Body mass index and risk of Parkinson, Alzheimer, Dementia, and Dementia mortality: a systematic review and dose–response meta-analysis of cohort studies among 5 million participants

Identifying potential causal effects of Parkinson's disease: A polygenic risk score-based phenome-wide association and mendelian randomization study in UK Biobank

There is considerable uncertainty regarding the associations between various risk factors and Parkinson's Disease (PD). This study systematically screened and validated a wide range of potential PD risk factors from 502,364 participants in the UK Biobank. Baseline data for 1851 factors across 11 categories were analyzed through a phenome-wide association study (PheWAS). Polygenic risk scores (PRS) for PD were used to diagnose Parkinson's Disease and identify factors associated with PD diagnosis through PheWAS. Two-sample Mendelian randomization (MR) analysis was employed to assess causal relationships. PheWAS results revealed 267 risk factors significantly associated with PD-PRS among the 1851 factors, and of these, 27 factors showed causal evidence from MR analysis. Compelling evidence suggests that fluid intelligence score, age at first sexual intercourse, cereal intake, dried fruit intake, and average total household income before tax have emerged as newly identified risk factors for PD. Conversely, maternal smoking around birth, playing computer games, salt added to food, and time spent watching television have been identified as novel protective factors against PD. The integration of phenotypic and genomic data may help to identify risk factors and prevention targets for PD.

Association of Body Mass Index and Parkinson Disease: A Bidirectional Mendelian Randomization Study

BACKGROUND AND OBJECTIVES

The role of body mass index (BMI) in Parkinson disease (PD) is unclear. Based on the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in PD (Courage-PD) consortium, we used 2-sample Mendelian randomization (MR) to replicate a previously reported inverse association of genetically predicted BMI with PD and investigated whether findings were robust in analyses addressing the potential for survival and incidence-prevalence biases. We also examined whether the BMI-PD relation is bidirectional by performing a reverse MR.

METHODS

We used summary statistics from a genome-wide association study (GWAS) to extract the association of 501 single-nucleotide polymorphisms (SNPs) with BMI and from the Courage-PD and international Parkinson Disease Genomics Consortium (iPDGC) to estimate their association with PD. Analyses are based on participants of European ancestry. We used the inverse-weighted method to compute odds ratios (ORIVW per 4.8 kg/m2 [95% CI]) of PD and additional pleiotropy robust methods. We performed analyses stratified by age, disease duration, and sex. For reverse MR, we used SNPs associated with PD from 2 iPDGC GWAS to assess the effect of genetic liability toward PD on BMI.

RESULTS

Summary statistics for BMI are based on 806,834 participants (54% women). Summary statistics for PD are based on 8,919 (40% women) cases and 7,600 (55% women) controls from Courage-PD, and 19,438 (38% women) cases and 24,388 (51% women) controls from iPDGC. In Courage-PD, we found an inverse association between genetically predicted BMI and PD (ORIVW 0.82 [0.70-0.97], p = 0.012) without evidence for pleiotropy. This association tended to be stronger in younger participants (≤67 years, ORIVW 0.71 [0.55-0.92]) and cases with shorter disease duration (≤7 years, ORIVW 0.75 [0.62-0.91]). In pooled Courage-PD + iPDGC analyses, the association was stronger in women (ORIVW 0.85 [0.74-0.99], p = 0.032) than men (ORIVW 0.92 [0.80-1.04], p = 0.18), but the interaction was not statistically significant (p-interaction = 0.48). In reverse MR, there was evidence for pleiotropy, but pleiotropy robust methods showed a significant inverse association.

DISCUSSION

Using an independent data set (Courage-PD), we replicate an inverse association of genetically predicted BMI with PD, not explained by survival or incidence-prevalence biases. Moreover, reverse MR analyses support an inverse association between genetic liability toward PD and BMI, in favor of a bidirectional relation.

Charting Alzheimer's Disease and Dementia: Epidemiological Insights, Risk Factors and Prevention Pathways

Alzheimer's disease (AD), the most common cause of dementia, is a complex and multifactorial condition without cure at present. The latest treatments, based on anti-amyloid monoclonal antibodies, have only a modest effect in reducing the progression of cognitive decline in AD, whereas the possibility of preventing AD has become a crucial area of research. In fact, recent studies have observed a decrease in dementia incidence in developed regions such as the US and Europe. However, these trends have not been mirrored in non-Western countries (Japan or China), and the contributing factors of this reduction remain unclear. The Lancet Commission has delineated a constrained classification of 12 risk factors across different life stages. Nevertheless, the scientific literature has pointed to over 200 factors-including sociodemographic, medical, psychological, and sociocultural conditions-related to the development of dementia/AD. This narrative review aims to synthesize the risk/protective factors of dementia/AD. Essentially, we found that risk/protective factors vary between individuals and populations, complicating the creation of a unified prevention strategy. Moreover, dementia/AD explanatory mechanisms involve a diverse array of genetic and environmental factors that interact from the early stages of life. In the future, studies across different population-based cohorts are essential to validate risk/protective factors of dementia. This evidence would help develop public health policies to decrease the incidence of dementia.

The influence of time-restricted eating/feeding on Alzheimer's biomarkers and gut microbiota

OBJECTIVES

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting approximately 55 million individuals globally. Diagnosis typically occurs in advanced stages, and there are limited options for reversing symptoms. Preventive strategies are, therefore, crucial. Time Restricted Eating (TRE) or Time Restricted Feeding (TRF) is one such strategy. Here we review recent research on AD and TRE/TRF in addition to AD biomarkers and gut microbiota.

METHODS

A comprehensive review of recent studies was conducted to assess the impact of TRE/TRF on AD-related outcomes. This includes the analysis of how TRE/TRF influences circadian rhythms, beta-amyloid 42 (Aß42), pro-inflammatory cytokines levels, and gut microbiota composition.

RESULTS

TRE/TRF impacts circadian rhythms and can influence cognitive performance as observed in AD. It lowers beta-amyloid 42 deposition in the brain, a key AD biomarker, and reduces pro-ininflammatory cytokines. The gut microbiome has emerged as a modifiable factor in AD treatment. TRE/TRF changes the structure and composition of the gut microbiota, leading to increased diversity and a decrease in harmful bacteria.

DISCUSSION

These findings underscore the potential of TRE/TRF as a preventive strategy for AD. By reducing Aß42 plaques, modulating pro-inflammatory cytokines, and altering gut microbiota composition, TRE/TRF may slow the progression of AD. Further research is needed to confirm these effects and to understand the mechanisms involved. This review highlights TRE/TRF as a promising non-pharmacological intervention in the fight against AD.

Predictors for survival in patients with Alzheimer's disease: a large comprehensive meta-analysis

The prevalence of Alzheimer's disease (AD) is increasing as the population ages, and patients with AD have a poor prognosis. However, knowledge on factors for predicting the survival of AD remains sparse. Here, we aimed to systematically explore predictors of AD survival. We searched the PubMed, Embase and Cochrane databases for relevant literature from inception to December 2022. Cohort and case-control studies were selected, and multivariable adjusted relative risks (RRs) were pooled by random-effects models. A total of 40,784 reports were identified, among which 64 studies involving 297,279 AD patients were included in the meta-analysis after filtering based on predetermined criteria. Four aspects, including demographic features (n = 7), clinical features or comorbidities (n = 13), rating scales (n = 3) and biomarkers (n = 3), were explored and 26 probable prognostic factors were finally investigated for AD survival. We observed that AD patients who had hyperlipidaemia (RR: 0.69) were at a lower risk of death. In contrast, male sex (RR: 1.53), movement disorders (including extrapyramidal signs) (RR: 1.60) and cancer (RR: 2.07) were detrimental to AD patient survival. However, our results did not support the involvement of education, hypertension, APOE genotype, Aβ42 and t-tau in AD survival. Our study comprehensively summarized risk factors affecting survival in patients with AD, provided a better understanding on the role of different factors in the survival of AD from four dimensions, and paved the way for further research.

Assessing the Global, Regional, and National Impact of High Body Mass Index on Alzheimer's Disease and Other Dementias Between 1990 and 2019

BACKGROUND

Obesity significantly increases Alzheimer's disease (AD) and dementia risk. Understanding the link between a high body mass index (BMI) and these conditions is crucial for effective management and prevention.

OBJECTIVE

We aimed to estimate the burden of AD and other dementias attributed to high BMI from 1990 to 2019 based on sex, age, and socio-demographic indicators (SDI) at global, regional, and national levels.

