Lifestyle and dietary factors, iron status and one-carbon metabolism polymorphisms in a sample of Italian women and men attending a Transfusion Medicine Unit: a cross-sectional study

Iron (Fe) status among healthy male and female blood donors, aged 18–65 years, is estimated. General characteristics and lifestyle factors, dietary habits and major one-carbon metabolism-related polymorphisms were also investigated. An explorative cross-sectional study design was used to examine a sample of blood donors attending the Transfusion Medicine Unit of the Verona University Hospital, Italy. From April 2016 to May 2018, 499 subjects were enrolled (255 men, 244 women, 155 of whom of childbearing age). Major clinical characteristics including lifestyle, dietary habits and Fe status were analysed. The MTHFR 677C > T, cSHMT 1420C > T, DHFR 19bp ins/del and RFC1 80G > A polymorphisms were also assayed. Mean plasma concentrations of Fe and ferritin were 16·6 µmol/l (95 % CI 16·0, 17·2) and 33·8 µg/l (95 % CI 31·5, 36·2), respectively. Adequate plasma Fe concentrations (> 10·74 µmol/l) were detected in 84·3 % and adequate ferritin concentrations (20–200 µg/l) was found in 72·5 % of the whole cohort. Among the folate-related polymorphisms analysed, carriers of the DHFR 19bp del/del mutant allele showed lower ferritin concentration when compared with DHFR 19bp ins/del genotypes. In a sample of Italian healthy blood donors, adequate plasma concentrations of Fe and ferritin were reached in a large proportion of subjects. The relationship of Fe status with lifestyle factors and folate-related polymorphisms requires more investigation to clarify further gene–nutrient interactions between folate and Fe metabolism

Neighbourhood socioeconomic deprivation and allostatic load : a multi-cohort study

Living in deprived neighbourhoods may have biological consequences, but few studies have assessed this empirically. We examined the association between neighbourhood deprivation and allostatic load, a biological marker of wear and tear, taking into account individual's socioeconomic position. We analysed data from three cohort studies (CoLaus-Switzerland; EPIPorto-Portugal; Whitehall II-UK) comprising 16,364 participants. We defined allostatic load using ten biomarkers of dysregulated metabolic, cardiovascular, and inflammatory systems (body mass index; waist circumference; total, high and low density lipoprotein cholesterol; trig lycerides; glucose; systolic and diastolic blood pressure; C-reactive protein). Mixed Poisson regression models were fitted to examine associations with neighbourhood deprivation (in quintiles, Q1-least deprived as reference). After adjustment for confounding variables, participants living in the most deprived quintile had 1.13 times higher allostatic load than those living in the least deprived quintile (Relative Risk, RR, for Q2 RR = 1.06, 95%CI 1.03-1.09; Q3 = 1.06, 1.03-1.10; Q4 = 1.09, 1.06-1.12; Q5 = 1.13, 1.09-1.16). This association was partially modified by individual's socioeconomic position, such that the relative risk was higher in participants with low socioeconomic position (Q5 vs Q11.16, 1.11-1.22) than those with high socioeconomic position (Q5 vs Q1 1.07, 1.11-1.13). Neighbourhood deprivation is associated with biological wear and tear, suggesting that neighbourhood-level interventions may yield health gains.Peer reviewe

The association between pesticide use and cutaneous melanoma: a systematic review and meta-analysis

