Heterogeneity of glycaemic phenotypes in type 1 diabetes.

AIMS/HYPOTHESIS: Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes. METHODS: In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison. RESULTS: We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes. CONCLUSIONS/INTERPRETATION: Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.

Sex inequalities in cardiovascular risk factors and their management in primary prevention in adults living with type 1 diabetes in Germany and France: findings from DPV and SFDT1.

INTRODUCTION & OBJECTIVES: To evaluate whether cardiovascular risk factors and their management differ in primary prevention between adult males and females with type 1 diabetes (T1D) in two European countries in 2020-2022 and sex inequalities in achievement of standards of care in diabetes. METHODS: We used 2020-2022 data of patients without a cardiovascular history in the Prospective Diabetes Follow-up registry (DPV) centres, in Germany, and the Société Francophone du Diabète- Cohorte Diabète de Type 1 cohort (SFDT1), in France. RESULTS: We included 2,657 participants from the DPV registry and 1,172 from the SFDT1 study. Body mass indexes were similar in females and males with similar proportions of HbA1c < 7% (DPV: 36.6 vs 33.0%, p = 0.06, respectively; SFDT1: 23.4 vs 25.7%, p = 0.41). Females were less overweight compared to men in DPV (55.4 vs 61.0%, p < 0.01) but not in SFDT1 (48.0 vs 44.9%, p = 0.33) and were less prone to smoke (DPV: 19.7 vs 25.8%, p < 0.01; SFDT1: 21.0 vs 26.0%, p = 0.07). Systolic blood pressure was lower in females than males with a higher rate of antihypertensive therapy in case of hypertension in females in DPV (70.5 vs 63.7%, p = 0.02) but not in SFDT1 (73.3 vs 68.6%, p = 0.64). In the case of microalbuminuria, ACEi-ARB were less often prescribed in women than men in DPV (21.4 vs 37.6%, p < 0.01) but not SFDT1 (73.3 vs 67.5.0%, p = 0.43). In females compared to males, HDL-cholesterol levels were higher; triglycerides were lower in both countries. In those with LDL-cholesterol > 3.4 mmol/L (DPV: 19.9 (females) vs 23.9% (males), p = 0.01; SFDT1 17.0 vs 19.2%, p = 0.43), statin therapy was less often prescribed in females than males in DPV (7.9 vs 17.0%, p < 0.01), SFDT1 (18.2 vs 21.0%, p = 0.42). CONCLUSION: In both studies, females in primary prevention have a better cardiovascular risk profile than males. We observed a high rate of therapeutic inertia, which might be higher in females for statin treatment and nephroprotection with ACEi-ARB, especially in Germany. Diabetologists should be aware of sex-specific differences in the management of cardiorenal risk factors to develop more personalized prevention strategies.

Relationship between multimorbidity, functional limitation, and quality of life among middle-aged and older adults: findings from the longitudinal analysis of the 2013-2020 Survey of Health, Ageing, and Retirement in Europe (SHARE).

PURPOSE: The increased burden of multimorbidity is restricting individuals' ability to live autonomously, leading to a poorer quality of life. This study estimated trajectories of functional limitation and quality of life among middle-aged (ages 50 to 64 years) and older (aged 65 years and older) individuals with and without multimorbidity. We also assessed differences in the relationship between these two trajectories by multimorbidity status and separately for each age cohort. METHODS: Data originated from the Survey of Health, Ageing, and Retirement in Europe (SHARE). In Luxembourg, data were obtained between 2013 and 2020, involving 1,585 respondents ≥ 50 years of age. Multimorbidity was defined as a self-reported diagnosis of two or more out of 16 chronic conditions; functional limitation was assessed by a combined (Instrumental) Activities of Daily Living (ADL/IADLI) scale; and to measure quality of life, we used the Control, Autonomy, Self-Realization, and Pleasure (CASP-12) scale. Latent growth curve modelling techniques were used to conduct the analysis where repeated measures of quality of life and functional limitation were treated as continuous and zero-inflated count variables, respectively. The model was assessed separately in each age cohort, controlling for the baseline covariates, and the estimates from the two cohorts were presented as components of a synthetic cohort covering the life course from the age of 50. RESULTS: Middle-aged and older adults living with multimorbidity experienced poorer quality of life throughout the life course and were at a higher risk of functional limitation than those without multimorbidity. At baseline, functional limitation had a negative impact on quality of life. Furthermore, among middle-aged adults without multimorbidity and older adults with multimorbidity, an increase in the number of functional limitations led to a decline in quality of life. These results imply that the impact of multimorbidity on functional limitation and quality of life may vary across the life course. CONCLUSION: Using novel methodological techniques, this study contributes to a better understanding of the longitudinal relationship between functional limitation and quality of life among individuals with and without multimorbidity and how this relationship changes across the life course. Our findings suggest that lowering the risk of having multimorbidity can decrease functional limitation and increase quality of life.

