Functional and metabolic burden of air pollution: relevance of early disease (prediabetes) stage for progression to overt diabetes mellitus

Functional and metabolic burden of air pollution: relevance of early disease (prediabetes) stage for progression to overt diabetes mellitus

Eric V. Balti1,2,3, Andre Pascal Kengne4,5

1Diabetes Research Center, Vrije Universiteit Brussel (VUB), Brussels, Belgium; 2Department of Clinical Chemistry, 3Diabetes Clinic, Department of Internal Medicine, Universitair Ziekenhuis Brussel (UZ Brussel), Brussels, Belgium; 4Non-Communicable Diseases Research Unit, South African Medical Research Council and University of Cape Town, Cape Town, South Africa; 5Department of Medicine, University of Cape Town, Cape Town, South Africa

Correspondence to: Andre Pascal Kengne, MD, PhD. Non-Communicable Diseases Research Unit, South African Medical Research Council and University of Cape Town, Cape Town, South Africa. Email:

Provenance: This is a Guest Editorial commissioned by the Editor-in-Chief: Baoli Zhu (Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China).

Comment on: Wolf K, Popp A, Schneider A, et al. Association Between Long-term Exposure to Air Pollution and Biomarkers Related to Insulin Resistance, Subclinical Inflammation, and Adipokines. Diabetes 2016;65:3314-26.

Received: 05 April 2017; Accepted: 10 April 2017; Published: 07 June 2017.

doi: 10.21037/jphe.2017.05.01

The growing burden of diabetes mellitus has raised interest in uncovering disease susceptibility factors, in order to contain further increases in the burden (1). It is currently admitted that both genetic and environmental factors play a critical role in the disease occurrence and progression. Besides the traditional diabetes risk factors such as unhealthy lifestyles, obesity, and family history of diabetes, interest for emerging factors such as ambient air pollutants, has significantly increased in recent years. This is reflected in a number of studies recently summarized by our group and other investigators (2-4). While existing studies suggest a modest effect of exposure to ambient air pollutants on diabetes risk, the underlying mechanisms largely remain elusive. With regard to type 2 diabetes, the progression to clinically overt disease is determined by the interplay between insulin resistance and alteration of beta-cell secretory capacity (5). It has been suggested that air pollutants could possibly interfere with these pathophysiological derangements either directly or via multiple pathways including endothelial dysfunction, systemic inflammation, dysregulation of visceral adipose tissue, mitochondrial dysfunction, non-alcoholic steatohepatosis, among others (6).

In a recent study, Wolf et al. have undertaken to explore some of the pathways linking air pollution with diabetes risk, by investigating the association of long-term exposure to air pollutants including PM10, PMcoarse, PM2.5 and nitrogen oxides (NO2 and NOX) with insulin resistance using the homeostatic model assessment of insulin resistance (HOMA-IR) as a surrogate, subclinical inflammation using high-sensitivity C-reactive protein (hs-CRP), and leptin as a member of adipokines family (7). They also explored the effects of two traffic related indicators of air pollution (i.e., the traffic intensity on the nearest road, and traffic load on major roads within 100 m of the residence). The study was conducted among residents of Augsburg in Germany and in two rural counties in its neighborhood. Oral glucose tolerance test (OGTT) was performed in individuals not previously diagnosed with diabetes, and various stages of glucose tolerance including: normal glucose metabolism, new-onset diabetes, impaired fasting glucose, impaired glucose tolerance and the combination of the two latter states were defined. Average annual exposure to air pollutions was assessed in the framework of the ESCAPE project by land use regression models incorporating participants home addresses and long-term exposure to the investigated air pollutants (8). Hierarchical linear regression models were developed to minimize the effect of potential confounders and model selection used Bayesian information criterion after adjustment, when applicable, of traffic related parameters for background air pollution. Analyses were performed in the general population and replicated in each of the metabolic states in a sensitivity analysis. Further analyses were conducted after minimizing the number of adjustments factors in the regression models, after exclusion of individuals with relatively elevated hs-CRP (>10 mg/dL) and those receiving glucose-lowering agents or statins, then patients treated with diuretics and/or beta-blockers (7).

In the overall sample, the majority (72%, n=2,155) had no diabetes and respectively 17% (n=496) and 11% (n=323) were diagnosed with prediabetes and diabetes mellitus. Using the difference between the 5th and 95th percentile as estimate of exposure, the authors reported a positive association between all air pollutants except PM2.5 and traffic related covariates with HOMA-IR and insulin. A tendency was observed for PM2.5 and NOX with glucose, while leptin increased with nitrogen oxides accretion. There was no association between all pollutants or traffic related exposure with HbA1c or hs-CRP. In analyses stratified by status for glucose tolerance, the above associations were mostly apparent in the prediabetic group, while participants with diabetes and those without showed weak or no association.

The association of exposure to air pollution with insulin resistance, driven by the effect in people with prediabetes in the sample of Wolf and colleagues (7), suggests a contribution of air pollution to the initiation or potentiation of pathophysiological process from normal glucose tolerance to prediabetes, and subsequently to diabetes mellitus. Abnormal glucose metabolism (prediabetes) is already a major determinant of the progression to overt diabetes. This risk therefore seems to be accentuated upon exposure to air pollution, by the superimposed insulin resistance state reported by Wolf et al. and other investigators (7,9,10). Interestingly, this process seems to occur predominantly in an inflammatory environment. Indeed, hs-CRP, a biomarker of inflammation increased with higher exposure to most of the pollutants except PM2.5 and road traffic associated indicators, and the association of air pollutants with insulin resistance attenuated after exclusion of participants with elevated hs-CRP (7). In line with this report, other inflammatory markers have been identified as key mediators of disease susceptibility associated with ambient air pollution (9,11). The lack of association with traffic load or intensity with the outcomes of interest, emphasizes the remaining work to clarify the link between road traffic proximity and diabetes mellitus (12,13).

The findings of Wolf and co-workers have to be interpreted in the context of some important study limitations, reflecting the methodological challenges involved in such undertaking. HOMA-IR is not the best predictor of insulin resistance (14), and whether results could have been different if a more accurate measure like the euglycemic hyperinsulinemic clamp was used, is unknown. However, clamps are very challenging procedures that are not directly applicable in large population-based surveys. Similarly, land-use regression (LUR) methods have got some limitations in approximating long-term exposure to air pollution, including the risk of exposure misclassification (15). Lastly, air pollution in the study was measured years after the measurements of the biomarkers (outcomes) of interest, and as such inference about the direction of the observed association is not strictly possible. Nevertheless, the study adds to the current literature, by further highlighting a possible role of exposure to air pollution in diabetes occurrence. Indeed, the most relevant study outcomes of Wolf and co-workers (HOMA-IR and leptin) have been associated with obesity, metabolic syndrome and a higher risk of diabetes mellitus (16,17).

The interest for exposure to air pollution in relation with diabetes and chronic diseases risk has relevance, particularly to inform population-based strategies to prevent further increases in the burden. With the rapid urbanization and industrialization of the developing world, an important segment of the global population is increasingly living in polluted environment. In parallel, either incidentally or through causal links, diabetes and other chronic diseases burden are rapidly increasing in those parts of the world. Whether effective interventions to improve air quality in those settings can lower diabetes and other diseases risk, should be actively investigated.


Funding: Study partially funded by the South African Medical Research Council.


Conflicts of Interest: The authors have no conflicts of interest to declare.


  1. NCD Risk Factor Collaboration. Worldwide trends in diabetes since 1980: a pooled analysis of 751 population-based studies with 4.4 million participants. Lancet 2016;387:1513-30. [Crossref] [PubMed]
  2. Balti EV, Echouffo-Tcheugui JB, Yako YY, et al. Air pollution and risk of type 2 diabetes mellitus: a systematic review and meta-analysis. Diabetes Res Clin Pract 2014;106:161-72. [Crossref] [PubMed]
  3. Meo SA, Memon AN, Sheikh SA, et al. Effect of environmental air pollution on type 2 diabetes mellitus. Eur Rev Med Pharmacol Sci 2015;19:123-8. [PubMed]
  4. Wang B, Xu D, Jing Z, et al. Effect of long-term exposure to air pollution on type 2 diabetes mellitus risk: a systemic review and meta-analysis of cohort studies. Eur J Endocrinol 2014;171:R173-82. [Crossref] [PubMed]
  5. American Diabetes Association. 2. Classification and Diagnosis of Diabetes. Diabetes Care 2017;40:S11-24. [Crossref] [PubMed]
  6. Liu C, Ying Z, Harkema J, et al. Epidemiological and experimental links between air pollution and type 2 diabetes. Toxicol Pathol 2013;41:361-73. [Crossref] [PubMed]
  7. Wolf K, Popp A, Schneider A, et al. Association Between Long-term Exposure to Air Pollution and Biomarkers Related to Insulin Resistance, Subclinical Inflammation, and Adipokines. Diabetes 2016;65:3314-26. [Crossref] [PubMed]
  8. ESCAPE - European Study of Cohorts for Air Pollution Effects. Accessed 03.04 2017. Available online:
  9. O'Neill MS, Veves A, Sarnat JA, et al. Air pollution and inflammation in type 2 diabetes: a mechanism for susceptibility. Occup Environ Med 2007;64:373-9. [Crossref] [PubMed]
  10. Eze IC, Imboden M, Kumar A, et al. A common functional variant on the pro-inflammatory Interleukin-6 gene may modify the association between long-term PM10 exposure and diabetes. Environ Health 2016;15:39. [Crossref] [PubMed]
  11. Hoffmann B, Moebus S, Dragano N, et al. Chronic residential exposure to particulate matter air pollution and systemic inflammatory markers. Environ Health Perspect 2009;117:1302-8. [Crossref] [PubMed]
  12. Münzel T, Sorensen M, Gori T, et al. Environmental stressors and cardio-metabolic disease: part I-epidemiologic evidence supporting a role for noise and air pollution and effects of mitigation strategies. Eur Heart J 2017;38:550-6. [PubMed]
  13. Münzel T, Sorensen M, Gori T, et al. Environmental stressors and cardio-metabolic disease: part II-mechanistic insights. Eur Heart J 2017;38:557-64. [PubMed]
  14. Sobngwi E, Kengne AP, Echouffo-Tcheugui JB, et al. Fasting insulin sensitivity indices are not better than routine clinical variables at predicting insulin sensitivity among Black Africans: a clamp study in sub-Saharan Africans. BMC Endocr Disord 2014;14:65. [Crossref] [PubMed]
  15. Ryan PH, LeMasters GK. A review of land-use regression models for characterizing intraurban air pollution exposure. Inhal Toxicol 2007;19 Suppl 1:127-33. [Crossref] [PubMed]
  16. Weyer C, Tataranni PA, Bogardus C, et al. Insulin resistance and insulin secretory dysfunction are independent predictors of worsening of glucose tolerance during each stage of type 2 diabetes development. Diabetes Care 2001;24:89-94. [Crossref] [PubMed]
  17. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature 2006;444:840-6. [Crossref] [PubMed]
doi: 10.21037/jphe.2017.05.01
Cite this article as: Balti EV, Kengne AP. Functional and metabolic burden of air pollution: relevance of early disease (prediabetes) stage for progression to overt diabetes mellitus. J Public Health Emerg 2017;1:55.