Association between ambient beta particle radioactivity and lower hemoglobin concentrations in a cohort of elderly men

Risk analysis of air pollutants and types of anemia: a UK Biobank prospective cohort study

Previous studies have suggested that exposure to air pollutants may be associated with specific blood indicators or anemia in certain populations. However, there is insufficient epidemiological data and prospective evidence to evaluate the relationship between environmental air pollution and specific types of anemia. We conducted a large-scale prospective cohort study based on the UK Biobank. Annual average concentrations of NO2, PM2.5, PM2.5-10, and PM10 were obtained from the ESCAPE study using the Land Use Regression (LUR) model. The association between atmospheric pollutants and different types of anemia was investigated using the Cox proportional hazards model. Furthermore, restricted cubic splines were used to explore exposure-response relationships for positive associations, followed by stratification and effect modification analyses by gender and age. After adjusting for demographic characteristics, 3-4 of the four types of air pollution were significantly associated with an increased risk of iron deficiency, vitamin B12 deficiency and folate deficiency anemia, while there was no significant association with other defined types of anemia. After full adjustment, we estimated that the hazard ratios (HRs) of iron deficiency anemia associated with each 10 μg/m3 increase in NO2, PM2.5, and PM10 were 1.04 (95%CI: 1.02, 1.07), 2.00 (95%CI: 1.71, 2.33), and 1.10 (95%CI: 1.02, 1.20) respectively. The HRs of folate deficiency anemia with each 10 μg/m3 increase in NO2, PM2.5, PM2.5-10, and PM10 were 1.25 (95%CI: 1.12, 1.40), 4.61 (95%CI: 2.03, 10.47), 2.81 (95%CI: 1.11, 7.08), and 1.99 (95%CI: 1.25, 3.15) respectively. For vitamin B12 deficiency anemia, no significant association with atmospheric pollution was found. Additionally, we estimated almost linear exposure-response curves between air pollution and anemia, and interaction analyses suggested that gender and age did not modify the association between air pollution and anemia. Our research provided reliable evidence for the association between long-term exposure to PM10, PM2.5, PM2.5-10, NO2, and several types of anemia. NO2, PM2.5, and PM10 significantly increased the risk of iron deficiency anemia and folate deficiency anemia. Additionally, we found that the smaller the PM diameter, the higher the risk, and folate deficiency anemia was more susceptible to air pollution than iron deficiency anemia. No association was observed between the four types of air pollution and hemolytic anemia, aplastic anemia, and other types of anemia. Although the mechanisms are not well understood, we emphasize the need to limit the levels of PM and NO2 in the environment to reduce the potential impact of air pollution on folate and iron deficiency anemia.

High ambient temperature may increase the risk of anemia in pregnancy: Identifying susceptible exposure windows

Anemia in pregnancy (AIP) is associated with multiple severe maternal and perinatal adverse outcomes. However, there is a lack of evidence on the association between environmental factors and AIP. Aim to explore the association between ambient temperature and the risk of AIP, and identify susceptible exposure windows, we conducted a matched case-control study from 2013 to 2016 in Xi'an, China, which included 710 women with AIP and 1420 women without AIP. The conditional logistic regression model was used to evaluate the association between ambient temperature and AIP at different gestational weeks and gestational months. The association between extreme temperature and AIP was evaluated using the distributed lag nonlinear model (DLNM). We conducted stratified analyses of age, parity, and season of conception, and estimated the interaction between ambient temperature and air pollutants on AIP. Ambient temperature was significantly positively associated with the risk of AIP, and the susceptible exposure windows were 2-25 gestational weeks and 1-6 gestational months, respectively. The strongest effect was observed in the week 8 and month 2, for each 1 °C increase in weekly and monthly mean temperature, the odds ratio (OR) for AIP was 1.038 (95 % confidence interval (CI): 1.022, 1.055) and 1.040 (95 % CI: 1.020, 1.060), respectively. Extreme heat may increase the risk of AIP. Stratified analyses showed that there was no significant difference among different age, parity, and season of conception groups. No significant interaction effect of ambient temperature with air pollution on AIP was found. In summary, high ambient temperature may increase the risk of AIP, and the first and second trimesters may be susceptible exposure windows. Understanding the effect of temperature on pregnant women will be beneficial to reduce the occurrence of AIP.

Exposure to air pollution as a risk factor for anaemia: a global scoping review

Anaemia is an important global health issue with various factors responsible for its occurrence. Though nutritional deficiency is one of the main causes of the disease, evidence suggests a potential link between long-term exposure to ambient air pollution and an increased risk of developing anaemia. Our scoping review evaluates studies conducted across the world to examine possible associations between anaemia and ambient air pollution. Six databases were searched, 153 sources were identified, and 21 articles were included in the review. Apart from one article which showed no significant effect, studies reported positive associations between anaemia and air pollution. This was true for both indoor and outdoor air pollution, various types of particulate matter exposure, and across demographic groups. The review highlights the importance of recognizing exposure to air pollution as a potential risk factor for anaemia and emphasizes the imperative for focused interventions and policy measures to mitigate air pollution.

Use of Blood Powder (Ground and Irradiated) for the Manufacture of Chocolate Agar

Chocolate agar (CA) is an enriched medium for the isolation and identification of fastidious bacteria. Defibrinated blood is used to manufacture CA, but this expensive product is not always affordable for companies in developing countries. Blood powder (BP) is potentially a cheaper alternative, although its pre-treatment using autoclaving can impair the quality of the media. Therefore, optimization of BP as a substitute for defibrinated blood for CA manufacture deserves further research. CA was manufactured with irradiated BP (dehydrated bovine blood powder) and its physical and microbiological characteristics were compared with those of conventional CA and CA prepared with autoclaved BP. Each medium was seeded with 20-200 CFU of target bacteria using the spiral pouring method. Finally, another medium was prepared using BP pre-treated by grinding and gamma irradiation and its performance assessed. Compared to conventional CA, the medium containing ground and irradiated BP provided a similar CFU count for both fastidious (Neisseria, Haemophilus, Campylobacter, and Streptococcus) and non-fastidious (Moraxella, Staphylococcus, Enterococcus, Klebsiella, and Pseudomonas) species, unlike the medium prepared with BP subjected only to irradiation, which provided a lower growth of fastidious species. Morphology and characteristics of all bacterial colonies were very similar in conventional CA and the new medium, the number of Pseudomonas CFU being higher in the latter. The medium prepared with ground plus irradiated vs. irradiated BP more closely resembled conventional CA, having a browner background. The new CA medium prepared with ground and gamma irradiation-sterilized BP has comparable productivity properties to conventional CA. Therefore, it could be a more practical and economical methodology to facilitate large-scale CA manufacture.

Associations between solar and geomagnetic activity and peripheral white blood cells in the Normative Aging Study

It has been hypothesized that solar and geomagnetic activity can affect the function of the autonomic nervous system (ANS) and melatonin secretion, both of which may influence immune response. We investigated the association between solar geomagnetic activity and white blood cell counts in the Normative Aging Study (NAS) Cohort between 2000 and 2013. Linear mixed effects models with moving day averages ranging from 0 to 28 days were used to evaluate the effects of solar activity measures, interplanetary magnetic field (IMF), and sunspot number (SSN), and a measure of geomagnetic activity, K Index (K), on total white blood cell (WBC), neutrophil, monocytes, lymphocyte, eosinophil, and basophil concentrations. After adjusting for demographic and health-related factors, there were consistently significant associations between IMF, SSN, and K_p index, with reductions in total WBC, neutrophils, and basophil counts. These associations were stronger with longer moving averages. The associations were similar after adjusting for ambient air particulate pollution and particle radioactivity. Our findings suggest that periods of increased solar and geomagnetic activity result in lower WBC, neutrophil, and basophil counts that may contribute to mil mild immune suppression.

A spatiotemporal ensemble model to predict gross beta particulate radioactivity across the contiguous United States

Particulate radioactivity, a characteristic of particulate matter, is primarily determined by the abundance of radionuclides that are bound to airborne particulates. Exposure to high levels of particulate radioactivity has been associated with negative health outcomes. However, there are currently no spatially and temporally resolved particulate radioactivity data for exposure assessment purposes. We estimated the monthly distributions of gross beta particulate radioactivity across the contiguous United States from 2001 to 2017 with a spatial resolution of 32 km, via a multi-stage ensemble-based model. Particulate radioactivity was measured at 129 RadNet monitors across the contiguous U.S. In stage one, we built 264 base learning models using six methods, then selected nine base models that provide different predictions. In stage two, we used a non-negative geographically and temporally weighted regression method to aggregate the selected base learner predictions based on their local performance. The results of block cross-validation analysis suggested that the non-negative geographically and temporally weighted regression ensemble learning model outperformed all base learning model with the smallest rooted mean square error (0.094 mBq/m³). Our model provided an accurate estimation of particulate radioactivity, thus can be used in future health studies.