Background: The incidence of cutaneous melanoma (CM), the deadliest form of skin cancer, has gradually increased in the last decades among populations of European origin. Epidemiological studies suggested that farmers and agricultural workers are at an increased risk of CM because they were exposed to pesticides. However, little is known about the relationship between pesticides and CM. Objectives: To investigate the association between exposure to pesticides and CM by systematically reviewing the literature. Secondary aim was to determine the categories of pesticides mainly involved in CM development. Methods: A systematic review of the literature was performed up to September 2018 using MEDLINE, Embase and Web of Science. Studies assessing CM risk in licensed pesticide applicators were considered. Strict criteria were established to select independent studies and risk estimates; random effect models, taking into account heterogeneity, were applied. A pooled risk estimate for CM was calculated for the use of each type of pesticide and type of exposure. Between-study and estimate heterogeneity was assessed and publication bias investigated. Results: A total of nine studies (two case-controls and seven cohorts) comprising 184 389 unique subjects were included. The summary relative risks for the categories 'herbicides - ever exposure', 'insecticides - ever exposure', 'any pesticide - ever exposure' and 'any pesticide - high exposure' resulted 1.85 [95% confidence interval (CI): 1.01, 3.36], 1.57 (95% CI: 0.58, 4.25), 1.31 (95% CI: 0.85, 2.04) and 2.17 (95% CI: 0.45, 10.36), respectively. Herbicides and insecticides had no between-study heterogeneity (I2 = 0%), while a significant heterogeneity (I2 > 50%) was detected for the high exposure to any pesticide. No indication for publication bias was found. Conclusions: Individuals exposed to herbicides are at an increased risk of CM. Future properly designed observational studies are required to confirm this finding

Patterning of educational attainment across inflammatory markers : Findings from a multi-cohort study

Background: Evidence suggests that the inflammatory reaction, an adaptive response triggered by a variety of harmful stimuli and conditions involved in the risk and development of many chronic diseases, is a potential pathway through which the socioeconomic environment is biologically embedded. Difficulty in interpreting the role of the inflammatory system in the embodiment dynamic arises because of heterogeneity across studies that use a limited but varied number of inflammatory markers. There is no consensus in the literature as to which inflammatory markers beyond the C-reactive protein and to a lesser extent interleukin 6 are related to the social environment. Accordingly, we aimed to investigate the association between educational attainment, and several markers of inflammation - C-reactive protein, fibrinogen, interleukin 6, interleukin 1 beta and tumor necrosis factor alpha- in 6 European cohort studies. Methods: Up to 17,470 participants from six European cohort studies with data on educational attainment, health behaviors and lifestyle factors, and at least two different inflammatory markers. Four sub-datasets were drawn with varying numbers of participants to allow pairwise comparison of the social patterning of C-reactive protein and any other inflammatory markers. To evaluate within each sub-dataset the importance of the context and cohort specificities, linear regression-based analyses were performed separately for each cohort and combined in a random effect meta-analysis to determine the relationship between educational attainment and inflammation. Results: We found that the magnitude of the relationship between educational attainment and five inflammatory biomarkers (C-reactive protein, fibrinogen, interleukin 6 and 1 beta and tumor necrosis factor alpha) was variable. By far the most socially patterned biomarker was C-reactive protein, followed by fibrinogen and to lesser extent interleukin 6, where a low educational attainment was associated with higher inflammation even after adjusting for health behaviours and body mass index. No association was found with interleukin 1 beta and tumor necrosis factor alpha. Conclusions: Our study suggests different educational patterning of inflammatory biomarkers. Further large-scale research is needed to explore social differences in the inflammatory cascade in greater detail and the extent to which these differences contribute to social inequalities in health.Peer reviewe

Multi-cohort study identifies social determinants of systemic inflammation over the life course

Chronic inflammation has been proposed as having a prominent role in the construction of social inequalities in health. Disentangling the effects of early life and adulthood social disadvantage on inflammation is key in elucidating biological mechanisms underlying socioeconomic disparities. Here we explore the relationship between socioeconomic position (SEP) across the life course and inflammation (as measured by CRP levels) in up to 23,008 participants from six European cohort studies from three countries conducted between 1958 and 2013. We find a consistent inverse association between SEP and CRP across cohorts, where participants with a less advantaged SEP have higher levels of inflammation. Educational attainment is most strongly related to inflammation, after adjusting for health behaviours, body mass index and later-in-life SEP. These findings suggest socioeconomic disadvantage in young adulthood is independently associated with later life inflammation calling for further studies of the pathways operating through educational processes.Peer reviewe

Reducing socio-economic inequalities in all-cause mortality: a counterfactual mediation approach.

Socio-economic inequalities in mortality are well established, yet the contribution of intermediate risk factors that may underlie these relationships remains unclear. We evaluated the role of multiple modifiable intermediate risk factors underlying socio-economic-associated mortality and quantified the potential impact of reducing early all-cause mortality by hypothetically altering socio-economic risk factors. Data were from seven cohort studies participating in the LIFEPATH Consortium (total n = 179 090). Using both socio-economic position (SEP) (based on occupation) and education, we estimated the natural direct effect on all-cause mortality and the natural indirect effect via the joint mediating role of smoking, alcohol intake, dietary patterns, physical activity, body mass index, hypertension, diabetes and coronary artery disease. Hazard ratios (HRs) were estimated, using counterfactual natural effect models under different hypothetical actions of either lower or higher SEP or education. Lower SEP and education were associated with an increase in all-cause mortality within an average follow-up time of 17.5 years. Mortality was reduced via modelled hypothetical actions of increasing SEP or education. Through higher education, the HR was 0.85 [95% confidence interval (CI) 0.84, 0.86] for women and 0.71 (95% CI 0.70, 0.74) for men, compared with lower education. In addition, 34% and 38% of the effect was jointly mediated for women and men, respectively. The benefits from altering SEP were slightly more modest. These observational findings support policies to reduce mortality both through improving socio-economic circumstances and increasing education, and by altering intermediaries, such as lifestyle behaviours and morbidities

Socioeconomic status, non-communicable disease risk factors, and walking speed in older adults: Multi-cohort population based study

Objective To assess the association of low socioeconomic status and risk factors for non-communicable diseases (diabetes, high alcohol intake, high blood pressure, obesity, physical inactivity, smoking) with loss of physical functioning at older ages. Design Multi-cohort population based study. Setting 37 cohort studies from 24 cou

Patterning of educational attainment across inflammatory markers: Findings from a multi-cohort study

Background: Evidence suggests that the inflammatory reaction, an adaptive response triggered by a variety of harmful stimuli and conditions involved in the risk and development of many chronic diseases, is a potential pathway through which the socioeconomic environment is biologically embedded. Difficulty in interpreting the role of the inflammatory system in the embodiment dynamic arises because of heterogeneity across studies that use a limited but varied number of inflammatory markers. There is no consensus in the literature as to which inflammatory markers beyond the C-reactive protein and to a lesser extent interleukin 6 are related to the social environment. Accordingly, we aimed to investigate the association between educational attainment, and several markers of inflammation - C-reactive protein, fibrinogen, interleukin 6, interleukin 1 beta and tumor necrosis factor alpha- in 6 European cohort studies.Methods: Up to 17,470 participants from six European cohort studies with data on educational attainment, health behaviors and lifestyle factors, and at least two different inflammatory markers. Four sub-datasets were drawn with varying numbers of participants to allow pairwise comparison of the social patterning of C-reactive protein and any other inflammatory markers. To evaluate within each sub-dataset the importance of the context and cohort specificities, linear regression-based analyses were performed separately for each cohort and combined in a random effect meta-analysis to determine the relationship between educational attainment and inflammation.Results: We found that the magnitude of the relationship between educational attainment and five inflammatory biomarkers (C-reactive protein, fibrinogen, interleukin 6 and 1 beta and tumor necrosis factor alpha) was variable. By far the most socially patterned biomarker was C-reactive protein, followed by fibrinogen and to lesser extent interleukin 6, where a low educational attainment was associated with higher inflammation even after adjusting for health behaviours and body mass index. No association was found with interleukin 1 beta and tumor necrosis factor alpha.Conclusions: Our study suggests different educational patterning of inflammatory biomarkers. Further large-scale research is needed to explore social differences in the inflammatory cascade in greater detail and the extent to which these differences contribute to social inequalities in health.</div

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis