Area Environment and Health in the Netherlands

__Abstract__ Geographical differences in health are becoming an increasingly important theme in the field of public health. Studies focusing on health differences between countries, or regions within countries, or even at a smaller geographical scale, provide evidence for geographical variations in health. The unequal distribution of health across geographical areas implies that where one lives does matter to health. The studies in this thesis aim to contribute to this discussion by focusing on the area environment and its relation to health at the small geographical scale. This introduction starts with a brief historical description of the role of place of residence in public health, followed by an explanation for observed geographical health patterns. We then elaborate on the mechanisms that might explain how the area environment can influence health. Next, five area features - which are the focus of this thesis - and their possible relation to health are discussed. Finally, we present an outline of this thesis with a brief summary of the individual chapters

Too Informal? How a Chatbot’s Communication Style Affects Brand Attitude and Quality of Interaction

This study investigated the effects of (in)formal chatbot responses and brand familiarity on social presence, appropriateness, brand attitude, and quality of interaction. An online experiment using a 2 (Communication Style: informal vs. formal) by 2 (Brand: familiar vs. unfamiliar) between subject design was conducted in which participants performed customer service tasks with the assistance of chatbots developed for the study. Subsequently, they filled out an online questionnaire. An indirect effect of communication style on brand attitude and quality of interaction through social presence was found. Thus, a chatbot’s informal communication style induced a higher perceived social presence which in turn positively influenced quality of the interaction and brand attitude. However, brand familiarity did not enhance perceptions of appropriateness, indicating participants do not assign different roles to chatbots as communication partner

Linguistic elements of conversational human voice in online brand communication: Manipulations and perceptions

The conversational human voice (CHV) is an extensively studied and adopted communication style in online brand communication. However, in previous research the way in which CHV is operationalized differs considerably: the type and the number of linguistic elements used to establish a sense of CHV in online brand messages varies. Moreover, it is still unknown how CHV operationalizations contribute to consumers’ perceptions of CHV, which consequently could affect their evaluation regarding the message and the brand. In this paper, we addressed these issues by conducting an integrative literature review and a perception experiment, and consequently present a taxonomy of linguistic elements related to message personalization, informal speech, and invitational rhetoric that can be used to operationalize CHV systematically in future studies in online brand communication. Directions for future research and managerial implications are discussed

Community social capital and suicide mortality in the Netherlands: A cross-sectional registry-based study

Background: Evidence on the effect of community social capital on suicide mortality rates is fragmentary and inconsistent. The present study aims to determine whether geographic variations in suicide mortality across the Netherlands were associated with community social capital. Methods. We included 3507 neighbourhoods with 6207 suicide deaths in the period 1995-2000. For each neighbourhood, we measured perceived social capital using information from interview surveys, and we measured structural aspects of social capital using population registers. Associations with mortality were determined using Poisson regression analysis with control for confounders at individual level (age, sex, marit

Maternal risk associated with the VACTERL association:A case-control study

Background The VACTERL association (VACTERL) includes at least three of these congenital anomalies: vertebral, anal, cardiac, trachea-esophageal, renal, and limb anomalies. Assisted reproductive techniques (ART), pregestational diabetes mellitus, and chronic lower obstructive pulmonary disorders (CLOPD) have been associated with VACTERL. We aimed to replicate these findings and were interested in additional maternal risk factors. Methods A case-control study using self-administered questionnaires was performed including 142 VACTERL cases and 2,135 population-based healthy controls. Multivariable logistic regression analyses were performed to estimate confounder adjusted odds ratios (aOR) and 95% confidence intervals (95%CI). Results Parents who used invasive ART had an increased risk of VACTERL in offspring (aOR 4.4 [95%CI 2.1-8.8]), whereas the increased risk for mothers with CLOPD could not be replicated. None of the case mothers had pregestational diabetes mellitus. Primiparity (1.5 [1.1-2.1]) and maternal pregestational overweight and obesity (1.8 [1.2-2.8] and 1.8 [1.0-3.4]) were associated with VACTERL. Consistent folic acid supplement use during the advised periconceptional period may reduce the risk of VACTERL (0.5 [0.3-1.0]). Maternal smoking resulted in an almost twofold increased risk of VACTERL. Conclusion We identified invasive ART, primiparity, pregestational overweight and obesity, lack of folic acid supplement use, and smoking as risk factors for VACTERL

Predicting clinical benefit from everolimus in patients with advanced solid tumors, the CPCT-03 study

Background: In this study, our aim was to identify molecular aberrations predictive for response to everolimus, an mTOR inhibitor, regardless of tumor type. Methods: To generate hypotheses about potential markers for sensitivity to mTOR inhibition, drug sensitivity and genomic profiles of 835 cell lines were analyzed. Subsequently, a multicenter study was conducted. Patients with advanced solid tumors lacking standard of care treatment options were included and underwent a pre-treatment tumor biopsy to enable DNA sequencing of 1,977 genes, derive copy number profiles and determine activation status of pS6 and pERK. Treatment benefit was determined according to TTP ratio and RECIST. We tested for associations between treatment benefit and single molecular aberrations, clusters of aberrations and pathway perturbation. Results: Cell line screens indicated several genes, such as PTEN (P = 0.016; Wald test), to be associated with sensitivity to mTOR inhibition. Subsequently 73 patients were included, of which 59 started treatment with everolimus. Response and molecular data were available from 43 patients. PTEN aberrations, i.e. copy number loss or mutation, were associated with treatment benefit (P = 0.046; Fisher's exact test). Conclusion: Loss-of-function aberrations in PTEN potentially represent a tumor type agnostic biomarker for benefit from everolimus and warrants further confirmation in subsequent studies

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset

© 2015 Luo et al. For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease