Sarcopenia using muscle mass prediction model and cognitive impairment: a longitudinal analysis from the English Longitudinal Study on Ageing

BackgroundLiterature on the association between sarcopenia and cognitive impairment is largely unclear and mainly limited to non-European populations. Therefore, the aim of this study is to explore if the presence of sarcopenia at the baseline could increase the risk of cognitive impairment in a large cohort of older people participating to the English Longitudinal Study of Ageing (ELSA), over ten years of follow-up.MethodsSarcopenia was diagnosed as having low handgrip strength and low skeletal muscle mass index at the baseline, using a muscle mass prediction model; cognitive function was evaluated in the ELSA through several tests. The results are reported in the whole sample adjusted for potential baseline confounders and after matching sarcopenic and non-sarcopenic participants with a propensity score.Results2738 people (mean age: 68.7 years, 54.4% males) were included. During the ten years of follow-up, sarcopenia was associated with significantly lower scores in memory (p Conclusions and implicationsSarcopenia was found to be associated with a significantly higher incidence of poor cognitive status in a large population of elderly people followed up for 10 years, suggesting it may be an important potential risk factor for dementia.</p

Diet Variety and Nutritional Status in Anorexic Subjects^§.

<p>° Food groups considered: “milk and dairy products”, “meat, fish, and eggs”, “cereals and derivatives” “fruit and vegetables”. The dimension of portions for each food were based on Italian Recommended Daily Allowances (LARN: Livelli di Assunzione Raccomandati di Energia e Nutrienti) (23).</p>§<p>Data represented as Mean ± Standard deviation, unless otherwise stated.</p><p>Abbreviations: MMSE: Mini Mental State Examination; GDS: Geriatric Depression Scale; ADL: Activities of Daily Living; IADL: Instrumental Activities of Daily Living; BMI: Body Mass Index; MNA: Mini Nutritional Assessment; CRP: C-reactive protein.</p

Characteristics of the Study Participants^§.

§<p>Data represented as mean ± standard deviation, unless otherwise stated.</p>*<p>p<0.05 for differences between settings; differences between gender didn't reach any statistical significance.</p

Prevalence of sarcopenia in Africa: a systematic review and meta-analysis of observational studies

Background: Existing literature suggests that sarcopenia is a highly prevalent condition in older people. However, most studies to date reporting data on its prevalence have been mainly carried out in Western countries, while data on sarcopenia in Africa is scarce. With this systematic review and meta‐analysis, we aimed to determine the prevalence of sarcopenia in African countries and to explore potential factors that could explain higher or lower prevalence of this condition in Africa. Methods: Major databases for studies reporting data on sarcopenia in African countries were searched from inception to June 2023. We conducted a meta-analysis of the prevalence [and 95% confdence intervals (95% CIs)] of sarcopenia in Africa, applying a random efect model. Several sensitivity and meta-regression analyses were run.Results: Among 147 articles initially screened, six articles (with seven cohorts) including a total of 10,656 participants were included. Mean age of participants was 66.9 years, and the majority were female (58.1%). The weighted prevalence of sarcopenia in the selected countries of Africa was 25.72% (95%CI: 18.90–32.55). This outcome was characterized by a high heterogeneity (I 2=99%) and by publication bias. Among the factors investigated, sarcopenia was lower when assessed using only one anthropometric measure, or in South Africa.Conclusion: Sarcopenia is a prevalent condition in Africa and thus research regarding this topic is a public health priority. Future studies that cover African countries for which data are not available and using standardized criteria are needed.</p

Baseline Characteristics of the Sample According to the Diagnosis of Anorexia^§.

§<p>Data represented as mean ± standard deviation, unless otherwise stated; * p<0.05.</p><p>Abbreviations: A: anorexia; NES: normally eating subjects; MMSE: Mini Mental State Examination; GDS: Geriatric Depression Scale; ADL: Activities of Daily Living; IADL: Instrumental Activities of Daily Living; BMI: Body Mass Index; MNA: Mini Nutritional Assessment; TSF: triceps skinfold; AC: arm circumference; AMC: arm muscle circumference; CRP: C-reactive protein.</p

Odds ratio (OR) and 95% confidence interval (CI) for incident gestational diabetes according to frequency of fast food consumption in the SUN project (n = 3,048 pregnant women).

<p>Respective numbers (gestational diabetes incidence) for fast food intake of 0–3 times per month (low), >3 times a month and ≤2 times per week (intermediate), and >2 times per week (high) were 616 (24), 1,461 (70), 971 (65). Results represent fully adjusted model (age, baseline BMI, total energy intake, smoking, physical activity, family history of diabetes, cardiovascular disease/hypertension at baseline, parity, adherence to Mediterranean dietary pattern, fiber intake, alcohol intake, and sugar-sweetened soft drinks consumption).</p

Flow chart depicting the selection process among participants of the SUN project to be included in the present analyses.

<p>Flow chart depicting the selection process among participants of the SUN project to be included in the present analyses.</p

Characteristics of 3,048 pregnant women in the SUN cohort according to their frequency of fast food consumption.

<p>*<i>1 serving = 100 g</i>.</p><p><i>METs: metabolic equivalent tasks; CVD: cardiovascular disease; SFA: saturated fatty acid; MUFA: monounsaturated fatty acid; PUFA: polyunsaturated fatty acid</i>.</p><p>Values are means (SD) for age, BMI, physical activity, Mediterranean diet score, alcohol, fiber, and total energy intake.</p><p>Characteristics of 3,048 pregnant women in the SUN cohort according to their frequency of fast food consumption.</p

Scoring criteria for the Diabetes Dietary Score in the SUN cohort, 1999–2014.

<p>PUFA: Polyunsaturated Fatty Acids; SSB: sugar sweetened beverages</p><p>Scoring criteria for the Diabetes Dietary Score in the SUN cohort, 1999–2014.</p

OR and 95% confidence interval of incident gestational diabetes according to fast food consumption.

<p>The SUN project 1999–2012.</p><p><i>*1 serving = 100 g</i>.</p><p><i>OR: odd ratio; CI: confidence interval; Rate: crude incident gestational diabetes rate per 10,000 person-years; PCO: polycystic ovary syndrome; w/o: without</i>.</p><p><i>Model 1: adjusted for age</i>.</p><p><i>Model 2: model 1 plus adjustment for total energy intake, smoking, physical activity, family history of diabetes, cardiovascular disease/hypertension at baseline, parity, adherence to Mediterranean dietary pattern score, alcohol intake, fiber intake, and sugar-sweetened soft drinks consumption</i>.</p><p><i>Model 3: model 2 plus adjustment for baseline BMI</i>.</p><p>OR and 95% confidence interval of incident gestational diabetes according to fast food consumption.</p