Intrauterine programming of obesity and type 2 diabetes

Abstract: The type 2 diabetes epidemic and one of its predisposing factors, obesity, are major influences on global health and economic burden. It is accepted that genetics and the current environment contribute to this epidemic; however, in the last two decades, both human and animal studies have consolidated considerable evidence supporting the ‘developmental programming’ of these conditions, specifically by the intrauterine environment. Here, we review the various in utero exposures that are linked to offspring obesity and diabetes in later life, including epidemiological insights gained from natural historical events, such as the Dutch Hunger Winter, the Chinese famine and the more recent Quebec Ice Storm. We also describe the effects of gestational exposure to endocrine disruptors, maternal infection and smoking to the fetus in relation to metabolic programming. Causal evidence from animal studies, motivated by human observations, is also discussed, as well as some of the proposed underlying molecular mechanisms for developmental programming of obesity and type 2 diabetes, including epigenetics (e.g. DNA methylation and histone modifications) and microRNA interactions. Finally, we examine the effects of non-pharmacological interventions, such as improving maternal dietary habits and/or increasing physical activity, on the offspring epigenome and metabolic outcomes

Circumpolar permafrost maps and geohazard indices for near-future infrastructure risk assessments

Ongoing climate change is causing fundamental changes in the Arctic, some of which can be hazardous to nature and human activity. In the context of Earth surface systems, warming climate may lead to rising ground temperatures and thaw of permafrost. This Data Descriptor presents circumpolar permafrost maps and geohazard indices depicting zones of varying potential for development of hazards related to near-surface permafrost degradation, such as ground subsidence. Statistical models were used to predict ground temperature and the thickness of the seasonally thawed (active) layer using geospatial data on environmental conditions at 30 arc-second resolution. These predictions, together with data on factors (ground ice content, soil grain size and slope gradient) affecting permafrost stability, were used to formulate geohazard indices. Using climate-forcing scenarios (Representative Concentration Pathways 2.6, 4.5 and 8.5), permafrost extent and hazard potential were projected for the 2041-2060 and 2061-2080 time periods. The resulting data (seven permafrost and 24 geohazard maps) are relevant to near-future infrastructure risk assessments and for targeting localized geohazard analyses.Peer reviewe

Combined lifestyle factors and the risk of LADA and type 2 diabetes - Results from a Swedish population-based case-control study

Aims: We investigated the risk of latent autoimmune diabetes in adults (LADA) and type 2 diabetes in relation to a healthy lifestyle, the proportion of patients attributable to an unhealthy lifestyle, and the influence of family history of diabetes (FHD) and genetic susceptibility. Methods: The population-based study included incident LADA (n = 571), type 2 diabetes (n = 1962), and matched controls (n = 2217). A healthy lifestyle was defined by BMI < 25 kg/m2, moderate-to-high physical activity, a healthy diet, no smoking, and moderate alcohol consumption. We estimated odds ratios (OR) with 95% confidence intervals (CIs) adjusted for age, sex, education, and FHD. Results: Compared to a poor/moderate lifestyle, a healthy lifestyle was associated with a reduced risk of LADA (OR 0.51, CI 0.34-0.77) and type 2 diabetes (OR 0.09, CI 0.05-0.15). A healthy lifestyle conferred a reduced risk irrespective of FHD and high-risk HLA genotypes. Having a BMI < 25 kg/m2 conferred the largest risk reduction for both LADA (OR 0.54, CI 0.43-0.66) and type 2 diabetes (OR 0.12, CI 0.10-0.15) out of the individual items. Conclusion: People with a healthy lifestyle, especially a healthy body weight, have a reduced risk of LADA including those with genetic susceptibility to diabetes. (C) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).Peer reviewe

Patient safety culture lives in departments and wards: Multilevel partitioning of variance in patient safety culture

<p>Abstract</p> <p>Background</p> <p>Aim of study was to document 1) that patient safety culture scores vary considerably by hospital department and ward, and 2) that much of the variation is across the lowest level organizational units: the wards. Setting of study: 500-bed Norwegian university hospital, September-December 2006.</p> <p>Methods</p> <p>Data collected from 1400 staff by (the Norwegian version of) the generic version of the Safety Attitudes Questionnaire (SAQ Short Form 2006). Multilevel analysis by MLwiN version 1.10.</p> <p>Results</p> <p>Considerable parts of the score variations were at the ward and department levels. More organization level variation was seen at the ward level than at the department level.</p> <p>Conclusions</p> <p>Patient safety culture improvement efforts should not be limited to all-hospital interventions or interventions aimed at entire departments, but include involvement at the ward level, selectively aimed at low-scoring wards. Patient safety culture should be studied as closely to the patient as possible. There may be such a thing as "hospital safety culture" and the variance across hospital departments indicates the existence of department safety cultures. However, neglecting the study of patient safety culture at the ward level will mask important local variations. Safety culture research and improvement should not stop at the lowest formal level of the hospital (wards, out-patient clinics, ERs), but proceed to collect and analyze data on the micro-units within them.</p

Re-examining the consumption-wealth relationship : the role of model uncertainty

This paper discusses the consumption-wealth relationship. Following the recent influential workof Lettau and Ludvigson [e.g. Lettau and Ludvigson (2001), (2004)], we use data on consumption, assets andlabor income and a vector error correction framework. Key …ndings of their work are that consumption doesrespond to permanent changes in wealth in the expected manner, but that most changes in wealth are transitoryand have no e¤ect on consumption. We investigate the robustness of these results to model uncertainty andargue for the use of Bayesian model averaging. We …nd that there is model uncertainty with regards to thenumber of cointegrating vectors, the form of deterministic components, lag length and whether the cointegratingresiduals a¤ect consumption and income directly. Whether this uncertainty has important empirical implicationsdepends on the researcher's attitude towards the economic theory used by Lettau and Ludvigson. If we workwith their model, our findings are very similar to theirs. However, if we work with a broader set of models andlet the data speak, we obtain somewhat di¤erent results. In the latter case, we …nd that the exact magnitudeof the role of permanent shocks is hard to estimate precisely. Thus, although some support exists for the viewthat their role is small, we cannot rule out the possibility that they have a substantive role to play

Interaction Between Overweight and Genotypes of HLA, TCF7L2, and FTO in Relation to the Risk of Latent Autoimmune Diabetes in Adults and Type 2 Diabetes

Objective: We investigated potential interactions between body mass index (BMI) and genotypes of human leukocyte antigen (HLA), TCF7L2-rs7903146, and FTO-rs9939609 in relation to the risk of latent autoimmune diabetes in adults (LADA) and type 2 diabetes. Methods: We pooled data from two population-based studies: (i) a Swedish study with incident cases of LADA [positive for glutamic acid decarboxylase autoantibodies (GADA); n = 394) and type 2 diabetes (negative for GADA; n = 1290) and matched controls without diabetes (n = 2656) and (ii) a prospective Norwegian study that included incident cases of LADA (n = 131) and type 2 diabetes (n = 1901) and 886,120 person-years of follow-up. Analyses were adjusted for age, sex, physical activity, and smoking. Interaction between overweight (BMI >= 25 kg/m(2)) and HLA/TCF7L2/FTO high-risk genotypes was assessed by attributable proportion due to interaction (AP). Results: The combination of overweight and high-risk genotypes of HLA, TCF7L2, and FTO was associated with pooled relative risk (RRpooled) of 7.59 (95% CI, 5.27 to 10.93), 2.65 (95% CI, 1.97 to 3.56), and 2.21 (95% CI, 1.60 to 3.07), respectively, for LADA, compared with normal-weight individuals with low/intermediate genetic risk. There was a significant interaction between overweight and HLA (AP, 0.29; 95% CI, 0.10 to 0.47), TCF7L2 (AP, 0.31; 95% CI, 0.09 to 0.52), and FTO (AP, 0.38; 95% CI, 0.15 to 0.61). The highest risk of LADA was seen in overweight individuals homozygous for the DR4 genotype [RR, 26.76 (95% CI, 15.42 to 46.43); AP, 0.58 (95% CI, 0.32 to 0.83) (Swedish data)]. Overweight and TCF7L2 also significantly interacted in relation to type 2 diabetes (AP, 0.26; 95% CI, 0.19 to 0.33), but no interaction was observed with high-risk genotypes of HLA or FTO. Conclusions: Overweight interacts with HLA high-risk genotypes but also with genes associated with type 2 diabetes in the promotion of LADA.Peer reviewe

Rhino Conjunctivitis and Asthma Among Seafood Processing Workers in Greenland. A Cross-Sectional Study

Introduction: The fishing- and the seafood processing industries are the largest industrial sectors in Greenland. Despite this, only a few cases of occupational diseases in this industry have been reported to the Danish Labor Market Insurance. Occupational asthma and allergy are well-known occupational diseases in the seafood processing industry worldwide and underreporting of occupational diseases in Greenland is suspected.Objective: The aim of the current study was to examine the associations between job exposures and occupational asthma and rhino conjunctivitis in workers in the Greenlandic seafood processing industry and to compare the prevalence of sensitization by type and degree of exposure to snow crab, shrimp, fish, and the fish parasite, Anisakis simplex.Methods: Data from 382 Greenlandic seafood processing workers were collected during 2016–2018. Data included questionnaire answers, lung function measurements, skin prick tests, and blood samples with ImmunoCAP. For all analyses, p &lt; 0.05 was considered the level of significance.Results: 5.5% of the workers had occupational asthma and 4.6% had occupational rhino conjunctivitis. A large proportion of the workers were sensitized to allergens specific to the workplace; 18.1% to snow crab, 13.6% to shrimp, 1.4% to fish, and 32.6% to the fish parasite, A. simplex. We found a dose-response relationship between the risk of being sensitized to snow crab and A. simplex and years of exposure to the allergens in the seafood processing industry.Conclusion: This study showed that a considerable proportion of workers in the Greenlandic seafood processing industry had occupational asthma and rhino conjunctivitis. Additionally, the study showed high sensitization levels toward snow crab, shrimp, and the fish parasite, A. simplex. This supports the hypothesis of a considerable degree of underreporting of occupational allergic airway disease in the Greenlandic seafood processing industry. Prospectively, it is important to inform workers, leaders, and health care professionals of the health problems and the law on worker's compensation, and to initiate preventive actions at factory and trawler level

Integrated Clustering and Anomaly Detection (INCAD) for Streaming Data (Revised)

Most current clustering based anomaly detection methods use scoring schema and thresholds to classify anomalies. These methods are often tailored to target specific data sets with "known" number of clusters. The paper provides a streaming clustering and anomaly detection algorithm that does not require strict arbitrary thresholds on the anomaly scores or knowledge of the number of clusters while performing probabilistic anomaly detection and clustering simultaneously. This ensures that the cluster formation is not impacted by the presence of anomalous data, thereby leading to more reliable definition of "normal vs abnormal" behavior. The motivations behind developing the INCAD model and the path that leads to the streaming model is discussed.Comment: 13 pages; fixes typos in equations 5,6,9,10 on inference using Gibbs samplin