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Background: A dietary pattern can be defined as the quantities, proportions, variety, or combination of foods and drinks typically consumed. The dietary pattern approach aims to place emphasis on the total diet as a long-term health determinant, instead of focussing on separate foods and nutrients, which may interact or confound each other. Aim: This scoping review describes the totality of evidence for the role of dietary patterns for health-related outcomes as a basis for setting and updating food-based dietary guidelines in the Nordic Nutrition Recommendations 2023 (NNR2023). Methods: We used evidence from 10 qualified systematic reviews identified by the NNR2023 project. No additional literature search was conducted. Results: Strong or moderate evidence linked dietary patterns high in vegetables, fruits, whole grains, fish, low-fat dairy and legumes, and low in red and processed meats, sugar-sweetened beverages, sugary foods- and refined grains with beneficial health outcomes, such as reduced risk of cardiovascular disease (CVD), type 2 diabetes, obesity, cancer, bone health, and premature death. We also found limited evidence suggesting a relationship with the described dietary patterns in childhood and decreased risk of obesity and hypertension later in life. Most studies have been conducted among adult populations, and thus, there is a need for studies in certain subgroups, such as children and adolescents as well as the elderly.

Abstract Background Modifying the choice architecture of behavioural contexts can facilitate health behaviour change, but existing evidence builds mostly on small-scale interventions limited in duration, targets, strategies, and settings. We evaluated the effectiveness of a one-year hybrid type 2 implementation-effectiveness trial aimed at promoting healthy eating and daily physical activity with subtle modifications to the choice architecture of heterogeneous worksites. The intervention was contextualised to and integrated into the routine operations of each worksite. Effectiveness was evaluated in a quasi-experimental pre-post design. Methods Intervention sites (n = 21) implemented a median of two (range 1–9) intervention strategies for healthy eating and one (range 1–5) for physical activity. Questionnaires pre (n = 1126) and post (n = 943) intervention surveyed employees’ behavioural patterns at work (food consumption: vegetables/roots, fruit/berries, nuts/almonds/seeds, sweet treats, fast food, water; physical activity: restorative movement, exercise equipment use, stair use). The post-intervention questionnaire also measured employees’ perception of and response to three intervention strategies: a packed lunch recipe campaign, a fruit crew-strategy, and movement prompts. Multi- and single-level regression models evaluated effectiveness, treating intervention as a continuous predictor formed of the site-specific dose (n intervention strategies employed) and mean quality (three-point rating per strategy halfway and at the end of the intervention) of implementation relevant to each outcome. Results Multinomial logistic regression models found the intervention significantly associated with a favourable change in employees’ fruit and berry consumption (interaction effect of time and implementation p = 0.006) and with an unfavourable change in sweet treat consumption (p = 0.048). The evidence was strongest for the finding concerning fruit/berry consumption—an outcome that sites with greater dose and quality of implementation targeted by using strategies that reduced the physical effort required to have fruit/berries at work and by covering multiple eating-related contexts at the worksite. The quality of implementation was positively associated with the perception of (p = 0.044) and response to (p = 0.017) the packed lunch recipes, and with response to the fruit crew-strategy (p

Abstract Background The optimal nutritional treatment for gestational diabetes (GDM) is still a matter of debate. With increasing rates of GDM and potential negative consequences for the health of mother and child, the best treatment should be established. The Nordic diet with emphasis on plant-based protein show promising health outcomes in other populations but has yet to be investigated in GDM population. The aim of this study, which is part of the “Effect of plant-based Nordic diet versus carbohydrate-restricted diet on glucose levels in gestational diabetes” (eMOM) pilot study was to compare the short-term effects of healthy Nordic diet (HND) and the currently recommended moderate restriction of carbohydrates diet (MCRD) on glucose and lipid metabolism in women with GDM. Methods This was a randomized crossover where each of the diet interventions (HND and MCRD) were consumed for 3 days with a 3-day wash-out period in between. In total, 42 pregnant women diagnosed with GDM (

Objective When considering proposals to improve diets, it is important to understand how factors like price and income can affect saturated fat (SF) intake and demand. In this study, we examine and estimate the influence of price and income on intake across 160 countries, by age and sex, and derive sensitivity measures (price elasticities) that vary by age, sex and world region.Design We econometrically estimate intake responsiveness to income and prices across countries, accounting for differences by world region, age and sex. Intake data by age, sex and country were obtained from the 2018 Global Dietary Database. These data were then linked to global price data for select food groups from the World Bank International Comparison Programme and income data from the World Development Indicators Databank (World Bank).Results Intake differences due to price were highly significant, with a 1% increase in price associated with a lower SF intake (% energy/d) of about 4.3 percentage points. We also find significant differences across regions. In high-income countries, median (age 40) intake reductions were 1.4, 0.8 and 0.2 percentage points, given a 1% increase in the price of meat, dairy, and oils and fats, respectively. Price elasticities varied with age but not sex. Intake differences due to income were insignificant when regional binary variables were included in the analysis.Conclusion The results of this study show heterogeneous associations among prices and intake within and across countries. Policymakers should consider these heterogeneous effects as they address global nutrition and health challenges.

Abstract Aim To examine the association between the integrated care competencies and cross‐cultural competence of registered nurses prior to the integration of social and healthcare services in Finland. Design A descriptive correlational cross‐sectional questionnaire survey was conducted. Methods A simple random sample of 10,000 registered nurses was drawn from the Finnish Central Register of Valvira (National Supervisory Authority for Welfare and Health); 7000 of them were sent the online questionnaire, and a total of 1232 registered nurses participated in the study. We collected data using background questions, revised versions of the Competent Workforce for the Future tool in the four domains of client orientation, responsibility for personal or relative's welfare, fluency and clarity of services and access to the services and of the Cross‐Cultural Competence of Healthcare Professional tool in the four domains of motivation/curiosity, attitude, skill and emotion/empathy. Results Participants demonstrated a high level of integrated care competencies (mean = 4.00, SD ± 0.49). An association was observed between integrated care competencies and their domains of skills, motivation/curiosity, emotions/empathy, and cross‐cultural competence (p

Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.

Abstract Aims Type 2 diabetes (T2D) is a progressive disease often associated with comorbidities that complicate the management of T2D and affect the achievement of treatment targets. However, adherence to guidelines and individualized treatments can potentially improve treatment outcomes. This study assessed the association between different glucose lowering and lipid lowering medication lines and the achievement of treatment targets with different comorbidities among a T2D cohort in North Karelia, Finland (2011-12 to 2015-16). Methods The data on all diagnosed T2D patients (n = 10,190) in North Karelia were collated retrospectively from regional electronic health records (EHRs). Analyses were performed considering the age, sex, and comorbidities such as cardiovascular diseases (CVD) and any mental disorders (AMD). We analyzed the trends in using glucose lowering and lipid lowering medications and the effect of changes in medication on the achievement of treatment targets among different patient groups. Results Metformin was the most common treatment in all patient groups. The use of only metformin declined and the use of metformin and/or other non-insulin medications increased during the follow-up. A Combination of insulin and non-insulin medication was mostly used by T2D patients with both cardiovascular diseases and mental disorders (T2D + CVD + AMD), and the use of insulin increased among this group in follow-up. Achievement of the glucose treatment target deteriorated even after the intensification of medication among all patient groups during the follow-up. A considerably higher number of patients with T2D + AMD and T2D + CVD + AMD did not use lipid lowering medication when compared to the T2D + CVD patients both at baseline and follow-up. However, the achievement of the LDL treatment target improved during the follow-up. Conclusion Achievement of the glucose target deteriorated even after the intensification of treatment, and especially among patients with multiple diseases. Many T2D patients with AMD and CVD remained without lipid lowering medication, which needs further attention.

Abstract Background A healthy lifestyle decreases the risk of developing type 2 diabetes mellitus. The current cross-sectional study aimed to describe self-reported lifestyle behaviours and compare them to current health guidelines in European Feel4Diabetes-families at risk for developing type 2 diabetes across six countries (Belgium, Finland, Spain, Greece, Hungary and Bulgaria). Methods Parents and their children were recruited through primary schools located in low socio-economic status areas. Parents filled out the FINDRISC-questionnaire (eight items questioning age, Body Mass Index, waist circumference, PA, daily consumption of fruit, berries or vegetables, history of antihypertensive drug treatment, history of high blood glucose and family history of diabetes), which was used for the risk assessment of the family. Sociodemographic factors and several lifestyle behaviours (physical activity, sedentary behaviour, water consumption, fruit and vegetable consumption, soft drink consumption, sweets consumption, snack consumption, breakfast consumption) of both adults and children were assessed by parental questionnaires. Multilevel regression analyses were conducted to investigate families’ lifestyle behaviours, to compare these levels to health guidelines and to assess potential differences between the countries. Analyses were controlled for age, sex and socio-economic status. Results Most Feel4Diabetes-families at risk (parents and their children) did not comply with the guidelines regarding healthy behaviours, set by the WHO, European or national authorities. Less than half of parents and children complied with the physical activity guidelines, less than 15% of them complied with the fruit and vegetable guideline, and only 40% of the children met the recommendations of five glasses of water per day. Clear differences in lifestyle behaviours in Feel4Diabetes-families at risk exist between the countries. Conclusions Countries are highly recommended to invest in policy initiatives to counter unhealthy lifestyle behaviours in families at risk for type 2 diabetes development, taking into account country-specific needs. For future research it is of great importance to focus on families at risk in order to counter the development of type 2 diabetes and reduce health inequity.

Abstract Background Early identification of people at elevated risk of type 2 diabetes (T2D) is an important step in preventing or delaying its onset. Pharmacies can serve as a significant channel to reach these people. This study aimed to assess the potential health economic impact of screening and recruitment services in pharmacies in referring people to preventive interventions. Methods A decision analytic model was constructed to perform a cost-utility analysis of the expected national health economic consequences (in terms of costs and quality-adjusted life years, QALYs) of a hypothetical pharmacy-based service where people screened and recruited through pharmacies would participate in a digital lifestyle program. Cost-effectiveness was considered in terms of net monetary benefit (NMB). In addition, social return on investment (SROI) was calculated as the ratio of the intervention and recruitment costs and the net present value of expected savings. Payback time was the time taken to reach the break-even point in savings. In the base scenario, a 20-year time horizon was applied. Probabilistic and deterministic sensitivity analyses were applied to study robustness of the results. Results In the base scenario, the expected savings from the pharmacy-based screening and recruitment among the reached target cohort were 255.3 m€ (95% CI − 185.2 m€ to 717.2 m€) in pharmacy visiting population meaning 1412€ (95% CI − 1024€ to 3967€) expected savings per person. Additionally, 7032 QALYs (95% CI − 1344 to 16,143) were gained on the population level. The intervention had an NMB of 3358€ (95% CI − 1397€ to 8431€) using a cost-effectiveness threshold of 50,000 €/QALY. The initial costs were 122.2 m€ with an SROI of 2.09€ (95% CI − 1.52€ to 5.88€). The expected payback time was 10 and 8 years for women and men, respectively. Results were most sensitive for changes in effectiveness of the intervention and selected discount rate. Conclusions T2D screening and recruitment to prevention programs conducted via pharmacies was a dominant option providing both cost savings and QALY gains. The highest savings can be potentially reached by targeting recruitment at men at elevated risk of T2D.

Type 2 diabetes (T2D) with increasing prevalence is a significant global public health challenge. Obesity, unhealthy diet, and low physical activity are one of the major determinants of the rise in T2D prevalence. In addition, family history and genetic risk of diabetes also play a role in the process of developing T2D. Therefore, solutions for the early identification of individuals at high risk for T2D for early targeted detection of T2D, prevention, and intervention are highly preferred. Recently, novel genomic-based polygenic risk scores (PRSs) have been suggested to improve the accuracy of risk prediction supporting the targeting of preventive interventions to those at highest risk for T2D. Therefore, the aim of the present study was to assess the cost-utility of an additional PRS testing information (as a part of overall risk assessment) followed by a lifestyle intervention and an additional medical therapy when estimated 10-year overall risk for T2D exceeded 20% among Finnish individuals screened as at the high-risk category (i.e., 10%–20% 10-year overall risk of T2D) based on traditional risk factors only. For a cost-utility analysis, an individual-level state-transition model with probabilistic sensitivity analysis was constructed. A 1-year cycle length and a lifetime time horizon were applied in the base-case. A 3% discount rate was used for costs and QALYs. Cost-effectiveness acceptability curve (CEAC) and estimates for the expected value of perfect information (EVPI) were calculated to assist decision makers. The use of the targeted PRS strategy reclassified 12.4 percentage points of individuals to be very high-risk individuals who would have been originally classified as high risk using the usual strategy only. Over a lifetime horizon, the targeted PRS was a dominant strategy (i.e., less costly, more effective). One-way and scenario sensitivity analyses showed that results remained dominant in almost all simulations. However, there is uncertainty, since the probability (EVPI) of cost-effectiveness at a WTP of 0€/QALY was 63.0% (243€) indicating the probability that the PRS strategy is a dominant option. In conclusion, the results demonstrated that the PRS provides moderate additional value in Finnish population in risk screening leading to potential cost savings and better quality of life when compared with the current screening methods for T2D risk.

Background: The databases of children’s anthropometric parameters are often outdated, rarely representative and are not always available at an international level. Objectives: To present children’s anthropometric parameters in six European countries that contributed to the Feel4Diabetes project and find country-specific differences. Design/Setting: The Feel4Diabetes study was performed between 2016 and 2018, targeting children in Belgium, Bulgaria, Finland, Greece, Hungary and Spain. The current study presents data from the baseline and the yearly follow-up anthropometric measurements. Subjects: In total, 20,832 measurements of children (48.7% boys) between 6 and 10 years of age were conducted. Main outcome measure: weight, height, BMI. Results: Belgian boys had the lowest body weight and height, while Greek boys had the highest body weight, and Finnish had the highest body height. The highest proportion of overweight (percentile above 85%) and obese boys (percentile above 95%) was in Greece, followed by Hungarian, Spanish, Bulgarian and Finnish boys. In contrast, Belgian boys had the lowest ratio in both categories. Among girls, Greece had the highest; Belgium had the lowest body weight; Finland was the highest in all age categories. The ratio in the overweight range was the highest in Greece, followed by Spanish, Bulgarian and Hungarian girls, who were second in the obese category. Finnish girls had lower and Belgian girls had the lowest ratio in both BMI categories. All the detailed data are presented in tables, and the trends are figures. Conclusions: Our study presents fresh and comparable anthropometric data of children between 6 and 10 years of age in six European countries, supporting the need for appropriate obesity prevention.

Sex differences in fasting glucose and insulin have been identified, but the genetic loci underlying these differences have not. Here, the authors perform a meta-analysis of genome-wide association studies to detect sex-specific and sex-dimorphic loci associated with fasting glucose and insulin.

OBJECTIVES: In a prospective study among workers in an airline company, we explored whether change in work stress symptoms or night shifts was associated with nutrient intake. METHODS: Participants in a workplace type 2 diabetes (T2D) prevention study completed a questionnaire on lifestyle, work stress symptoms, work schedule, and food intake at baseline and after 2.4-years follow-up (211 men and 155 women, 93% with increased risk for T2D). Multiple linear regression models with covariates were used to explore the associations between change in work stress symptoms or night shifts and change in nutrient intake during the follow-up. RESULTS: Among men, an increase in stress and a decrease in perceived workability was associated with a higher proportion of energy (E%) from fat [β 0.6, 95% confidence interval (CI) 0.07–1.11, β 1.3, 95% CI 0.57–2.05] and saturated fat (β 0.3, 95% CI 0.02–0.58, β 0.5, 95% CI 0.14–0.90), respectively. Furthermore, a decrease in workability was associated with lower vitamin C intake (β-9.2, 95% CI -16.56– -1.84) and an increase in sleepiness with higher E% from saturated fat (β 0.7, 95% CI 0.00–0.15). Among women, an increase in work-related fatigue was associated with higher alcohol intake (β 7.5, 95% CI 1.25–13.74) and an increase of night shifts was associated with higher E% from fat (β 0.24, 95% CI 0.00–0.47) and saturated fat (β 0.17, 95% CI 0.04–0.29). CONCLUSIONS: Work stress symptoms were associated with a reduction in diet quality especially among men. The possible impact of work stress symptoms on workers’ dietary habits should be acknowledged and the assessment of dietary habits should consequently be incorporated into occupational health examinations.

Abstract Background The aim of this paper is to present the development of the Feel4Diabetes Healthy Diet Score and to evaluate its clinical validity. Methods Study population consisted of 3268 adults (63% women) from high diabetes risk families living in 6 European countries. Participants filled in questionnaires at baseline and after 1 year, reflecting the dietary goals of the Feel4Diabetes intervention. Based on these questions the Healthy Diet Score was constructed, consisting of the following components: breakfast, vegetables, fruit and berries, sugary drinks, whole-grain cereals, nuts and seeds, low-fat dairy products, oils and fats, red meat, sweet snacks, salty snacks, and family meals. Maximum score for each component was set based on its estimated relative importance regarding T2DM risk, higher score indicating better quality of diet. Clinical measurements included height, weight, waist circumference, heart rate, blood pressure, and fasting blood sampling, with analyses of glucose, total cholesterol, HDL-cholesterol, LDL-cholesterol, and triglycerides. Analysis of (co) variance was used to compare the Healthy Diet Score and its components between countries and sexes using baseline data, and to test differences in clinical characteristics between score categories, adjusted for age, sex and country. Pearson’s correlations were used to study the association between changes from baseline to year 1 in the Healthy Diet Score and clinical markers. To estimate reproducibility, Pearson’s correlations were studied between baseline and 1 year score, within the control group only. Results The mean total score was 52.8 ± 12.8 among women and 46.6 ± 12.8 among men (p

Abstract Background Feel4Diabetes was a school and community based intervention aiming to promote healthy lifestyle and tackle obesity for the prevention of type 2 diabetes among families in 6 European countries. We conducted this literature review in order to guide the development of evidence-based implementation of the Feel4Diabetes intervention. We focused on type 2 diabetes prevention strategies, including all the phases from risk identification to implementation and maintenance. Special focus was given to prevention among vulnerable groups and people under 45 years. Methods Scientific and grey literature published between January 2000 and January 2015 was searched for relevant studies using electronic databases. To present the literature review findings in a systematic way, we used the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. A complementary literature search from February 2015 to December 2018 was also conducted. Results The initial review included 27 studies with a follow-up ≥12 months and 9 studies with a follow-up ≥6 months and with a participant mean age

Abstract Background The implementation of population screening and early prevention strategies targeting individuals at high-risk for type 2 diabetes (T2D) seems to be a public health priority. The current work aimed to describe the screening procedure applied in the Feel4Diabetes-study and examine its effectiveness in identifying individuals and families at high risk, primarily for T2D and secondarily for hypertension, among vulnerable populations in low to middle-income countries (LMICs) and high-income countries (HICs) across Europe. Methods A two-stage screening procedure, using primary schools as the entry-point to the community, was applied in low socioeconomic status (SES) regions in LMICs (Bulgaria-Hungary), HICs (Belgium-Finland) and HICs under austerity measures (Greece-Spain). During the first-stage screening via the school-setting, a total of 20,501 parents (mothers and/or fathers) of schoolchildren from 11,396 families completed the Finnish Diabetes Risk Score (FINDRISC) questionnaire, while their children underwent anthropometric measurements in the school setting. Parents from the identified “high-risk families” (n = 4484) were invited to participate in the second-stage screening, including the measurement of fasting plasma glucose (FPG) and blood pressure (BP). In total, 3153 parents participated in the second-stage screening (mean age 41.1 ± 5.6 years, 65.8% females). Results Among parents who attended the second-stage screening, the prevalence of prediabetes (as defined by impaired fasting glucose; FPG 100-125 mg/dl) and T2D (FPG > 126 mg/dl) was 23.2 and 3.0% respectively, and it was found to be higher in the higher FINDRISC categories. The percentage of undiagnosed T2D among the participants identified with T2D was 53.5%. The prevalence of high normal BP (systolic BP 130-139 mmHg and/ or diastolic BP 85-89 mmHg) and hypertension (systolic BP ≥ 140 mmHg and/ or diastolic BP ≥ 90 mmHg) was 14 and 18.6% respectively, which was also higher in the higher FINDRISC categories. The percentage of cases not receiving antihypertensive treatment among the participants identified with hypertension was 80.3%. Conclusion The findings of the current study indicate that the two-stage school and community-based screening procedure followed, effectively identified high-risk individuals and families in vulnerable populations across Europe. This approach could be potentially scalable and sustainable and support initiatives for the early prevention of T2D and hypertension. Trial registration The Feel4Diabetes-intervention is registered at https://clinicaltrials.gov/ (NCT02393872; date of trial registration: March 20, 2015).

BackgroundDigital health interventions may offer a scalable way to prevent type 2 diabetes (T2D) with minimal burden on health care systems by providing early support for healthy behaviors among adults at increased risk for T2D. However, ensuring continued engagement with digital solutions is a challenge impacting the expected effectiveness. ObjectiveWe aimed to investigate the longitudinal usage patterns of a digital healthy habit formation intervention, BitHabit, and the associations with changes in T2D risk factors. MethodsThis is a secondary analysis of the StopDia (Stop Diabetes) study, an unblinded parallel 1-year randomized controlled trial evaluating the effectiveness of the BitHabit app alone or together with face-to-face group coaching in comparison with routine care in Finland in 2017-2019 among community-dwelling adults (aged 18 to 74 years) at an increased risk of T2D. We used longitudinal data on usage from 1926 participants randomized to the digital intervention arms. Latent class growth models were applied to identify user engagement trajectories with the app during the study. Predictors for trajectory membership were examined with multinomial logistic regression models. Analysis of covariance was used to investigate the association between trajectories and 12-month changes in T2D risk factors. ResultsMore than half (1022/1926, 53.1%) of the participants continued to use the app throughout the 12-month intervention. The following 4 user engagement trajectories were identified: terminated usage (904/1926, 46.9%), weekly usage (731/1926, 38.0%), twice weekly usage (208/1926, 10.8%), and daily usage (83/1926, 4.3%). Active app use during the first month, higher net promoter score after the first 1 to 2 months of use, older age, and better quality of diet at baseline increased the odds of belonging to the continued usage trajectories. Compared with other trajectories, daily usage was associated with a higher increase in diet quality and a more pronounced decrease in BMI and waist circumference at 12 months. ConclusionsDistinct long-term usage trajectories of the BitHabit app were identified, and individual predictors for belonging to different trajectory groups were found. These findings highlight the need for being able to identify individuals likely to disengage from interventions early on, and could be used to inform the development of future adaptive interventions. Trial RegistrationClinicalTrials.gov NCT03156478; https://clinicaltrials.gov/ct2/show/NCT03156478 International Registered Report Identifier (IRRID)RR2-10.1186/s12889-019-6574-y

We present a method for communicating personalized genetic risk information to citizens and their physicians using a secure web portal. We apply the method for 3,177 Finnish individuals in the P5 Study where estimates of genetic and absolute risk, based on genetic and clinical risk factors, of future disease are reported to study participants, allowing individuals to participate in managing their own health. Our method facilitates using polygenic risk score as a personalized tool to estimate a person’s future disease risk while offering a way for health care professionals to utilize the polygenic risk scores as a preventive tool in patient care.

BackgroundClinical trials have shown that type 2 diabetes (T2D) is preventable through lifestyle interventions targeting high-risk people. Nevertheless, large-scale implementation of risk identification followed by preventive interventions has proven to be challenging. Specifically, recruitment of participants into preventive interventions is an important but often overlooked part of the intervention. ObjectiveThis study aims to compare the reach and yield of different communication channels to engage people at increased risk of T2D to fill in a digital screening questionnaire, with emphasis on reaching those at most risk. The participants expressing their willingness to participate is the final step in the risk screening test, and we aim to determine which channels had the most participants reach this step. MethodsWe established a stepwise web-based T2D risk screening tool with automated feedback according to the T2D risk level and, for those who were eligible, an invitation to participate in the StopDia prevention intervention study conducted in a primary health care setting. The risk estimate was based on the Finnish Diabetes Risk Score; history of repeatedly measured high blood glucose concentration; or, among women, previous gestational diabetes. We used several channels to invite people to the StopDia web-based screening tool, and respondents were classified into 11 categories based on the channel through which they reported having learned about StopDia. The demographics of respondents reached via different communication channels were compared using variance analysis. Logistic regression was used to study the respondents’ likelihood of progressing through risk screening steps. ResultsA total of 33,399 persons started filling the StopDia screening tool. Of these, 86.13% (28,768/33,399) completed the test and named at least one communication channel as the source of information about StopDia. Altogether, 26,167 persons filled in sufficient information to obtain risk estimates. Of them, 53.22% (13,925/26,167) were at increased risk, 30.06% (7866/26,167) were men, and 39.77% (10,136/25,485) had low or middle education levels. Most frequently mentioned channels were workplace (n=6817), social media or the internet (n=6712), and newspapers (n=4784). The proportion of individuals at increased risk was highest among those reached via community pharmacies (415/608, 68.3%) and health care (1631/2535, 64.33%). The communication channel reaching the largest percentage of interested and eligible men (1353/3979, 34%) was relatives or friends. Health care (578/1069, 54.07%) and radio or television (225/487, 46.2%) accounted for the largest proportion of people with lower education. ConclusionsCommunication channels reaching a large number of people, such as social media and newspapers, were the most effective channels for identifying at-risk people. Personalized approaches increased the engagement of men and less-educated people. Community pharmacies and health care services reached people with a particularly high T2D risk. Thus, communication and recruitment channels should be selected and modified based on the intended target group. International Registered Report Identifier (IRRID)RR2-10.1186/s12889-019-6574-y

Abstract Background Most research on parenting and childhood obesity and obesity-related behaviours has focused on mothers while fathers have been underrepresented. Yet, recent literature has suggested that fathers uniquely influence their children’s lifestyle behaviours, and hence could also affect their weight status, but this has not yet been scientifically proven. Therefore, the present study aimed to determine whether the association between fathers’ weight status and their children’s weight status is mediated by fathers’ and children’s movement behaviours (i.e. physical activity (PA) and screen time (ST)). Methods Cross-sectional data of 899 European fathers and their children were analyzed. Fathers/male caregivers (mean age = 43.79 ± 5.92 years, mean BMI = 27.08 ± 3.95) completed a questionnaire assessing their own and their children’s (mean age = 8.19 ± 0.99 years, 50.90% boys, mean BMI zscore = 0.44 ± 1.07) movement behaviours. Body Mass Index (BMI, in kg/m2) was calculated based on self-reported (fathers) and objectively measured (children) height and weight. For children, BMI z-scores (SD scores) were calculated to obtain an optimal measure for their weight status. Serial mediation analyses were performed using IBM SPSS 25.0 Statistics for Windows to test whether the association between fathers’ BMI and children’s BMI is mediated by fathers’ PA and children’s PA (model 1) and fathers’ ST and children’s ST (model 2), respectively. Results The present study showed a (partial) mediation effect of fathers’ PA and children’s PA (but not father’s ST and children’s ST) on the association between fathers’ BMI and children’s BMI (model for PA; coefficient: 0.001, 95% CI: [0.0001, 0.002]; model for ST; coefficient: 0.001, 95% CI: [0.000, 0.002]). Furthermore, fathers’ movement behaviours (PA and ST) were positively associated with their children’s movement behaviours (PA and ST) (model for PA, coefficient: 0.281, SE: 0.023, p

Abstract Background The StopDia study is based on the convincing scientific evidence that type 2 diabetes (T2D) and its comorbidities can be prevented by a healthy lifestyle. The need for additional research is based on the fact that the attempts to translate scientific evidence into actions in the real-world health care have not led to permanent and cost-effective models to prevent T2D. The specific aims of the StopDia study following the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework are to 1) improve the Reach of individuals at increased risk, 2) evaluate the Effectiveness and cost-effectiveness of the digital lifestyle intervention and the digital and face-to-face group lifestyle intervention in comparison to routine care in a randomized controlled trial (RCT), and 3) evaluate the Adoption and Implementation of the StopDia model by the participants and the health care organizations at society level. Finally, we will address the Maintenance of the lifestyle changes at participant level and that of the program at organisatory level after the RCT. Methods The StopDia study is carried out in the primary health care system as part of the routine actions of three provinces in Finland, including Northern Savo, Southern Carelia, and Päijät-Häme. We estimate that one fifth of adults aged 18–70 years living in these areas are at increased risk of T2D. We recruit the participants using the StopDia Digital Screening Tool, including questions from the Finnish Diabetes Risk Score (FINDRISC). About 3000 individuals at increased risk of T2D (FINDRISC ≥12 or a history of gestational diabetes, impaired fasting glucose, or impaired glucose tolerance) participate in the one-year randomized controlled trial. We monitor lifestyle factors using the StopDia Digital Questionnaire and metabolism using laboratory tests performed as part of routine actions in the health care system. Discussion Sustainable and scalable models are needed to reach and identify individuals at increased risk of T2D and to deliver personalized and effective lifestyle interventions. With the StopDia study we aim to answer these challenges in a scientific project that is fully digitally integrated into the routine health care. Trial registration ClinicalTials.gov. Identifier: NCT03156478. Date of registration 17.5.2017.

Objective. The strongest locus which associated with type 2 diabetes (T2D) by the common variant rs7903146 is the transcription factor 7-like 2 gene (TCF7L2). We aimed to quantify the interaction of diet/lifestyle interventions and the genetic effect of TCF7L2 rs7903146 on glycemic traits, body weight, or waist circumference in overweight or obese adults in several randomized controlled trials (RCTs). Methods. From October 2016 to May 2018, a large collaborative analysis was performed by pooling individual-participant data from 7 RCTs. These RCTs reported changes in glycemic control and adiposity of the variant rs7903146 after dietary/lifestyle-related interventions in overweight or obese adults. Gene treatment interaction models which used the genetic effect encoded by the allele dose and common covariates were applicable to individual participant data in all studies. Results. In the joint analysis, a total of 7 eligible RCTs were included (n=4,114). Importantly, we observed a significant effect modification of diet/lifestyle-related interventions on the TCF7L2 variant rs7903146 and changes in fasting glucose. Compared with the control group, diet/lifestyle interventions were related to lower fasting glucose by -3.06 (95% CI, -5.77 to -0.36) mg/dL (test for heterogeneity and overall effect: I2=45.1%, p

OBJECTIVES:To assess the effects of early management of hyperglycaemia with antidiabetic drugs plus lifestyle intervention compared with lifestyle alone, on microvascular function in adults with pre-diabetes. METHODS:Trial design: International, multicenter, randomised, partially double-blind, placebo-controlled, clinical trial. PARTICIPANTS:Males and females aged 45-74 years with IFG, IGT or IFG+IGT, recruited from primary care centres in Australia, Austria, Bulgaria, Greece, Kuwait, Poland, Serbia, Spain and Turkey. INTERVENTION:Participants were randomized to placebo; metformin 1.700 mg/day; linagliptin 5 mg/day or fixed-dose combination of linagliptin/metformin. All patients were enrolled in a lifestyle intervention program (diet and physical activity). Drug intervention will last 2 years. Primary Outcome: composite end-point of diabetic retinopathy estimated by the Early Treatment Diabetic Retinopathy Study Score, urinary albumin to creatinine ratio, and skin conductance in feet estimated by the sudomotor index. Secondary outcomes in a subsample include insulin sensitivity, beta-cell function, biomarkers of inflammation and fatty liver disease, quality of life, cognitive function, depressive symptoms and endothelial function. RESULTS:One thousand three hundred ninety one individuals with hyperglycaemia were assessed for eligibility, 424 excluded after screening, 967 allocated to placebo, metformin, linagliptin or to fixed-dose combination of metformin + linagliptin. A total of 809 people (91.1%) accepted and initiated the assigned treatment. Study sample after randomization was well balanced among the four groups. No statistical differences for the main risk factors analysed were observed between those accepting or rejecting treatment initiation. At baseline prevalence of diabetic retinopathy was 4.2%, severe neuropathy 5.3% and nephropathy 5.7%. CONCLUSIONS:ePREDICE is the first -randomized clinical trial with the aim to assess effects of different interventions (lifestyle and pharmacological) on microvascular function in people with pre-diabetes. The trial will provide novel data on lifestyle modification combined with glucose lowering drugs for the prevention of early microvascular complications and diabetes. REGISTRATION:- ClinicalTrials.Gov Identifier: NCT03222765 - EUDRACT Registry Number: 2013-000418-39.

Abstract Background Real life implementation studies performed in different settings have proved that lifestyle interventions in the prevention of type 2 diabetes (DM2) can be effective, although the weight reduction results are typically modest compared to randomized control trials. Our objective was to identify the factors that predict successful weight loss in a less intensive, lower budget, real life setting lifestyle diabetes prevention intervention. Methods Study participants (n = 175) with increased DM2 risk (Finnish Diabetes Risk Score (FINDRISC) > 14) but no diabetes at baseline received ten group lifestyle counselling sessions, physical activity and motivation sessions during a ten-month intervention. Stepwise regression analysis was used to determine demographic, clinical, and lifestyle predictors of successful weight reduction defined as a reduction of ≥5% of the initial body weight. Results At 12 months following the initiation of the intervention, 23.4% of study participants lost ≥5% weight (mean loss of 7.9 kg, SD = 5.8). Increased physical activity (44% vs 25%, p = 0.03), decreased total fat consumption (88% vs 65%, p = 0.006) and adherence to four-five lifestyle goals (71% vs 46%, p = 0.007) were more often reported among those who managed to lose ≥5% weight versus those who did not. In a multivariate analysis, meeting the ≥5% weight loss goal was most effective in individuals with a higher baseline BMI (OR 1.1, 95%CI 1.0–1.2), baseline and medium versus higher education (OR 5.4, 95% CI 1.2–24.7) and a history of increased glucose (OR 2.6, 95%CI 1.1–1.3). A reduction of total fat in the diet was an independent lifestyle predictor, increasing the probability of successful weight loss by 3.8 times (OR 3.8, 95% CI 1.2–11.4). Conclusion Baseline higher BMI, lower education and a history of increased glucose predicted the successful weight loss among individuals with a high risk for the DM2 following lifestyle intervention in a real life primary health care setting. People who manage to lose weight more often adhere to lifestyle changes, while the reduction of total fat in diet independently predicts successful weight loss. Further studies exploring the predictors of success in implementation studies in DM2 prevention should help health care providers redesign interventions to improve their effectiveness and outcomes. Trial registration ISRCTN, ID ISRCTN96692060 , registered 03.08.2016 retrospectively.

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21276-3

Abstract Background Real life implementation studies performed in different settings and populations proved that lifestyle interventions in prevention of type 2 diabetes can be effective. However, little is known about long term results of these translational studies. Therefore, the purpose of this study was to examine the maintenance of diabetes type 2 risk factor reduction achieved 1 year after intervention and during 3 year follow-up in primary health care setting in Poland. Methods Study participants (n = 262), middle aged, slightly obese, with increased type 2 diabetes risk ((age 55.5 (SD = 11.3), BMI 32 (SD = 4.8), Finnish Diabetes Risk Score FINDRISC 18.4 (SD = 2.9)) but no diabetes at baseline, were invited for 1 individual and 10 group lifestyle counselling sessions as well as received 6 motivational phone calls and 2 letters followed by organized physical activity sessions combined with counselling to increase physical activity. Measurements were performed at baseline and then repeated 1 and 3 years after the initiation of the intervention. Results One hundred five participants completed all 3 examinations (baseline age 56.6 (SD = 10.7)), BMI 31.1 (SD = 4.9)), FINDRISC 18.57 (SD = 3.09)). Males comprised 13% of the group, 10% of the patients presented impaired fasting glucose (IFG) and 14% impaired glucose tolerance (IGT). Mean weight of participants decreased by 2.27 kg (SD = 5.25) after 1 year (p = 5% was achieved after 1 and 3 years by 27 and 19% of the participants, respectively. Repeated measures analysis revealed significant changes observed from baseline to year 1 and year 3 in: weight (p = 0.048), BMI (p = 0.001), total cholesterol (p = 0.013), TG (p = 0.061), fasting glucose level (p = 0.037) and FINDRISC (p = 0.001) parameters. The conversion rate to diabetes was 2% after 1 year and 7% after 3 years. Conclusions Type 2 diabetes prevention in real life primary health care setting through lifestyle intervention delivered by trained nurses leads to modest weight reduction, favorable cardiovascular risk factors changes and decrease of diabetes risk. These beneficial outcomes can be maintained at a 3-year follow-up. Trial registration ISRCTN, ID ISRCTN96692060 , registered 03.08.2016 retrospectively

Past genome-wide associate studies have identified hundreds of genetic loci that influence body size and shape when examined one trait at a time. Here, Jeff and colleagues develop an aggregate score of various body traits, and use meta-analysis to find new loci linked to body shape.

Abstract Background The aim was to develop and validate a food-based diet quality index for measuring adherence to the Nordic Nutrition Recommendations (NNR) in a pregnant population with high risk of gestational diabetes (GDM). Methods This study is a part of the Finnish Gestational Diabetes Prevention Study (RADIEL), a lifestyle intervention conducted between 2008 and 2014. The 443 pregnant participants (61 % of those invited), were either obese or had a history of GDM. Food frequency questionnaires collected at 1st trimester served for composing the HFII; a sum of 11 food groups (available score range 0–17) with higher scores reflecting higher adherence to the NNR. Results The average HFII of the participants was 10.2 (SD 2.8, range 2–17). Factor analysis for the HFII component matrix revealed three factors that explained most of the distribution (59 %) of the HFII. As an evidence of the component relevance 9 out of 11 of the HFII components independently contributed to the total score (item-rest correlation coefficients

Lifestyle interventions in type 2 diabetes (DM2) prevention implementation studies can be effective and lasting. Long-term weight loss maintenance enhances the intervention effect through a significant decrease in diabetes incidence over time. Our objective was to identify factors predicting long-term successful weight reduction maintenance achieved during a DM2 prevention program in patients with high DM2 risk in primary health care. Study participants (n = 263), middle-aged, slightly obese with baseline increased DM2 risk (Finnish Diabetes Risk Score (FINDRISC)>14), but no diabetes were invited to receive 11 lifestyle counselling sessions, guided physical activity sessions and motivational support during 10-months. The study participants had three clinical examinations during the study (baseline, one and three years). Stepwise regression analysis was used to determine demographic, clinical, and lifestyle predictors of weight reduction maintenance two years after the discontinuation of the intervention. Out of 105 patients who completed all three examinations (baseline age 56.6 (standard deviation (SD) = 10.7), body mass index 31.1 kg/m2 (SD = 4.9), FINDRISC 18.6 (SD = 3.1)), 73 patients (70%) showed weight loss during the intervention (mean weight loss 4.2 kg, SD = 5.1). The total weight loss achieved in the maintainers (27 of 73 study participants) two years after the intervention had finished was 6.54 kg (4.47 kg+2.0 kg). The non-maintainers, on the other hand, returned to their initial weight at the start of the intervention (+0.21 kg). In multivariable analysis baseline history of increased glucose (odds ratio (OR) = 3.7; 95% confidence interval (CI) 1.0-13.6) and reduction of total fat in diet during follow-up (OR = 4.3; 95% CI 1.5-12.2) were independent predictors of successful weight loss. Further studies exploring predictors of weight loss maintenance in diabetes prevention are needed to help health care providers to redesign interventions and improve long-term outcomes of real life interventions.

The DE-PLAN-CAT project (Diabetes in Europe-Prevention using lifestyle, physical activity and nutritional intervention-Catalonia) has shown that an intensive lifestyle intervention is feasible in the primary care setting and substantially reduces the incidence of diabetes among high-risk Mediterranean participants. The DP-TRANSFERS project (Diabetes Prevention-Transferring findings from European research to society) is a large-scale national programme aimed at implementing this intervention in primary care centres whenever feasible.A multidisciplinary committee first evaluated the programme in health professionals and then participants without diabetes aged 45-75 years identified as being at risk of developing diabetes: FINDRISC (Finnish Diabetes Risk Score)>11 and/or pre-diabetes diagnosis. Implementation was supported by a 4-channel transfer approach (institutional relationships, facilitator workshops, collaborative groupware, programme website) and built upon a 3-step (screening, intervention, follow-up) real-life strategy. The 2-year lifestyle intervention included a 9-hour basic module (6 sessions) and a subsequent 15-hour continuity module (10 sessions) delivered by trained primary healthcare professionals. A 3-level (centre, professionals and participants) descriptive analysis was conducted using cluster sampling to assess results and barriers identified one year after implementation.The programme was started in June-2016 and evaluated in July-2017. In all, 103 centres covering all the primary care services for 1.4 million inhabitants (27.9% of all centres in Catalonia) and 506 professionals agreed to develop the programme. At the end of the first year, 83 centres (80.6%) remained active and 305 professionals (60.3%) maintained regular web-based activities. Implementation was not feasible in 20 centres (19.4%), and 5 main barriers were prioritized: lack of healthcare manager commitment; discontinuity of the initial effort; substantial increase in staff workload; shift in professional status and lack of acceptance. Overall, 1819 people were screened and 1458 (80.1%) followed the lifestyle intervention, with 1190 (81.6% or 65.4% of those screened) participating in the basic module and 912 in the continuity module (62.5% or 50.1%, respectively).A large-scale lifestyle intervention in primary care can be properly implemented within a reasonably short time using existing public healthcare resources. Regrettably, one fifth of the centres and more than one third of the professionals showed substantial resistance to performing these additional activities.

AIM. To present the most common quality criteria in health promotion interventions in type 2 diabetes mellitus (T2DM). METHODS. A systematic literature search was conducted to identify review articles, health technology assessments and policy reports of evaluated health promotion interventions in T2DM. A descriptive analysis of study characteristics and evaluation criteria are presented. RESULTS. Seven studies met the inclusion criteria. The findings indicate that the most common health promotion interventions used in T2DM are initiatives targeting health care professionals. The main ambition of the programs was to increase the collaboration between health care professionals and patients, and between health care centres, program managers and community stakeholders. CONCLUSIONS. This investigation extends our knowledge of the most common health promotion interventions in T2DM and which structure, process and outcome measurements that are reported in such interventions. Future research could usefully explore how the effectiveness of multicomponent and complex interventions may be evaluated and extend the association of these factors into other settings and in relation to other lifestyle related chronic diseases.

OBJECTIVE. To contribute to the development of a set of quality criteria for patient education and health professionals training that could be applied in European countries. METHODS. Literature review quality criteria, pre-selection based on a comparison of the criteria, peer group and expert based selection of the criteria. RESULTS. 14 quality criteria were selected: goals, rationale, target group, setting, scheduling of the education/training sessions, environmental requirements, qualification of the trainers/educators, core components of the educator/trainer's role, curriculum, education methods, education didactics, monitoring of the effectiveness and quality of the program, implementation level and source of funding. DISCUSSION. A set of preliminary quality criteria for patient education and health professionals training was developed, which could be applied in European countries.

OBJECTIVE. Type 2 diabetes can be efficiently prevented by lifestyle intervention provided for people at high diabetes risk. The aim of this paper was to conduct a literature search on existing quality indicators for type 2 diabetes prevention and to collate and present a set of indicators that could be applied in European countries with different health care systems and cultures. METHODS. Scientific and grey literature was searched for relevant studies using electronic databases. We also hand searched previous systematic reviews and reference lists of relevant articles. RESULTS. The only publication identified was the report presenting the results from the IMAGE project. The IMAGE indicators were used as the basis for the proposed indicators. CONCLUSIONS. Publications on quality indicators of diabetes prevention programmes are scarce. The quality indicators presented here are a first step toward the definition of a core set of European indicators to monitor and improve the quality of diabetes prevention.

Working in shifts, especially if night shifts are included, is associated with many adverse health effects varying from gastrointestinal disturbances to cardiovascular diseases, metabolic syndrome, and type 2 diabetes (1–4). The exact mechanisms for these associations are not firmly established (5). Short-term sleep restriction is known to induce insulin resistance and, for example, disturbances in fat metabolism (6), and shift workers are known to suffer from sleep loss. It is plausible that lifestyle factors related to shift work play a role as well. The accumulation of body fat leading to overweight and obesity is one of the key factors behind the development of metabolic disturbances in general population, and we can assume it to be so also among shift workers (7). There seems to be even a dose–response association, with an increasing trend in weight with increasing duration of shift work (8). But what exactly is it in shift work that predisposes those who do it to weight gain? And can we do something about it? In their systematic review of longitudinal studies, Van Drongelen et al (9) found a strong evidence for a crude association between shift work exposure and body weight increase; however the confounder-adjusted associations were found to be inconclusive. This indicates that it is not shift work per se but other factors related to or associated with shift work that lead to body fat accumulation. On the other hand, in a recent systematic review, Bonham et al (10) concluded that energy intake does not differ between day and shift workers, and suggest that other factors such as circadian misalignment, meal timing, food choice and diurnal variation of energy metabolism at night may be responsible for the increased rates of obesity observed among shift workers. In general, only minor differences in nutrient intake between day and shift workers have been identified, and the results have been somewhat conflicting. It has been suggested that shift workers have more eating events per day than day workers (11), and it seems that shift workers make more unfavorable food choices than day workers do, preferring snack foods and sugary drinks (11, 12). In a recent study, shift working men were less likely to consume vegetables and fruits daily and women had higher intake of saturated fat compared with day workers (13). In a paper by Hulsegge et al (14) in this issue, shift workers were found to have a higher energy intake than day workers (56 kcal/d) and a slightly higher consumption of grains, dairy products, meat and fish and lower consumption of cakes and biscuits. No difference in savory snacks, sweets, soft drinks or juices were found. The difference in energy intake was largest for shift workers with ≥5 night shifts/month, who consumed 103 kcal/d more than day workers. The authors conclude that shift and day workers’ dietary quality is the same, but suggest that a higher energy intake among shift workers may be one of the causes of shift-work-induced overweight, obesity, and other adverse health outcomes; a reasonable suggestion if we acknowledge as fact that overweight indeed develops as a result of positive energy balance. The study included a relatively large population-based sample of 683 and 7173 shift and day workers, respectively from the original cohort of 40 010 men and women. The analyses were cross-sectional, with dietary data collection based on a 178-item semi-quantitative food frequency questionnaire for the past year diet and retrospective data collection on work schedule 14–20 years earlier. The analyses were adjusted for several confounders, including age, sex, smoking, physical activity, and body mass index (BMI). No differences were presented for clinical risk factors, except that shift workers had slightly higher BMI compared with day workers. BMI is a crude measure of body adiposity, but does not tell anything about the actual body size, which is the most important predictor of energy expenditure (15). Due to the study’s cross-sectional study design, we do not know if the workers were eating more calories because they had higher BMI or if they had higher BMI because they were eating more calories. Furthermore, level of physical activity was estimated with a short questionnaire, including one question about type of work (sedentary, standing, physical, or heavy manual). This simple categorization may not be able to fully adjust for differing energy needs in different occupations. Therefore, Hulsegge at al’s conclusion that “…future studies need to confirm that shift workers indeed have a higher energy intake than day workers independent of energy requirements” is justified. Another important point in future studies is to use reliable and valid methods for dietary data collection. A review by Lowden et al (16) evaluated the results of shift workers’ dietary intake studies since 1967. They highlighted several shortcomings of dietary studies among shift workers, including unreliable methods used for nutrition research. Shift work can change food timing while a healthy diet can be difficult to maintain especially if the facilities for eating outside the normal working hours are not well organized and healthy food choices are not available. Having catering services in worksites may be associated with healthier eating habits (17). If and when food frequency questionnaires are used, they should specifically be designed to capture the typical nutritional features in shift work, such as the irregularities in dietary patterns. Food diaries collected for a sufficient number of days can still be regarded as the most reliable way of collecting data on both the pattern and composition of diet. They are not bound by fixed food items, dish compositions, and portion sizes but allow free, real-time recording of meals and snacks, without the need for retrospection and food-item classification. Can we improve shift worker’s diet? Nutrition advice should be a standard part of the shift workers’ lifestyle counselling in occupational healthcare and the obligatory health check-ups demanded by national legislation in many countries (18). Whether or not shift work in general predisposes individuals to poor food choices or increased energy intake is not definitively proven. Either way, every shift worker should be considered individually and lifestyle counselling based on personal situation and estimation of individual risk factors for metabolic and other chronic diseases should be provided. References 1. Pietroiusti A, Neri A, Somma G, Coppeta L, Iavicoli I, Bergamaschi A, Magrini A. Incidence of metabolic syndrome among night-shift healthcare workers. Occup Environ Med. 2010; 67:54-57. http://dx.doi.org/10.1136/oem.2009.046797 2. Knutsson A, Boggild H. Gastrointestinal disorders among shift workers. Scand J Work Environ Health. 2010; 36:85-95. http://dx.doi.org/10.5271/sjweh.2897 3. Vyas MV, Garg AX, Iansavichus AV, Costella J, Donner A, Laugsand LE, Janszky I, Mrkobrada M, Parraga G, Hackam DG. Shift work and vascular events: Systematic review and meta-analysis. BMJ. 2012; 345:e4800. http://dx.doi.org/10.1136/bmj.e4800 4. Hansen AB, Stayner L, Hansen J, Andersen ZJ. Night shift work and incidence of diabetes in the danish nurse cohort. Occup Environ Med. 2016; 73:262-268. http://dx.doi.org/10.1136/oemed-2015-103342 5. Puttonen S, Härmä M, Hublin C. Shift work and cardiovascular disease – pathways from circadian stress to morbidity. Scand J Work Environ Health. 2010; 36:96-108. http://dx.doi.org/10.5271/sjweh.2894 6. Broussard JL, Chapotot F, Abraham V, Day A, Delebecque F, Whitmore HR, Tasali E. Sleep restriction increases free fatty acids in healthy men. Diabetologia. 2015; 58:791-798. http://dx.doi.org/10.1007/s00125-015-3500-4 7. Proper KI, van de Langenberg D, Rodenburg W, Vermeulen RC, van der Beek AJ, van Steeg H, van Kerkhof LW. The relationship between shift work and metabolic risk factors: A systematic review of longitudinal studies. Am J Prev Med. 2016; 50:e147-57. http://dx.doi.org/10.1016/j.amepre.2015.11.013 8. van Amelsvoort LG, Schouten EG, Kok FJ. Duration of shiftwork related to body mass index and waist to hip ratio. Int J Obes Relat Metab Disord. 1999; 23:973-978. http://dx.doi.org/10.1038/sj.ijo.0801028 9. van Drongelen A, Boot CR, Merkus SL, Smid T, van der Beek AJ. The effects of shift work on body weight change - a systematic review of longitudinal studies. Scand J Work Environ Health. 2011; 37:263-275. http://dx.doi.org/10.5271/sjweh.3143 10. Bonham MP, Bonnell EK, Huggins CE. Energy intake of shift workers compared to fixed day workers: A systematic review and meta-analysis. Chronobiol Int. 2016; 33:1086-1100. http://dx.doi.org/10.1080/07420528.2016.1192188 11. de Assis MA, Kupek E, Nahas MV, Bellisle F. Food intake and circadian rhythms in shift workers with a high workload. Appetite. 2003; 40:175-183. http://dx.doi.org/10.1016/S0195-666302)00133-2 12. Waterhouse J, Buckley P, Edwards B, Reilly T. Measurement of, and some reasons for, differences in eating habits between night and day workers. Chronobiol Int. 2003; 20:1075-1092. http://dx.doi.org/10.1081/CBI-120025536 13. Hemio K, Puttonen S, Viitasalo K, Harma M, Peltonen M, Lindstrom J. Food and nutrient intake among workers with different shift systems. Occup Environ Med. 2015; 72:513-520. http://dx.doi.org/10.1136/oemed-2014-102624 14. Hulsegge G, Boer JMA, van der Beek AJ, Verschuren WMM, Sluijs I, Vermeulen R, et al. Shift workers have a similar diet quality but higher energy intake than day workers. Scand J Work Environ Health – online first. http://dx.doi.org/10.5271/sjweh.3593 15. Mifflin MD, St Jeor ST, Hill LA, Scott BJ, Daugherty SA, Koh YO. A new predictive equation for resting energy expenditure in healthy individuals. Am J Clin Nutr. 1990; 51:241-247. 16. Lowden A, Moreno C, Holmbäck U, Lennernäs M, Tucker P. Eating and shift work - effects on habits, metabolism and performance. Scand J Work Environ Health. 2010; 36:150-162. http://dx.doi.org/10.5271/sjweh.2898 17. Raulio S, Roos E, Prattala R. School and workplace meals promote healthy food habits. Public Health Nutr. 2010; 13:987-992. http://dx.doi.org/10.1017/S1368980010001199 18. Viitasalo K, Hemio K, Puttonen S, Hyvarinen HK, Leiviska J, Harma M, Peltonen M, Lindstrom J. Prevention of diabetes and cardiovascular diseases in occupational health care: Feasibility and effectiveness. Prim Care Diabetes. 2015; 9:96-104. http://dx.doi.org/10.1016/j.pcd.2014.07.008

Healthcare systems do not fit well with the "modern" patient, who has a right to autonomy and self-determination. The services that are designed and delivered in policy contexts are not prone to encourage innovation. National Diabetes Plans, defined as "any formal strategy for improving diabetes policy, services and outcomes that encompass structured and integrated or linked activities which are planned and co-ordinated nationally and conducted at the national, regional, and local level", may hold a great potential not only to improve prevention and care for type 2 diabetes, but also for transforming healthcare delivery. Today, changes to adapt healthcare delivery tend to be implemented within existing provider structures, with limited understanding of specific context, structures, processes and potential for change. National Diabetes Plan can be a diagnostic tool for barriers, can be a driver for planning the change, and can help develop capacities and competences that are needed to strengthen healthcare systems to better address health promotion and chronic diseases.

[This corrects the article DOI: 10.1371/journal.pgen.1005378.].

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR

To determine the association between HbA1c, fasting plasma glucose (FPG), 1-hour (1 hPG) and 2-hour (2 hPG) glucose after an oral glucose tolerance test (OGTT) and cardiovascular disease in individuals with elevated risk for diabetes.We studied the relationship between baseline, updated mean and updated (last) value of HbA1c, FPG, 1 hPG and 2 hPG after an oral 75 g glucose tolerance test (OGTT) and acute CVD events in 504 individuals with impaired glucose tolerance (IGT) at baseline enrolled in the Finnish Diabetes Prevention Study.Follow-up of clinical trial.504 individuals with IGT were followed with yearly evaluations with OGTT, FPG and HbA1c.Relative risk of CVD.Over a median follow-up of 9.0 years 34 (6.7%) participants had a CVD event, which increased to 52 (10.3%) over a median follow-up of 13.0 years when including events that occurred among participants following a diagnosis of diabetes. Updated mean HbA1c, 1 hPG and 2 hPG, HR per 1 unit SD of 1.57 (95% CI 1.16 to 2.11), p = 0.0032, 1.51 (1.03 to 2.23), p = 0.036 and 1.60 (1.10 to 2.34), p = 0.014, respectively, but not FPG (p = 0.11), were related to CVD. In analyses of the last value prior to the CVD event the same three glycaemic measurements were associated with the CVD events, with HRs per 1 unit SD of 1.45 (1.06 to 1.98), p = 0.020, 1.55 (1.04 to 2.29), p = 0.030 and 2.19 (1.51 to 3.18), p

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR

Genome-wide association studies (GWAS) have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C), respectively, in individuals of African American (n = 6,832), East Asian (n = 9,449), and European (n = 10,829) ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P

Prevalence of type 2 diabetes (T2D) is increasing worldwide. T2D prevention by lifestyle intervention is effective. Pragmatic scalable interventions are needed, with evidence to efficiently target and monitor such interventions. We report pooled analyses of data from three European trial cohorts: to analyse T2D incidence, sustained weight loss and utility of risk predictors.We analysed data on 749 adults with impaired glucose tolerance (278 men and 471 women, mean age 56 years, mean BMI 31 kgm(-2)) recruited between 1993 and 2003, and randomised to intensive lifestyle intervention (I) or lifestyle advice control (C). The intervention aimed to increase physical activity, modify diet, and promote weight loss≥5%. Using Cox-regression survival analysis, we assessed T2D incidence and the impact on T2D incidence of sustained weight loss, and of baseline cut-point values of FINDRISC score, fasting plasma glucose (FPG), and HbA1c.Mean follow-up duration was 3.1 years. T2D was diagnosed in 139 participants (I = 45/379, C = 94/370). Cumulative T2D incidence was 57% lower in the intervention compared with the control group (HR 0.42 (95% CI 0.29 to 0.60) P

Leukocyte telomere length (TL) is considered a biomarker for biological aging. Shortened TL has been observed in many complex diseases, including type 2 diabetes (T2DM). Lifestyle intervention studies, e.g. the Diabetes Prevention Study (DPS), have shown a decrease in the incidence of T2DM by promoting healthy lifestyles in individuals with impaired glucose tolerance (IGT). Our aim was to study in the DPS the influence of the lifestyle intervention on TL. TL was measured by quantitative PCR-based method at two time points (N = 334 and 343) on average 4.5 years apart during the active intervention and post-intervention follow-up. TL inversely correlated with age. Our main finding was that TL increased in about two thirds of the individuals both in the intervention and in the control groups during follow-up; TL increased most in individuals with the shortest TL at the first measurement. TL was not associated with development of T2DM, nor did lifestyle intervention have an effect on TL. No association between insulin secretion or insulin resistance indices and TL was observed. We did not detect an association between TL and development of T2DM in the DPS participants. It could be due to all participants being overweight and having IGT at baseline, both of which have been found to be independently associated with shorter leukocyte TL in some earlier studies. TL had no substantial role in worsening of glucose tolerance in people with IGT. Our study confirms that leukocyte TL can increase with time even in obese people with impaired glucose metabolism.

The Finnish Diabetes Prevention Study (DPS) was a randomized controlled trial, which showed that it is possible to prevent type 2 diabetes by lifestyle changes. The aim of the present study was to examine whether the lifestyle intervention had an effect on the ten-year mortality and cardiovascular morbidity in the DPS participants originally randomized either into an intervention or control group. Furthermore, we compared these results with a population-based cohort comprising individuals of varying glucose tolerance states.Middle-aged, overweight people with IGT (n = 522) were randomized into intensive intervention (including physical activity, weight reduction and dietary counseling), or control "mini-intervention" group. Median length of the intervention period was 4 years and the mean follow-up was 10.6 years. The population-based reference study cohort included 1881 individuals (1570 with normal glucose tolerance, 183 with IGT, 59 with screen-detected type 2 diabetes, 69 with previously known type 2 diabetes) with the mean follow-up of 13.8 years. Mortality and cardiovascular morbidity data were collected from the national Hospital Discharge Register and Causes of Death Register. Among the DPS participants who consented for register linkage (n = 505), total mortality (2.2 vs. 3.8 per 1000 person years, hazard ratio HR = 0.57, 95% CI 0.21-1.58) and cardiovascular morbidity (22.9 vs. 22.0 per 1000 person years, HR = 1.04, 95% CI 0.72-1.51) did not differ significantly between the intervention and control groups. Compared with the population-based cohort with impaired glucose tolerance, adjusted HRs were 0.21 (95% CI 0.09-0.52) and 0.39 (95% CI 0.20-0.79) for total mortality, and 0.89 (95% CI 0.62-1.27) and 0.87 (0.60-1.27) for cardiovascular morbidity in the intervention and control groups of the DPS, respectively. The risk of death in DPS combined cohort was markedly lower than in FINRISK IGT cohort (adjusted HR 0.30, 95% CI 0.17-0.54), but there was no significant difference in the risk of CVD (adjusted HR 0.88, 95% CI 0.64-1.21).Lifestyle intervention among persons with IGT did not decrease cardiovascular morbidity during the first 10 years of follow-up. However, the statistical power may not be sufficient to detect small differences between the intervention and control groups. Low total mortality among participants of the DPS compared with individuals with IGT in the general population could be ascribed to a lower cardiovascular risk profile at baseline and regular follow-up.ClinicalTrials.gov NCT00518167.

Ghrelin may influence the development of obesity through its role in the control of energy balance, food intake, and regulation of body weight. The effects of ghrelin are mediated via the growth hormone secretagogue receptor (GHSR).We genotyped 7 single nucleotide polymorphisms (SNPs) in the GHSR gene and assessed the association between those SNPs and obesity and type 2 diabetes-related phenotypes from 507 middle-aged overweight persons with impaired glucose tolerance participating in the Finnish Diabetes Prevention Study (DPS). Additionally, we performed in silico screening of the 5'-regulatory region of GHSR and evaluated SNPs disrupting putative transcription factor (TF) binding sites in vitro with gelshift assays to determine differences in protein binding between different alleles of SNPs. Rs9819506 in the promoter region of GHSR was associated with body weight (p = 0.036); persons with rs9819506-AA genotype having the lowest body weight. Individuals with rs490683-CC genotype displayed highest weight loss in the whole study population (p = 0.032). The false discovery rate for these results was

ABSTRACT: Introduction: The Finnish Diabetes Risk Score (FINDRISC) is a tool that was initially developed to predict the risk of developing type 2 diabetes mellitus in adults. This tool is simple, quick to apply, non-invasive, and low-cost. The aims of this study were to perform a translation and cultural adaptation of the original version of FINDRISC into Brazilian Portuguese and to assess test-retest reliability. Methodology: This work was done following the ISPOR Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes Measures. Once the final Brazilian Portuguese version (FINDRISC-Br) was developed, the reliability assessment was performed using a non-random sample of 83 individuals attending a primary care health center. Each participant was interviewed by trained registered dieticians on two occasions with a mean interval of 14 days. The reliability assessment was performed by analyzing the level of agreement between the test-retest responses of FINDRISC-Br using Cohen’s kappa coefficient and the intraclass correlation coefficient (ICC). Results: The steps of ISPOR guidelines were consecutively followed without major problems. Regarding the reliability assessment, the questionnaire as a whole presented adequate reliability (Cohen’s kappa = 0.82, 95%CI 0.72 - 0.92 and ICC = 0.94, 95%CI 0.91 - 0.96). Conclusion: FINDRISC was translated into Brazilian Portuguese and culturally adapted following standard procedures. FINDRISC-Br has thus become available for use and has potential as a screening tool in different Brazilian settings and applications.