Basic lifestyle advice to individuals at high risk of type 2 diabetes : a 2-year population-based diabetes prevention study. The DE-PLAN intervention in the HUNT Study, Norway

Objective Among individuals at high risk for diabetes identified through a population survey, we performed an intervention study with basic lifestyle advice aiming to prevent diabetes. Research design and methods Among 50 806 participants in the HUNT3 Survey (2006-2008), 5297 individuals with Finnish Diabetes Risc Score (FINDRISC >= 15 were invited to an oral glucose tolerance test (OGTT) and an education session with lifestyle advice, and 2634 (49.7%) attended. Among them, 2380 people without diabetes were included in the prevention study with repeated examinations and education sessions after 6, 12, and 24 months. We examined participation, diabetes incidence, glycemia, and adiposity during follow-up. Results Of 2380 participants, 1212 (50.9%) participated in >= 3 of the four examinations. Diabetes was detected in 3.5%, 3.1%, and 4.0% of individuals at the 6-month, 12-month, and 24-month examinations, respectively, indicating a 10.3% 2-year diabetes incidence. Mean (95% CI) increases from baseline to 2-year follow-up were 0.30 (0.29 to 0.32) percentage points (3.3 (3.2 to 3.5) mmol/mol) for Hemoglobin A 1c, 0.13 (0.10 to 0.16) mmol/L for fasting serum-glucose, 0.46 (0.36 to 0.56) mmol/L for 2-hour OGTT s-glucose, 0.30 (0.19 to 0.40) kg/m(2) forbody mass index (BMI) (all p 5% weight loss during follow-up; their fasting and 2-hour s-glucose did not increase, and HbA 1c increased less than in other participants. Conclusion Basic lifestyle advice given to high-risk individuals during three group sessions with 6-month intervals was not effective in reducing 2-year diabetes risk.Peer reviewe

Genetic associations with temporal shifts in obesity and severe obesity during the obesity epidemic in Norway:A longitudinal population-based cohort (the HUNT Study)

Background Obesity has tripled worldwide since 1975 as environments are becoming more obesogenic. Our study investigates how changes in population weight and obesity over time are associated with genetic predisposition in the context of an obesogenic environment over 6 decades and examines the robustness of the findings using sibling design. Methods and findings A total of 67,110 individuals aged 13–80 years in the Nord-Trøndelag region of Norway participated with repeated standardized body mass index (BMI) measurements from 1966 to 2019 and were genotyped in a longitudinal population-based health study, the Trøndelag Health Study (the HUNT Study). Genotyping required survival to and participation in the HUNT Study in the 1990s or 2000s. Linear mixed models with observations nested within individuals were used to model the association between a genome-wide polygenic score (GPS) for BMI and BMI, while generalized estimating equations were used for obesity (BMI ≥ 30 kg/m2) and severe obesity (BMI ≥ 35 kg/m2). The increase in the average BMI and prevalence of obesity was steeper among the genetically predisposed. Among 35-year-old men, the prevalence of obesity for the least predisposed tenth increased from 0.9% (95% confidence interval [CI] 0.6% to 1.2%) to 6.5% (95% CI 5.0% to 8.0%), while the most predisposed tenth increased from 14.2% (95% CI 12.6% to 15.7%) to 39.6% (95% CI 36.1% to 43.0%). Equivalently for women of the same age, the prevalence of obesity for the least predisposed tenth increased from 1.1% (95% CI 0.7% to1.5%) to 7.6% (95% CI 6.0% to 9.2%), while the most predisposed tenth increased from 15.4% (95% CI 13.7% to 17.2%) to 42.0% (95% CI 38.7% to 45.4%). Thus, for 35-year-old men and women, respectively, the absolute change in the prevalence of obesity from 1966 to 2019 was 19.8 percentage points (95% CI 16.2 to 23.5, p < 0.0001) and 20.0 percentage points (95% CI 16.4 to 23.7, p < 0.0001) greater for the most predisposed tenth compared with the least predisposed tenth, defined using the GPS for BMI. The corresponding absolute changes in the prevalence of severe obesity for men and women, respectively, were 8.5 percentage points (95% CI 6.3 to 10.7, p < 0.0001) and 12.6 percentage points (95% CI 9.6 to 15.6, p < 0.0001) greater for the most predisposed tenth. The greater increase in BMI in genetically predisposed individuals over time was apparent after adjustment for family-level confounding using a sibling design. Key limitations include a slightly lower survival to date of genetic testing for the older cohorts and that we apply a contemporary genetic score to past time periods. Future research should validate our findings using a polygenic risk score constructed from historical data. Conclusions In the context of increasingly obesogenic changes in our environment over 6 decades, our findings reveal a growing inequality in the risk for obesity and severe obesity across GPS tenths. Our results suggest that while obesity is a partially heritable trait, it is still modifiable by environmental factors. While it may be possible to identify those most susceptible to environmental change, who thus have the most to gain from preventive measures, efforts to reverse the obesogenic environment will benefit the whole population and help resolve the obesity epidemic

Is smoking heaviness causally associated with alcohol use? A Mendelian randomization study in four European cohorts

BACKGROUND: Observational studies have shown that tobacco and alcohol use co-occur, but it is not clear whether this relationship is causal. METHODS: Using data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and UK Biobank, we used observational methods to test the hypothesis that smoking heaviness increases alcohol consumption. Mendelian randomization (MR) analyses were then used to test the causal relationship between smoking heaviness and alcohol consumption using 55 967 smokers from four European studies [ALSPAC, The Nord-Trøndelag Health Study (HUNT), the Copenhagen General Population Study (CGPS) and UK Biobank]. MR analyses used rs1051730/rs16969968 as a genetic proxy for smoking heaviness. RESULTS: Observational results provided evidence of an association between cigarettes per day and weekly alcohol consumption (increase in units of alcohol per additional cigarette smoked per day = 0.10, 95% confidence interval (CI) 0.05 to 0.15, P ≤ 0.001 in ALSPAC; and 0.48, 95% CI 0.45 to 0.52, P ≤ 0.001 in UK Biobank). However, there was little evidence for an association between rs1051730/rs16969968 and units of alcohol consumed per week across ALSPAC, HUNT, CGPS and UK Biobank (standard deviation increase in units of alcohol per additional copy of the risk allele = –0.004, 95% CI –0.023 to 0.016, P=0.708, I² = 51.9%). We had 99% and 88% power to detect a change of 0.03 and 0.02 standard deviation units of alcohol per additional copy of the risk allele, respectively. CONCLUSIONS: Previously reported associations between smoking and alcohol are unlikely to be causal, and may be the result of confounding and/or reverse causation. This has implications for public health research and intervention research

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Investigating the possible causal association of smoking with depression and anxiety using Mendelian randomisation meta-analysis : the CARTA consortium

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Stratification by Smoking Status Reveals an Association of CHRNA5-A3-B4 Genotype with Body Mass Index in Never Smokers

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Heavier smoking may lead to a relative increase in waist circumference : evidence for causal relationship from a Mendelian iandomisation meta-analysis. The CARTA consortium

Objectives: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity. Design: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes. Participants: 148 731 current, former and neversmokers of European ancestry aged >= 16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). Primary outcome measures: Waist and hip circumferences, and waist-hip ratio. Results: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% Cl -0.57% to - 0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% Cl - 0.42% to -0.19), -0.08% (-0.19% to 0.03%) and - 0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele. Conclusions: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity.Peer reviewe

Validity of the FINDRISC as a prediction tool for diabetes in a contemporary Norwegian population : a 10-year follow-up of the HUNT study

Objective The Finnish Diabetes Risk Score (FINDRISC) is a recommended tool for type 2 diabetes prediction. There is a lack of studies examining the performance of the current 0-26 point FINDRISC scale. We examined the validity of FINDRISC in a contemporary Norwegian risk environment. Research design and methods We followed 47 804 participants without known diabetes and aged >= 20 years in the HUNT3 survey (2006-2008) by linkage to information on glucose-lowering drug dispensing in the Norwegian Prescription Database (2004-2016). We estimated the C-statistic, sensitivity and specificity of FINDRISC as predictor of incident diabetes, as indicated by incident use of glucose-lowering drugs. We estimated the 10-year cumulative diabetes incidence by categories of FINDRISC. Results The C-statistic (95% CI) of FINDRISC in predicting future diabetes was 0.77 (0.76 to 0.78). FINDRISC >= 15 (the conventional cut-off value) had a sensitivity of 38% and a specificity of 90%. The 10-year cumulative diabetes incidence (95% CI) was 4.0% (3.8% to 4.2%) in the entire study population, 13.5% (12.5% to 14.5%) for people with FINDRISC >= 15 and 2.8% (2.6% to 3.0%) for people with FINDRISC = 15 had a positive predictive value of 13.5% and a negative predictive value of 97.2% for diabetes within the next 10 years. To approach a similar sensitivity as in the study in which FINDRISC was developed, we would have to lower the cut-off value for elevated FINDRISC to >= 11. This would yield a sensitivity of 73%, specificity of 67%, positive predictive value of 7.7% and negative predictive value of 98.5%. Conclusions The validity of FINDRISC and the risk of diabetes among people with FINDRISC >= 15 is substantially lower in the contemporary Norwegian population than assumed in official guidelines. To identify similar to 3/4 of those developing diabetes within the next 10 years, we would have to lower the threshold for elevated FINDRISC to >= 11, which would label similar to 1/3 of the entire adult population as having an elevated FINDRISC necessitating a glycemia assessment.Peer reviewe