Interaction between plasma phospholipid odd-chain fatty acids and GAD65 autoantibodies on the incidence of adult-onset diabetes: the EPIC-InterAct case-cohort study.

AIMS/HYPOTHESIS: Islet autoimmunity may progress to adult-onset diabetes. We investigated whether circulating odd-chain fatty acids (OCFA) 15:0 and 17:0, which are inversely associated with type 2 diabetes, interact with autoantibodies against GAD65 (GAD65Ab) on the incidence of adult-onset diabetes. METHODS: We used the European EPIC-InterAct case-cohort study including 11,124 incident adult-onset diabetes cases and a subcohort of 14,866 randomly selected individuals. Adjusted Prentice-weighted Cox regression estimated HRs and 95% CIs of diabetes in relation to 1 SD lower plasma phospholipid 15:0 and/or 17:0 concentrations or their main contributor, dairy intake, among GAD65Ab-negative and -positive individuals. Interactions between tertiles of OCFA and GAD65Ab status were estimated by proportion attributable to interaction (AP). RESULTS: Low concentrations of OCFA, particularly 17:0, were associated with a higher incidence of adult-onset diabetes in both GAD65Ab-negative (HR 1.55 [95% CI 1.48, 1.64]) and GAD65Ab-positive (HR 1.69 [95% CI 1.34, 2.13]) individuals. The combination of low 17:0 and high GAD65Ab positivity vs high 17:0 and GAD65Ab negativity conferred an HR of 7.51 (95% CI 4.83, 11.69), with evidence of additive interaction (AP 0.25 [95% CI 0.05, 0.45]). Low dairy intake was not associated with diabetes incidence in either GAD65Ab-negative (HR 0.98 [95% CI 0.94, 1.02]) or GAD65Ab-positive individuals (HR 0.97 [95% CI 0.79, 1.18]). CONCLUSIONS/INTERPRETATION: Low plasma phospholipid 17:0 concentrations may promote the progression from GAD65Ab positivity to adult-onset diabetes.

A nutritional biomarker score of the Mediterranean diet and incident type 2 diabetes: Integrated analysis of data from the MedLey randomised controlled trial and the EPIC-InterAct case-cohort study.

BACKGROUND: Self-reported adherence to the Mediterranean diet has been modestly inversely associated with incidence of type 2 diabetes (T2D) in cohort studies. There is uncertainty about the validity and magnitude of this association due to subjective reporting of diet. The association has not been evaluated using an objectively measured biomarker of the Mediterranean diet. METHODS AND FINDINGS: We derived a biomarker score based on 5 circulating carotenoids and 24 fatty acids that discriminated between the Mediterranean or habitual diet arms of a parallel design, 6-month partial-feeding randomised controlled trial (RCT) conducted between 2013 and 2014, the MedLey trial (128 participants out of 166 randomised). We applied this biomarker score in an observational study, the European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct case-cohort study, to assess the association of the score with T2D incidence over an average of 9.7 years of follow-up since the baseline (1991 to 1998). We included 22,202 participants, of whom 9,453 were T2D cases, with relevant biomarkers from an original case-cohort of 27,779 participants sampled from a cohort of 340,234 people. As a secondary measure of the Mediterranean diet, we used a score estimated from dietary-self report. Within the trial, the biomarker score discriminated well between the 2 arms; the cross-validated C-statistic was 0.88 (95% confidence interval (CI) 0.82 to 0.94). The score was inversely associated with incident T2D in EPIC-InterAct: the hazard ratio (HR) per standard deviation of the score was 0.71 (95% CI: 0.65 to 0.77) following adjustment for sociodemographic, lifestyle and medical factors, and adiposity. In comparison, the HR per standard deviation of the self-reported Mediterranean diet was 0.90 (95% CI: 0.86 to 0.95). Assuming the score was causally associated with T2D, higher adherence to the Mediterranean diet in Western European adults by 10 percentiles of the score was estimated to reduce the incidence of T2D by 11% (95% CI: 7% to 14%). The study limitations included potential measurement error in nutritional biomarkers, unclear specificity of the biomarker score to the Mediterranean diet, and possible residual confounding. CONCLUSIONS: These findings suggest that objectively assessed adherence to the Mediterranean diet is associated with lower risk of T2D and that even modestly higher adherence may have the potential to reduce the population burden of T2D meaningfully. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12613000602729 https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=363860.

Genome-wide Association Analysis in Humans Links Nucleotide Metabolism to Leukocyte Telomere Length.

Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.

Machine learning for predicting neurodegenerative diseases in the general older population: a cohort study.

BACKGROUND: In the older general population, neurodegenerative diseases (NDs) are associated with increased disability, decreased physical and cognitive function. Detecting risk factors can help implement prevention measures. Using deep neural networks (DNNs), a machine-learning algorithm could be an alternative to Cox regression in tabular datasets with many predictive features. We aimed to compare the performance of different types of DNNs with regularized Cox proportional hazards models to predict NDs in the older general population. METHODS: We performed a longitudinal analysis with participants of the English Longitudinal Study of Ageing. We included men and women with no NDs at baseline, aged 60 years and older, assessed every 2 years from 2004 to 2005 (wave2) to 2016-2017 (wave 8). The features were a set of 91 epidemiological and clinical baseline variables. The outcome was new events of Parkinson's, Alzheimer or dementia. After applying multiple imputations, we trained three DNN algorithms: Feedforward, TabTransformer, and Dense Convolutional (Densenet). In addition, we trained two algorithms based on Cox models: Elastic Net regularization (CoxEn) and selected features (CoxSf). RESULTS: 5433 participants were included in wave 2. During follow-up, 12.7% participants developed NDs. Although the five models predicted NDs events, the discriminative ability was superior using TabTransformer (Uno's C-statistic (coefficient (95% confidence intervals)) 0.757 (0.702, 0.805). TabTransformer showed superior time-dependent balanced accuracy (0.834 (0.779, 0.889)) and specificity (0.855 (0.0.773, 0.909)) than the other models. With the CoxSf (hazard ratio (95% confidence intervals)), age (10.0 (6.9, 14.7)), poor hearing (1.3 (1.1, 1.5)) and weight loss 1.3 (1.1, 1.6)) were associated with a higher DNN risk. In contrast, executive function (0.3 (0.2, 0.6)), memory (0, 0, 0.1)), increased gait speed (0.2, (0.1, 0.4)), vigorous physical activity (0.7, 0.6, 0.9)) and higher BMI (0.4 (0.2, 0.8)) were associated with a lower DNN risk. CONCLUSION: TabTransformer is promising for prediction of NDs with heterogeneous tabular datasets with numerous features. Moreover, it can handle censored data. However, Cox models perform well and are easier to interpret than DNNs. Therefore, they are still a good choice for NDs.

The role of multimorbidity and socio-economic characteristics as potential risk factors for Long Covid: evidence from the multilevel analysis of the Survey of Health, Ageing and Retirement in Europe's corona surveys (2020-2021).

BACKGROUND: A substantial proportion of individuals continue experiencing persistent symptoms following the acute stage of their Covid-19 illness. However, there is a shortage of population-based studies on Long Covid risk factors. OBJECTIVE: To estimate the prevalence of Long Covid in the population of middle-aged and older Europeans having contracted Covid-19 and to assess the role of multimorbidity and socio-economic characteristics as potential risk factors of Long Covid. METHODS: A population-based longitudinal prospective study involving a sample of respondents 50 years and older (n = 4,004) from 27 countries who participated in the 2020 and 2021 Survey of Health, Ageing and Retirement in Europe (SHARE), in particular the Corona Surveys. Analyses were conducted by a multilevel (random intercept) hurdle negative binomial model. RESULTS: Overall, 71.6% (95% confidence interval = 70.2-73.0%) of the individuals who contracted Covid-19 had at least one symptom of Long Covid up to 12 months after the infection, with an average of 3.06 (standard deviation = 1.88) symptoms. There were significant cross-country differences in the prevalence of Long Covid and number of symptoms. Higher education and being a man were associated with a lower risk of Long Covid, whilst being employed was associated with a higher risk of having Long Covid. Multimorbidity was associated with a higher number of symptoms and older age was associated with a lower number of symptoms. CONCLUSION: Our results provide evidence on the substantial burden of Long Covid in Europe. Individuals who contracted Covid-19 may require long-term support or further medical intervention, putting additional pressure on national health care systems.

Validation of a SARS-CoV-2 Surrogate Neutralization Test Detecting Neutralizing Antibodies against the Major Variants of Concern.

SARS-CoV-2 infection and/or vaccination elicit a broad range of neutralizing antibody responses against the different variants of concern (VOC). We established a new variant-adapted surrogate virus neutralization test (sVNT) and assessed the neutralization activity against the ancestral B.1 (WT) and VOC Delta, Omicron BA.1, BA.2, and BA.5. Analytical performances were compared against the respective VOC to the reference virus neutralization test (VNT) and two CE-IVD labeled kits using three different cohorts collected during the COVID-19 waves. Correlation analyses showed moderate to strong correlation for Omicron sub-variants (Spearman's r = 0.7081 for BA.1, r = 0.7205 for BA.2, and r = 0.6042 for BA.5), and for WT (r = 0.8458) and Delta-sVNT (r = 0.8158), respectively. Comparison of the WT-sVNT performance with two CE-IVD kits, the "Icosagen SARS-CoV-2 Neutralizing Antibody ELISA kit" and the "Genscript cPass, kit" revealed an overall good correlation ranging from 0.8673 to -0.8773 and a midway profile between both commercial kits with 87.76% sensitivity and 90.48% clinical specificity. The BA.2-sVNT performance was similar to the BA.2 Genscript test. Finally, a correlation analysis revealed a strong association (r = 0.8583) between BA.5-sVNT and VNT sVNT using a double-vaccinated cohort (n = 100) and an Omicron-breakthrough infection cohort (n = 91). In conclusion, the sVNT allows for the efficient prediction of immune protection against the various VOCs.

Impact of intra-category food substitutions on the risk of type 2 diabetes: a modelling study on the pizza category.

Advice on replacing unhealthy foods with healthier alternatives within the same food category may be more acceptable and might ease the transition towards a healthy diet. Here, we studied the potential impact of substitutions within the pizza category on the risk of type 2 diabetes (T2D). The study sample consisted of 2510 adults from the INCA2 French national survey. Based on their nutritional characteristics, the 353 pizzas marketed in France were grouped into 100 clusters that were used to run various scenarios of pizza substitutions, which were either isoenergetic (IE) or non-isoenergetic (NIE). We then used a model structurally similar to the Preventable Risk Integrated ModEl to assess the expected rate of change in risk of T2D. Pizzas characterised by a low energy, high vegetable content and whole grain dough were associated with a greater reduction in the risk of T2D. The rates of change in risk of T2D were markedly stronger in men and for NIE substitutions. When the rates of change were estimated in the subsample of pizza consumers, replacing the observed pizzas with the best pizza resulted in a T2D risk reduction of -6·7 % (-8·4 %; -4·9 %, IE) and -8·9 % (-11·2 %; -6·3 %, NIE), assuming that this is their usual diets. The greatest risk reduction induced by an IE substitution of the observed pizza with a mixed dish was similar to that observed with the best pizzas. Overall, this modelling study suggests that healthy swaps within a category can effectively supplement broader dietary changes towards a healthier diet.

Sugar- and artificially-sweetened soda consumption and subclinical atherosclerosis among Mexican women.

BACKGROUND AND AIMS: Sugar-sweetened soda consumption is associated with most cardiometabolic risk factors. The role of artificially-sweetened beverages in cardiovascular disease (CVD) is inconclusive, but their consumption correlates with health impairment. Little is known about the contribution of soda consumption in subclinical stages of atherosclerosis. Therefore, we evaluated the relation between sugar- and artificially-sweetened soda consumption and carotid intima-media thickness (IMT) among Mexican women. METHODS AND RESULTS: We cross-sectionally evaluated 1093 women enrolled in the Mexican Teachers' Cohort who were free of CVD, diabetes or cancer. Sugar- and artificially-sweetened soda consumption was estimated from a validated 140-item food frequency questionnaire in 2008 and all women underwent a carotid ultrasound assessment three years later. Participants were categorized into tertiles of soda consumption in servings/week. Subclinical atherosclerosis was defined as a mean left and/or right IMT ≥0.8 mm or the presence of plaque on either common carotid artery. In multivariable regression models, women in the highest tertile of sugar-sweetened soda consumption had 2.6% (95%CI: 0.8, 4.5) mean increased IMT, and had 2-fold the risk of carotid atherosclerosis (PR: 2.0, 95%CI: 1.3, 3.2) compared to those in the lowest tertile. In stratified analyses, older and postmenopausal women who consumed sugar-sweetened soda had an increased IMT and atherosclerosis risk. Artificially-sweetened soda consumption was not associated with IMT or carotid atherosclerosis. CONCLUSIONS: Sugar-sweetened soda consumption was associated with subclinical atherosclerosis among disease-free Mexican women. Public health strategies to decrease CVD should consider the impact of sugar-sweetened soda consumption, particularly in older women.

Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review.

Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, hereinafter referred to as wearable-specific indicators of PA behavior (WIPAB), used to assess PA behavior. The strengths and limitations of those indicators as well as potential associations with certain health-related factors were also investigated. Three databases (MEDLINE, Embase, and Web of Science) were screened for articles published in English between January 2010 and April 2020. Articles, which assessed the PA behavior, gathered objective measures of PA using tri-axial accelerometers, and investigated WIPAB, were selected. All studies reporting WIPAB in the context of PA monitoring were synthesized and presented in four summary tables: study characteristics, details of the WIPAB, strengths, and limitations, and measures of association between those indicators and health-related factors. In total, 7247 records were identified, of which 24 articles were included after assessing titles, abstracts, and full texts. Thirteen WIPAB were identified, which can be classified into three different categories specifically focusing on (1) the activity intensity distribution, (2) activity accumulation, and (3) the temporal correlation and regularity of the acceleration signal. Only five of the thirteen WIPAB identified in this review have been used in the literature so far to investigate the relationship between PA behavior and health, while they may provide useful additional information to the conventional PA variables.

Improving Diabetes-Related Biomedical Literature Exploration in the Clinical Decision-making Process via Interactive Classification and Topic Discovery: Methodology Development Study.

BACKGROUND: The amount of available textual health data such as scientific and biomedical literature is constantly growing and becoming more and more challenging for health professionals to properly summarize those data and practice evidence-based clinical decision making. Moreover, the exploration of unstructured health text data is challenging for professionals without computer science knowledge due to limited time, resources, and skills. Current tools to explore text data lack ease of use, require high computational efforts, and incorporate domain knowledge and focus on topics of interest with difficulty. OBJECTIVE: We developed a methodology able to explore and target topics of interest via an interactive user interface for health professionals with limited computer science knowledge. We aim to reach near state-of-the-art performance while reducing memory consumption, increasing scalability, and minimizing user interaction effort to improve the clinical decision-making process. The performance was evaluated on diabetes-related abstracts from PubMed. METHODS: The methodology consists of 4 parts: (1) a novel interpretable hierarchical clustering of documents where each node is defined by headwords (words that best represent the documents in the node), (2) an efficient classification system to target topics, (3) minimized user interaction effort through active learning, and (4) a visual user interface. We evaluated our approach on 50,911 diabetes-related abstracts providing a hierarchical Medical Subject Headings (MeSH) structure, a unique identifier for a topic. Hierarchical clustering performance was compared against the implementation in the machine learning library scikit-learn. On a subset of 2000 randomly chosen diabetes abstracts, our active learning strategy was compared against 3 other strategies: random selection of training instances, uncertainty sampling that chooses instances about which the model is most uncertain, and an expected gradient length strategy based on convolutional neural networks (CNNs). RESULTS: For the hierarchical clustering performance, we achieved an F1 score of 0.73 compared to 0.76 achieved by scikit-learn. Concerning active learning performance, after 200 chosen training samples based on these strategies, the weighted F1 score of all MeSH codes resulted in a satisfying 0.62 F1 score using our approach, 0.61 using the uncertainty strategy, 0.63 using the CNN, and 0.45 using the random strategy. Moreover, our methodology showed a constant low memory use with increased number of documents. CONCLUSIONS: We proposed an easy-to-use tool for health professionals with limited computer science knowledge who combine their domain knowledge with topic exploration and target specific topics of interest while improving transparency. Furthermore, our approach is memory efficient and highly parallelizable, making it interesting for large Big Data sets. This approach can be used by health professionals to gain deep insights into biomedical literature to ultimately improve the evidence-based clinical decision making process.

BMI in the Associations of Plant-Based Diets with Type 2 Diabetes and Hypertension Risks in Women: The E3N Prospective Cohort Study.

BACKGROUND: Few studies have evaluated the quality of plant-based diets in relation to chronic diseases, and the potential role of BMI is not clearly explored. OBJECTIVES: To study the associations between plant-based diet indices and type 2 diabetes (T2D) and hypertension risks, as well as the extent to which the associations were modified and/or mediated by BMI. METHODS: The study included 74,522 women from the Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale prospective cohort [mean (SD): age, 52.94 (6.7) years; BMI, 22.970 (3.328) kg/m2]. Dietary data were collected at baseline (1993) via an FFQ. Overall plant-based diet index (PDI), healthful PDI (hPDI), and unhealthful PDI (uPDI) were developed. Multivariable Cox regression models were used to derive HRs and 95% CIs. Effect modification and mediation by BMI were explored. RESULTS: There were 3292 (4.64%) incident cases of T2D and 12,504 (27.14%) incident cases of hypertension over ∼20 years of follow-up. In the multivariable model further adjusted for BMI, higher adherence to PDI and hPDI was associated with lower T2D and hypertension risks, with an HR per 1-SD increase (95% CI) of 0.88 (0.85, 0.91) and 0.96 (0.94, 0.98) for PDI and 0.88 (0.85, 0.92) and 0.94 (0.92, 0.95) for hPDI, respectively. uPDI was not associated with T2D [0.98 (0.94, 1.01)], whereas a positive association was observed with hypertension: 1.04 (1.02, 1.06). There was interaction between PDI and uPDI, as well as BMI, on T2D (P-interaction < 0.001) but not on hypertension (P-interaction > 0.05). In addition, BMI mediated 26-59% and 0.2-59% of diet-T2D and diet-hypertension associations, respectively. CONCLUSIONS: Differential associations between plant-based diets and T2D and hypertension risks were observed among women in this large prospective study. Only healthier plant foods were associated with lower risks, partly through decreasing BMI. The protocol was registered at clinicaltrials.gov as NCT03285230.

The associations of the Palaeolithic diet alone and in combination with lifestyle factors with type 2 diabetes and hypertension risks in women in the E3N prospective cohort.

PURPOSE: Patterns of change from the traditional Palaeolithic lifestyle to the modern lifestyle may partly explain the epidemic proportions of non-communicable diseases (NCDs). We investigated to what extent adherence to the Palaeolithic diet (PD) and the Palaeolithic-like lifestyle was associated with type 2 diabetes (T2D) and hypertension risks. METHODS: A study of 70,991 women from the E3N (Etude Epidémiologique auprès de femmes de la Mutuelle Générale de l'Education Nationale) cohort, followed up for nearly 20 years. There were 3292 incident T2D and 12,504 incident hypertension cases that were validated. Dietary data were collected at baseline in 1993 via a food frequency questionnaire. The PD score and the Palaeolithic-like lifestyle score (PD, physical activity, smoking status, and body mass index [BMI]) were derived and considered in quintiles. Multivariable Cox regression models were employed to estimate hazard ratios (HR) and 95% confidence intervals (CI) for incident T2D and hypertension. RESULTS: In the fully adjusted models, a 1-SD increase of the PD score was associated with 4% and 3% lower risks of T2D and hypertension, respectively. Those in the highest versus the lowest quintile of the score had HR (95% CI) of 0.88 (0.79, 0.98) and 0.91 (0.86, 0.96) for T2D and hypertension, respectively (P-trend < 0.0001). Associations were stronger for the Palaeolithic-like lifestyle score; in the fully adjusted model, a 1-SD increase of the score was associated with 19% and 6% lower risks of T2D and hypertension, respectively. Risks lowered successively with each increase in quintile; those in the highest versus the lowest quintile had HR (95% CI) of 0.58 (0.52, 0.65) and 0.85 (0.80, 0.90) for T2D and hypertension, respectively (P-trend < 0.0001). CONCLUSIONS: Our data suggest that adhering to a PD based on fruit, vegetables, lean meats, fish, and nuts, and incorporating a Palaeolithic-like lifestyle could be promising options to prevent T2D and hypertension.

The Use of Social Media for Health Research Purposes: Scoping Review.

BACKGROUND: As social media are increasingly used worldwide, more and more scientists are relying on them for their health-related projects. However, social media features, methodologies, and ethical issues are unclear so far because, to our knowledge, there has been no overview of this relatively young field of research. OBJECTIVE: This scoping review aimed to provide an evidence map of the different uses of social media for health research purposes, their fields of application, and their analysis methods. METHODS: We followed the scoping review methodologies developed by Arksey and O'Malley and the Joanna Briggs Institute. After developing search strategies based on keywords (eg, social media, health research), comprehensive searches were conducted in the PubMed/MEDLINE and Web of Science databases. We limited the search strategies to documents written in English and published between January 1, 2005, and April 9, 2020. After removing duplicates, articles were screened at the title and abstract level and at the full text level by two independent reviewers. One reviewer extracted data, which were descriptively analyzed to map the available evidence. RESULTS: After screening 1237 titles and abstracts and 407 full texts, 268 unique papers were included, dating from 2009 to 2020 with an average annual growth rate of 32.71% for the 2009-2019 period. Studies mainly came from the Americas (173/268, 64.6%, including 151 from the United States). Articles used machine learning or data mining techniques (60/268) to analyze the data, discussed opportunities and limitations of the use of social media for research (59/268), assessed the feasibility of recruitment strategies (45/268), or discussed ethical issues (16/268). Communicable (eg, influenza, 40/268) and then chronic (eg, cancer, 24/268) diseases were the two main areas of interest. CONCLUSIONS: Since their early days, social media have been recognized as resources with high potential for health research purposes, yet the field is still suffering from strong heterogeneity in the methodologies used, which prevents the research from being compared and generalized. For the field to be fully recognized as a valid, complementary approach to more traditional health research study designs, there is now a need for more guidance by types of applications of social media for health research, both from a methodological and an ethical perspective. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1136/bmjopen-2020-040671.

Methods to Generate Innovative Research Ideas and Improve Patient and Public Involvement in Modern Epidemiological Research: Review, Patient Viewpoint, and Guidelines for Implementation of a Digital Cohort Study.

BACKGROUND: Patient and public involvement (PPI) in research aims to increase the quality and relevance of research by incorporating the perspective of those ultimately affected by the research. Despite these potential benefits, PPI is rarely included in epidemiology protocols. OBJECTIVE: The aim of this study is to provide an overview of methods used for PPI and offer practical recommendations for its efficient implementation in epidemiological research. METHODS: We conducted a review on PPI methods. We mirrored it with a patient advocate's viewpoint about PPI. We then identified key steps to optimize PPI in epidemiological research based on our review and the viewpoint of the patient advocate, taking into account the identification of barriers to, and facilitators of, PPI. From these, we provided practical recommendations to launch a patient-centered cohort study. We used the implementation of a new digital cohort study as an exemplary use case. RESULTS: We analyzed data from 97 studies, of which 58 (60%) were performed in the United Kingdom. The most common methods were workshops (47/97, 48%); surveys (33/97, 34%); meetings, events, or conferences (28/97, 29%); focus groups (25/97, 26%); interviews (23/97, 24%); consensus techniques (8/97, 8%); James Lind Alliance consensus technique (7/97, 7%); social media analysis (6/97, 6%); and experience-based co-design (3/97, 3%). The viewpoint of a patient advocate showed a strong interest in participating in research. The most usual PPI modalities were research ideas (60/97, 62%), co-design (42/97, 43%), defining priorities (31/97, 32%), and participation in data analysis (25/97, 26%). We identified 9 general recommendations and 32 key PPI-related steps that can serve as guidelines to increase the relevance of epidemiological studies. CONCLUSIONS: PPI is a project within a project that contributes to improving knowledge and increasing the relevance of research. PPI methods are mainly used for idea generation. On the basis of our review and case study, we recommend that PPI be included at an early stage and throughout the research cycle and that methods be combined for generation of new ideas. For e-cohorts, the use of digital tools is essential to scale up PPI. We encourage investigators to rely on our practical recommendations to extend PPI in future epidemiological studies.

Type 2 diabetes and its characteristics are associated with poor oral health: findings from 60,590 senior women from the E3N study.

BACKGROUND: Type 2 diabetes (T2D) has been identified as a risk factor for poor oral health, however, a limited number of oral health and T2D characteristics have been studied so far. We sought to assess T2D status, age at diagnosis, duration since diagnosis and treatment in relation to a variety of oral diseases. METHODS: Cross-sectional data were analyzed from the E3N (Etude Epidémiologique auprès de femmes de l'Education Nationale) cohort study which enrolled 60,590 women. Participants self-reported oral health status, and T2D cases were identified using diabetes-specific questionnaires and drug reimbursement insurance databases. Multivariable-adjusted ORs and 95% CIs were estimated using logistic regression models. RESULTS: The mean age (SD) of the women was 70 years (7.2), and 4.7% (n = 2857) had T2D. Compared to women without T2D, women with T2D were more likely to report a poor perceived oral health (OR 1.37 [95% CI 1.18, 1.60]), wearing dental prostheses (1.26 [1.14, 1.39]) and having problems of biting and chewing food (1.19 [1.07, 1.33]). In addition, for women with T2D the age at diagnosis (inversely) and the duration (positively) were associated with the likelihood to report poor oral health. CONCLUSIONS: For women with T2D, duration and age at diagnosis are associated with wearing prostheses, problems of biting and chewing, periodontitis and gingivitis.

Autoimmunity plays a role in the onset of diabetes after 40 years of age.

AIMS/HYPOTHESIS: Type 1 and type 2 diabetes differ with respect to pathophysiological factors such as beta cell function, insulin resistance and phenotypic appearance, but there may be overlap between the two forms of diabetes. However, there are relatively few prospective studies that have characterised the relationship between autoimmunity and incident diabetes. We investigated associations of antibodies against the 65 kDa isoform of GAD (GAD65) with type 1 diabetes and type 2 diabetes genetic risk scores and incident diabetes in adults in European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a case-cohort study nested in the EPIC cohort. METHODS: GAD65 antibodies were analysed in EPIC participants (over 40 years of age and free of known diabetes at baseline) by radioligand binding assay in a random subcohort (n = 15,802) and in incident diabetes cases (n = 11,981). Type 1 diabetes and type 2 diabetes genetic risk scores were calculated. Associations between GAD65 antibodies and incident diabetes were estimated using Prentice-weighted Cox regression. RESULTS: GAD65 antibody positivity at baseline was associated with development of diabetes during a median follow-up time of 10.9 years (HR for GAD65 antibody positive vs negative 1.78; 95% CI 1.43, 2.20) after adjustment for sex, centre, physical activity, smoking status and education. The genetic risk score for type 1 diabetes but not type 2 diabetes was associated with GAD65 antibody positivity in both the subcohort (OR per SD genetic risk 1.24; 95% CI 1.03, 1.50) and incident cases (OR 1.97; 95% CI 1.72, 2.26) after adjusting for age and sex. The risk of incident diabetes in those in the top tertile of the type 1 diabetes genetic risk score who were also GAD65 antibody positive was 3.23 (95% CI 2.10, 4.97) compared with all other individuals, suggesting that 1.8% of incident diabetes in adults was attributable to this combination of risk factors. CONCLUSIONS/INTERPRETATION: Our study indicates that incident diabetes in adults has an element of autoimmune aetiology. Thus, there might be a reason to re-evaluate the present subclassification of diabetes in adulthood.

Consumption of Meat, Fish, Dairy Products, and Eggs and Risk of Ischemic Heart Disease.

BACKGROUND: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). METHODS: In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subsample. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. RESULTS: The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06-1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89-0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86-0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88-0.99] per 20-g/d increment); the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with ≈20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-high-density lipoprotein cholesterol. CONCLUSIONS: Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects.