Effects of long-term exposure to ambient fine particulate matter and its specific components on blood pressure and hypertension incidence

BACKGROUND

Epidemiological evidence on the association of PM2.5 (particulate matter with aerodynamic diameter ≤ 2.5 μm) and its specific components with hypertension and blood pressure is limited.

METHODS

We applied information of participants from the World Health Organization's (WHO) Study on Global Ageing and Adult Health (SAGE) to estimate the associations of long-term PM2.5 mass and its chemical components exposure with blood pressure (BP) and hypertension incidence in Chinese adults ≥ 50 years during 2007-2018. Generalized linear mixed model and Cox proportional hazard model were applied to investigate the effects of PM2.5 mass and its chemical components on the incidence of hypertension and BP, respectively.

RESULTS

Each interquartile range (IQR = 16.80 μg/m3) increase in the one-year average of PM2.5 mass concentration was associated with a 17 % increase in the risk of hypertension (HR = 1.17, 95 % CI: 1.10, 1.24), and the population attributable fraction (PAF) was 23.44 % (95 % CI: 14.69 %, 31.55 %). Each IQR μg/m3 increase in PM2.5 exposure was also related to increases of systolic blood pressure (SBP) by 2.54 mmHg (95 % CI:1.99, 3.10), and of diastolic blood pressure (DBP) by 1.36 mmHg (95 % CI: 1.04, 1.68). Additionally, the chemical components of SO42-, NO3-, NH4+, OM, and BC were also positively associated with an increased risk of hypertension incidence and elevated blood pressure.

CONCLUSIONS

These results indicate that long-term exposure to PM2.5 mass and its specific components may be major drivers of escalation in hypertension diseases.

Burden of cardiovascular disease attributable to long-term exposure to ambient PM2.5 concentration and the cost-benefit analysis for the optimal control level

Environmental exposure to fine particulate matter PM_2.5 is known to be associated with many hazardous health effects, including cardiovascular diseases (CVDs). To reduce the related health burden, it is crucial that policy-makers throughout the world set regulation levels according to their own evidence-based study outcomes. However, there appears to be a lack of decision-making methods for the control level of PM_2.5 based on the burden of disease. In this study, 117,882 CVD-free participants (≥30-years-old) of the MJ Health Database were followed-up (for a median of 9 years) between 2007 and 2017. Each participant's residential address was matched to the 3× 3 km grid PM_2.5 concentration estimates with a 5-year average for long-term exposure. We used a time-dependent nonlinear weight-transformation Cox regression model for the concentration-response function (CRF) between exposure to PM_2.5 and CVD incidence. Town/district-specific PM_2.5-attributable years of life in disability (YLDs) in CVD incidence were calculated by using the relative risk (RR) of the PM_2.5 concentration level relative to the reference level. A cost-benefit analysis was proposed by assessing the trade-off between the gain in avoidable YLDs (given a reference level at u and considering mitigation cost) versus the loss in unavoidable YLDs by not setting at the lowest observed health effect level u₀. The CRF varied across different areas with dissimilar PM_2.5 exposure ranges. Areas with low PM2.5 concentrations and population sizes provided crucial information for the CVD health effect at the lower end. Additionally, women and older participants were more susceptible. The avoided town/district-specific YLDs in CVD incidence due to lower RRs ranged from 0 to 3000 person-years comparing the PM_2.5 concentration levels in 2019 with the levels in 2011. Based on the cost-benefit analysis, an annual PM_2.5 concentration of 13 μg/m³ would be optimal, which provides a guideline for the updated regulation level (currently at 15 μg/m³). The proposed cost-benefit analysis method may be applied to other countries/regions for regulation levels that are most suitable for their air pollution status and population health.

Lung cancer occurrence attributable to passive smoking among never smokers in China: a systematic review and meta-analysis

Background

Quantifying the occurrence of lung cancer due to passive smoking is a necessary step when forming public health policy. In this study, we estimated the proportion of lung cancer cases attributable to passive smoking among never smokers in China.

Methods

Six databases were searched up to July 2019 for original observational studies reporting relative risks (RRs) or odds ratios (ORs) for the occurrence of lung cancer associated with passive smoking in Chinese never smokers. The population attributable fraction (PAF) was then calculated using the combined proportion of lung cancer cases exposed to passive smoking and the pooled ORs from meta-analysis. Data are reported with their 95% confidence intervals.

Results

We identified 31 case-control studies of never smokers and no cohort studies. These comprised 9,614 lung cancer cases and 13,093 controls. The overall percentages of lung cancers attributable to passive smoking among never smokers were 15.5% (9.0-21.4%) for 9 population-based studies and 22.7% (16.6-28.3%) for 22 hospital-based studies. The PAFs for women were 17.9% (11.4-24.0%) for the population-based studies and 20.9% (14.7-26.7%) for the hospital-based studies. The PAF for men was only calculable for hospital-based studies, which was 29.0% (95% CI: 8.0-45.2%). Among women, the percentage of lung cancer cases attributable to household exposure (19.5%) was much higher than that due to workplace exposure (7.2%).

Conclusions

We conclude that approximately 16% of lung cancer cases among never smokers in China are potentially attributable to passive smoking. This is slightly higher among women (around 18%), with most cases occurring due to household exposure.