Associations of improved air quality with lung function growth from childhood to adulthood: the BAMSE study.

BACKGROUND: The beneficial effect of improving air quality on lung function development remains understudied. We assessed associations of changes in ambient air pollution levels with lung function growth from childhood until young adulthood in a Swedish cohort study. METHODS: In the prospective birth cohort BAMSE (Children, Allergy, Environment, Stockholm, Epidemiology (in Swedish)), spirometry was conducted at the 8-year (2002-2004), 16-year (2011-2013) and 24-year (2016-2019) follow-ups. Participants with spirometry data at 8 years and at least one other measurement in subsequent follow-ups were included (1509 participants with 3837 spirometry measurements). Ambient air pollution levels (particulate matter with diameter ≤2.5 µm (PM2.5), particulate matter with diameter ≤10 µm (PM10), black carbon (BC) and nitrogen oxides (NO x )) at residential addresses were estimated using dispersion modelling. Linear mixed effect models were used to estimate associations between air pollution exposure change and lung function development. RESULTS: Overall, air pollution levels decreased progressively during the study period. For example, the median (interquartile range (IQR)) level of PM2.5 decreased from 8.24 (0.92) µg·m-3 during 2002-2004 to 5.21 (0.67) µg·m-3 during 2016-2019. At the individual level, for each IQR reduction of PM2.5 the lung function growth rate increased by 4.63 (95% CI 1.64-7.61) mL per year (p<0.001) for forced expiratory volume in 1 s and 9.38 (95% CI 4.76-14.00) mL per year (p<0.001) for forced vital capacity. Similar associations were also observed for reductions of BC and NO x . Associations persisted after adjustment for potential confounders and were not modified by asthma, allergic sensitisation, overweight, early-life air pollution exposure or dietary antioxidant intake. CONCLUSIONS: Long-term reduction of air pollution is associated with positive lung function development from childhood to young adulthood.

Ambient ultrafine particles and asthma onset until age 20: The PIAMA birth cohort.

RATIONALE: Evidence regarding the role of long-term exposure to ultrafine particles (<0.1 µm, UFP) in asthma onset is scarce. OBJECTIVES: We examined the association between exposure to UFP and asthma development in the Dutch PIAMA (Prevention and Incidence of Asthma and Mite Allergy) birth cohort and assessed whether there is an association with UFP, independent of other air pollutants. METHODS: Data from birth up to age 20 years from 3687 participants were included. Annual average exposure to UFP at the residential addresses was estimated with a land-use regression model. Overall and age-specific associations of exposure at the birth address and current address at the time of follow-up with asthma incidence were assessed using discrete-time hazard models adjusting for potential confounders. We investigated both single- and two-pollutant models accounting for co-exposure to other air pollutants (PM2.5 and PM10 mass concentrations, nitrogen dioxide, and PM2.5 absorbance). MEASUREMENTS AND MAIN RESULTS: A total of 812 incident asthma cases were identified. Overall, we found that higher UFP exposure was associated with higher asthma incidence (adjusted odds ratio (95% confidence interval) 1.08 (1.02,1.14) and 1.06 (1.00, 1.12) per interquartile range increase in exposure at the birth address and current address at the time of follow-up, respectively). Age-specific associations were not consistent. The association was no longer significant after adjustment for other traffic-related pollutants (nitrogen dioxide and PM2.5 absorbance). CONCLUSIONS: Our findings support the importance of traffic-related air pollutants for asthma development through childhood and adolescence, but provide little support for an independent effect of UFP.

Ambient air pollution and hospital visits for peptic ulcer disease in China: A three-year analysis.

BACKGROUND: Peptic ulcer disease (PUD) continued to be a source of significant morbidity and mortality worldwide. Recently, it has been reported that exposure to air pollution is a potential risk factor for PUD, but evidence on the association still remains inconsistent. METHODS: We performed an ecological study to examine the association between short-term exposure to air pollution and daily hospital visits for PUD in Yinzhou, China from January 1st, 2017 to December 31st, 2019. Distributed lag nonlinear models were used to estimate the nonlinear and lag-response effects of air pollutants. Subgroup analyses stratified by sex, age and season were conducted to examine the effect modifications. RESULTS: Overall, we found that short-term exposure to air pollution including SO2, NO2, CO, O3 and PM2.5 was significantly associated with hospital visits for PUD among all subjects. The lag-response effects of SO2, NO2 and O3 varied at different concentrations and lag days. The cumulative risk ratios of CO and PM2.5 showed nearly linear adverse effects and increased to maxima of 2.68 (95% CI: 1.49-4.78) and 2.40 (95% CI: 1.36-4.24) with their ranges from the references to the maximum concentrations, respectively. Moreover, the cumulative risks of particulate matters on hospital visits for PUD increased significantly in cold seasons, but not in warm seasons. CONCLUSIONS: Our findings could provide growing evidence regarding the adverse health effects of air pollution on PUD, thereby strengthening the hypothesis that air pollutants have harmful impacts on digestive system.

Air pollution, surrounding green, road proximity and Parkinson's disease: A prospective cohort study.

BACKGROUND: Though growing evidence has linked air pollution to Parkinson's disease (PD), the results remain inconsistent. Less is known about the relevance of road proximity and surrounding green. We aimed to investigate the individual and joint associations of air pollution, road proximity and surrounding green with the incidence of PD in a prospective cohort study. METHODS: We used data from a prospective cohort of 47,516 participants recruited from July 2015 to January 2018 in Ningbo, China. Long-term exposure to particulate matter with aerodynamic diameter ≤2.5 µm (PM2.5) and ≤10 µm (PM10) and nitrogen dioxide (NO2) estimated by land-use regression models, road proximity and surrounding green assessed by Normalized Difference Vegetation Index (NDVI) were calculated based on the residential address for each participant. Cox proportional hazard models were used to analyze the individual and joint effects of air pollution, road proximity, and surrounding green on PD. RESULTS: In single-exposure models, PM2.5, PM10, NO2 and road proximity was associated with increased risk of PD (e.g. Hazard Ratio (HR) = 1.51, 95%CI:1.02, 2.24 per interquartile range (IQR) increase for PM2.5) while surrounding green was associated with decreased risk of PD (e.g. HR = 0.80, 95%CI:0.65, 0.98 per IQR increase for NDVI in 300 m buffer). In two-exposure models, the associations of PM2.5 and surrounding green persisted while the associations of NO2 and road proximity attenuated towards unity. CONCLUSIONS: We found that PM2.5 were associated with increased risk of incident PD while surrounding green was associated with decreased risk of PD. Future studies about PD etiology may benefit from including multiple environmental exposures to address potential joint associations.

HDL-C, longitudinal change and risk of mortality in a Chinese cohort study.

BACKGROUND AND AIMS: High-density lipoprotein cholesterol (HDL-C) concentration and variability are both important factors of cardiovascular disease (CVD) and mortality. We aimed to explore the associations of HDL-C and longitudinal change in HDL-C with risk of mortality. METHODS AND RESULTS: We recruited a total of 69,163 participants aged ≥40 years and had medical examination records of HDL-C during 2010-2014 from the Yinzhou District, Ningbo, China. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazards regression models. We observed a non-linear association of HDL-C with risks of non-accidental and CVD mortality. Compared with the moderate concentration group (1.4-1.6 mmol/L), HDL-C <1 mmol/L was associated with a higher risk of non-accidental mortality (HR: 1.13 (95% CI: 1.01-1.27)) and both HDL-C <1 mmol/L and ≥2 mmol/L were associated with a higher risk of CVD mortality (HRs: 1.23 (95% CI: 1.01-1.50) and 1.37 (95% CI: 1.03-1.82), respectively). Compared with the stable group ([-0.1, +0.1 mmol/L]), a large decrease ([-0.5, -0.3 mmol/L]) and very large decrease (<-0.5 mmol/L) in HDL-C were associated with a higher risk of non-accidental mortality (HRs: 1.40 (95% CI: 1.21-1.63) and 1.78 (95% CI: 1.44-2.20), respectively). Similar results were observed for CVD mortality and cancer mortality. CONCLUSION: Extremely low or high HDL-C and a large decrease or very large decrease in HDL-C were associated with a higher risk of cause-specific mortality. Monitoring of HDL-C may have utility in identifying individuals at higher risk of mortality.

Association of long-term exposure to ambient air pollution with the incidence of sleep disorders: A cohort study in China.

BACKGROUND: Sleep disorders have been verified to be associated with adverse health outcomes. Recent studies have linked ambient air pollution to sleep disorders. However, evidence with large sample size and especially prospective studies is very limited. METHODS: We used data from a prospective cohort study established from 2015 to 2018 in Ningbo, China. Participants were followed-up after baseline survey through linkage to the regional Health Information System (HIS). Sleep disorders were defined based on International Classification of Disease 10 (ICD-10). Spatial-temporal land-use regression (LUR) models were used to estimate the annual exposure to particulate matter with diameter ≤ 2.5 µm (PM2.5), ≤ 10 µm (PM10) and nitrogen dioxides (NO2). The associations between long-term exposure to air pollutants and prevalence of sleep disorders were examined using logistic regression models, and Cox regression models for the effects of air pollution on the incidence of sleep disorders. A generalized weighted quantile sum (gWQS) regression was used in the multipollutant analysis. RESULTS: A total of 38,775 participants were included in the final analysis. Based on baseline data, we observed significant positive associations between air pollution exposure and increased odds of prevalent sleep disorders (Odds Ratio (OR)= 1.48, 95% confidence interval (CI): 1.41-1.55 for PM2.5; OR= 1.47,95%CI:1.38-1.57 for PM10; OR= 1.38, 95%CI:1.31-1.46 for NO2). In the longitudinal analysis, hazard ratios for incident sleep disorders associated with per interquartile range (IQR) increase in PM2.5, PM10 and NO2 were 1.14 (1.03, 1.25), 1.13 (1.01, 1.27) and 1.13 (1.04, 1.23), respectively. A gWQS regression analysis showed significant association between air pollution mixture and incident sleep disorders (OR=1.11, 95%CI: 1.03-1.20). CONCLUSIONS: Long-term exposure to PM2.5, PM10 and NO2 were associated with increased risk of sleep disorders in a Chinese population. Our findings could provide evidence for a more general role in the adverse health impact of air pollution.

Association between visit-to-visit variability of HbA1c and cognitive decline: a pooled analysis of two prospective population-based cohorts.

AIMS/HYPOTHESIS: The aim of this study was to investigate the association between visit-to-visit variability in HbA1c and cognitive function decline in the elderly population. METHODS: We performed a pooled analysis of two prospective population-based cohorts (the Health Retirement Study [HRS] and the English Longitudinal Study of Ageing [ELSA]). Cognitive function, including memory and executive function, were assessed at baseline and every 2 years, while HbA1c levels were assessed at baseline and every 4 years. Visit-to-visit variability (VVV) in HbA1c was calculated using the CV, SD and variation independent of the mean (VIM) during the follow-up period. Linear mixed models were used to evaluate the association between HbA1c variability and cognitive function decline with adjustment for demographics, mean HbA1c, education, smoking, alcohol consumption, BMI, baseline hypertension, baseline diabetes status and HDL-cholesterol. RESULTS: The study enrolled 6237 participants (58.23% women, mean age 63.38 ± 8.62 years) with at least three measurements of HbA1c. The median follow-up duration was 10.56 ± 1.86 years. In the overall sample, compared with the lowest quartile of HbA1c variability, participants in the highest quartile of HbA1c variability had a significantly worse memory decline rate (-0.094 SD/year, 95% CI -0.185, -0.003) and executive function decline rate (-0.083 SD/year, 95% CI -0.125, -0.041), irrespective of mean HbA1c values over time. Among individuals without diabetes, each 1-SD increment in HbA1c CV was associated with a significantly higher rate of memory z score decline (-0.029, 95% CI -0.052, -0.005) and executive function z score decline (-0.049, 95% CI -0.079, -0.018) in the fully adjusted model. CONCLUSIONS/INTERPRETATION: We observed a significant association between long-term HbA1c variability and cognitive decline among the non-diabetic population in this study. The effect of maintaining steady glucose control on the rate of cognitive decline merits further investigation.

Regression-based normative data for social health scale for the elderly (short version) in eastern China.

BACKGROUNDS: Social Health Scale for the Elderly short version (SHSE-S) is a psychometrically sound instrument that comprehensively assesses the social health status of older adults in China. The aim of the present study was to establish continuous normative data of SHSE-S. METHODS: We conducted a multicenter cross-sectional study among 31 communities in eastern China. Older adults aged 60 years and above were invited to participate in the study. Each participant was interviewed in-person to finish a structured questionnaire. The SHES-S score was calculated and standardized for each participant. We split the sample into generation and validation datasets and compared the distribution of SHSE-S score between two datasets. Multivariable linear regression was used to assess the SHSE-S score and demographic variables. Regression-based norms were built using a four-step process. RESULTS: A total of 6089 participants (51.2% females) aged 60 years old and above (mean age = 71.3, SD = 8.0) were enrolled as the normative sample. No significant difference was found between the distribution of SHSE-S standardized score in the generation (N = 2392) and validation (N = 3697) datasets. Multivariable linear regression showed that females, higher education levels were positive indicators while aging, living alone, divorced or never married, multimorbidity were negative factors. The regression-based norm which taking demographic factors into account was established and a user-friendly worksheet was also provided to facilitate the scoring and norming of the SHSE-S. CONCLUSIONS: The population-based regression norm of SHSE-S can be a useful tool for assessing the social health status of the Chinese elderly population.

Association between social health status and health-related quality of life among community-dwelling elderly in Zhejiang.

BACKGROUND: Population aging is an inevitable trend and previous studies have showed the relationship between social health related factors and health-related quality of life (HR-QOL) in the elderly. The objective of this study is to investigate the association of social health status with HR-QOL among community-dwelling elderly in Zhejiang. METHODS: This cross-sectional study was based on community-dwelling elderly individuals from July 2018 to September 2018 in Zhejiang, China. HR-QOL was measured by the 12-item Short-Form Health Survey (SF-12). Social health status was estimated by the long-form of the Social Health Scale for the Elderly (SHSE-L) and classified into three categories (poor, moderate and good). Multivariable linear regression models were conducted to evaluate the association between social health status and HR-QOL (PCS, MCS and SF-12 total score). RESULTS: A total of 2952 elderly participants were included in this study. The mean age was 70.68 ± 7.75 years (mean ± SD); of the eligible participants, more than half (50.4%) were females; the mean scores were 48.10 ± 8.49, 47.70 ± 7.09 and 47.90 ± 5.86 for PCS, MCS and SF-12 total score, separately. Results from the multivariable models showed that social health status was positively related to HR-QOL after adjusting for covariates. Compared with individuals with a poor social health status, those who had a moderate or good social health status were more likely to report better HR-QOL (for moderate social health status: ß = 1.90(95%CI: 1.09, 2.71) for PCS, ß = 1.78(1.08, 2.48) for MCS, ß = 1.84(1.29, 2.39) for SF-12 total score; for good social health status: ß = 3.29(2.24, 4.34) for PCS, ß = 3.10(2.12, 4.01) for MCS, ß = 3.20(2.48, 3.91) for SF-12 total score). CONCLUSION: In our study, we found that social health status was positively associated with HR-QOL among the elderly in Zhejiang. Our findings could provide valuable information for decision-makers to develop interventions to improve the HR-QOL of the elderly.

Intra-individual variability of total cholesterol is associated with cardiovascular disease mortality: A cohort study.

BACKGROUND AND AIMS: The relationship between serum total cholesterol (TC) and mortality remains inconsistent. Additionally, intra-individual variability of cholesterol has been of increasing interest as a new indicator for health outcomes. We aimed to examine the association between TC and its variability and risk of mortality. METHODS AND RESULTS: We performed a retrospective cohort study with 122,645 individuals aged over 40 years in Ningbo, China. The intra-individual variability was calculated using four metrics including standard deviation, coefficient variation, variation independent of mean and average successive variability. Hazard ratios and 95% confidence intervals were estimated for the associations of baseline and variability in TC with risk of mortality by Cox proportional hazards regression models. During 591,585.3 person-years of follow-up, 4563 deaths (including 1365 from cardiovascular disease, 788 from stroke and 1514 from cancer) occurred. A U-shaped association was observed for baseline TC level and risk of total, cardiovascular and cancer mortality, with lowest mortality at 5.46 mmol/L, 5.04 mmol/L and 5.51 mmol/L, respectively. As compared with subjects with TC variability in the lowest quartile, individuals in the highest quartile had 21% higher risk of all-cause mortality (HR = 1.21, 95% CI: 1.05 to 1.40), and 41% higher risk of CVD mortality (HR = 1.41, 95%CI: 1.10 to 1.81). CONCLUSION: Both too low and too high baseline TC level were associated with higher risk of total, cardiovascular disease and cancer mortality. Variability of TC could be a risk factor of total and CVD mortality, independent of mean TC level. Future studies are needed to confirm these findings.

Air pollution exposures and blood pressure variation in type-2 diabetes mellitus patients: A retrospective cohort study in China.

Air pollution exposure has been associated with hypertension, but limited studies have examined the associations in diabetic patients. We aimed to examine the associations of exposure to air pollution with blood pressure in diabetic patients. We identified patients who were previously diagnosed as type-2 diabetes mellitus from hospital records from January 2013 to May 2017. We used generalized linear models to estimate adverse effects of air pollution on systolic/diastolic blood pressure in diabetic patients. A total of 40,125 patients were enrolled in this study. An IQR increase in PM2.5, PM10, NO2, SO2, and O3 exposure was associated with an increased risk of higher systolic blood pressure level (ß = 0.628 for PM2.5, ß = 0.758 for PM10, ß = 0.766 for NO2, ß = 0.516 for SO2, ß = 0.482 for O3, all P value < 0.05). Significant associations were observed for some air pollutants and SBP among patients with fasting blood glucose (FBG) ≥ 7.0 mmol/L, normal weight, and younger age. Little evidence was available for the associations between particulate matter (PM) or O3 exposure and diastolic blood pressure in present study. In our study, diabetic patients were at increased risk of higher blood pressure when exposed to higher residential PM, NO2 and SO2. Individuals with lower BMI, younger age, and FBG ≥ 7.0 mmol/L were more susceptible to the adverse effects of ambient air pollution.

The development of the social health scale for the elderly.

BACKGROUND: With the elderly population comprising an increasing large proportion of society, a valid and reliable measure of social health in the elderly is indispensable for a comprehensive health assessment. The objective of this study is to develop a Social Health Scale for the Elderly (SHSE). METHODS: A draft scale was generated based on a literature review and expert surveys. Pilot testing was conducted from December 14, 2015, to January 8, 2016. Some items were removed after assessment with five statistical analysis methods. Field testing began on November 6, 2016, and ended on January 20, 2017. After field testing, the reliability and validity of the scale were assessed and the norms in Hangzhou were calculated. RESULTS: In the two tests, 430 and 2404 subjects were included in the statistical analyses. The long form of the SHSE (SHSE-L) contained 25 items, 14 of which were also in the short form (SHSE-S). The internal consistency of the SHSE-L was acceptable. The test-rest reliability and inter-rater reliability were moderate, but the concurrent validity, construct validity, and convergent and discriminant validity were desirable in both versions. The standard and percentile rank norms in Hangzhou, China were developed based on the field testing data. CONCLUSIONS: The population-based social health of the Chinese elderly can be validly and reliably assessed with the SHSE.

Association between ambient air pollutants and preterm birth in Ningbo, China: a time-series study.

BACKGROUND: Exposure to air pollutants has been related to preterm birth, but little evidence can be available for PM2.5, O3 and CO in China. This study aimed to investigate the short-term effect of exposure to air pollutants on risk preterm birth during 2014-2016 in Ningbo, China. METHODS: We conducted a time-series study to evaluate the associations between daily preterm birth and major air pollutants (including PM2.5, PM10, SO2, NO2, O3 and CO) in Ningbo during 2014-2016. A General Additive Model extend Poisson regression was used to evaluate the relationship between preterm birth and air pollution with adjustment for time-trend, meteorological factors and day of the week (DOW). We also conducted a subgroup analysis by season and age. RESULTS: In this study, a total of 37,389 birth occurred between 2014 and 2016 from the Electronic Medical Records System of Ningbo Women and Children's Hospital, of which 5428 were verified as preterm birth. The single pollutant model suggested that lag effect of PM2.5, PM10, NO2 reached a peak at day 3 before delivery and day 6 for SO2, and no relationships were observed for O3 and preterm birth. Excess risks (95% confidence intervals) for an increase of IQR of air pollutant concentrations were 4.84 (95% CI: 1.77, 8.00) for PM2.5, 3.56 (95% CI: 0.07, 7.17) for PM10, 3.65 (95% CI: 0.86, 6.51) for SO2, 6.49 (95% CI: 1.86, 11.34) for NO2, - 0.90 (95% CI: -4.76, 3.11) for O3, and 3.36 (95% CI: 0.50, 6.30) for CO. Sensitivity analyses by exclusion of maternal age < 18 or > 35 years did not materially alter our results. CONCLUSIONS: This study indicates that short-term exposure to air pollutants (including PM2.5, PM10, SO2, NO2) are positively associated with risk of preterm birth in Ningbo, China.

[A community-based survey on risk factors of type 2 diabetic kidney disease in Ningbo, China].

OBJECTIVE: To investigate the prevalence and risk factors of diabetic nephropathy in Ningbo Yinzhou district. METHODS: Nephropathy screening was conducted among patients with type 2 diabetes mellitus (T2DM) registered in Ningbo Yinzhou district. Demographic information, clinical examination information, diabetes complications and behavioral risk factors of enrolled patients were collected. Logistic regression model was used to identify possible risk factors for the occurrence of diabetic nephropathy. RESULTS: Among 10 604 T2DM patients included in this study, there were 3744 cases of diabetic nephropathy(35.31%). Univariate analysis showed that gender, age, education level, diabetes duration, glycemic control, hypertension, stroke, smoking and waist circumference were associated with diabetic nephropathy (P<0.05 or P<0.01). Multivariate logistic regression analysis showed that male, elders, long diabetes duration, hypertension and smoking were independent risk factors of diabetic nephropathy (P<0.05 or P<0.01). CONCLUSIONS: sDiabetic nephropathy is of high prevalence in T2DM patients. Male patients, elders, and those with long diabetes duration, hypertension and smoking habits are more likely to have diabetic nephropathy.

Improved Air Quality and Asthma Incidence from School-Age to Young Adulthood: A Population-based Prospective Cohort Study.

Background The benefits of improved air quality on asthma remain understudied. Therefore, our aim was to investigate associations of changes in ambient air pollution with incident asthma from school-age until young adulthood in an area with mostly low air pollution levels. Methods Participants in the BAMSE birth cohort from Stockholm without asthma before the 8-year follow-up were included (N=2371). We estimated the association of change in individual-level air pollutant exposure (particulate matter with diameter ⩽2.5 µm (PM2.5) and, ⩽10 µm (PM10), black carbon (BC) and nitrogen oxides (NOx)) from the first year of life to the 8-year follow-up with asthma incidence from the 8-year until the 24-year follow-up. Multi-pollutant trajectories were identified using Group-Based Multivariate Trajectory model. We also used parametric g-computation to quantify the asthma incidence under different hypothetical interventions regarding air pollution levels. Results Air pollution levels at residency decreased during the period, with median reductions of 5.6% for PM2.5, 3.1% for PM10, 5.9% for BC, and 26.8% for NOx. A total of 395 incident asthma cases were identified from the 8-year until the 24-year follow-up. The odds ratio for asthma was 0.89 (95%CI: 0.80, 0.99) for each interquartile range reduction in PM2.5 (equal to 8.1% reduction). Associations appeared less clear for PM10, BC and NOx. Five multi-pollutant trajectories were identified, where the largest reduction trajectory displayed the lowest odds of asthma (OR=0.55, 95%CI: 0.31, 0.98) compared with the least reduction trajectory. If the PM2.5 exposure had not declined up to the 8-year follow-up, the hypothetical asthma incidence was estimated to have been 10.9% higher (95%CI: 0.8%, 20.8%). Conclusions Decrease in PM2.5 levels during childhood was associated with lower risk of incident asthma from school-age to young adulthood in an area with relatively low air pollution levels, suggesting broad respiratory health benefits from improved air quality. This article is open access and distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/).

Ambient air pollution exposure linked to long COVID among young adults: a nested survey in a population-based cohort in Sweden.

Background: Post COVID-19 conditions, also known as long COVID, are of public health concern, but little is known about their underlying risk factors. We aimed to investigate associations of air pollution exposure with long COVID among Swedish young adults. Methods: We used data from the BAMSE (Children, Allergy, Environment, Stockholm, Epidemiology [in Swedish]) cohort. From October 2021 to February 2022 participants answered a web-questionnaire focusing on persistent symptoms following acute SARS-CoV-2 infection. Long COVID was defined as symptoms after confirmed infection with SARS-CoV-2 lasting for two months or longer. Ambient air pollution levels (particulate matter ≤2.5 µm [PM2.5], ≤10 µm [PM10], black carbon [BC] and nitrogen oxides [NOx]) at individual-level addresses were estimated using dispersion modelling. Findings: A total of 753 participants with SARS-CoV-2 infection were included of whom 116 (15.4%) reported having long COVID. The most common symptoms were altered smell/taste (n = 80, 10.6%), dyspnea (n = 36, 4.8%) and fatigue (n = 34, 4.5%). Median annual PM2.5 exposure in 2019 (pre-pandemic) was 6.39 (interquartile range [IQR] 6.06-6.71) µg/m3. Adjusted Odds Ratios (95% confidence intervals) of PM2.5 per IQR increase were 1.28 (1.02-1.60) for long COVID, 1.65 (1.09-2.50) for dyspnea symptoms and 1.29 (0.97-1.70) for altered smell/taste. Positive associations were found for the other air pollutants and remained consistent across sensitivity analyses. Associations tended to be stronger among participants with asthma, and those having had COVID during 2020 (versus 2021). Interpretation: Ambient long-term PM2.5 exposure may affect the risk of long COVID in young adults, supporting efforts for continuously improving air quality. Funding: The study received funding from the Swedish Research Council (grant no. 2020-01886, 2022-06340), the Swedish Research Council for Health, Working life and Welfare (FORTE grant no. 2017-01146), the Swedish Heart-Lung Foundation, Karolinska Institute (no. 2022-01807) and Region Stockholm (ALF project for cohort and database maintenance).

Effect of residential relocation on environmental exposures in European cohorts: An exposome-wide approach.

Residential relocation is increasingly used as a natural experiment in epidemiological studies to assess the health impact of changes in environmental exposures. Since the likelihood of relocation can be influenced by individual characteristics that also influence health, studies may be biased if the predictors of relocation are not appropriately accounted for. Using data from Swedish and Dutch adults (SDPP, AMIGO), and birth cohorts (BAMSE, PIAMA), we investigated factors associated with relocation and changes in multiple environmental exposures across life stages. We used logistic regression to identify baseline predictors of moving, including sociodemographic and household characteristics, health behaviors and health. We identified exposure clusters reflecting three domains of the urban exposome (air pollution, grey surface, and socioeconomic deprivation) and conducted multinomial logistic regression to identify predictors of exposome trajectories among movers. On average, 7 % of the participants relocated each year. Before relocating, movers were consistently exposed to higher levels of air pollution than non-movers. Predictors of moving differed between the adult and birth cohorts, highlighting the importance of life stages. In the adult cohorts, moving was associated with younger age, smoking, and lower education and was independent of cardio-respiratory health indicators (hypertension, BMI, asthma, COPD). Contrary to adult cohorts, higher parental education and household socioeconomic position were associated with a higher probability of relocation in birth cohorts, alongside being the first child and living in a multi-unit dwelling. Among movers in all cohorts, those with a higher socioeconomic position at baseline were more likely to move towards healthier levels of the urban exposome. We provide new insights into predictors of relocation and subsequent changes in multiple aspects of the urban exposome in four cohorts covering different life stages in Sweden and the Netherlands. These results inform strategies to limit bias due to residential self-selection in epidemiological studies using relocation as a natural experiment.

Identifying oscillations under multi-site sensory stimulation for high-level peripheral nerve injured patients: a pilot study.

Objective.For high-level peripheral nerve injuryed (PNI) patients with severe sensory dysfunction of upper extremities, identifying the multi-site tactile stimulation is of great importance to provide neurorehabilitation with sensory feedback. In this pilot study, we showed the feasibility of identifying multi-site and multi-intensity tactile stimulation in terms of electroencephalography (EEG).Approach.Three high-level PNI patients and eight non-PNI participants were recruited in this study. Four different sites over the upper arm, forearm, thumb finger and little finger were randomly stimulated at two intensities (both sensory-level) based on the transcutaneous electrical nerve stimulation. Meanwhile, 64-channel EEG signals were recorded during the passive tactile sense stimulation on each side.Main results.The spatial-spectral distribution of brain oscillations underlying multi-site sensory stimulation showed dominant power attenuation over the somatosensory and prefrontal cortices in both alpha-band (8-12 Hz) and beta-band (13-30 Hz). But there was no significant difference among different stimulation sites in terms of the averaged power spectral density over the region of interest. By further identifying different stimulation sites using temporal-spectral features, we found the classification accuracies were all above 89% for the affected arm of PNI patients, comparable to that from their intact side and that from the non-PNI group. When the stimulation site-intensity combinations were treated as eight separate classes, the classification accuracies were ranging from 88.89% to 99.30% for the affected side of PNI subjects, similar to that from their non-affected side and that from the non-PNI group. Other performance metrics, including specificity, precision, and F1-score, also showed a sound identification performance for both PNI patients and non-PNI subjects.Significance.These results suggest that reliable brain oscillations could be evoked and identified well, even though induced tactile sense could not be discerned by the PNI patients. This study have implication for facilitating bidirectional neurorehabilitation systems with sensory feedback.

Long-term exposure to ambient air pollution and incidence of depression: A population-based cohort study in China.

BACKGROUND: Long-term exposure to ambient air pollution was linked to depression incidence, although the results were limited and inconsistent. OBJECTIVES: To investigate the effects of long-term air pollution exposure on depression risk prospectively in China. METHODS: The present study used data from Yinzhou Cohort on adults without depression at baseline, and followed up until April 2020. Two-year moving average concentrations of particulate matter with a diameter ≤ 2.5 µm (PM2.5), ≤10 µm (PM10) and nitrogen dioxide (NO2) were measured using land-use regression (LUR) models for each participant. Depression cases were ascertained using the Health Information System (HIS) of the local health administration by linking the unique identifiers. We conducted Cox regression models with time-varying exposures to estimate the hazard ratios (HRs) and 95% confidence intervals (95% CIs) of depression with each pollutant, after adjusting for a sequence of individual covariates as demographic characteristics, lifestyles, and comorbidity. Besides, physical activity, baseline potential depressive symptoms, cancer status, COVID-19 pandemic, different outcome definitions and air pollution exposure windows were considered in sensitivity analyses. RESULTS: Among the 30,712 adults with a mean age of 62.22 ± 11.25, 1024 incident depression cases were identified over totaling 98,619 person-years of observation. Interquartile range increments of the air pollutants were associated with increased risks of depression, and the corresponding HRs were 1.59 (95%CI: 1.46, 1.72) for PM2.5, 1.49 (95%CI: 1.35, 1.64) for PM10 and 1.58 (95%CI: 1.42, 1.77) for NO2. Subgroup analyses suggested that participants without taking any protective measures towards air pollution were more susceptible. The results remained robust in all sensitivity analyses. CONCLUSIONS: Long-term exposure to ambient air pollution was identified as a risk factor for depression onset. Strategies to reduce air pollution are necessary to decrease the disease burden of depression.

Association of residential greenness and incident depression: Investigating the mediation and interaction effects of particulate matter.

BACKGROUND: Growing evidence has linked residential greenness to depression, the results from prospective cohort study are still limited. And it remains unclear whether particulate matter (PM) modify, mediate, or interact the greenness-depression relationship. METHODS: We collected data from Yinzhou Cohort(N = 47,516) which was recruited between June 2015 and December 2017. Depression cases before April 2020 were ascertained from local Health Information System covered all residents' health care records. Residential greenness (the Normalized Difference Vegetation Index, NDVI, and the Enhanced Vegetation Index, EVI) and PM (particulate matters with diameters≤2.5 µm, PM2.5 and particulate matters with diameters≤10 µm, PM10) were estimated based on participants' residential coordinates. We conducted Cox models employing age as timescale to estimate the association between residential greenness within different buffers and incident depression. Furthermore, we explored the potential confounding, mediation and interaction relationship between greenness and PM. RESULTS: During the 99,556 person-years of follow-up, 1043 incident depression cases occurred. In single exposure models, residential greenness was inversely associated with depression incidence (e.g. Hazard Ratio (HR) = 0.86, 95% confidence interval (CI): 0.79, 0.94 for per interquartile range (IQR) increase NDVI 250 m). The protective association between greenness was attenuated after introducing PM2.5 and PM10 into the models. We identified multiplicative interactions between greenness and PM exposure for depression (e.g. HR interaction = 0.91, 95%CI: 0.85, 0.98 for per IQR decrease NDVI 250 m and per IQR increase PM2.5). Besides, we found the protective association of greenness was partly mediated by PM (e.g. mediation proportion = 52.9% between NDVI 250 m and PM2.5). CONCLUSIONS: In this longitudinal cohort study, residents living in greener neighborhoods had a lower risk of depression incidence and the benefits were interacted and partly mediated by PM. Improvement in residential greenness could be an actionable and planning intervention to prevent depression.