Objective This study explores the gender differences in the prevalence of mild cognitive impairment (MCI) and the correlation between multiple influencing factors. Materials and methods The sample was comprised of 1325 relatively healthy participants aged ≥ 60 years in a Shanghai community-dwelling (557 males and 768 females). Cognitive function was assessed by Mini-Mental State Examination (MMSE). The Instrumental Activities of Daily Living (IADL) scale was used to assess the activities of daily living. Results The overall prevalence of MCI was 15.2%, with 10.2% in men and 18.9% in women. In older male subjects, those with higher the Geriatric Depression Scale (GDS) scores [odds ratio (OR) = 1.07, 95% confidence interval (CI) = 1.01–1.14] and hypertension (OR = 2.33, 95% CI = 1.15–4.73) had a higher risk of MCI. female subjects who were illiterate (OR = 2.95, 95% CI = 1.82–4.78), had a farming background (OR = 1.69, 95% CI = 1.05–2.72), and a history of stroke (OR = 1.96, 95% CI = 1.07–3.59) had a higher risk of MCI, but this was not true for males. However, Male subjects who never smoked were less likely to have MCI (OR = 0.22, 95% CI = 0.09–0.54). Additionally, the prevalence of MCI was lower in older women with high grip strength (OR = 0.96, 95% CI = 0.92–0.99) and hyperlipidemia (OR = 0.45, 95% CI = 0.22–0.96). Conclusion The prevalence of MCI was higher in the population of elderly women compared to men. Moreover, it was found that members with MCI tended to having higher GDS scores, smoking, and hypertension; whereas a history of farming, illiteracy, stroke, grip strength, and hyperlipidemia were correlated with MCI in women.

/pdf/gender-specific-prevalence-and-risk-factors-of-mild-2ppygtas.pdf

Gender-specific prevalence and risk factors of mild cognitive impairment among older adults in Chongming, Shanghai, China

In the last decades, it has been proposed that executive functions may be particularly vulnerable to weight-related issues. However, evidence on the matter is mixed, especially when the effects of sociodemographic variables are weighted. Thus, the current study aimed at further examining the relationship between executive functions and obesity. To this aim, we compared treatment-seeking overweight, obese, and morbidly obese patients with normal-weight control participants. We examined general executive functioning (Frontal Assessment Battery–15) and different executive subdomains (e.g., inhibitory control, verbal fluency, and psychomotor speed) in a clinical sample including 208 outpatients with different degrees of BMI (52 overweight, BMI 25–30, M age = 34.38; 76 obese, BMI 30–40, M age = 38.00; 80 morbidly obese, BMI > 40, M age = 36.20). Ninety-six normal-weight subjects served as controls. No difference on executive scores was detected when obese patients were compared with over- or normal-weight subjects. Morbidly obese patients reported lower performance on executive scores than obese, overweight, and normal-weight subjects. Between-group difference emerged also when relevant covariates were taken into account. Our results support the view that morbid obesity is associated with lower executive performance, also considering the critical role exerted by sociodemographic (i.e., sex, age, and education) variables. Our results support the view that executive functioning should be accounted into the management of the obese patient because of non-negligible clinical relevance in diagnostic, therapeutic, and prognostic terms.

/pdf/functional-relationship-between-inhibitory-control-cognitive-1fxts5o7.pdf

Functional Relationship between Inhibitory Control, Cognitive Flexibility, Psychomotor Speed and Obesity

Background: Recent evidence suggests that a higher body weight may be linked to cognitive impairment in different domains involving executive/frontal functioning. However, challenging results are also available. Accordingly, our study was designed to verify whether (i) poor executive functions are related to a higher body weight and (ii) executive functioning could contribute to weight loss in treatment-seeking overweight and obese patients. Methods: We examined general executive functioning, inhibitory control, verbal fluency, and psychomotor speed in a sample including 104 overweight and obese patients. Forty-eight normal-weight subjects participated in the study as controls. Results: Univariate Analysis of Variance showed that obese patients obtained lower scores than overweight and normal-weight subjects in all executive measures, except for errors in the Stroop test. However, when sociodemographic variables entered the model as covariates, no between-group difference was detected. Furthermore, an adjusted multiple linear regression model highlighted no relationship between weight loss and executive scores at baseline. Conclusions: Our results provide further evidence for the lack of association between obesity and the executive domains investigated. Conflicting findings from previous literature may likely be due to the unchecked confounding effects exerted by sociodemographic variables and inclusion/exclusion criteria.

