to approaches based on healthy behaviour, but the 80% who do not respond should not be stigmatised but rather their treatment should be escalated. The unintended consequences of promoting healthy behaviours to patients with obesity can be mitigated by understanding that obesity is likely to be a subset of complex diseases, that require chronic disease management. Once the biology of the disease has been addressed, then healthy behaviours may play an invaluable role in optimising self-care within a chronic disease management strategy.