Muscle area decreased significantly during chemotherapy and was independently associated with survival in patients with mCRC. Further clinical evaluation is required to determine whether nutritional interventions and exercise training may preserve muscle area and thereby improve outcome.
BackgroundThe built environment influences behaviour, like physical activity, diet and sleep, which affects the risk of type 2 diabetes mellitus (T2DM). This study systematically reviewed and meta-analysed evidence on the association between built environmental characteristics related to lifestyle behaviour and T2DM risk/prevalence, worldwide.MethodsWe systematically searched PubMed, EMBASE.com and Web of Science from their inception to 6 June 2017. Studies were included with adult populations (>18 years), T2DM or glycaemic markers as outcomes, and physical activity and/or food environment and/or residential noise as independent variables. We excluded studies of specific subsamples of the population, that focused on built environmental characteristics that directly affect the cardiovascular system, that performed prediction analyses and that do not report original research. Data appraisal and extraction were based on published reports (PROSPERO-ID: CRD42016035663).ResultsFrom 11,279 studies, 109 were eligible and 40 were meta-analysed. Living in an urban residence was associated with higher T2DM risk/prevalence (n = 19, odds ratio (OR) = 1.40; 95% CI, 1.2–1.6; I2 = 83%) compared to living in a rural residence. Higher neighbourhood walkability was associated with lower T2DM risk/prevalence (n = 8, OR = 0.79; 95% CI, 0.7–0.9; I2 = 92%) and more green space tended to be associated with lower T2DM risk/prevalence (n = 6, OR = 0.90; 95% CI, 0.8–1.0; I2 = 95%). No convincing evidence was found of an association between food environment with T2DM risk/prevalence.ConclusionsAn important strength of the study was the comprehensive overview of the literature, but our study was limited by the conclusion of mainly cross-sectional studies. In addition to other positive consequences of walkability and access to green space, these environmental characteristics may also contribute to T2DM prevention. These results may be relevant for infrastructure planning.Electronic supplementary materialThe online version of this article (doi:10.1186/s12916-017-0997-z) contains supplementary material, which is available to authorized users.
Background: Obesogenic food environments may influence dietary behaviours and contribute to obesity. Few countries quantified changes in their foodscape. We explored how the availability of different types of food retailers has changed in the Netherlands across levels of neighbourhood socioeconomic status (SES) and urbanisation. Methods: This longitudinal ecological study conducted in the Netherlands had as unit of analysis administrative neighbourhoods. From 2004 to 2018, the geographic location and type of each food retailer were objectively assessed by a commercial company. Food retailers were categorised as local food shops, fast food restaurants, food delivery, restaurants, supermarkets, and convenience stores. Information on neighbourhood SES and urbanisation was obtained from Central Bureau of Statistics (CBS). To test the change in the counts of food retailers we used negative binomial generalized estimating equations (GEE), with neighbourhoods as the group variable, time as the independent variable and the counts of each type of food retailer as outcome. To account for changes in population density, analyses were adjusted for the number of inhabitants per neighbourhood. We tested effect modification by adding an interaction term for neighbourhood SES and urbanisation to the models. Results: In Dutch neighbourhoods between 2004 and 2018, a 120 and 35% increase was found in the count of food delivery outlets and restaurants, respectively, and a 24% decrease in count of local food shops. Stratified analyses showed an increase in the availability of supermarkets and convenience stores in the more urbanised and lower SES neighbourhoods, while a decrease was observed in the less urbanised and higher SES neighbourhoods. Conclusions:We observed considerable changes in the Dutch foodscape. Over a 14 years period, the foodscape changed towards a higher availability of food retailers offering convenience and ready-to-eat foods. These findings can help policy makers aiming to promote a healthier food environment and obesity prevention.
Type 2 diabetes is one of the major chronic diseases accounting for a substantial proportion of disease burden in Western countries. The majority of the burden of type 2 diabetes is attributed to environmental risks and modifiable risk factors such as lifestyle. The environment we live in, and changes to it, can thus contribute substantially to the prevention of type 2 diabetes at a population level. The 'exposome' represents the (measurable) totality of environmental, i.e. nongenetic, drivers of health and disease. The external exposome comprises aspects of the built environment, the social environment, the physico-chemical environment and the lifestyle/food environment. The internal exposome comprises measurements at the epigenetic, transcript, proteome, microbiome or metabolome level to study either the exposures directly, the imprints these exposures leave in the biological system, the potential of the body to combat environmental insults and/or the biology itself. In this review, we describe the evidence for environmental risk factors of type 2 diabetes, focusing on both the general external exposome and imprints of this on the internal exposome. Studies provided established associations of air pollution, residential noise and area-level socioeconomic deprivation with an increased risk of type 2 diabetes, while neighbourhood walkability and green space are consistently associated with a reduced risk of type 2 diabetes. There is little or inconsistent evidence on the contribution of the food environment, other aspects of the social environment and outdoor temperature. These environmental factors are thought to affect type 2 diabetes risk mainly through mechanisms incorporating lifestyle factors such as physical activity or diet, the microbiome, inflammation or chronic stress. To further assess causality of these associations, future studies should focus on investigating the longitudinal effects of our environment (and changes to it) in relation to type 2 diabetes risk and whether these associations are explained by these proposed mechanisms.
Background Walkability indices have been developed and linked to behavioural and health outcomes elsewhere in the world, but not comprehensively for Europe. We aimed to 1) develop a theory-based and evidence-informed Dutch walkability index, 2) examine its cross-sectional associations with total and purpose-specific walking behaviours of adults across socioeconomic (SES) and urbanisation strata, 3) explore which walkability components drive these associations. Methods Components of the index included: population density, retail and service density, land use mix, street connectivity, green space, sidewalk density and public transport density. Each of the seven components was calculated for three Euclidean buffers: 150 m, 500 m and 1000 m around every 6-digit postal code location and for every administrative neighbourhood in GIS. Componential z-scores were averaged, and final indices normalized between 0 and 100. Data on self-reported demographic characteristics and walking behaviours of 16,055 adult respondents (aged 18–65) were extracted from the Dutch National Travel Survey 2017. Using Tobit regression modelling adjusted for individual- and household-level confounders, we assessed the associations between walkability and minutes walking in total, for non-discretionary and discretionary purposes. By assessing the attenuation in associations between partial indices and walking outcomes, we identified which of the seven components drive these associations. We also tested for effect modification by urbanization degree, SES, age and sex. Results In fully adjusted models, a 10% increase in walkability was associated with a maximum increase of 8.5 min of total walking per day (95%CI: 7.1–9.9). This association was consistent across buffer sizes and purposes of walking. Public transport density was driving the index’s association with walking outcomes. Stratified results showed that associations with minutes of non-discretionary walking were stronger in rural compared to very urban areas, in neighbourhoods with low SES compared to high SES, and in middle-aged (36–49 years) compared to young (18–35 years old) and older adults (50–65 years old). Conclusions The walkability index was cross-sectionally associated with Dutch adult’s walking behaviours, indicating its validity for further use in research.
BackgroundAlthough there are many effective lifestyle interventions for type 2 diabetes (T2DM) prevention, insight into effective intervention pathways, especially of long-term interventions, is often lacking. This study aims to provide insight into the effective intervention pathways of the SLIMMER diabetes prevention intervention using mediation analyses.MethodsIn total, 240 participants at increased risk of T2DM were included in the analyses over 18 months. The intervention was a combined lifestyle intervention with a dietary and a physical activity (PA) component. The primary and secondary outcomes were change in fasting insulin (pmol/L) and change in body weight (kg) after 18 months, respectively. Firstly, in a multiple mediator model, we investigated whether significant changes in these outcomes were mediated by changes in dietary and PA behavior. Secondly, in multiple single mediator models, we investigated whether changes in dietary and PA behavior were mediated by changes in behavioral determinants and the participants’ psychological profile. The mediation analyses used linear regression models, where significance of indirect effects was calculated with bootstrapping.ResultsThe effect of the intervention on decreased fasting insulin was 40% mediated by change in dietary and PA behavior, where dietary behavior was an independent mediator of the association (34%). The effect of the intervention on decreased body weight was 20% mediated by change in dietary and PA behavior, where PA behavior was an independent mediator (17%). The intervention significantly changed intake of fruit, fat from bread spread, and fiber from bread. Change in fruit intake was mediated by change in action control (combination of consciousness, self-control, and effort), motivation, self-efficacy, intention, and skills. Change in fat intake was mediated by change in action control and psychological profile. No mediators could be identified for change in fiber intake. The change in PA behavior was mediated by change in action control, motivation, and psychological profile.ConclusionThe effect of the SLIMMER intervention on fasting insulin and body weight was mediated by changes in dietary and PA behavior, in distinct ways. These results indicate that changing dietary as well as PA behavior is important in T2DM prevention.Electronic supplementary materialThe online version of this article (doi:10.1186/s12966-017-0532-9) contains supplementary material, which is available to authorized users.
BackgroundThe availability of outdoor recreational facilities is associated with increased leisure-time physical activity (PA). We investigated how much of this association is attributable to selection effects, and explored whether usage of recreational facilities was an explanatory mechanism.MethodsWe analysed data from 5199 participants in the SPOTLIGHT survey residing in five European urban regions. Adults completed a survey and a Google Street View-based virtual audit was conducted to objectively measure the availability of outdoor recreational facilities in the residential neighbourhood. We used negative binomial GEE models to examine the association between objective and subjective availability of outdoor recreational facilities and leisure-time PA, and explored whether this association was attenuated after adjustment for socioeconomic status and preference for neighbourhoods with recreational facilities (as indicators of self-selection). We examined whether reported use of recreational facilities was associated with leisure-time PA (as explanatory mechanism), and summarized the most important motivations for (not) using recreational facilities.ResultsSubjective – but not objective – availability of outdoor recreational facilities was associated with higher levels of total leisure-time PA. After adjustment for self-selection (which attenuated the association by 25%), we found a 25% difference in weekly minutes of total leisure-time PA between individuals with and without self-reported availability of outdoor recreational facilities. For our study population, this translates to about 28 min per week. Participants who reported outdoor recreational facilities to be present but indicated not to use them (RR = 1.19, 95% CI = 1.03;1.22), and those reporting outdoor recreational facilities to be present and to use them (RR = 1.33, 95% CI = 1.22, 1.45) had higher levels of total leisure-time PA than those who reported outdoor recreational facilities not to be present. Proximity to outdoor recreational facilities was the most important motivation for use.ConclusionThe modest attenuation in the association between availability of outdoor recreational facilities and self-reported leisure-time PA suggests that individuals’ higher activity levels may be due more to the perceived availability of outdoor recreational facilities than to self-selection. The use of these facilities seemed to be an important underlying mechanism, and proximity was the main motivator for using recreational facilities.Electronic supplementary materialThe online version of this article (10.1186/s12966-018-0689-x) contains supplementary material, which is available to authorized users.
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