/pdf/executive-functions-in-overweight-and-obese-treatment-2ngqnsse.pdf

Executive Functions in Overweight and Obese Treatment-Seeking Patients: Cross-Sectional Data and Longitudinal Perspectives

Objective This study aims to investigate the prevalence and risk factors of falls among the elderly in Guangdong, China. Methods A cross-sectional study was conducted in six communities of Guangdong province. People over 60 years old were selected with multistage random-cluster sampling. Data on falls within the previous 12 months and fall-related risk factors were collected through a face-to-face interview. Results The prevalence of falls among older adults was 11.9% (95% CI: 11.0% to 12.8%) among 5374 interviewees. The common injuries caused by falls were bruises/scrapes (40.0%) and fractures (15.5%), and most people fall while doing housework (35.0%). Univariate analysis showed that 14 factors were associated with falls among older adults, including gender, age, residence, occupation, education level, balance ability, situation of cognition, disease, depression, living arrangement, marital status, the behaviour of exercise, drinking and drug use (p<0.05). Multivariate analysis showed that the associated factors of falls among older adults included woman (OR=1.68, 95% CI: 1.40 to 2.02), age from 70 to 79 years (OR=1.31, 95% CI: 1.09 to 1.58), age over 80 (OR=1.63, 95% CI: 1.25 to 2.13), impaired balance ability (OR=1.45, 95% CI: 1.20 to 1.75), exercise several times per month (OR=1.69, 95% CI: 1.13 to 2.53), polypharmacy (OR=1.54, 95% CI: 1.19 to 2.00), cognition impairment (OR=1.35, 95% CI: 1.08 to 1.69), mild depression (OR=1.89, 95% CI: 1.47 to 2.45) and moderate depression (OR=3.07, 95% CI: 1.99 to 4.73). Conclusions The hazards caused by falls to the elderly in China cannot be ignored. A multidimensional customised fall prevention programme should be considered to reduce the risk of falls among the elderly based on the results above.

/pdf/cross-sectional-study-on-prevalence-and-risk-factors-for-15dq4r4r.pdf

Cross-sectional study on prevalence and risk factors for falls among the elderly in communities of Guangdong province, China

Obesity and sarcopenic obesity (SO) are characterized by excess body fat with or without low muscle mass affecting bio‐psycho‐social health, functioning, and subsequently quality of life in older adults. We mapped outcomes addressed in randomized controlled trials (RCTs) on lifestyle interventions in community‐dwelling older people with (sarcopenic) obesity. Systematic searches in Medline, Embase, Cochrane Central, CINAHL, PsycInfo, Web of Science were conducted. Two reviewers independently performed screening and extracted data on outcomes, outcome domains, assessment methods, units, and measurement time. A bubble chart and heat maps were generated to visually display results. Fifty‐four RCTs (7 in SO) reporting 464 outcomes in the outcome domains: physical function (n = 42), body composition/anthropometry (n = 120), biomarkers (n = 190), physiological (n = 30), psychological (n = 47), quality of life (n = 14), pain (n = 4), sleep (n = 2), medications (n = 3), and risk of adverse health events (n = 5) were included. Heterogeneity in terms of outcome definition, assessment methods, measurement units, and measurement times was found. Psychological and quality of life domains were investigated in a minority of studies. There is almost no information beyond 52 weeks. This evidence map is the first step of a harmonization process to improve comparability of RCTs in older people with (sarcopenic) obesity and facilitate the derivation of evidence‐based clinical decisions.

