A proposed potential role for increasing atmospheric CO2 as a promoter of weight gain and obesity

Human obesity has evolved into a global epidemic. Interestingly, a similar trend has been observed in many animal species, although diet composition, food availability and physical activity have essentially remained unchanged. This suggests a common factor—potentially an environmental factor affecting all species. Coinciding with the increase in obesity, atmospheric CO2 concentration has increased more than 40%. Furthermore, in modern societies, we spend more time indoors, where CO2 often reaches even higher concentrations. Increased CO2 concentration in inhaled air decreases the pH of blood, which in turn spills over to cerebrospinal fluids. Nerve cells in the hypothalamus that regulate appetite and wakefulness have been shown to be extremely sensitive to pH, doubling their activity if pH decreases by 0.1 units. We hypothesize that an increased acidic load from atmospheric CO2 may potentially lead to increased appetite and energy intake, and decreased energy expenditure, and thereby contribute to the current obesity epidemic

Support for smoke-free policies in the Cyprus hospitality industry

Objectives The present study used attitudinal and behavioural indicators to measure support for smoke-free policies among employers and employees in the hospitality industry in Cyprus. Methods A representative sample of 600 participants (95 % response rate) completed anonymous structured questionnaires on demographic variables, smoking status, exposure to second-hand smoke at work and related health beliefs, social norms, and smoke-free policy support. Results Participants were predominantly males (68.3 %), with a mean age of 40 years (SD = 12.69), and 39.7 % were employers/owners of the hospitality venue. Analysis of variance showed that employers and smokers were less supportive of smoke-free policies, as compared to employees and non-smokers. Linear regression models showed that attitudes towards smoke-free policy were predicted by smoking status, SHS exposure and related health beliefs, and social norm variables. Logistic regression analysis showed that willingness to confront a policy violator was predicted by SHS exposure, perceived prevalence of smoker clients, and smoke-free policy attitudes. Conclusions SHS exposure and related health beliefs, and normative factors should be targeted by interventions aiming to promote policy support in the hospitality industry in Cyprus

Augmenting Smart Buildings and Autonomous Vehicles with Wearable Thermal Technology

Smart buildings and autonomous vehicles are expected to see rapid growth and adoption in the coming decades. Americans spend over 90% of their lives in buildings or automobiles, meaning that 90% of their lives could be spent interfacing with intelligent environments. EMBR Labs has developed EMBR WaveTM, a wearable thermoelectric system, for introducing thermal sensation as a connected mode of interaction between smart environments and their occu-pants. In this paper we highlight applications of wearable thermal technology for passengers in autonomous vehicles and occupants of smart buildings. Initial find-ings, collected through partnerships with Draper and UC Berkeley, respectively, are presented that illustrate the potential for wearable thermal technology to im-prove the situational awareness of passengers in autonomous vehicles and im-prove personal comfort in smart buildings

Longitudinal variability of time-location/activity patterns of population at different ages: a longitudinal study in California

<p>Abstract</p> <p>Background</p> <p>Longitudinal time-activity data are important for exposure modeling, since the extent to which short-term time-activity data represent long-term activity patterns is not well understood. This study was designed to evaluate longitudinal variations in human time-activity patterns.</p> <p>Method</p> <p>We report on 24-hour recall diaries and questionnaires collected via the internet from 151 parents of young children (mostly under age 55), and from 55 older adults of ages 55 and older, for both a weekday and a weekend day every three months over an 18-month period. Parents also provided data for their children. The self-administrated diary and questionnaire distinguished ~30 frequently visited microenvironments and ~20 activities which we selected to represent opportunities for exposure to toxic environmental compounds. Due to the non-normal distribution of time-location/activity data, we employed generalized linear mixed-distribution mixed-effect models to examine intra- and inter-individual variations. Here we describe variation in the likelihood of and time spent engaging in an activity or being in a microenvironment by age group, day-type (weekday/weekend), season (warm/cool), sex, employment status, and over the follow-up period.</p> <p>Results</p> <p>As expected, day-type and season influence time spent in many location and activity categories. Longitudinal changes were also observed, e.g., young children slept less with increasing follow-up, transit time increased, and time spent on working and shopping decreased during the study, possibly related to human physiological changes with age and changes in macro-economic factors such as gas prices and the economic recession.</p> <p>Conclusions</p> <p>This study provides valuable new information about time-activity assessed longitudinally in three major age groups and greatly expands our knowledge about intra- and inter-individual variations in time-location/activity patterns. Longitudinal variations beyond weekly and seasonal patterns should be taken into account in simulating long-term time-activity patterns in exposure modeling.</p

Quantification of ETS exposure in hospitality workers who have never smoked

<p>Abstract</p> <p>Background</p> <p>Environmental Tobacco Smoke (ETS) was classified as human carcinogen (K1) by the German Research Council in 1998. According to epidemiological studies, the relative risk especially for lung cancer might be twice as high in persons who have never smoked but who are in the highest exposure category, for example hospitality workers. In order to implement these results in the German regulations on occupational illnesses, a valid method is needed to retrospectively assess the cumulative ETS exposure in the hospitality environment.</p> <p>Methods</p> <p>A literature-based review was carried out to locate a method that can be used for the German hospitality sector. Studies assessing ETS exposure using biological markers (for example urinary cotinine, DNA adducts) or questionnaires were excluded. Biological markers are not considered relevant as they assess exposure only over the last hours, weeks or months. Self-reported exposure based on questionnaires also does not seem adequate for medico-legal purposes. Therefore, retrospective exposure assessment should be based on mathematical models to approximate past exposure.</p> <p>Results</p> <p>For this purpose a validated model developed by Repace and Lowrey was considered appropriate. It offers the possibility of retrospectively assessing exposure with existing parameters (such as environmental dimensions, average number of smokers, ventilation characteristics and duration of exposure). The relative risk of lung cancer can then be estimated based on the individual cumulative exposure of the worker.</p> <p>Conclusion</p> <p>In conclusion, having adapted it to the German hospitality sector, an existing mathematical model appears to be capable of approximating the cumulative exposure. However, the level of uncertainty of these approximations has to be taken into account, especially for diseases with a long latency period such as lung cancer.</p

Inhaled steroid/tobacco smoke particle interactions: a new light on steroid resistance

<p>Abstract</p> <p>Background</p> <p>Inhaled steroid resistance is an obstacle to asthma control in asthmatic smokers. The reasons of this phenomenon are not yet entirely understood. Interaction of drug particles with environmental tobacco smoke (ETS) could change the aerodynamic profile of the drug through the particle coagulation phenomenon. Aim of the present study was to examine whether steroid particles interact with smoke when delivered in the presence of ETS.</p> <p>Methods</p> <p>Beclomethasone-hydrofluoralkane (BDP-HFA) pMDI particle profile was studied after a single actuation delivered in ambient air or in the presence of ETS in an experimental chamber using a light scattering Optical Particle Counter capable of measuring the concentrations of particle sized 0.3–1.0, 1.1–2.0, 2.1–3.0, 3.1–4.0, 4.1–5.0, and > 5.1 μm in diameter with a sampling time of one second. The number of drug particles delivered after a single actuation was measured as the difference between total particle number after drug delivery and background particle number. Two groups of experiments were carried out at different ambient background particle concentrations. Two-tail Student's t-test was used for statistical analysis.</p> <p>Results</p> <p>When delivered in ambient air, over 90% of BDP-HFA particles were found in the 0.3–1.0 μm size class, while particles sized 1.1–2.0 μm and 2.1–3.0 represented less than 6.6% and 2.8% of total particles, respectively. However, when delivered in the presence of ETS, drug particle profile was modified, with an impressive decrease of 0.3–1.0 μm particles, the most represented particles resulting those sized 1.1–2.0 μm (over 66.6% of total particles), and 2.1–3.0 μm particles accounting up to 31% of total particles.</p> <p>Conclusion</p> <p>Our data suggest that particle interaction between inhaled BDP-HFA pMDI and ETS takes place in the first few seconds after drug delivery, with a decrease in smaller particles and a concurrent increase of larger particles. The resulting changes in aerosol particle profile might modify regional drug deposition with potential detriment to drug efficacy, and represent a new element of steroid resistance in smokers. Although the present study does not provide any functional or clinical assessment, it might be useful to advise smokers and non smokers with obstructive lung disease such as asthma or COPD, to avoid to act inhaled drugs in the presence of ETS in order to obtain the best therapeutic effect.</p

Automated time activity classification based on global positioning system (GPS) tracking data

<p>Abstract</p> <p>Background</p> <p>Air pollution epidemiological studies are increasingly using global positioning system (GPS) to collect time-location data because they offer continuous tracking, high temporal resolution, and minimum reporting burden for participants. However, substantial uncertainties in the processing and classifying of raw GPS data create challenges for reliably characterizing time activity patterns. We developed and evaluated models to classify people's major time activity patterns from continuous GPS tracking data.</p> <p>Methods</p> <p>We developed and evaluated two automated models to classify major time activity patterns (i.e., indoor, outdoor static, outdoor walking, and in-vehicle travel) based on GPS time activity data collected under free living conditions for 47 participants (N = 131 person-days) from the Harbor Communities Time Location Study (HCTLS) in 2008 and supplemental GPS data collected from three UC-Irvine research staff (N = 21 person-days) in 2010. Time activity patterns used for model development were manually classified by research staff using information from participant GPS recordings, activity logs, and follow-up interviews. We evaluated two models: (a) a rule-based model that developed user-defined rules based on time, speed, and spatial location, and (b) a random forest decision tree model.</p> <p>Results</p> <p>Indoor, outdoor static, outdoor walking and in-vehicle travel activities accounted for 82.7%, 6.1%, 3.2% and 7.2% of manually-classified time activities in the HCTLS dataset, respectively. The rule-based model classified indoor and in-vehicle travel periods reasonably well (Indoor: sensitivity > 91%, specificity > 80%, and precision > 96%; in-vehicle travel: sensitivity > 71%, specificity > 99%, and precision > 88%), but the performance was moderate for outdoor static and outdoor walking predictions. No striking differences in performance were observed between the rule-based and the random forest models. The random forest model was fast and easy to execute, but was likely less robust than the rule-based model under the condition of biased or poor quality training data.</p> <p>Conclusions</p> <p>Our models can successfully identify indoor and in-vehicle travel points from the raw GPS data, but challenges remain in developing models to distinguish outdoor static points and walking. Accurate training data are essential in developing reliable models in classifying time-activity patterns.</p

Predictors of children's secondhand smoke exposure at home: a systematic review and narrative synthesis of the evidence

BACKGROUND: Children's exposure to secondhand smoke (SHS) has been causally linked to a number of childhood morbidities and mortalities. Over 50% of UK children whose parents are smokers are regularly exposed to SHS at home. No previous review has identified the factors associated with children's SHS exposure in the home. AIM: To identify by systematic review, the factors which are associated with children's SHS exposure in the home, determined by parent or child reports and/or biochemically validated measures including cotinine, carbon monoxide or home air particulate matter. METHODS: Electronic searches of MEDLINE, EMBASE, PsychINFO, CINAHL and Web of Knowledge to July 2014, and hand searches of reference lists from publications included in the review were conducted. FINDINGS: Forty one studies were included in the review. Parental smoking, low socioeconomic status and being less educated were all frequently and consistently found to be independently associated with children's SHS exposure in the home. Children whose parents held more negative attitudes towards SHS were less likely to be exposed. Associations were strongest for parental cigarette smoking status; compared to children of non-smokers, those whose mothers or both parents smoked were between two and 13 times more likely to be exposed to SHS. CONCLUSION: Multiple factors are associated with child SHS exposure in the home; the best way to reduce child SHS exposure in the home is for smoking parents to quit. If parents are unable or unwilling to stop smoking, they should instigate smoke-free homes. Interventions targeted towards the socially disadvantaged parents aiming to change attitudes to smoking in the presence of children and providing practical support to help parents smoke outside the home may be beneficial