METHODS

We collected data on deaths, disability-adjusted life years (DALYs), age-standardized mortality rates (ASMR), and age-standardized DALY rates (ASDR) from the 2019 Global Burden of Disease study for AD and dementia attributed to high BMI. We explored the correlation between SDI levels and ASDR.

RESULTS

In 2019, there were 198,476.2 deaths (95% UI: 32,695.4-593,366.4) and 3,159,912.4 DALYs (848,330.5-8,042,531) attributed to high BMI. Numbers of deaths, DALYs, ASMR, and ASDR increased since 1990. Females had higher deaths, ASMR, and ASDR than males. Mortality and DALYs rates increased with age. ASMR and ASDR increased across five SDI levels, with the highest rise in Low-middle SDI. High-income North America had the most deaths [30,993.9 (5,101.7-89,912.9)], while North Africa and the Middle East had the highest ASMR [4.61 (0.79-13.64)] and ASDR [72.56 (20.98-181.16)] in 2019.

CONCLUSIONS

The burden of AD and other dementias attributed to high BMI increased since 1990 globally and is still heaviest in developed regions. Females accounted predominantly for the burden than males. Timely measures are needed to against high BMI.

Association Between Body Mass Index Changes and All-Cause Mortality in Parkinson's Disease

Background

Whether body weight changes are associated with Parkinson's disease (PD) mortality remains uncertain.

Objective

To investigate the association between changes in body mass index (BMI) and all-cause mortality in patients with PD.

Methods

This nationwide cohort study enrolled 20,703 individuals with new-onset PD (ICD-10 code: G20 and a rare intractable disease registration code: V124) who underwent health screening program by the Korean National Health Insurance Service within two years from pre- and post-PD diagnosis. We identified nine BMI change groups based on three BMI status: underweight (BMI < 18.5 kg/m2), normal or overweight (18.5 kg/m2≤BMI < 25 kg/m2), and obese (BMI≥25 kg/m2).

Results

Of 20,703 individuals, 3,789 (18.0%) died during the follow-up period. Excessive weight loss to underweight in the obese group (hazard ratio [HR] = 3.36, 95% CI:1.60-7.08), weight loss in the normal to overweight group (HR = 2.04, 95% CI:1.75-2.39), sustained underweight status (HR = 2.05, 95% CI:1.67-2.52), and weight gain from underweight to normal or overweight (HR = 1.52, 95% CI:1.15-2.02) were associated with increased mortality. Sustained obese status (HR = 0.80, 95% CI:0.74-0.87) and weight gain in the normal to overweight group (HR = 0.82, 95% CI:0.71-0.95) were associated with reduced mortality.

Conclusions

We found that BMI change at diagnosis was associated with mortality in patients with PD. Specifically, being underweight either before or after diagnosis as well as experiencing weight loss, were associated with increased mortality. These findings provide valuable insights for weight management planning in PD, highlighting the importance of individualized approach that consider pre-diagnosis BMI.

Potential risk of proton pump inhibitors for Parkinson's disease: A nationwide nested case-control study

Proton pump inhibitor (PPI) use is a potential risk factor for neurodegenerative disease development; however, its role in Parkinson's disease (PD) remains unclear. This study aimed to investigate the association between PPI use and PD risk. A total of 31,326 patients with newly diagnosed PD were matches by age, sex, body mass index, diabetes, and hypertension with 125,304 controls at a ratio of 1:4. The data were collected from the Korean National Health Insurance Services Database from January 2010 to December 2019. Cumulative defined daily doses of PPIs were extracted from treatment claims. We examined the association between PPI use and PD risk using conditional logistic regression. To prevent protopathic bias, we excluded patients diagnosed with PD within a 1-year lag period after PPI exposure. We applied 2- and 3-year lag periods for sensitivity analysis. PPI use was associated with an increased risk of PD when a 1-year lag period was applied between PPI exposure and PD development (adjusted odds ratio, 1.10; 95% confidence interval, 1.07-1.13). A significant positive dose-response relationship existed between the cumulative defined daily doses of PPIs and PD development (P<0.001). Similar results were obtained for the 2- or 3-year lag periods. The association did not vary based on gender. Older age, a higher Charlson Comorbidity Index score, no alcohol consumption, and a non-smoking status were associated with a significantly increased PD risk with PPI use. We observed an association between PPI use and PD risk, although long-term follow-up studies are necessary to verify this association.

Association Between Weight Status and Rate of Cognitive Decline: China Health and Nutrition Survey 1997-2018

BACKGROUND

There is a close relationship between weight status and cognitive impairment in older adults. This study examined the association between weight status and the trajectory of cognitive decline over time in a population-based cohort of older adults in China.

METHODS

We used data from adults aged ≥55 years participating in the China health and nutrition survey (1997-2018). Underweight (body mass index [BMI] ≤ 18.5 kg/m2), normal weight (18.5-23 kg/m2), overweight (23-27.5 kg/m2), and obesity (BMI ≥ 27.5 kg/m2) were defined using the World Health Organization Asian cutpoints. Global cognition was estimated every 2-4 years through a face-to-face interview using a modified telephone interview for cognitive status (scores 0-27). The association between BMI and the rate of global cognitive decline, using a restricted cubic spline for age and age category, was examined with linear mixed-effects models accounting for correlation within communities and individuals.

RESULTS

We included 5 992 adults (53% female participants, mean age of 62 at baseline). We found differences in the adjusted rate of global cognitive decline by weight status (p = .01 in the cubic spline model). Models were adjusted for sex, marital status, current employment status, income, region, urbanization, education status, birth cohort, leisure activity, smoking status, and self-reported diagnosis of hypertension, diabetes, or Myocardial Infarction (MI)/stroke. In addition, significant declines by age in global cognitive function were found for all weight status categories except individuals with obesity.

CONCLUSIONS

In a cohort of adults in China, cognitive decline trajectory differed by weight status. A slower rate of change was observed in participants classified as having obesity.

Body mass index and death by cognitive impairment

BACKGROUND

Epidemiological studies have reported that among participants with impaired cognitive, overweight and mild obesity are associated with substantially improved survival, this finding has been termed the "obesity paradox" and has led to uncertainty about secondary prevention.

AIMS

To explore whether the association of BMI with mortality differed in different MMSE score, and whether the obesity paradox in patient with cognitive impairment (CI) is real.

METHODS

The study used data from CLHLS, a representative prospective population-based cohort study in China, which included 8348 participants aged ≥ 60 years between 2011 and 2018. The independent association between BMI and mortality in differed MMSE score by calculating hazard ratios (HRs) in multivariate Cox regression analysis.

RESULTS

During a median (IQR) follow-up of 41.18 months, a total of 4216 participants died. In the total population, underweight increased the risk of all-cause mortality (HRs, 1.33; 95% CI 1.23-1.44), compared with normal weight, and overweight was associated with a decreased risk of all-cause mortality (HR 0.83; 95% CI 0.74-0.93). However,  compared to normal weight, only underweight was associated with increased mortality risk among participants with MMSE scores of 0-23, 24-26, 27-29, and 30, and the fully-adjusted HRs (95% CIs) for mortality were 1.30 (1.18, 1.43), 1.31 (1.07, 1.59), 1.55 (1.34, 1.80) and 1.66 (1.26, 2.20), respectively. The obesity paradox was not found in individuals with CI. Sensitivity analyses carried out had hardly any impact on this result.

CONCLUSION

We found no evidence of an obesity paradox in patients with CI, compared with patients of normal weight. But underweight individuals may have increased mortality risk whether in the population with CI or not. And overweight/obese people with CI should continue to aim for normal weight.

Body Mass Index, Abdominal Adiposity, and Incidence of Parkinson Disease in French Women From the E3N Cohort Study

BACKGROUND AND OBJECTIVES

Previous studies on the relationship between body mass index (BMI) and Parkinson disease (PD) provided inconsistent results, likely due to reverse causation explained by weight loss during the prodromal phase. We examined the association of BMI and abdominal adiposity with PD incidence using lagged analyses to address the potential for reverse causation and compared BMI trajectories in patients before diagnosis and matched controls.

METHODS

We used data from the E3N cohort study of French women with a 29-year follow-up (1990-2018). BMI (kg/m²) was computed based on self-reported weight and height up to 11 times; up to 6 waist circumference (WC) and hip circumference measures were available. PD diagnoses were validated based on medical records and drug claim databases. Multivariable time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% CIs according to BMI categories (underweight <18.5 kg/m²; normal = [18.5-25.0[ kg/m²; overweight = [25.0-30.0[ kg/m²; obese ≥30.0 kg/m²). Exposures were lagged by 5 years in main analyses; we used longer lags (10 and 20 years) in sensitivity analyses. We examined trajectories of BMI categories within a nested case-control study using multivariable generalized estimating equations multinomial logistic models.

RESULTS

Of 96,702 women (baseline age = 40-65 years), 1,164 developed PD. PD incidence was lower (HR = 0.76, 95% CI = 0.59-0.98, p = 0.032) among women with obesity compared with those with normal BMI. There was a similar association in analyses using longer lag times (20 years, 598 cases, HR = 0.52, 95% CI = 0.30-0.88, p = 0.016). A similar pattern was seen for WC and waist-height ratio but not waist-hip ratio. Trajectories of BMI categories (1,196 patients and 23,876 controls) showed that obesity was less frequent in patients with PD before diagnosis than in controls, with a statistically significant difference 29 years before. In addition, the frequency of obesity decreased 5-10 years before diagnosis in patients.

DISCUSSION

In this large cohort of women with a long follow-up, obesity was associated with a lower hazard of PD, even when measured 20 years before diagnosis, in agreement with Mendelian randomization studies. Our analyses underscore the importance of lagged analyses to account for reverse causation. These findings warrant further investigations to understand the mechanisms underlying this inverse association.

Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study

BACKGROUND

In the older general population, neurodegenerative diseases (NDs) are associated with increased disability, decreased physical and cognitive function. Detecting risk factors can help implement prevention measures. Using deep neural networks (DNNs), a machine-learning algorithm could be an alternative to Cox regression in tabular datasets with many predictive features. We aimed to compare the performance of different types of DNNs with regularized Cox proportional hazards models to predict NDs in the older general population.

METHODS

We performed a longitudinal analysis with participants of the English Longitudinal Study of Ageing. We included men and women with no NDs at baseline, aged 60 years and older, assessed every 2 years from 2004 to 2005 (wave2) to 2016-2017 (wave 8). The features were a set of 91 epidemiological and clinical baseline variables. The outcome was new events of Parkinson's, Alzheimer or dementia. After applying multiple imputations, we trained three DNN algorithms: Feedforward, TabTransformer, and Dense Convolutional (Densenet). In addition, we trained two algorithms based on Cox models: Elastic Net regularization (CoxEn) and selected features (CoxSf).

RESULTS

5433 participants were included in wave 2. During follow-up, 12.7% participants developed NDs. Although the five models predicted NDs events, the discriminative ability was superior using TabTransformer (Uno's C-statistic (coefficient (95% confidence intervals)) 0.757 (0.702, 0.805). TabTransformer showed superior time-dependent balanced accuracy (0.834 (0.779, 0.889)) and specificity (0.855 (0.0.773, 0.909)) than the other models. With the CoxSf (hazard ratio (95% confidence intervals)), age (10.0 (6.9, 14.7)), poor hearing (1.3 (1.1, 1.5)) and weight loss 1.3 (1.1, 1.6)) were associated with a higher DNN risk. In contrast, executive function (0.3 (0.2, 0.6)), memory (0, 0, 0.1)), increased gait speed (0.2, (0.1, 0.4)), vigorous physical activity (0.7, 0.6, 0.9)) and higher BMI (0.4 (0.2, 0.8)) were associated with a lower DNN risk.

CONCLUSION

TabTransformer is promising for prediction of NDs with heterogeneous tabular datasets with numerous features. Moreover, it can handle censored data. However, Cox models perform well and are easier to interpret than DNNs. Therefore, they are still a good choice for NDs.

Sex Differences in the Association Between Body Mass Index and Dementia Risk in Community-Dwelling Japanese People Aged 40-74 Years

BACKGROUND

The association between body mass index (BMI) and dementia risk is heterogeneous across age groups and might be influenced by sex.

OBJECTIVE

This study aimed to clarify sex differences in the association between BMI and dementia risk in community-dwelling people.

METHODS

This cohort study with an 8-year follow-up targeted 13,802 participants aged 40-74 years at baseline in 2011-2013. A self-administered questionnaire requested information on body size, including height, weight, and waist circumference (the values of which were validated by direct measurement), socio-demographics, lifestyle, and disease history. BMI was calculated and categorized as < 18.5 (underweight), 18.5-20.6 (low-normal), 20.7-22.6 (mid-normal), 22.7-24.9 (high-normal), 25.0-29.9 (overweight), and≥30.0 kg/m2 (obese). Incident cases of dementia were obtained from the long-term care insurance database. A Cox proportional hazards model was used to calculate multivariable-adjusted hazard ratios (HRs).

RESULTS

The mean age of participants was 59.0 years. In men, higher BMI was associated with lower dementia risk (fully-adjusted p for trend = 0.0086). In women, the association between BMI and dementia risk was U-shaped; the "underweight," "low-normal," and "overweight" groups had a significantly higher risk (fully-adjusted HR = 2.12, 2.08, and 1.78, respectively) than the reference ("high-normal" group). These findings did not change after excluding dementia cases which occurred within the first four years of the follow-up period.

CONCLUSION

Overweight/obese women, but not men, had an increased risk of dementia, suggesting that sex differences in adiposity might be involved in the development of dementia.

Association of late-life body mass index with the risk of Alzheimer disease: a 10-year nationwide population-based cohort study

Existing data for the association between late-life body mass index (BMI) and the risk of Alzheimer’s disease (AD) in the underweight population are limited with conflicting results. A large population-based cohort study of 148,534 individuals aged ≥ 65 years who participated in the national health screening program from 2002 to 2005 was performed using the Korean National Health Insurance Service-Senior cohort database 2006–2015. The risk of AD according to BMI category (kg/m²) in Asians was evaluated using a multivariable Cox regression model, after adjustments for age, sex, lifestyle, low-income status, and comorbidities. To evaluate the association between BMI and AD risk, the underweight population was further subdivided according to the degree of thinness. During the 10-year follow-up period, 22,279 individuals developed AD. Relative to the normal-weight population, the estimated adjusted hazard ratio (HR) for incident AD in the underweight, overweight, and obese populations was 1.17 (95% confidence interval [CI], 1.09–1.24), 0.90 (0.87–0.93), and 0.83 (0.80–0.85), respectively. In the underweight population, AD risk increased as the degree of thinness increased (p for the trend, < .001). Late-life BMI showed a significant inverse relationship with AD risk, especially in the underweight population. Public health strategies to screen for AD more actively in the underweight population and improve their weight status may help reduce the burden of AD.

Association Between Body Mass Index and Incident Dementia Among Community-Dwelling Older Adults: The Shanghai Aging Study

BACKGROUND

The relationship between body mass index (BMI) and dementia is inconclusive. Undesirable loss of fat-free mass is a risk factor for cognitive decline while obesity is also a risk factor for cardio-metabolic disorders among the older adults.

OBJECTIVE

This study aimed to examine the association between BMI and incident all-cause dementia among Chinese older adults using a prospective study.

METHODS

Participants were 1,627 community residents aged 60 or older without dementia from the Shanghai Aging Study. Cox regression models, incorporated with restricted cubic splines, were used to explore a nonlinear association between baseline BMI and risk of all-cause dementia as measured by hazard ratio (HR) using both frequentist and Bayesian approach.

RESULTS

We diagnosed 136 incident dementia cases during the mean follow-up of 5.3 years. Compared with moderate BMI (18.5-24.0 kg/m2), low BMI (<  18.5 kg/m2) were related to an increased risk of dementia with the HR as 3.38 (95% CI 1.50-7.63), while high BMI (≥24.0 kg/m2) showed a decreased risk of dementia without statistical significance (HR = 0.91, 95% CI 0.60 to 1.39). Sensitivity analysis in participants without central obesity indicated that the association was still significant with even higher HR. Bayesian approach presented the similar results.

CONCLUSION

Our result indicates that low BMI may contribute to high risk of incident dementia, even in individuals without central obesity.

Causal role of high body mass index in multiple chronic diseases: a systematic review and meta-analysis of Mendelian randomization studies

BACKGROUND

Obesity is a worldwide epidemic that has been associated with a plurality of diseases in observational studies. The aim of this study was to summarize the evidence from Mendelian randomization (MR) studies of the association between body mass index (BMI) and chronic diseases.

METHODS

PubMed and Embase were searched for MR studies on adult BMI in relation to major chronic diseases, including diabetes mellitus; diseases of the circulatory, respiratory, digestive, musculoskeletal, and nervous systems; and neoplasms. A meta-analysis was performed for each disease by using results from published MR studies and corresponding de novo analyses based on summary-level genetic data from the FinnGen consortium (n = 218,792 individuals).

RESULTS

In a meta-analysis of results from published MR studies and de novo analyses of the FinnGen consortium, genetically predicted higher BMI was associated with increased risk of type 2 diabetes mellitus, 14 circulatory disease outcomes, asthma, chronic obstructive pulmonary disease, five digestive system diseases, three musculoskeletal system diseases, and multiple sclerosis as well as cancers of the digestive system (six cancer sites), uterus, kidney, and bladder. In contrast, genetically predicted higher adult BMI was associated with a decreased risk of Dupuytren's disease, osteoporosis, and breast, prostate, and non-melanoma cancer, and not associated with Alzheimer's disease, amyotrophic lateral sclerosis, or Parkinson's disease.

CONCLUSIONS

The totality of the evidence from MR studies supports a causal role of excess adiposity in a plurality of chronic diseases. Hence, continued efforts to reduce the prevalence of overweight and obesity are a major public health goal.

Urban-Rural Disparities in the Association Between Body Mass Index and Cognitive Impairment in Older Adults: A Cross-Sectional Study in Central China

BACKGROUND

Some studies have demonstrated an association between low and high body mass index (BMI) and an increased risk of dementia. However, only a few of these studies were performed in rural areas.

OBJECTIVE

This cross-sectional study investigated the associations between BMI and cognitive impairment among community-dwelling older adults from rural and urban areas.

METHODS

8,221 older persons enrolled in the Hubei Memory & Ageing Cohort Study (HMACS) were recruited. Sociodemographic and lifestyle data, comorbidities, physical measurements, and clinical diagnoses of cognitive impairment were analyzed. Logistic regression was performed to assess the associations of BMI categories with cognitive impairment. A series of sensitivity analyses were conducted to test whether reverse causality could influence our results.

RESULTS

Being underweight in the rural-dwelling participants increased the risk of cognitive impairment. Being overweight was a protective factor in rural-dwelling participants aged 65-69 years and 75-79 years, whereas being underweight was significantly associated with cognitive impairment (OR, 1.37; 95% CI: 1.03-1.83; p < 0.05). Sensitivity analyses support that underweight had an additive effect on the odds of cognitive impairment and was related to risk of dementia. Interaction test revealed that the differences between urban/rural in the relationship between BMI and cognitive impairment are statistically significant.

CONCLUSION

Associations between BMI and cognitive impairment differ among urban/rural groups. Older people with low BMI living in rural China are at a higher risk for dementia than those living in urban areas.

Is Obesity Associated with Lower Mini Mental Test Scores among Elderly? A Cross Sectional Study

OBJECTIVES

Obesity leads to many chronic diseases and its association with cognitive impairment is controversial. The objective was to investigate the association between obesity, anthropometric measurements and cognitive functions of elderly.

METHODS

Planned cross-sectionally, community-dwelling Cypriots (aged ≥ 50 years) without any neurological disorders, were included. Cognitive impairment evaluated by Mini Mental State Examination (MMSE) was the dependent variable. Socio-demographic variables, anthropometric measurements and obesity were the independent variables. The data was collected via face-to-face interview. Logistic regression models were constituted to determine the association of anthropometric measurements, obesity and dementia.

RESULTS

The mean age of participants (n = 541) was 60.0 ± 8.7 for women (n = 377) and 61.5 ± 6.0 years for men (n = 164). According to MMSE, 26.0% of women and 11.0% of men had mild-dementia, and the rest scored normal. After adjusted for age and sex, each unit increase in BMI (OR: 1.045, 95%CI: 1.008-1.091), Waist to height ratio (WHtR; OR: 1.030, 95%CI: 1.006-1.055) and Mid upper arm circumference (MUAC; OR: 1.077, 95%CI: 1.016-1.141) increases the risk of mild-dementia. When education, employment and smoking were included in the models, significance of anthropometric measurements was diminished and only sex and education were remained significant for all.

CONCLUSION

After controlled for age and sex, increment in anthropometric measurements increased the risk of dementia but when education was taken into consideration, this significant association was diminished showing that sex and education is more predominant in a heterogeneous group in means of education. Thus, for heterogeneous groups it might be better to revise MMSE. To determine the association between obesity and dementia cohort studies with longer follow-up duration with larger samples are needed.