/pdf/outcomes-addressed-in-randomized-controlled-lifestyle-8ogs0x33.pdf

Outcomes addressed in randomized controlled lifestyle intervention trials in community‐dwelling older people with (sarcopenic) obesity—An evidence map

Background Studies relating obesity to cognition in older people show conflicting results, which may be explained by the choice of obesity indicators. Objectives This study aimed to investigate the relationship between obesity-related indicators and cognitive impairment, especially between different age or gender subgroups, and explore whether obesity-related indicators were related to specific cognitive domains. Methods This was a cross-sectional study on 1753 participants aged ≥ 60 years (41.0% men; aged 71.36 ± 5.96 years). Obesity-related indicators included body mass index (BMI), waist circumference (WC), calf circumference (CC), waist to hip ratio (WHR), waist to calf circumstance ratio (WCR), fat to fat-free mass ratio (FM/FFM). The Mini-Mental State Examination scale (MMSE) was used to assess cognitive function. Cognitive impairment was defined as a score ≤ 17 for illiterates, ≤ 20 for participants with primary school education, and ≤ 24 for those with junior high school degrees or above. Multiple logistic regression analysis was used to estimate multivariable-adjusted odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic splines were used to analyze and visualize the linear relationships. Results The prevalence of cognitive impairment was 18.77%. In the fully adjusted model, CC was negatively associated with cognitive impairment (OR = 0.94, 95% CI: 0.90−0.98). Further analysis showed that CC correlated positively with recall and place orientation. A higher FM/FFM was found to be associated with a higher prevalence of cognitive impairment (OR: 1.44, 95%CI: 0.88–2.35, P for trend = 0.029); this association was notable in women (P for trend = 0.002) and the oldest (P for trend = 0.009), and so did the potential effect of BMI on cognitive impairment (70–80 years: P for trend = 0.011; ≥ 80 years: P for trend = 0.013). No statistically significant association was found between cognitive impairment and WC, WHR, or WCR. Conclusion CC and FM/FFM were associated with cognitive impairment in older people. Future research needs to distinguish the effects of fat and muscle mass on cognitive function, with special attention to different ages and genders.

/pdf/relationship-between-obesity-related-anthropometric-3m7eqqek0f.pdf

Relationship between obesity-related anthropometric indicators and cognitive function in Chinese suburb-dwelling older adults.

Objective We examined the association between obesity and physical performance under different metabolic status. Methods The sample included 1395 Chinese community-dwelling participants (mean age, 71.88 ± 5.87 years; 40.9% men). Being metabolically healthy was defined as having the presence of 28 kg/m2. Participants were divided into four groups based on BMI (non-obese/obese) and metabolic health (healthy/unhealthy). Physical performance was measured by grip strength, 4-m walking speed, and the timed up and go test (TUGT). Results After multiple adjustments, compared with metabolically healthy non-obese group, the metabolically unhealthy obese group showed lower relative grip strength, lower 4-m walking speed, and higher TUGT (P all < 0.05), and only relative grip strength of the metabolically healthy obese group was significantly lower than that of metabolically healthy non-obese (P < 0.01). Relative grip strength was negatively associated with impaired fasting glucose (β = -0.071), elevated triglycerides (β = -0.062), abdominal obesity (β = -0.230) and general obesity (β = -0.225) (P all < 0.01). Walking speed and TUGT were only associated with general obesity, rather than other metabolic components. The associations of MetS with physical performance were mainly driven by abdominal obesity. Conclusion Even in those who are metabolically healthy, obesity (especially general obesity) increases the risk of poor physical performance. Elderly people with general obesity and MetS, whether in combination or alone, have an increased risk of muscle dysfunction, and that combination produces a higher risk of impaired mobility.

/pdf/obesity-even-in-the-metabolically-healthy-increases-the-risk-yr74gmvcsd.pdf

Obesity, Even in the Metabolically Healthy, Increases the Risk of Poor Physical Performance: A Cross-Sectional Study of Older People in a Chinese Community.

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Relationship between obesity-related anthropometric indicators and cognitive function in Chinese suburb-dwelling older adults.

Obesity, Even in the Metabolically Healthy, Increases the Risk of Poor Physical Performance: A Cross-Sectional Study of Older People in a Chinese Community.