Pathways through the Exposome: The Role of the Physicochemical and Food Environment in Cardiometabolic Health

The prevalence of cardiometabolic diseases (CMD), including type 2 diabetes (T2D), is increasing globally. The proportion of genetic predisposition explaining cardiometabolic disease risk is around 20%. Other contributors to CMD risk include lifestyle and environmental factors, such as diet, sleep quality and duration, stress, air pollution, and greenspace. Therefore, it is important to consider environmental determinants, alongside lifestyle factors, to reduce CMD risk. The Exposome framework consists of the totality of non-genetic exposures individuals are exposed to and comprises the general external Exposome (e.g., food environment and the physicochemical environment, such as noise and temperature), specific external Exposome (e.g., lifestyle factors) and internal Exposome (e.g., inflammation). The general aim of this thesis was to study associations between the physicochemical environment (e.g., noise, temperature), the community food environment (e.g., the count of food outlets), and cardiometabolic health outcomes. In addition, I aimed to study whether these associations were mediated or moderated by lifestyle factors, such as diet, stress, or sleep. This resulted into the following specific aims: (1) to investigate exposure to environmental noise, temperature, and the community food environment in relation to CMD risk and (2) to investigate whether lifestyle factors such as stress, dietary habits, or sleep mediate or moderate the associations between the community food environment, environmental noise and temperature with CMD and its risk factors. To answer the first aim, I systematically reviewed the evidence on GPS-based food environment exposures in relation to diet-related and cardiometabolic health outcomes (Chapter 2). I included 14 studies, which investigated GPS-based measures of the food environment. While some studies found associations between food outlet exposure and dietary intake—such as higher fast food intake associated with more fast food outlets within a 500-meter buffer around frequently visited locations—overall, I found no strong or consistent evidence for associations between GPS-based food environment exposures and diet-related or cardiometabolic health outcomes. In Chapter 3, I investigated the longitudinal associations between the count of fast food outlets (FFO) near participants’ homes (1998–2010) and inflammatory markers (CRP, IL-6, and adiponectin) using data from the Nurses’ Health Study II. The results showed no evidence of associations between residential FFO exposure and any of the inflammatory markers. For example, each additional FFO was associated with no change in CRP levels (β: -0.00, 95%CI: -0.01, 0.01). To address both aims, I examined whether noise exposure (Lden) and nighttime temperature (number of days with >10°C) were associated with T2D incidence, and whether sleep duration or BMI mediated these associations (chapter 4). I used data from Dutch cohort studies (Hoorn Study, Maastricht Study, NESDA, LASA, and HELIUS) and pooled the effect estimates in a meta-analysis. The findings showed no evidence that noise (OR 1.00, 95%CI: 0.97, 1.03) or temperature (OR 0.99, 95%CI: 0.97, 1.02) exposure was associated with T2D incidence. Mediation analyses showed no significant indirect effects via sleep duration or BMI. Lastly, I explored associations between stressful life events and changes in visceral obesity in the Hoorn Study, and examined mediation by lifestyle factors. Experiencing more than three stressful life events was associated with an increase in waist circumference of 0.93 cm (95%CI: 0.28, 1.57), compared to no stressful life events, with smoking partly mediating this association. Stratified analyses showed stronger effects among individuals with lower educational levels—for instance, an increase of 2.37 cm (95%CI: 0.28, 4.47) in waist circumference for those exposed to multiple stressful life events compared to no stressful life events. Smoking mediated approximately 13.2% of the observed associations. The findings of this thesis highlight the need for further research using refined exposure assessment to better understand how the Exposome contributes to CMD risk.