The role of air pollution in the aetiology of type 2 diabetes

Background. The public health burden of type 2 diabetes cannot be overestimated. Prevalence of type 2 diabetes is continuously increasing and has caused a great number of deaths and economic losses. Optimal prevention measures for type 2 diabetes entail that more risk factors need to be identified. Air pollution is one of the modifiable environmental risk factors causing health problems, most notably respiratory diseases. Recently there have been indications for a spill-over of its effects into the cardio-metabolic systems. Short-term exposure to air pollution may exert acute or sub-acute inflammatory cardio-metabolic responses which on long-term, sustained exposure could lead to overt cardiovascular diseases and type 2 diabetes. However, it is unclear if long-term exposure to pollutants in the air contributes to the development of type 2 diabetes. This work generates evidence to fill knowledge gaps on the impact of air pollutants on the development of type 2 diabetes and on how different susceptibilities in the general population could contribute to the understanding of the mechanisms involved in this relationship. Methods. First, this work summarized the existing evidence on the possible relationship between long-term exposure to air pollutants and type 2 diabetes. Furthermore, in the framework of the first follow-up of SAPALDIA- the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults, this work used indices for long-term exposure air pollution – 10-year mean particulate matter <10μm in diameter [PM10] and nitrogen dioxide [NO2] - assigned to participants’ residences using a combination of Gaussian dispersion and Land-use regression models, participants residential histories and pollutant trends at monitoring stations. It identified diabetes and metabolic syndrome cases in a comprehensive way considering self-reports, blood tests and other physical measures. It additionally identified genetic variants through genotyping on two different arrays – the Human Illumina610quad Bead Chip and the Taqman PCR assay - for 63 type 2 diabetes genetic polymorphisms [towards a diabetes gene score] and a functional polymorphism on the IL6 gene respectively. Based on the above and detailed health socio-demographic and lifestyle characteristics including smoking habits, occupational exposures, alcohol, nutrition, physical activity, body measurements and additional data collected in SAPALDIA, it was ideal to investigate the cross-sectional relationships between air pollutants and diabetes and to explore interactions [based on various susceptibilities] to understand mechanisms involved in the relationship between long-term exposure to air pollutants and type 2 diabetes. Results. In this work, we found a positive relationship between PM2.5 and NO2 and the risk of T2D in the pooled evidence synthesized from electronic databases. In the frame of SAPALDIA biobank, we found a moderate positive association between long-term exposure to PM10 [and NO2] and prevalent diabetes, and demonstrated a sustained effect of PM10 independent of NO2, while NO2 lost its association on accounting for PM10 in multi-pollutant models. Among the measures of cardio-metabolic function, PM10 impacted most on impairment of glucose homeostasis and least on blood lipoproteins and triglycerides. The relationship between PM10 and impaired fasting glycaemia was more apparent among the physically active. Age also appeared to influence the relationship between PM10 and impaired fasting glycaemia. People at higher polygenic risk for type 2 diabetes were more susceptible to PM10. Genetic risk for insulin resistance and obesity appeared to be more relevant than those for beta-cell function in modifying the effects of PM10, especially among those with some background inflammatory conditions. Carriers of the pro-inflammatory major ‘G’ allele of IL6-572GC, with allele frequency of 93%, were also more susceptible to PM10 in relation to diabetes. Conclusions. This work has greatly contributed to evidence suggesting the possible role of air pollutants in diabetes aetiology. The reported associations were observed at mean concentrations below current air quality guidelines. PM10 may be a good marker for aspects of air pollution [rather than NO2] relevant for the development of diabetes. In particular, PM10 might act through sub-clinical inflammation and resultant impaired insulin sensitivity. Impairment of insulin secretion may be a less relevant pathway for PM10 action. Physical activity, though beneficial, presented another likely pathway for PM10 effects. These findings, if confirmed, call for the strengthening of air quality policies and adaptation of physical activity promotion to environmental contrasts. Future studies should explore the totality of environmental exposures – exposomics –in a life-course fashion. The mediating role of DNA methylation influencing genetic expression should be further explored. For global generalizability, there is a strong need for evidence replication in developing countries where outdoor and indoor air pollution is quite high and mostly unregulated, and the burden of non-communicable diseases is rapidly growing

Transportation noise exposure and cardiovascular mortality : a nationwide cohort study from Switzerland

Most studies published to date consider single noise sources and the reported noise metrics are not informative about the peaking characteristics of the source under investigation. Our study focuses on the association between cardiovascular mortality in Switzerland and the three major transportation noise sources-road, railway and aircraft traffic-along with a novel noise metric termed intermittency ratio (IR), expressing the percentage contribution of individual noise events to the total noise energy from all sources above background levels. We generated Swiss-wide exposure models for road, railway and aircraft noise for 2001. Noise from the most exposed façade was linked to geocodes at the residential floor height for each of the 4.41 million adult (&gt;30 y) Swiss National Cohort participants. For the follow-up period 2000-2008, we investigated the association between all noise exposure variables [Lden(Road), Lden(Rail), Lden(Air), and IR at night] and various cardiovascular primary causes of death by multipollutant Cox regression models adjusted for potential confounders including NO2. The most consistent associations were seen for myocardial infarction: adjusted hazard ratios (HR) (95% CI) per 10 dB increase of exposure were 1.038 (1.019-1.058), 1.018 (1.004-1.031), and 1.026 (1.004-1.048) respectively for Lden(Road), Lden(Rail), and Lden(Air). In addition, total IR at night played a role: HRs for CVD were non-significant in the 1st, 2nd and 5th quintiles whereas they were 1.019 (1.002-1.037) and 1.021 (1.003-1.038) for the 3rd and 4th quintiles. Our study demonstrates the impact of all major transportation noise sources on cardiovascular diseases. Mid-range IR levels at night (i.e. between continuous and highly intermittent) are potentially more harmful than continuous noise levels of the same average level

Review on Atherogenic Index of Plasma Lipids and Dyslipidemia

Dyslipidemia is defined as abnormally levels of lipids in the blood. Different types of lipids and lipoproteins have been identified. Dyslipidemia is a single strong risk factor for the development of cardiovascular events and atherosclerosis is the most common. It has been described as a disease of the economically advanced societies, but recently, it has found its way into the semi-urban societies and among its dwellers, who are at the increasing risk of developing cardiovascular accidents. Hence, early identification and diagnosis of dyslipidemia at its earliest stage among this populace is a worthwhile cardiovascular preventive measure. The study of hyperlipidaemia is of considerable importance, mainly because of the involvement of lipids in cardiovascular diseases. The classification system of hyperlipidaemia is based on which plasma lipoprotein concentrations were increased. Fredrickson classification helped to put lipidology on the clinical map, though it was not a diagnostic classification. It gives little clue as to the aetiology of the disorder. Currently, a more descriptive classification is used for the primary hyperlipidaemia although they can be genetic or secondary factors. This review presents the overview of plasma lipids. This article illustrates the theoretical background and details about dyslipidemias. Keywords: Dyslipidemia, Atherogenic index, Hyperlipidaemia, Atherosclerosis, Lipoprotein