Psychosocial factors, health behaviors and risk of cancer incidence: Testing interaction and effect modification in an individual participant data meta-analysis.

Depression, anxiety and other psychosocial factors are hypothesized to be involved in cancer development. We examined whether psychosocial factors interact with or modify the effects of health behaviors, such as smoking and alcohol use, in relation to cancer incidence. Two-stage individual participant data meta-analyses were performed based on 22 cohorts of the PSYchosocial factors and CAncer (PSY-CA) study. We examined nine psychosocial factors (depression diagnosis, depression symptoms, anxiety diagnosis, anxiety symptoms, perceived social support, loss events, general distress, neuroticism, relationship status), seven health behaviors/behavior-related factors (smoking, alcohol use, physical activity, body mass index, sedentary behavior, sleep quality, sleep duration) and seven cancer outcomes (overall cancer, smoking-related, alcohol-related, breast, lung, prostate, colorectal). Effects of the psychosocial factor, health behavior and their product term on cancer incidence were estimated using Cox regression. We pooled cohort-specific estimates using multivariate random-effects meta-analyses. Additive and multiplicative interaction/effect modification was examined. This study involved 437,827 participants, 36,961 incident cancer diagnoses, and 4,749,481 person years of follow-up. Out of 744 combinations of psychosocial factors, health behaviors, and cancer outcomes, we found no evidence of interaction. Effect modification was found for some combinations, but there were no clear patterns for any particular factors or outcomes involved. In this first large study to systematically examine potential interaction and effect modification, we found no evidence for psychosocial factors to interact with or modify health behaviors in relation to cancer incidence. The behavioral risk profile for cancer incidence is similar in people with and without psychosocial stress.

Associations of Anti-COVID-19 Measures and Lifestyle Changes During the COVID-19 Pandemic With Sleep Patterns in the Netherlands: A Longitudinal Study.

Although there is scientific evidence for an increased prevalence of sleep disorders during the coronavirus disease 2019 (COVID-19) pandemic, there is still limited information on how lifestyle factors might have affected sleep patterns. Therefore, we followed a large cohort of participants in the Netherlands (n = 5,420) for up to 1 year (September 2020-2021) via monthly Web-based questionnaires to identify lifestyle changes (physical activity, cigarette smoking, alcohol consumption, electronic device use, and social media use) driven by anti-COVID-19 measures and their potential associations with self-reported sleep (latency, duration, and quality). We used the Containment and Health Index (CHI) to assess the stringency of anti-COVID-19 measures and analyzed associations through multilevel ordinal response models. We found that more stringent anti-COVID-19 measures were associated with higher use of electronic devices (per interquartile-range increase in CHI, odds ratio (OR) = 1.47, 95% confidence interval (CI): 1.40, 1.53), less physical activity (OR = 0.94, 95% CI: 0.90, 0.98), lower frequency of alcohol consumption (OR = 0.63, 95% CI: 0.60, 0.66), and longer sleep duration (OR = 1.11, 95% CI: 1.05, 1.16). Lower alcohol consumption frequency and higher use of electronic devices and social media were associated with longer sleep latency. Lower physical activity levels and higher social media and electronic device use were related to poorer sleep quality and shorter sleep duration.

Regression calibration of self-reported mobile phone use to optimize quantitative risk estimation in the COSMOS study.

The Cohort Study of Mobile Phone Use and Health (COSMOS) has repeatedly collected self-reported and operator-recorded data on mobile phone use. Assessing health effects using self-reported information is prone to measurement error, but operator data were available prospectively for only part of the study population and did not cover past mobile phone use. To optimize the available data and reduce bias, we evaluated different statistical approaches for constructing mobile phone exposure histories within COSMOS. We evaluated and compared the performance of 4 regression calibration (RC) methods (simple, direct, inverse, and generalized additive model for location, shape, and scale), complete-case analysis, and multiple imputation in a simulation study with a binary health outcome. We used self-reported and operator-recorded mobile phone call data collected at baseline (2007-2012) from participants in Denmark, Finland, the Netherlands, Sweden, and the United Kingdom. Parameter estimates obtained using simple, direct, and inverse RC methods were associated with less bias and lower mean squared error than those obtained with complete-case analysis or multiple imputation. We showed that RC methods resulted in more accurate estimation of the relationship between mobile phone use and health outcomes by combining self-reported data with objective operator-recorded data available for a subset of participants.

The mediating role of health behaviors in the association between depression, anxiety and cancer incidence: an individual participant data meta-analysis.

BACKGROUND: Although behavioral mechanisms in the association among depression, anxiety, and cancer are plausible, few studies have empirically studied mediation by health behaviors. We aimed to examine the mediating role of several health behaviors in the associations among depression, anxiety, and the incidence of various cancer types (overall, breast, prostate, lung, colorectal, smoking-related, and alcohol-related cancers). METHODS: Two-stage individual participant data meta-analyses were performed based on 18 cohorts within the Psychosocial Factors and Cancer Incidence consortium that had a measure of depression or anxiety (N = 319 613, cancer incidence = 25 803). Health behaviors included smoking, physical inactivity, alcohol use, body mass index (BMI), sedentary behavior, and sleep duration and quality. In stage one, path-specific regression estimates were obtained in each cohort. In stage two, cohort-specific estimates were pooled using random-effects multivariate meta-analysis, and natural indirect effects (i.e. mediating effects) were calculated as hazard ratios (HRs). RESULTS: Smoking (HRs range 1.04-1.10) and physical inactivity (HRs range 1.01-1.02) significantly mediated the associations among depression, anxiety, and lung cancer. Smoking was also a mediator for smoking-related cancers (HRs range 1.03-1.06). There was mediation by health behaviors, especially smoking, physical inactivity, alcohol use, and a higher BMI, in the associations among depression, anxiety, and overall cancer or other types of cancer, but effects were small (HRs generally below 1.01). CONCLUSIONS: Smoking constitutes a mediating pathway linking depression and anxiety to lung cancer and smoking-related cancers. Our findings underline the importance of smoking cessation interventions for persons with depression or anxiety.

Associations of light exposure patterns with sleep among Dutch children: The ABCD cohort study.

Light exposure affects the circadian system and consequently can affect sleep quality. Only few studies examined this relationship in children. We evaluated associations between light exposure patterns and sleep metrics in children. We measured the sleep parameters of 247 Dutch children, aged between 11 and 13 years and recruited from the ABCD cohort, using actigraphy and sleep records for 7 consecutive nights. Personal light exposures were measured with a light meter during the whole day and night. We applied generalized mixed-effects regression models, adjusted for possible confounders, to evaluate the associations of light exposure patterns on sleep duration, sleep efficiency and sleep-onset delay. In the models mutually adjusted for potential confounders, we found the amount of hours between the first time of bright light in the morning and going to sleep and the duration of bright light to be significantly associated with decreased sleep duration (in min; ß: -2.02 [95% confidence interval: -3.84, -0.25], ß: -8.39 [95% confidence interval: -16.70, -0.07], respectively) and with shorter sleep-onset delay (odds ratio: 0.88 [95% confidence interval: 0.80, 0.97], odds ratio: 0.40 [95% confidence interval: 0.19, 0.87], respectively). Increased light intensities at night were associated with decreased sleep duration (T2 ß: -8.54 [95% confidence interval: -16.88, -0.20], T3 ß: -14.83 [95% confidence interval: -28.04, -1.62]), while increased light intensities before going to bed were associated with prolonged sleep onset (odds ratio: 4.02 [95% confidence interval: 2.09, 7.73]). These findings further suggest that children may be able to influence their sleep quality by influencing the light exposure patterns during day and night.

Socioeconomic Inequalities in the External Exposome in European Cohorts: The EXPANSE Project.

Socioeconomic inequalities in the exposome have been found to be complex and highly context-specific, but studies have not been conducted in large population-wide cohorts from multiple countries. This study aims to examine the external exposome, encompassing individual and environmental factors influencing health over the life course, and to perform dimension reduction to derive interpretable characterization of the external exposome for multicountry epidemiological studies. Analyzing data from over 25 million individuals across seven European countries including 12 administrative and traditional cohorts, we utilized domain-specific principal component analysis (PCA) to define the external exposome, focusing on air pollution, the built environment, and air temperature. We conducted linear regression to estimate the association between individual- and area-level socioeconomic position and each domain of the external exposome. Consistent exposure patterns were observed within countries, indicating the representativeness of traditional cohorts for air pollution and the built environment. However, cohorts with limited geographical coverage and Southern European countries displayed lower temperature variability, especially in the cold season, compared to Northern European countries and cohorts including a wide range of urban and rural areas. The individual- and area-level socioeconomic determinants (i.e., education, income, and unemployment rate) of the urban exposome exhibited significant variability across the European region, with area-level indicators showing stronger associations than individual variables. While the PCA approach facilitated common interpretations of the external exposome for air pollution and the built environment, it was less effective for air temperature. The diverse socioeconomic determinants suggest regional variations in environmental health inequities, emphasizing the need for targeted interventions across European countries.

Headache in the international cohort study of mobile phone use and health (COSMOS) in the Netherlands and the United Kingdom.

Headache is a common condition with a substantial burden of disease worldwide. Concerns have been raised over the potential impact of long-term mobile phone use on headache due to radiofrequency electromagnetic fields (RF-EMFs). We explored prospectively the association between mobile phone use at baseline (2009-2012) and headache at follow-up (2015-2018) by analysing pooled data consisting of the Dutch and UK cohorts of the Cohort Study of Mobile Phone Use and Health (COSMOS) (N = 78,437). Frequency of headache, migraine, and information on mobile phone use, including use of hands-free devices and frequency of texting, were self-reported. We collected objective operator data to obtain regression calibrated estimates of voice call duration. In the model mutually adjusted for call-time and text messaging, participants in the high category of call-time showed an adjusted odds ratio (OR) of 1.04 (95 % CI: 0.94-1.15), with no clear trend of reporting headache with increasing call-time. However, we found an increased risk of weekly headache (OR = 1.40, 95 % CI: 1.25-1.56) in the high category of text messaging, with a clear increase in reporting headache with increasing texting. Due to the negligible exposure to RF-EMFs from texting, our results suggest that mechanisms other than RF-EMFs are responsible for the increased risk of headache that we found among mobile phone users.

International study of childhood leukemia in residences near electrical transformer rooms.

OBJECTIVES: New epidemiologic approaches are needed to reduce the scientific uncertainty surrounding the association between extremely low frequency magnetic fields (ELF-MF) and childhood leukemia. While most previous studies focused on power lines, the Transformer Exposure study sought to assess this association using a multi-country study of children who had lived in buildings with built-in electrical transformers. ELF-MF in apartments above built-in transformers can be 5 times higher than in other apartments in the same building. This novel study design aimed to maximize the inclusion of highly exposed children while minimising the potential for selection bias. METHODS: We assessed associations between residential proximity to transformers and risk of childhood leukemia using registry based matched case-control data collected in five countries. Exposure was based on the location of the subject's apartment relative to the transformer, coded as high (above or adjacent to transformer), intermediate (same floor as apartments in high category), or unexposed (other apartments). Relative risk (RR) for childhood leukemia was estimated using conditional logistic and mixed logistic regression with a random effect for case-control set. RESULTS: Data pooling across countries yielded 16 intermediate and 3 highly exposed cases. RRs were 1.0 (95% CI: 0.5, 1.9) for intermediate and 1.1 (95% CI: 0.3, 3.8) for high exposure in the conditional logistic model. In the mixed logistic model, RRs were 1.4 (95% CI: 0.8, 2.5) for intermediate and 1.3 (95% CI: 0.4, 4.4) for high. Data of the most influential country showed RRs of 1.1 (95% CI: 0.5, 2.4) and 1.7 (95% CI: 0.4, 7.2) for intermediate (8 cases) and high (2 cases) exposure. DISCUSSION: Overall, evidence for an elevated risk was weak. However, small numbers and wide confidence intervals preclude strong conclusions and a risk of the magnitude observed in power line studies cannot be excluded.

Validation of mobile phone use recall in the multinational MOBI-kids study.

Potential differential and non-differential recall error in mobile phone use (MPU) in the multinational MOBI-Kids case-control study were evaluated. We compared self-reported MPU with network operator billing record data up to 3 months, 1 year, and 2 years before the interview date from 702 subjects aged between 10 and 24 years in eight countries. Spearman rank correlations, Kappa coefficients and geometric mean ratios (GMRs) were used. No material differences in MPU recall estimates between cases and controls were observed. The Spearman rank correlation coefficients between self-reported and recorded MPU in the most recent 3 months were 0.57 and 0.59 for call number and for call duration, respectively. The number of calls was on average underestimated by the participants (GMR = 0.69), while the duration of calls was overestimated (GMR = 1.59). Country, years since start of using a mobile phone, age at time of interview, and sex did not appear to influence recall accuracy for either call number or call duration. A trend in recall error was seen with level of self-reported MPU, with underestimation of use at lower levels and overestimation of use at higher levels for both number and duration of calls. Although both systematic and random errors in self-reported MPU among participants were observed, there was no evidence of differential recall error between cases and controls. Nonetheless, these sources of exposure measurement error warrant consideration in interpretation of the MOBI-Kids case-control study results on the association between children's use of mobile phones and potential brain cancer risk.

Depression, anxiety, and the risk of cancer: An individual participant data meta-analysis.

BACKGROUND: Depression and anxiety have long been hypothesized to be related to an increased cancer risk. Despite the great amount of research that has been conducted, findings are inconclusive. To provide a stronger basis for addressing the associations between depression, anxiety, and the incidence of various cancer types (overall, breast, lung, prostate, colorectal, alcohol-related, and smoking-related cancers), individual participant data (IPD) meta-analyses were performed within the Psychosocial Factors and Cancer Incidence (PSY-CA) consortium. METHODS: The PSY-CA consortium includes data from 18 cohorts with measures of depression or anxiety (up to N = 319,613; cancer incidences, 25,803; person-years of follow-up, 3,254,714). Both symptoms and a diagnosis of depression and anxiety were examined as predictors of future cancer risk. Two-stage IPD meta-analyses were run, first by using Cox regression models in each cohort (stage 1), and then by aggregating the results in random-effects meta-analyses (stage 2). RESULTS: No associations were found between depression or anxiety and overall, breast, prostate, colorectal, and alcohol-related cancers. Depression and anxiety (symptoms and diagnoses) were associated with the incidence of lung cancer and smoking-related cancers (hazard ratios [HRs], 1.06-1.60). However, these associations were substantially attenuated when additionally adjusting for known risk factors including smoking, alcohol use, and body mass index (HRs, 1.04-1.23). CONCLUSIONS: Depression and anxiety are not related to increased risk for most cancer outcomes, except for lung and smoking-related cancers. This study shows that key covariates are likely to explain the relationship between depression, anxiety, and lung and smoking-related cancers. PREREGISTRATION NUMBER: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=157677.

Residential exposure to livestock farms and lung function in adolescence - The PIAMA birth cohort study.

BACKGROUND: There is a growing interest in the impact of air pollution from livestock farming on respiratory health. Studies in adults suggest adverse effects of livestock farm emissions on lung function, but so far, studies involving children and adolescents are lacking. OBJECTIVES: To study the association of residential proximity to livestock farms and modelled particulate matter ≤10 µm (PM10) from livestock farms with lung function in adolescence. METHODS: We performed a cross-sectional study among 715 participants of the Dutch prospective PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort study. Relationships of different indicators of residential livestock farming exposure (distance to farms, distance-weighted number of farms, cattle, pigs, poultry, horses and goats within 3 km; modelled atmospheric PM10 concentrations from livestock farms) with forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) at age 16 were assessed by linear regression taking into account potential confounders. Associations were expressed per interquartile range increase in exposure. RESULTS: Higher exposure to livestock farming was consistently associated with a lower FEV1, but not with FVC among participants living in less urbanized municipalities (<1500 addresses/km2, N = 402). Shorter distances of homes to livestock farms were associated with a 1.4% (0.2%; 2.7%) lower FEV1. Larger numbers of farms within 3 km and higher concentrations of PM10 from livestock farming were associated with a 1.8% (0.8%, 2.9%) and 0.9% (0.4%,1.5%) lower FEV1, respectively. CONCLUSIONS: Our findings suggest that higher exposure to livestock farming is associated with a lower FEV1 in adolescents. Replication and more research on the etiologic agents involved in these associations and the underlying mechanisms is needed.

Environmental risk factors of type 2 diabetes-an exposome approach.

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.

A Multipollutant Approach to Estimating Causal Effects of Air Pollution Mixtures on Overall Mortality in a Large, Prospective Cohort.

BACKGROUND: Several studies have confirmed associations between air pollution and overall mortality, but it is unclear to what extent these associations reflect causal relationships. Moreover, few studies to our knowledge have accounted for complex mixtures of air pollution. In this study, we evaluate the causal effects of a mixture of air pollutants on overall mortality in a large, prospective cohort of Dutch individuals. METHODS: We evaluated 86,882 individuals from the LIFEWORK study, assessing overall mortality between 2013 and 2017 through national registry linkage. We predicted outdoor concentration of five air pollutants (PM2.5, PM10, NO2, PM2.5 absorbance, and oxidative potential) with land-use regression. We used logistic regression and mixture modeling (weighted quantile sum and boosted regression tree models) to identify potential confounders, assess pollutants' relevance in the mixture-outcome association, and investigate interactions and nonlinearities. Based on these results, we built a multivariate generalized propensity score model to estimate the causal effects of pollutant mixtures. RESULTS: Regression model results were influenced by multicollinearity. Weighted quantile sum and boosted regression tree models indicated that all components contributed to a positive linear association with the outcome, with PM2.5 being the most relevant contributor. In the multivariate propensity score model, PM2.5 (OR=1.18, 95% CI: 1.08-1.29) and PM10 (OR=1.02, 95% CI: 0.91-1.14) were associated with increased odds of mortality per interquartile range increase. CONCLUSION: Using novel methods for causal inference and mixture modeling in a large prospective cohort, this study strengthened the causal interpretation of air pollution effects on overall mortality, emphasizing the primary role of PM2.5 within the pollutant mixture.

Self-reported psychological distress and self-perceived health in residents living near pesticide-treated agricultural land: a cross-sectional study in The Netherlands.

OBJECTIVES: There is rising concern regarding possible health effects from exposure to pesticides in residents living near agricultural land. Some studies indicated increased risks of reporting symptoms of anxiety and depression among agricultural workers but less is known about the mental and perceived health of rural residents. We aimed to study possible associations between self-reported psychological distress (SPD) and self-perceived health (SPH) in residents near pesticide-treated agricultural land. METHODS: Using the Public Health Monitor national survey from 2012, we selected 216 932 participants who lived in rural and semi-urban areas of the Netherlands and changed addresses at most once in the period 2009-2012. Psychological distress (PD) was assessed via the Kessler Psychological Distress scale (K10) and participants were asked to assess their own health. We estimated the area of specific crop groups cultivated within buffers of 50 m, 100 m, 250 m and 500 m around each individual's residence for the period 2009-2012. Association between these exposure proxies and the outcomes was investigated using logistic regression, adjusting for individual, lifestyle and area-level confounders. RESULTS: Overall, results showed statistically non-significant OR across all buffer sizes for both SPD and SPH, except for the association between SPH and 'all crops' (total area of all considered crop groups) with OR (95% CI) ranging from 0.77 (0.63 to 0.93) in 50 m to 1.00 (1.00 to 1.00) in 500 m. We observed that most ORs were below unity for SPH. CONCLUSIONS: This study provides no evidence that residential proximity to pesticide treated-crops is associated with PD or poorer perceived health.

Malignant lymphoma and occupational exposure to extremely low frequency magnetic fields and electrical shocks: a nested case-control study in a cohort of four Nordic countries.

BACKGROUND: Exposure to extremely low frequency magnetic fields (ELF-MFs) and electric shocks is a common occupational risk factor in many workplaces. Recent investigations have highlighted a possible association between such exposures and lymphoma risk. This study was carried out to further explore the association between occupational exposure to ELF-MFs and electric shocks and risk of lymphoma in a large Nordic census-based cohort. METHODS: We included cases of non-Hodgkin's lymphoma (NHL, n=68 978), chronic lymphocytic leukaemia (CLL, n=20 615) and multiple myeloma (MM, n=35 467) diagnosed between 1961 and 2005 in Finland, Iceland, Norway and Sweden. Cases were matched to five controls by year of birth, sex and country. Lifetime occupational ELF-MF and electric shock exposures were assigned to jobs reported in population censuses using job-exposure matrices. The risk of cancer was assessed based on cumulative exposure to ELF-MF and electric shocks. ORs with 95% CIs were estimated using logistic models adjusted for occupational co-exposures relevant to lymphomas. RESULTS: Less than 7% of the cases experienced high levels of ELF-MF. We observed no increased risks among workers exposed to high levels of ELF-MF for NHL (OR: 0.93; CI 0.90 to 0.97), CLL (OR: 0.98; CI 0.92 to 1.05) or MM (OR: 0.96; CI 0.90 to 1.01). CONCLUSION: Our results do not provide support for an association between occupational exposure to ELF-MFs and electric shocks and lymphoma risk.

Impact of occupational pesticide exposure assessment method on risk estimates for prostate cancer, non-Hodgkin's lymphoma and Parkinson's disease: results of three meta-analyses.

Assessment of occupational pesticide exposure in epidemiological studies of chronic diseases is challenging. Biomonitoring of current pesticide levels might not correlate with past exposure relevant to disease aetiology, and indirect methods often rely on workers' imperfect recall of exposures, or job titles. We investigated how the applied exposure assessment method influenced risk estimates for some chronic diseases. In three meta-analyses the influence of exposure assessment method type on the summary risk ratio (sRR) of prostate cancer (PC) (25 articles), non-Hodgkin's lymphoma (NHL) (29 articles) and Parkinson's disease (PD) (32 articles) was investigated. Exposure assessment method types analysed were: group-level assessments (eg, job titles), self-reported exposures, expert-level assessments (eg, job-exposure matrices) and biomonitoring (eg, blood, urine). Additionally, sRRs were estimated by study design, publication year period and geographic location where the study was conducted. Exposure assessment method types were not associated with statistically significant different sRRs across any of the health outcomes. Heterogeneity in results varied from high in cancer studies to moderate and low in PD studies. Overall, case-control designs showed significantly higher sRR estimates than prospective cohort designs. Later NHL publications showed significantly higher sRR estimates than earlier. For PC, studies from North America showed significantly higher sRR estimates than studies from Europe. We conclude that exposure assessment method applied in studies of occupational exposure to pesticides appears not to have a significant effect on risk estimates for PC, NHL and PD. In systematic reviews of chronic health effects of occupational exposure to pesticides, epidemiological study design, publication year and geographic location, should primarily be considered.

Pesticide exposure among Czech adults and children from the CELSPAC-SPECIMEn cohort: Urinary biomarker levels and associated health risks.

Current-use pesticides (CUP) are extensively applied in both agricultural and urban settings. Exposure occurs mainly via the dietary pathway; however, other pathways such as inhalation or skin contact are also important. In this study, urinary levels of 12 CUP metabolites were investigated among 110 parent-child pairs during two seasons of 2020. Metabolites of pyrethroids (3-PBA, t/c-DCCA), chlorpyrifos (TCPY), and tebuconazole (TEB-OH) were detected in more than 60% of the samples. Chlorpyrifos metabolite was found at the highest concentration and tebuconazole was detected in almost all samples. CUP urinary metabolite levels were significantly higher in children in comparison to adults, except for tebuconazole, which was similar in both groups. In children, winter samples had significantly higher concentrations of pyrethroid and chlorpyrifos metabolites in comparison to the summer samples, but in adults, only chlorpyrifos metabolite concentrations were higher in the winter. No association between CUP urinary metabolite levels and proximity/surface of agricultural areas around residences was observed. Based on our findings, we suspect that CUP exposure is mainly driven by diet and that the effect of environmental exposure is less significant. Daily Intakes were estimated with three possible scenarios considering the amount of the metabolite excreted in urine and were compared to Acceptable Daily Intake values. Using a realistic scenario, exposure to chlorpyrifos exhibited the highest health risk, but still within a safe level. The Acceptable Daily Intake was exceeded only in one child in the case of cypermethrin. The cumulative risk assessment of pesticide mixtures having an effect on the nervous system, based on the total margin of exposure calculations, did not indicate any risk. The overall risk associated with pesticide exposure in the observed population was low. However, the risk observed using the worst-case scenario suggests the need for continuous evaluation of human exposure to such compounds, especially in children.

Estimated all-day and evening whole-brain radiofrequency electromagnetic fields doses, and sleep in preadolescents.

OBJECTIVE: To investigate the association of estimated all-day and evening whole-brain radiofrequency electromagnetic field (RF-EMF) doses with sleep disturbances and objective sleep measures in preadolescents. METHODS: We included preadolescents aged 9-12 years from two population-based birth cohorts, the Dutch Generation R Study (n = 974) and the Spanish INfancia y Medio Ambiente Project (n = 868). All-day and evening overall whole-brain RF-EMF doses (mJ/kg/day) were estimated for several RF-EMF sources including mobile and Digital Enhanced Cordless Telecommunications (DECT) phone calls (named phone calls), other mobile phone uses, tablet use, laptop use (named screen activities), and far-field sources. We also estimated all-day and evening whole-brain RF-EMF doses in these three groups separately (i.e. phone calls, screen activities, and far-field). The Sleep Disturbance Scale for Children was completed by mothers to assess sleep disturbances. Wrist accelerometers together with sleep diaries were used to measure sleep characteristics objectively for 7 consecutive days. RESULTS: All-day whole-brain RF-EMF doses were not associated with self-reported sleep disturbances and objective sleep measures. Regarding evening doses, preadolescents with high evening whole-brain RF-EMF dose from phone calls had a shorter total sleep time compared to preadolescents with zero evening whole-brain RF-EMF dose from phone calls [-11.9 min (95%CI -21.2; -2.5)]. CONCLUSIONS: Our findings suggest the evening as a potentially relevant window of RF-EMF exposure for sleep. However, we cannot exclude that observed associations are due to the activities or reasons motivating the phone calls rather than the RF-EMF exposure itself or due to chance finding.

Ultra-processed food consumption patterns among older adults in the Netherlands and the role of the food environment.

PURPOSE: To describe the patterns of ultra-processed foods (UPFs) consumption in the Netherlands; to test if exposure to the food environment is associated with UPFs consumption; and if this association differed across educational levels and neighbourhood urbanisation. METHODS: Cross-sectional study using 2015-data of 8104 older adults from the Dutch EPIC cohort. Proportion of UPFs consumption was calculated from a validated food-frequency questionnaire. Exposure to the food environment was defined as proximity and availability of supermarkets, fast-food restaurants, full-service restaurants, convenience stores, candy stores and cafés. Consumption of UPFs was expressed as both percentage of total grams and total kilocalories. RESULTS: The study population was aged 70(± 10 SD) years and 80.5% was female. Average UPFs consumption was 17.8% of total food intake in grams and 37% of total energy intake. Those who consumed greater amounts of UPFs had a poorer overall diet quality. Adjusted linear regression models showed that closer proximity and larger availability to any type of food retailer was associated with lower UPFs consumption (both in grams and kilocalories). Somewhat stronger significant associations were found for proximity to restaurants (ß = - 1.6%, 95% confidence interval (CI) = - 2.6; - 0.6), and supermarkets (ß = - 2.2%, 95%CI = - 3.3; - 1.1); i.e., Individuals living within 500 m from the closest supermarket, as compared to 1500 m, had 2.6% less calories from UPFs. No differences were found on analyses stratified for urbanisation and education. CONCLUSIONS: Using various measures of exposure to the food environment, we found that exposure to restaurants and supermarkets was associated with somewhat lower consumption of UPFs.

Radiofrequency electromagnetic fields from mobile communication: Description of modeled dose in brain regions and the body in European children and adolescents.

BACKGROUND: Little is known about radiofrequency electromagnetic fields (RF) from mobile technology and resulting dose in young people. We describe modeled integrated RF dose in European children and adolescents combining own mobile device use and surrounding sources. METHODS: Using an integrated RF model, we estimated the daily RF dose in the brain (whole-brain, cerebellum, frontal lobe, midbrain, occipital lobe, parietal lobe, temporal lobes) and the whole-body in 8358 children (ages 8-12) and adolescents (ages 14-18) from the Netherlands, Spain, and Switzerland during 2012-2016. The integrated model estimated RF dose from near-field sources (digital enhanced communication technology (DECT) phone, mobile phone, tablet, and laptop) and far-field sources (mobile phone base stations via 3D-radiowave modeling or RF measurements). RESULTS: Adolescents were more frequent mobile phone users and experienced higher modeled RF doses in the whole-brain (median 330.4 mJ/kg/day) compared to children (median 81.8 mJ/kg/day). Children spent more time using tablets or laptops compared to adolescents, resulting in higher RF doses in the whole-body (median whole-body dose of 81.8 mJ/kg/day) compared to adolescents (41.9 mJ/kg/day). Among brain regions, temporal lobes received the highest RF dose (medians of 274.9 and 1786.5 mJ/kg/day in children and adolescents, respectively) followed by the frontal lobe. In most children and adolescents, calling on 2G networks was the main contributor to RF dose in the whole-brain (medians of 31.1 and 273.7 mJ/kg/day, respectively). CONCLUSION: This first large study of RF dose to the brain and body of children and adolescents shows that mobile phone calls on 2G networks are the main determinants of brain dose, especially in temporal and frontal lobes, whereas whole-body doses were mostly determined by tablet and laptop use. The modeling of RF doses provides valuable input to epidemiological research and to potential risk management regarding RF exposure in young people.