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Background The increased adoption of the internet, social media, wearable devices, e-health services, and other technology-driven services in medicine and healthcare has led to the rapid generation of various types of digital data, providing a valuable data source beyond the confines of traditional clinical trials, epidemiological studies, and lab-based experiments. Methods We provide a brief overview on the type and sources of real-world data and the common models and approaches to utilize and analyze real-world data. We discuss the challenges and opportunities of using real-world data for evidence-based decision making This review does not aim to be comprehensive or cover all aspects of the intriguing topic on RWD (from both the research and practical perspectives) but serves as a primer and provides useful sources for readers who interested in this topic. Results and Conclusions Real-world hold great potential for generating real-world evidence for designing and conducting confirmatory trials and answering questions that may not be addressed otherwise. The voluminosity and complexity of real-world data also call for development of more appropriate, sophisticated, and innovative data processing and analysis techniques while maintaining scientific rigor in research findings, and attentions to data ethics to harness the power of real-world data.

Despite substantial advancements and extensive funding in obesity research—spanning the development of novel pharmacological and non-pharmacological treatments, as well as numerous public health initiatives—the global prevalence of obesity continues to escalate at an alarming rate [...]

Background Missing data is a common problem in epidemiological studies , while it becomes more critical, when the missing data concern a multi-item instrument, since lack of information in even one of its items, leads to the inability to calculate the total score of the instrument. The aim was to investigate the socio-demographic, lifestyle and clinical determinants of low response rate in two self- rating multi item scales, estimating the individuals’ nutritional habits and psychological disorders, as well as, to compare different missing data handling techniques regarding the imputation of missing values in this context. Methods The sample from ATTICA epidemiological study was used, with complete baseline information (2001–2002) regarding their demographic characteristics [ n  = 2194 subjects (1364 men: 64 years old (SD = 12 years) and 830 women: 66 years old (SD = 12 years))]. Adherence to the Mediterranean diet and depressive symptomatology were assessed at baseline, with the MedDietScore scale and the Zung’s Self- rating Depression Scale (SDS), respectively. Logistic and Poisson regression analysis were used, in order to explore the low response’s determinants in each scale. Seven missing data handling techniques were compared in terms of the estimated regression coefficients and their standard errors, under different scenarios of missingness, in the context of a multivariable logistic regression model examining the association of each scale with the participants’ likelihood of being hypertensive. Results Older age, lower educational level, poorer health status and unhealthy lifestyle habits, were found to be significant determinants of high nonresponse rates, both in the MedDietScore scale and the Zung’s SDS. Female participants were more likely to have missing data in the items of the MedDietScore scale, while a significantly higher number of missing items in the depression scale was found for male participants. Concerning the analysis of such data, multiple imputation was found to be the most effective technique, even when the number of missing items was large. Conclusions The present work augments prior evidence that higher non-response to health surveys is significantly affected by responders’ background characteristics, while it gives rise to research towards unrevealed paths behind this claim, especially in the era of nutritional epidemiology.

Rheumatoid arthritis (RA) is a chronic, autoimmune inflammatory disease of multiple joints that puts the patient at high risk for developing cardiovascular diseases (CVDs). The aim of the present study was to conduct an up-to-date systematic review and meta-analysis of published randomized controlled trials (RCTs) to assess potential changes in RA disease activity, inflammation, and CVD risk after oral intake of ω-3 polyunsaturated fatty acids. Publications up to July 31, 2016 were examined using the PubMed, SCOPUS, and EMBASE databases. Inclusion criteria: English language; human subjects; both sexes; RCTs; oral intake of ω-3 fatty acids; minimum duration of 3 mo; and no medication change throughout intervention. The Cochrane Risk of Bias tool was used to assess quality of trials. We included 20 RCTs, involving 717 patients with RA in the intervention group and 535 RA patients in the control group. Despite the evidence of overall low quality of trials, consumption of ω-3 fatty acids was found to significantly improve eight disease-activity–related markers. Regarding inflammation, only leukotriene B4 was reduced (five trials, standardized mean difference [SMD], –0.440; 95% confidence interval [CI], −0.676 to −0.205; I2 = 46.5%; P < 0.001). A significant amelioration was found for blood triacylglycerol levels (three trials, SMD, −0.316; 95% CI, −0.561 to −0.070; I2 = 0.0%; P = 0.012). The beneficial properties of ω-3 polyunsaturated fatty acids on RA disease activity confirm the results of previous meta-analyses. Among five proinflammatory markers evaluated, only leukotriene B4 was found to be reduced. However, a positive effect on blood lipid profile of patients with RA was evident, perhaps for the first time. •Rheumatoid arthritis (RA) is a chronic, autoimmune inflammatory disease that puts the patient at high risk for developing cardiovascular diseases.•Oral intake of ω-3 polyunsaturated fatty acids played a role in RA in some clinical trials.•In this meta-analysis of 20 randomized controlled trials, disease activity–related markers and leukotriene B4 were reduced with oral intake of ω-3 fatty acids.•An additional positive effect on blood lipid profile of patients with RA was evident for the first time.

Research of Efficacy and Safety Outcomes.1 Two concurrent phase 3 clinical trials (studies 004 and 006) investigated the role of pirfenidone in patients with mild to-moderate idiopathic pulmonary fibrosis (ie, forced vital capacity [FVC] ≥50% predicted, and diffusing capacity of the lung for carbon monoxide ≥35% predicted).

Background Research has suggested the positive impact of physical activity on health and wellbeing in older age, yet few studies have investigated the associations between physical activity and heterogeneous trajectories of healthy ageing. We aimed to identify how physical activity can influence healthy ageing trajectories using a harmonised dataset of eight ageing cohorts across the world. Methods Based on a harmonised dataset of eight ageing cohorts in Australia, USA, Mexico, Japan, South Korea, and Europe, comprising 130,521 older adults ( M age  = 62.81, SD age  = 10.06) followed-up up to 10 years ( M follow-up  = 5.47, SD follow-up  = 3.22) , we employed growth mixture modelling to identify latent classes of people with different trajectories of healthy ageing scores, which incorporated 41 items of health and functioning. Multinomial logistic regression modelling was used to investigate the associations between physical activity and different types of trajectories adjusting for sociodemographic characteristics and other lifestyle behaviours. Results Three latent classes of healthy ageing trajectories were identified: two with stable trajectories with high (71.4%) or low (25.2%) starting points and one with a high starting point but a fast decline over time (3.4%). Engagement in any level of physical activity was associated with decreased odds of being in the low stable (OR: 0.18; 95% CI: 0.17, 0.19) and fast decline trajectories groups (OR: 0.44; 95% CI: 0.39, 0.50) compared to the high stable trajectory group. These results were replicated with alternative physical activity operationalisations, as well as in sensitivity analyses using reduced samples. Conclusions Our findings suggest a positive impact of physical activity on healthy ageing, attenuating declines in health and functioning. Physical activity promotion should be a key focus of healthy ageing policies to prevent disability and fast deterioration in health.

For years, the CVD risk associated with obesity had been attributed to the high positive correlation between obesity and several metabolic risk factors, like blood pressure, triglycerides, low-density lipoprotein cholesterol (LDL-C), glucose and insulin levels. Current guidelines from various organisations strongly recommend health professionals and practitioners to offer overweight or obese adults who are at risk of CVD appropriate support for achieving and maintaining a healthy body weight, that is, a BMI between 20 and 25 kg/m2, and reducing waist circumference to <94 cm for men and <80 cm for women, for the management of abdominal obesity.8–12 The 2016 European Society of Cardiology/European Atherosclerosis Society guidelines, in specific, underline the crucial role of weight management on CVD prevention: in the recommendation for nutrition (Class/level of recommendation 1B), attaining a healthy ΒΜΙ between 20 and 25 kg/m2 is strongly promoted, whereas energy intake should be limited accordingly to achieve this goal.12 For most overweight or obese individuals, a healthy body weight is not a feasible goal. The review and meta-analysis of Zomer et al, demonstrated that weight loss contributes significantly to the improvement of CVD risk factors at least for the first 2 years following intervention and that these effects are seen after the achievement of both moderate and mild weight losses (5%–10% and <5% of initial body weight respectively).13 On the other hand, several studies, although recognising the beneficial, clinically relevant effects of moderate weight losses of 5%–10% of initial weight on most CVD risk factors, conclude that greater weight losses result in greater improvements in almost all risk factors and lower the incidence of CVD.14–16 The 2013 American College of Cardiology (ACC)/American Heart Association (AHA) and The Obesity Society Guideline for the Management of Overweight and Obesity in Adults propose a two-level approach: lifestyle changes resulting to modest, sustained weight loss of 3%–5% produce clinically meaningful health benefits, mainly reduction in triglycerides, blood glucose, haemoglobin A1c and the risk of developing type 2 diabetes, whereas greater weight losses produce greater benefits, that is, additional changes in blood pressure, LDL-C and high-density lipoprotein cholesterol (HDL-C).17 The most recent ACC/AHA Guidelines (2019) on the Primary Prevention of Cardiovascular Disease highlight evidence supporting that weight loss ≥5% of initial body weight is associated with moderate improvement in blood pressure, LDL-C, triglycerides and glucose blood concentrations.18 Table 1 provides a summary of the expected benefits in several CVD risk factors resulting from mild, moderate or greater weight losses. Table 1 Summary of the expected benefits resulting from mild, moderate or greater weight losses Weight loss Expected effects Mild (2.5%–5.0%) Systolic blood pressure LDL-C Triglyceride Blood glucose Haemoglobin A1c Moderate (5.0%–10.0%) Systolic blood pressure Diastolic blood pressure Total cholesterol LDL-C HDL-C Triglycerides Blood glucose Haemoglobin A1c Greater (>10.0%) Additional benefits in hepatic inflammation, hepatocellular injury and fibrosis HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol.