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Objective: Previous studies using longitudinal weight data to characterize obesity are based on populations of limited size and mostly include individuals of all body mass index (BMI) levels, without focusing on weight changes among people with obesity. This study aimed to identify BMI trajectories over 5 years in a large population with obesity, and to determine the trajectories' association with mortality. Methods: For inclusion, individuals aged 30–74 years at index date (1 January 2013) with continuous membership in Clalit Health Services from 2008 to 2012 were required to have ≥1 BMI measurement per year in ≥3 calendar years during this period, of which at least one was ≥30 kg/m2. Latent class analysis was used to generate BMI trajectories over 5 years (2008–2012). Cox proportional hazards models were used to assess the association between BMI trajectories and all‐cause mortality during follow‐up (2013–2017). Results: In total, 367,141 individuals met all inclusion criteria. Mean age was 57.2 years; 41% were men. The optimal model was a quadratic model with four classes of BMI clusters. Most individuals (90.0%) had stable high BMI over time. Individuals in this cluster had significantly lower mortality than individuals in the other trajectory clusters (p < 0.01), including clusters of people with dynamic weight trajectories. Conclusions: The results of the current study show that people with stable high weight had the lowest mortality of all four BMI trajectories identified. These findings help to expand the scientific understanding of the impact that weight trajectories have on health outcomes, while demonstrating the challenges of discerning the cumulative effects of obesity and weight change, and suggest that dynamic historical measures of BMI should be considered when assessing patients' future risk of obesity‐related morbidity and mortality, and when choosing a treatment strategy. [ABSTRACT FROM AUTHOR]

Objective: Obesity rates in the United Kingdom are some of the highest in Western Europe, with considerable clinical and societal impacts. Obesity is associated with type 2 diabetes (T2D), osteoarthritis, cardiovascular disease, and increased mortality; however, relatively few studies have examined the occurrence of multiple obesity‐related outcomes in the same patient population. This study was designed to examine the associations between body mass index (BMI) and a broad range of obesity‐related conditions in the same large cohort from a UK‐representative primary care database. Methods: Demographic data and diagnosis codes were extracted from the Clinical Practice Research Datalink GOLD database in January 2019. Adults registered for ≥ 3 years were grouped by BMI, with BMI 18.5–24.9 kg/m2 as reference group. Associations between BMI and 12 obesity‐related outcomes were estimated using Cox proportional hazard models, adjusted for age, sex, and smoking. Results: More than 2.9 million individuals were included in the analyses and were followed up for occurrence of relevant outcomes for a median of 11.4 years during the study period. Generally, there was a stepwise increase in risk of all outcomes with higher BMI. Individuals with BMI 40.0–45.0 kg/m2 were at particularly high risk of sleep apnea (hazard ratio [95% confidence interval] vs. reference group: 19.8 [18.9–20.8]), T2D (12.4 [12.1–12.7]), heart failure (3.46 [3.35–3.57]), and hypertension (3.21 [3.15–3.26]). Conclusions: This study substantiates evidence linking higher BMI to higher risk of a range of serious health conditions, in a large, representative UK cohort. By focusing on obesity‐related conditions, this demonstrates the wider clinical impact and the healthcare burden of obesity, and highlights the vital importance of management, treatment approaches, and public health programs to mitigate the impact of this disease. [ABSTRACT FROM AUTHOR]

Summary: Objective: Liraglutide 3.0 mg is associated with clinically significant weight loss in clinical trials, but real‐world data are lacking. In this analysis, weight loss and persistence outcomes with liraglutide 3.0 mg were assessed across obesity classes, in a real‐world clinical setting. Methods: Secondary analysis of an observational, retrospective study of liraglutide 3.0 mg for weight management (as adjunct to diet and exercise) at six Wharton Medical Clinics in Canada. Patients were categorized by body mass index (BMI, kg/m2) into obesity class I (BMI 30–34.9); class II (BMI 35–39.9); and class III (BMI ≥40). Change in weight, categorical weight loss, time to maintenance dose (defined as the time to reach the full liraglutide 3.0 mg maintenance dose) and persistence were assessed for each class and for differences between classes. Results: Of 308 patients, 70 (22.7%) had obesity class I, 83 (26.9%) obesity class II and 155 (50.3%) obesity class III. Similar percentage change in weight was observed between obesity classes (mean [standard deviation, SD]: −7.0% [6.0], −6.6% [6.0] and −6.1% [5.0], respectively; p =.640), and similar proportions achieved ≥5% weight loss (60.4%, 62.0% and 55.3%, respectively; p =.717) at 6 months. Mean time to maintenance dose (SD) was 64.2 (56.4) d, 76.4 (56.3) d and 71.4 (54.5) d for obesity classes I, II and III, respectively (p =.509). Persistence with medication was also similar between obesity classes (p =.358). Conclusions: These findings suggest that real‐world treatment with liraglutide 3.0 mg, regardless of obesity class, is associated with similar clinically significant weight loss, time to maintenance dose and medication persistence. [ABSTRACT FROM AUTHOR]

Summary: Objective: Weight management medications can significantly increase patients' chances of achieving a clinically meaningful weight loss if patients persist with treatment. This retrospective observational study of de‐identified medical records of 311 patients is the first real‐world study examining persistence with liraglutide 3.0 mg in Canada, and also investigates associations between the SaxendaCare® patient support program and persistence and weight loss. Methods: Overall persistence was assessed, as well as associations of enrollment in SaxendaCare®, persistence and weight loss. Results: Overall mean (standard deviation) persistence with liraglutide 3.0 mg was 6.3 (4.1) months, and 67.5% (n = 210) and 53.7% (n = 167) of patients persisted for ≥4 and ≥ 6 months, respectively. Enrollment in SaxendaCare® was associated with significantly longer persistence with liraglutide 3.0 mg and greater weight loss. Patients enrolled in SaxendaCare® (n = 119) persisted for 7.9 (4.0) versus 5.2 (3.8) months for those not enrolled (n = 184) (p < 0.001), and had significantly greater percent weight loss after 6 months regardless of the duration of their persistence (−7.9% vs −5.5% from baseline, p < 0.01). Conclusions: These findings suggest that, in clinical settings, persistence with liraglutide 3.0 mg can exceed 6 months, and that enrolling in SaxendaCare® may be associated with comparatively longer persistence and, regardless of persistence, greater weight loss. [ABSTRACT FROM AUTHOR]

Objective: Real-world clinical effectiveness of liraglutide 3.0 mg, in combination with diet and exercise, was investigated 4 and 6 months post initiation. Changes in absolute and percent body weight were examined from baseline.Methods: A cohort of liraglutide 3.0 mg initiators in 2015 and 2016 was identified from six Canadian weight-management clinics. Post initiation values at 4 and 6 months were compared with baseline values using a paired t test.Results: The full cohort consisted of 311 participants, with 210 in the ≥ 4-month persistence group and 167 in the ≥ 6-month persistence group. Average baseline BMI was 40.7 kg/m2 , and weight was 114.8 kg. There was a significant change in body weight 6 and 4 months after initiation of treatment in persistent subjects (≥ 6-month: -8.0 kg, P < 0.001; ≥ 4-month: -7.0 kg, P < 0.001) and All Subjects, regardless of persistence (-7.3 kg; P < 0.001). Percentage change in body weight from baseline was -7.1% in the ≥ 6-month group and -6.3% in the ≥ 4-month group, and All Subjects lost 6.5% body weight. Of participants in the ≥ 6-month group, 64.10% and 34.5% lost ≥ 5% and > 10% body weight, respectively.Conclusions: In a real-world setting, liraglutide 3.0 mg, when combined with diet and exercise, was associated with clinically meaningful weight loss. [ABSTRACT FROM AUTHOR]

Objective: We investigated the association of early achieved HbA1c level and magnitude of HbA1c reduction with subsequent risk of cardiovascular events or death in patients with type 2 diabetes who initiate metformin.Research Design and Methods: This was a population-based cohort study including all metformin initiators with HbA1c tests in Northern Denmark, 2000-2012. Six months after metformin initiation, we classified patients by HbA1c achieved (<6.5% or higher) and by magnitude of HbA1c change from the pretreatment baseline. We used Cox regression to examine subsequent rates of acute myocardial infarction, stroke, or death, controlling for baseline HbA1c and other confounding factors.Results: We included 24,752 metformin initiators (median age 62.5 years, 55% males) with a median follow-up of 2.6 years. The risk of a combined outcome event gradually increased with rising levels of HbA1c achieved compared with a target HbA1c of <6.5%: adjusted hazard ratio (HR) 1.18 (95% CI 1.07-1.30) for 6.5-6.99%, HR 1.23 (1.09-1.40) for 7.0-7.49%, HR 1.34 (1.14-1.57) for 7.5-7.99%, and HR 1.59 (1.37-1.84) for ≥8%. Results were consistent for individual outcome events and robust by age-group and other patient characteristics. A large absolute HbA1c reduction from baseline also predicted outcome: adjusted HR 0.80 (0.65-0.97) for Δ = -4, HR 0.98 (0.80-1.20) for Δ = -3, HR 0.92 (0.78-1.08) for Δ = -2, and HR 0.99 (0.89-1.10) for Δ = -1 compared with no HbA1c change (Δ = 0).Conclusions: A large initial HbA1c reduction and achievement of low HbA1c levels within 6 months after metformin initiation are associated with a lower risk of cardiovascular events and death in patients with type 2 diabetes. [ABSTRACT FROM AUTHOR]

Background The aetiology of ischaemic heart disease (IHD) is complex and is influenced by a spectrum of environmental factors and susceptibility genes. Traditional statistical modelling considers such factors to act independently in an additive manner. The Patient Rule-Induction Method (PRIM) is a multi-model building strategy for evaluating risk attributable to context-dependent gene and environmental effects.Methods PRIM was applied to 9073 participants from the prospective Copenhagen City Heart Study (CCHS). Gender-specific cumulative incidences were estimated for subgroups defined by categories of age, smoking, hypertension, diabetes, body mass index, total cholesterol, high-density lipoprotein cholesterol and triglycerides and by 94 single nucleotide variants (SNVs).Cumulative incidences for subgroups were validated using an independently ascertained sample of 58 240 participants from the Copenhagen General Population Study (CGPS).Results In the CCHS the overall cumulative incidences were 0.17 in women and 0.21 in men. PRIM identified six and four mutually exclusive subgroups in women and men, respectively, with cumulative incidences of IHD ranging from 0.02 to 0.34. Cumulative incidences of IHD generated by PRIM in the CCHS were validated in four of the six subgroups of women and two of the four subgroups of men in the CGPS.Conclusions PRIM identified high-risk subgroups characterized by specific contexts of selected values of traditional risk factors and genetic variants. These subgroups were validated in an independently ascertained cohort study. Thus, a multi-model strategy may identify groups of individuals with substantially higher risk of IHD than the overall risk for the general population. [ABSTRACT FROM PUBLISHER]

Rare genetic variants, identified by in-detail resequencing of loci, may contribute to complex traits. We used the apolipoprotein A-I gene (APOA1), a major high-density lipoprotein (HDL) gene, and population-based resequencing to determine the spectrum of genetic variants, the phenotypic characteristics of these variants, and how these results compared with results based on resequencing only the extremes of the apolipoprotein A-I (apoA-I) distribution. First, we resequenced APOA1 in 10,330 population-based participants in the Copenhagen City Heart Study. The spectrum and distribution of genetic variants was determined as a function of the number of individuals resequenced. Second, apoA-I and HDL cholesterol phenotypes were determined for nonsynonymous (NS) and synonymous (S) variants and were validated in the Copenhagen General Population Study (n = 45,239). Third, observed phenotypes were compared with those predicted using an extreme phenotype approach based on the apoA-I distribution. Our results are as follows: First, population-based resequencing of APOA1 identified 40 variants of which only 7 (18%) had minor allele frequencies >1%, and most were exceedingly rare. Second, 0.27% of individuals in the general population were heterozygous for NS variants which were associated with substantial reductions in apoA-I (up to 39 mg/dL) and/or HDL cholesterol (up to 0.9 mmol/L) and, surprisingly, 0.41% were heterozygous for variants predisposing to amyloidosis. NS variants associated with a hazard ratio of 1.72 (1.09-2.70) for myocardial infarction (MI), largely driven by A164S, a variant not associated with apoA-I or HDL cholesterol levels. Third, using the extreme apoA-I phenotype approach, NS variants correctly predicted the apoA-I phenotype observed in the population-based resequencing. However, using the extreme approach, between 79% (screening 0-1st percentile) and 21% (screening 0-20th percentile) of all variants were not identified; among these were variants previously associated with amyloidosis. Population-based resequencing of APOA1 identified a majority of rare NS variants associated with reduced apoA-1 and HDL cholesterol levels and/or predisposing to amyloidosis. In addition, NS variants associated with increased risk of MI. [ABSTRACT FROM AUTHOR]

Pseudoxanthoma elasticum (PXE) is an autosomal recessive disease caused by loss-of-function mutations in ABCC6 and characterized by elastic calcification leading to dermal, ocular, and ischemic vascular disease. We tested the hypothesis that heterozygosity for R1141X, the most frequent PXE-causing mutation in Caucasians, associated with risk of ischemic vascular disease, as previous studies suggested 4- to 11-fold risk of ischemic heart disease (IHD) in heterozygotes.We studied 10 276 persons from the general population, including 1985 with IHD and 989 with ischemic cerebrovascular disease (ICVD). We examined 45 603 individuals from a cross-sectional general population study, of whom 3738 had IHD and 2335 had ICVD. Finally, we compared 4851 patients with IHD and 625 patients with ICVD with, respectively, 4851 and 625 matched control subjects. We genotyped participants in all studies for ABCC6 R1141X. The frequency of R1141X was 0.6% in all populations studied. ABCC6 R1141X genotype was not associated with an increased risk of IHD, myocardial infarction, ICVD, or ischemic stroke. Furthermore, R1141X genotype did not interact with age on risk of the largest end point, IHD. Finally, R1141X genotype did not associate with variation in plasma levels of high-sensitivity C-reactive protein, fibrinogen, blood pressure, or lipid and lipoproteins in the general population.In 4 studies including 66 831 participants and 13 642 cases with ischemic vascular events, heterozygosity for ABCC6 R1141X did not associate with risk of IHD, myocardial infarction, ICVD, or ischemic stroke. [ABSTRACT FROM AUTHOR]

It is true that the patients in our study were not randomly assigned, that there was no comparison group, and that the data collected were variable in nature and partially reliant on patient self-reports, all of which are included in the limitations section of the article. The product monograph recommends that patients prescribed liraglutide 3.0 mg start at a dose of 0.6 mg and increase the dose by 0.6 mg weekly until the maximum clinical dose of 3.0 mg is reached [12]. Nonetheless, most patients achieved the 3.0-mg dose, with 85.7% (180 of 210 patients; 8 with an unknown dose) of those continuing on liraglutide 3.0 mg for 4 months after reaching the recommended maintenance dose of 3.0 mg (results not previously published). [Extracted from the article]

Objective: Obesity rates in the United Kingdom are some of the highest in Western Europe, with considerable clinical and societal impacts. Obesity is associated with type 2 diabetes (T2D), osteoarthritis, cardiovascular disease, and increased mortality; however, relatively few studies have examined the occurrence of multiple obesity-related outcomes in the same patient population. This study was designed to examine the associations between body mass index (BMI) and a broad range of obesity-related conditions in the same large cohort from a UK-representative primary care database., Methods: Demographic data and diagnosis codes were extracted from the Clinical Practice Research Datalink GOLD database in January 2019. Adults registered for ≥ 3 years were grouped by BMI, with BMI 18.5-24.9 kg/m 2 as reference group. Associations between BMI and 12 obesity-related outcomes were estimated using Cox proportional hazard models, adjusted for age, sex, and smoking., Results: More than 2.9 million individuals were included in the analyses and were followed up for occurrence of relevant outcomes for a median of 11.4 years during the study period. Generally, there was a stepwise increase in risk of all outcomes with higher BMI. Individuals with BMI 40.0-45.0 kg/m 2 were at particularly high risk of sleep apnea (hazard ratio [95% confidence interval] vs. reference group: 19.8 [18.9-20.8]), T2D (12.4 [12.1-12.7]), heart failure (3.46 [3.35-3.57]), and hypertension (3.21 [3.15-3.26])., Conclusions: This study substantiates evidence linking higher BMI to higher risk of a range of serious health conditions, in a large, representative UK cohort. By focusing on obesity-related conditions, this demonstrates the wider clinical impact and the healthcare burden of obesity, and highlights the vital importance of management, treatment approaches, and public health programs to mitigate the impact of this disease., Competing Interests: Christiane L. Haase, Kirsten T. Eriksen, Sandra Lopes, Altynai Satylganova and Volker Schnecke are employees of Novo Nordisk A/S. Altynai Satylganova and Sandra Lopes are also shareholders of Novo Nordisk A/S. Phil McEwan is an employee of Health Economics and Outcomes Research Ltd. Phil McEwan did not receive funding for this collaboration. HEOR Ltd have received funding from Novo Nordisk A/S for work conducted on previous studies., (© 2020 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.)

Objective: Previous studies using longitudinal weight data to characterize obesity are based on populations of limited size and mostly include individuals of all body mass index (BMI) levels, without focusing on weight changes among people with obesity. This study aimed to identify BMI trajectories over 5 years in a large population with obesity, and to determine the trajectories' association with mortality., Methods: For inclusion, individuals aged 30-74 years at index date (1 January 2013) with continuous membership in Clalit Health Services from 2008 to 2012 were required to have ≥1 BMI measurement per year in ≥3 calendar years during this period, of which at least one was ≥30 kg/m 2 . Latent class analysis was used to generate BMI trajectories over 5 years (2008-2012). Cox proportional hazards models were used to assess the association between BMI trajectories and all-cause mortality during follow-up (2013-2017)., Results: In total, 367,141 individuals met all inclusion criteria. Mean age was 57.2 years; 41% were men. The optimal model was a quadratic model with four classes of BMI clusters. Most individuals (90.0%) had stable high BMI over time. Individuals in this cluster had significantly lower mortality than individuals in the other trajectory clusters ( p  < 0.01), including clusters of people with dynamic weight trajectories., Conclusions: The results of the current study show that people with stable high weight had the lowest mortality of all four BMI trajectories identified. These findings help to expand the scientific understanding of the impact that weight trajectories have on health outcomes, while demonstrating the challenges of discerning the cumulative effects of obesity and weight change, and suggest that dynamic historical measures of BMI should be considered when assessing patients' future risk of obesity-related morbidity and mortality, and when choosing a treatment strategy., Competing Interests: Christiane Lundegaard Haase, Nick Finer and Altynai Satylganova are employees of Novo Nordisk A/S, and Nick Finer and Altynai Satylganova are shareholders of Novo Nordisk A/S. Morton Leibowitz is an employee of Clalit Research Institute. Orna Reges was an employee of Clalit Research Institute at the time of the analysis and is now a post‐doctoral research fellow at the Northwestern University, Chicago. Tomas Karpati was an employee of Clalit Research Institute at the time of the analysis and is now an employee of the Holon Institute of Technology. Dror Dicker is an employee of Hasharon Hospital, Petach Tikva, and Tel Aviv University. Becca Feldman was an employee of Clalit Research Institute at the time the analyses were conducted., (© 2020 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.)

Objective: We investigated the association of early achieved HbA 1c level and magnitude of HbA 1c reduction with subsequent risk of cardiovascular events or death in patients with type 2 diabetes who initiate metformin., Research Design and Methods: This was a population-based cohort study including all metformin initiators with HbA 1c tests in Northern Denmark, 2000-2012. Six months after metformin initiation, we classified patients by HbA 1c achieved (<6.5% or higher) and by magnitude of HbA 1c change from the pretreatment baseline. We used Cox regression to examine subsequent rates of acute myocardial infarction, stroke, or death, controlling for baseline HbA 1c and other confounding factors., Results: We included 24,752 metformin initiators (median age 62.5 years, 55% males) with a median follow-up of 2.6 years. The risk of a combined outcome event gradually increased with rising levels of HbA 1c achieved compared with a target HbA 1c of <6.5%: adjusted hazard ratio (HR) 1.18 (95% CI 1.07-1.30) for 6.5-6.99%, HR 1.23 (1.09-1.40) for 7.0-7.49%, HR 1.34 (1.14-1.57) for 7.5-7.99%, and HR 1.59 (1.37-1.84) for ≥8%. Results were consistent for individual outcome events and robust by age-group and other patient characteristics. A large absolute HbA 1c reduction from baseline also predicted outcome: adjusted HR 0.80 (0.65-0.97) for Δ = -4, HR 0.98 (0.80-1.20) for Δ = -3, HR 0.92 (0.78-1.08) for Δ = -2, and HR 0.99 (0.89-1.10) for Δ = -1 compared with no HbA 1c change (Δ = 0)., Conclusions: A large initial HbA 1c reduction and achievement of low HbA 1c levels within 6 months after metformin initiation are associated with a lower risk of cardiovascular events and death in patients with type 2 diabetes., (© 2017 by the American Diabetes Association.)