Explore the vast range of titles available.

Background Since the placenta also has a sex, fetal sex–specific differences in the occurrence of placenta-mediated complications could exist. Objective To determine the association of fetal sex with multiple maternal pregnancy complications. Search strategy Six electronic databases Ovid MEDLINE, EMBASE, Cochrane Central, Web-of-Science, PubMed, and Google Scholar were systematically searched to identify eligible studies. Reference lists of the included studies and contact with experts were also used for identification of studies. Selection criteria Observational studies that assessed fetal sex and the presence of maternal pregnancy complications within singleton pregnancies. Data collection and analyses Data were extracted by 2 independent reviewers using a predesigned data collection form. Main results From 6522 original references, 74 studies were selected, including over 12,5 million women. Male fetal sex was associated with term pre-eclampsia (pooled OR 1.07 [95%CI 1.06 to 1.09]) and gestational diabetes (pooled OR 1.04 [1.02 to 1.07]). All other pregnancy complications (i.e., gestational hypertension, total pre-eclampsia, eclampsia, placental abruption, and post-partum hemorrhage) tended to be associated with male fetal sex, except for preterm pre-eclampsia, which was more associated with female fetal sex. Overall quality of the included studies was good. Between-study heterogeneity was high due to differences in study population and outcome definition. Conclusion This meta-analysis suggests that the occurrence of pregnancy complications differ according to fetal sex with a higher cardiovascular and metabolic load for the mother in the presence of a male fetus. Funding None.

Sufficient protein intake has been suggested to be important for preventing physical frailty, but studies show conflicting results which may be explained because not all studies address protein source and intake of other macronutrients and total energy. Therefore, we studied 2504 subjects with data on diet and physical frailty, participating in a large population-based prospective cohort among subjects aged 45+ years (the Rotterdam Study). Dietary intake was assessed with a FFQ. Frailty was defined according to the frailty phenotype as the presence of at least three out of the following five symptoms: weight loss, low physical activity, weakness, slowness and fatigue. We used multinomial logistic regression models to evaluate the independent association between protein intake and frailty using two methods: nutrient residual models and energy decomposition models. With every increase in 10 g total, plant or animal protein per d, the odds to be frail were 1·06 (95 % CI 0·98, 1·15), 0·87 (95 % CI 0·71, 1·07) and 1·07 (95 % CI 0·99, 1·15), respectively, using the nutrient residual method. Using the energy partition model, we observed that the odds to be frail were lower with higher vegetable protein intake (OR per 418·4 kJ (100 kcal): 0·61, 95 % CI 0·39, 0·97), however, results disappeared when adjusting for physical activity. For energy intake from any source we observed that with every 418·4 kJ (100 kcal) increase, the odds to be frail were 5 % lower (OR: 0·95, 95 % CI 0·93, 0·97). Our results suggest that energy intake, but not protein specifically, is associated with less frailty. Considering other macronutrients, physical activity and diet quality seems to be essential for future studies on protein and frailty.

Background Sarcopenic obesity (SO) is a clinical condition defined by the coexistence of high body fat mass and low muscle function and mass, which increases the risk of adverse health outcomes, including disability and mortality. Early detection and frequent monitoring of SO are essential for preventive interventions and management strategies. The current binary approach for SO diagnosis is limited in capturing the spectrum of SO or its progression over time. The main objective of this study was to develop a continuous SOPi that integrates diagnostic criteria such as muscle function and body composition. We aimed to evaluate the association between SOPi and all‐cause mortality, to identify baseline‐related factors with SOPi and to assess changes in the SOPi over time. Methods Participants from the Rotterdam Study with baseline and follow‐up measures of handgrip strength (HGS), dual‐energy X‐ray absorptiometry‐measured appendicular lean mass index (ALM/kg) and body fat percentage (BF%) were included. SOPi was calculated as a sex‐specific equation integrating z‐scores (Z) of (BF%)—(HGS)—(ALM/kg). Cox regression and multivariable linear regression models were fitted to evaluate mortality risk and associated factors with SOPi, respectively. Subgroup analysis of SOPi changes was performed by linear mixed‐effects models. Results In the total population (n = 5888, age 69.5 ± 9.1 years, BMI 27.5 ± 4.3 kg/m2, 56.8% females) and over the 9.9‐year median follow‐up period, 1538 (26.1%) participants died. Each standard deviation (SD) increase in sex‐specific SOPi was associated with a 10% higher risk of premature death (HR = 1.10 [95%CI: 1.07; 1.13]). Thirteen factors were associated with high SOPi, such as reduced physical activity, higher triglyceride‐glucose index, HOMA‐IR, systemic inflammation, osteopenia, hypertension, liver steatosis, asthma, coronary heart disease, oral corticosteroid use, lower protein intake, lower quality of life and lower educational status. In participants with obesity, lower physical activity and/or insulin resistance (n = 1682), a significantly higher and faster increase in SOPi was observed compared to participants without these factors (males: β = 2.63 [95%CI: 2.22; 3.03]; females: β = 2.90 [95%CI: 2.58; 3.23]). Conclusion SOPi is a significant predictor of premature death and can identify associated factors, particularly useful among persons at risk of SO. SOPi is higher and increases faster in individuals with specific phenotypes. SOPi integrates prognosis information, which could be used as a risk indicator and for prevention of SO.

Background This study qualitatively investigates retirement-age adults' perspectives on engaging in health behaviors such as physical activity or a healthy diet, distinguishing facilitators, barriers, goals, and motivations (the two later in line with Self-Determination Theory). Methods Two clinical psychologists conducted four focus groups with Spanish adults around retirement age. We conducted inductive and deductive content analysis. Results The main facilitators and barriers identified were the presence and absence of social support/social network, mental health, willpower, time, and motivation. Participants reported different types of motivation (e.g., intrinsic motivation in the enjoyment of the activity of exercise or cooking) and goals (intrinsic and extrinsic); except for the goal of health management, which presented both types of motivation, participants regulated intrinsic goals autonomously, and extrinsic ones with controlled motivation. A process of internalizing the source of motivation was identified inductively by participants. Conclusions Facilitating social networks and addressing mental health issues could aid engagement in health behaviors among this population. Additionally, health management appeared as a significant goal, where autonomous motivation can develop even if the behavior initially arises from controlled motivation or external triggers, such as medical advice.

Purpose Several studies have reported seasonal variation in intake of food groups and certain nutrients. However, whether this could lead to a seasonal pattern of diet quality has not been addressed. We aimed to describe the seasonality of diet quality, and to examine the contribution of the food groups included in the dietary guidelines to this seasonality. Methods Among 9701 middle-aged and elderly participants of the Rotterdam Study, a prospective population-based cohort, diet was assessed using food-frequency questionnaires (FFQ). Diet quality was measured as adherence to the Dutch dietary guidelines, and expressed in a diet quality score ranging from 0 to 14 points. The seasonality of diet quality and of the food group intake was examined using cosinor linear mixed models. Models were adjusted for sex, age, cohort, energy intake, physical activity, body mass index, comorbidities, and education. Results Diet quality had a seasonal pattern with a winter-peak (seasonal variation = 0.10 points, December-peak) especially among participants who were men, obese and of high socio-economic level. This pattern was mostly explained by the seasonal variation in the intake of legumes (seasonal variation = 3.52 g/day, December-peak), nuts (seasonal variation = 0.78 g/day, January-peak), sugar-containing beverages (seasonal variation = 12.96 milliliters/day, June-peak), and dairy (seasonal variation = 17.52 g/day, June-peak). Conclusions Diet quality varies seasonally with heterogeneous seasonality of food groups counteractively contributing to the seasonal pattern in diet quality. This seasonality should be considered in future research on dietary behavior. Also, season-specific recommendations and policies are required to improve diet quality throughout the year.

Increasing awareness of the impact of frailty on elderly people resulted in research focusing on factors that contribute to the development and persistence of frailty including nutrition and physical activity. Most effort so far has been spent on understanding the association between protein intake and the physical domain of frailty. Far less is known for other domains of frailty: cognition, mood, social health and comorbidity. Therefore, in the present narrative review, we elaborate on the evidence currently known on the association between protein and exercise as well as the broader concept of frailty. Most, but not all, identified studies concluded that low protein intake is associated with a higher prevalence and incidence of physical frailty. Far less is known on the broader concept of frailty. The few studies that do look into this association find a clear beneficial effect of physical activity but no conclusions regarding protein intake can be made yet. Similar, for other important aspects of frailty including mood, cognition, and comorbidity, the number of studies are limited and results are inconclusive. Future studies need to focus on the relation between dietary protein and the broader concept of frailty and should also consider the protein source, amount and timing.

There are discrepancies in the seasonality of insulin resistance (IR) across the literature, probably due to age-related differences in the seasonality of lifestyle factors and thermoregulation mechanisms. To estimate the seasonality of IR according to the homeostatic model assessment-IR (HOMA-IR), glucose, and insulin levels and to examine the role of lifestyle markers [body mass index (BMI) and physical activity] and meteorological factors, according to age. Seasonality was examined using cosinor analysis among middle-aged (45 to 65 years) and elderly (≥65 years) participants of a population-based Dutch cohort. We analyzed 13,622 observations from 8979 participants (57.6% women) without diagnosis of diabetes and fasting glucose <7 mmol/L. BMI was measured, physical activity was evaluated using a validated questionnaire, and meteorological factors (daily mean ambient temperature, mean relative humidity, total sunlight hours, and total precipitation) were obtained from local records. Seasonality estimates were adjusted for confounders. Among the middle-aged participants, seasonal variation estimates were: 0.11 units (95% confidence interval: 0.03, 0.20) for HOMA-IR, 0.28 µIU/mL (-0.05, 0.69) for insulin, and 0.05 mmol/L (0.01, 0.09) for glucose. These had a summer peak, and lifestyle markers explained the pattern. Among the elderly, seasonal variations were: 0.29 units (0.21, 0.37) for HOMA-IR, 0.96 µIU/mL (0.58, 1.28) for insulin, and 0.01 mmol/L (-0.01, 0.05) for glucose. These had a winter peak and ambient temperature explained the pattern. Impaired thermoregulation mechanisms could explain the winter peak of IR among elderly people without diabetes. The seasonality of lifestyle factors may explain the seasonality of glucose.

Purpose To investigate the longitudinal association between the macronutrient composition of the diet and frailty. Methods Data were obtained from 5205 Dutch middle-aged and older adults participating in the Rotterdam Study. Frailty was measured using a frailty index based on the accumulation of 38 health-related deficits, score between 0 and 100, and a higher score indicating more frailty. Frailty was assessed at baseline and 11 years later (range of 23 years). Macronutrient intake was assessed using food-frequency questionnaires. The association between macronutrients and frailty over time was evaluated using multivariable linear regression, adjusted for the frailty index at baseline, energy intake, and other relevant confounders. All analyses were performed in strata of BMI. Results Median frailty index score was 13.8 points (IQR 9.6; 19.1) at baseline and increased by a median of 2.3 points (IQR − 2.0; 7.6) after 11 years. Overall, we found no significant associations between intake of carbohydrates or fat and frailty over time. We did observe a significant positive association between an iso-energetic intake of 10 g protein and frailty over time ( β 0.31 (95% CI 0.06; 0.55)) which was mainly driven by animal protein ( β 0.31 (95% CI 0.07; 0.56)). It did not depend on whether it was substituted fat or carbohydrates. Conclusions Our findings suggest that a reduction in the intake of animal protein may improve the overall health status over time in a relatively healthy population. More research is needed on the optimal macronutrient composition of the diet and frailty in more vulnerable populations.

PurposeTo determine the associations between a priori and a posteriori derived dietary patterns and a general state of health, measured as the accumulation of deficits in a frailty index.MethodsCross-sectional and longitudinal analysis embedded in the population-based Rotterdam Study (n = 2632) aged 45 years. Diet was assessed at baseline (year 2006) using food frequency questionnaires. Dietary patterns were defined a priori using an existing index reflecting adherence to national dietary guidelines and a posteriori using principal component analysis. A frailty index was composed of 38 health deficits and measured at baseline and follow-up (4 years later). Linear regression analyses were performed using adherence to each of the dietary patterns as exposure and the frailty index as outcome (all in Z-scores).ResultsAdherence to the national dietary guidelines was associated with lower frailty at baseline (β −0.05, 95% CI −0.08, −0.02). Additionally, high adherence was associated with lower frailty scores over time (β −0.08, 95% CI −0.12, −0.04). The PCA revealed three dietary patterns that we named a “Traditional” pattern, high in legumes, eggs and savory snacks; a “Carnivore” pattern, high in meat and poultry; and a “Health Conscious” pattern, high in whole grain products, vegetables and fruit. In the cross-sectional analyses adherence to these patterns was not associated with frailty. However, adherence to the “Traditional” pattern was associated with less frailty over time (β −0.09, 95% CI −0.14, −0.05).ConclusionNo associations were found for adherence to a “healthy” pattern or “Carnivore” pattern. However, Even in a population that is relatively young and healthy, adherence to dietary guidelines or adherence to the Traditional pattern could help to prevent, delay or reverse frailty levels.

Although there is some evidence that total dietary antioxidant capacity (TDAC) is inversely associated with the presence of obesity, no longitudinal studies have been performed investigating the effect of TDAC on comprehensive measures of body composition over time. In this study, we included 4595 middle-aged and elderly participants from the Rotterdam Study, a population-based cohort. We estimated TDAC among these individuals by calculating a ferric reducing ability of plasma (FRAP) score based on data from food-frequency questionnaires. Body composition was assessed by means of dual X-ray absorptiometry at baseline and every subsequent 3–5 years. From these data, we calculated fat mass index (FMI), fat-free mass index (FFMI), android-to-gynoid fat ratio (AGR), body fat percentage (BF%) and body mass index (BMI). We also assessed hand grip strength at two time points and prevalence of sarcopenia at one time point in a subset of participants. Data were analyzed using linear mixed models or multinomial logistic regression models with multivariable adjustment. We found that higher FRAP score was associated with higher FFMI (0.091 kg/m2 per standard deviation (SD) higher FRAP score, 95% CI 0.031; 0.150), lower AGR (−0.028, 95% CI −0.053; −0.003), higher BMI (0.115, 95% CI 0.020; 0.209) and lower BF% (−0.223, 95% CI −0.383; −0.064) across follow-up after multivariable adjustment. FRAP score was not associated with hand grip strength or sarcopenia. Additional adjustment for adherence to dietary guidelines and exclusion of individuals with comorbid disease at baseline did not change our results. In conclusion, dietary intake of antioxidants may positively affect the amount of lean mass and overall body composition among the middle-aged and elderly.