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      Sex-dependent and body weight-dependent associations between environmental PAHs exposure and insulin resistance: Korean urban elderly panel

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          Abstract

          Background

          The prevalence of metabolic diseases rises rapidly with an ageing population. Recent studies suggest the potential involvement of environmental chemicals in insulin resistance (IR) that plays a core role in the development of metabolic diseases. Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous components of outdoor and indoor air pollution. The influence of PAHs on IR may differ depending on sex and weight.

          Objectives

          We examined the association between exposure to environmental PAHs and IR in Korean urban elderly adults controlling for major risk factors that contribute to an increase in IR.

          Methods

          Between 2008 and 2010, PAH metabolite levels (urinary 1-hydroxypyrene (1-OHP)) and the homoeostatic model assessment index (HOMA-IR) were repeatedly measured in 502 adults aged ≥60 years. Linear mixed effect models were fit to evaluate the associations of 1-OHP concentration with HOMA-IR. Subgroups were modelled by sex and weight.

          Results

          After adjusting for sociodemographics, air pollution and metabolic disease status, the highest (vs lowest) quartile of 1-OHP was associated with an 0.57 (95% CI 0.10 to 1.04) increase in the HOMA-IR score (p trend=0.037). When stratified by sex, women presented a significantly dose-dependent trend of 1-OHP with HOMA-IR (p trend=0.013), whereas no association was observed in men (p trend=0.904). When further stratified by weight (body mass index ≥25 vs <25 kg/m 2), a significant association was found only in overweight women (p trend=0.023).

          Conclusions

          Our results suggest that environmental exposure to PAHs is associated with increased IR in elderly adults and that the association may be limited to overweight women.

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          Most cited references29

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          Glucose clamp technique: a method for quantifying insulin secretion and resistance.

          Methods for the quantification of beta-cell sensitivity to glucose (hyperglycemic clamp technique) and of tissue sensitivity to insulin (euglycemic insulin clamp technique) are described. Hyperglycemic clamp technique. The plasma glucose concentration is acutely raised to 125 mg/dl above basal levels by a priming infusion of glucose. The desired hyperglycemic plateau is subsequently maintained by adjustment of a variable glucose infusion, based on the negative feedback principle. Because the plasma glucose concentration is held constant, the glucose infusion rate is an index of glucose metabolism. Under these conditions of constant hyperglycemia, the plasma insulin response is biphasic with an early burst of insulin release during the first 6 min followed by a gradually progressive increase in plasma insulin concentration. Euglycemic insulin clamp technique. The plasma insulin concentration is acutely raised and maintained at approximately 100 muU/ml by a prime-continuous infusion of insulin. The plasma glucose concentration is held constant at basal levels by a variable glucose infusion using the negative feedback principle. Under these steady-state conditions of euglycemia, the glucose infusion rate equals glucose uptake by all the tissues in the body and is therefore a measure of tissue sensitivity to exogenous insulin.
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            Current approaches for assessing insulin sensitivity and resistance in vivo: advantages, limitations, and appropriate usage.

            Insulin resistance contributes to the pathophysiology of diabetes and is a hallmark of obesity, metabolic syndrome, and many cardiovascular diseases. Therefore, quantifying insulin sensitivity/resistance in humans and animal models is of great importance for epidemiological studies, clinical and basic science investigations, and eventual use in clinical practice. Direct and indirect methods of varying complexity are currently employed for these purposes. Some methods rely on steady-state analysis of glucose and insulin, whereas others rely on dynamic testing. Each of these methods has distinct advantages and limitations. Thus, optimal choice and employment of a specific method depends on the nature of the studies being performed. Established direct methods for measuring insulin sensitivity in vivo are relatively complex. The hyperinsulinemic euglycemic glucose clamp and the insulin suppression test directly assess insulin-mediated glucose utilization under steady-state conditions that are both labor and time intensive. A slightly less complex indirect method relies on minimal model analysis of a frequently sampled intravenous glucose tolerance test. Finally, simple surrogate indexes for insulin sensitivity/resistance are available (e.g., QUICKI, HOMA, 1/insulin, Matusda index) that are derived from blood insulin and glucose concentrations under fasting conditions (steady state) or after an oral glucose load (dynamic). In particular, the quantitative insulin sensitivity check index (QUICKI) has been validated extensively against the reference standard glucose clamp method. QUICKI is a simple, robust, accurate, reproducible method that appropriately predicts changes in insulin sensitivity after therapeutic interventions as well as the onset of diabetes. In this Frontiers article, we highlight merits, limitations, and appropriate use of current in vivo measures of insulin sensitivity/resistance.
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              The global burden of disease due to outdoor air pollution.

              As part of the World Health Organization (WHO) Global Burden of Disease Comparative Risk Assessment, the burden of disease attributable to urban ambient air pollution was estimated in terms of deaths and disability-adjusted life years (DALYs). Air pollution is associated with a broad spectrum of acute and chronic health effects, the nature of which may vary with the pollutant constituents. Particulate air pollution is consistently and independently related to the most serious effects, including lung cancer and other cardiopulmonary mortality. The analyses on which this report is based estimate that ambient air pollution, in terms of fine particulate air pollution (PM(2.5)), causes about 3% of mortality from cardiopulmonary disease, about 5% of mortality from cancer of the trachea, bronchus, and lung, and about 1% of mortality from acute respiratory infections in children under 5 yr, worldwide. This amounts to about 0.8 million (1.2%) premature deaths and 6.4 million (0.5%) years of life lost (YLL). This burden occurs predominantly in developing countries; 65% in Asia alone. These estimates consider only the impact of air pollution on mortality (i.e., years of life lost) and not morbidity (i.e., years lived with disability), due to limitations in the epidemiologic database. If air pollution multiplies both incidence and mortality to the same extent (i.e., the same relative risk), then the DALYs for cardiopulmonary disease increase by 20% worldwide.
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                Author and article information

                Journal
                J Epidemiol Community Health
                J Epidemiol Community Health
                jech
                jech
                Journal of Epidemiology and Community Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                0143-005X
                1470-2738
                July 2015
                10 February 2015
                : 69
                : 7
                : 625-631
                Affiliations
                [1 ]Department of Preventive Medicine, Gachon University Graduate School of Medicine , Incheon, Republic of Korea
                [2 ]Department of Environmental Health, Seoul National University School of Public Health , Seoul, Republic of Korea
                [3 ]Institute of Environmental Medicine, Seoul National University Medical Research Center , Seoul, Republic of Korea
                [4 ]Environmental Health Center, Seoul National University College of Medicine , Seoul, Republic of Korea
                Author notes
                [Correspondence to ] Dr Yun-Chul Hong, Department of Preventive Medicine, Seoul National University College of Medicine, 28 Yongon-Dong, Chongno-Gu, Seoul 110-799, Republic of Korea; ychong1@ 123456snu.ac.kr
                Article
                jech-2014-204801
                10.1136/jech-2014-204801
                4484041
                25669219
                7ead23fa-7e1c-45d3-8d9c-90c818e06674
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/

                History
                : 12 August 2014
                : 23 December 2014
                : 22 January 2015
                Categories
                1506
                Environmental Health
                Custom metadata
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                Public health
                biomonitoring,environmental epidemiology,elderly
                Public health
                biomonitoring, environmental epidemiology, elderly

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