Potentially modifiable risk factors for dementia in six low-income and middle-income countries: A multinational, population-based survey

OBJECTIVES

We aimed to determine the proportion of dementia cases potentially preventable in six low-income and middle-income countries.

STUDY DESIGN

We analyzed data from 19,278 adults aged 50 years or more from China, South Africa, Ghana, India, Russia, and Mexico included in the WHO's Study on global AGEing and adult health.

MAIN OUTCOME MEASURES

We calculated the population attributable fraction for ten potentially modifiable risk factors: less education, hearing loss, hypertension, diabetes, depression, heavy drinking, obesity, smoking, physical inactivity, and social isolation. Weighted attributable fraction was calculated considering communality among risk factors.

RESULTS

We estimated that 37.6 % of the burden of dementia might be attributable to these risk factors. The highest and lowest overall weighted attributable fractions were 38.3 % and 22.9 % in China and Ghana, respectively. Less education (8.3 %), smoking (6.3 %), and physical inactivity (5.7 %) showed the highest attributable fraction for dementia. The overall attributable fraction was higher in the poorest (38.1 %) than in the richest (30.9 %) income quintile. The burden of obesity, diabetes, and hypertension was 61 % higher in the wealthiest than in the poorest population. A total of 7.2 million cases of dementia in these six low- and middle-income countries are potentially caused by these ten potentially modifiable risk factors.

CONCLUSIONS

Overall, 38 % of cases of dementia in China, South Africa, Ghana, India, Russia, and Mexico can be attributable to ten potentially modifiable risk factors. Cardiometabolic risk factors account for a more significant burden of dementia in the wealthiest population. Less education had the highest population attributable fraction independent of living area and income.

Neuroinflammation Biomarkers in the AT(N) Framework Across the Alzheimer's Disease Continuum

In the past years, neuroinflammation has been widely investigated in Alzheimer's disease (AD). Evidence from animal, in vivo and post-mortem studies has shown that inflammatory changes are a common feature of the disease, apparently happening in response to amyloid-beta and tau accumulation. Progress in imaging and fluid biomarkers now allows for identifying surrogate markers of neuroinflammation in living individuals, which may offer unprecedented opportunities to better understand AD pathogenesis and progression. In this context, inflammatory mediators and glial proteins (mainly derived from microglial cells and astrocytes) seem to be the most promising biomarkers. Here, we discuss the biological basis of neuroinflammation in AD, revise the proposed neuroinflammation biomarkers, describe what we have learned from anti-inflammatory drug trials, and critically discuss the potential addition of these biomarkers in the AT(N) framework.

Advances in Proteomic and Metabolomic Profiling of Neurodegenerative Diseases

Proteomics and metabolomics are two emerging fields that hold promise to shine light on the molecular mechanisms causing neurodegenerative diseases. Research in this area may reveal and quantify specific metabolites and proteins that can be targeted by therapeutic interventions intended at halting or reversing the neurodegenerative process. This review aims at providing a general overview on the current status of proteomic and metabolomic profiling in neurodegenerative diseases. We focus on the most common neurodegenerative disorders, including Alzheimer's disease, Parkinson's disease, and amyotrophic lateral sclerosis. We discuss the relevance of state-of-the-art metabolomics and proteomics approaches and their potential for biomarker discovery. We critically review advancements made so far, highlighting how metabolomics and proteomics may have a significant impact in future therapeutic and biomarker development. Finally, we further outline technologies used so far as well as challenges and limitations, placing the current information in a future-facing context.

Dysfunctional traits in obese women and underweight men

BACKGROUND

The prevalence of obesity is rapidly increasing worldwide, together with its comorbidities. Our aim was to assess the emotional traits and affective temperaments, according to various Body Mass Index (BMI) groups, in a large sample.

METHODS

Data was collected by a web-survey on psychological and psychiatric measures (BRAINSTEP). The BMI was evaluated by self-reporting and temperament was evaluated by the Affective and Emotional Composite Temperament Scale (AFECTS). The final sample consisted of 10,786 individuals (mean age 27.9 ± 7.8 years, 70% females).

RESULTS

About 40% of the sample had a BMI score higher than normal. The overall BMI score was particularly associated with a higher Desire and a lower Control and Volition (p<0.001 for all), especially in women. Obese females also had significantly lower Coping, Stability, and Caution. In males only, underweight individuals were more fearful and sensitive, and they had a lower Coping and Volition character than normal weight subjects, suggesting a more fragile and immature profile. Linear regression with several adjustments confirmed these associations. Regarding affective temperaments, a Depressive type was more prevalent among underweight subjects, an Obsessive type was associated with a normal BMI, and a Hyperthymic type was apparent in overweight individuals of both genders. Underweight males and females were more prone to having an internalized temperament.

LIMITATIONS

Only self-reporting measures were used in a cross-sectional design.

CONCLUSIONS

Obese women and underweight men have a more dysfunctional trait profile. Addressing these traits may be important for prevention strategies and, possibly, for weight reduction in women.