Long-term exposure to air pollutants enhanced associations of obesity with blood pressure and hypertension

Particulate matter, polycyclic aromatic hydrocarbons and metals, platelet parameters and blood pressure alteration: Multi-pollutants study among population

Epidemiological findings have determined the linkage of fine particulate matter (PM2.5) and the morbidity of hypertension. However, the mode of action and specific contribution of PM2.5 component in the blood pressure elevation remain unclear. Platelets are critical for vascular homeostasis and thrombosis, which may be involved in the increase of blood pressure. Among 240 high-PM2.5 exposed, 318 low-PM2.5 exposed workers in a coking plant and 210 workers in the oxygen plant and cold-rolling mill enrolled in present study, both internal and external exposure characteristics were obtained, and we performed linear regression, adaptive elastic net regression, quantile g-computation and mediation analyses to analyze the relationship between urine metabolites of polycyclic aromatic hydrocarbons (PAHs) and metals fractions with platelets indices and blood pressure indicators. We found that PM2.5 exposure leads to increased systolic blood pressure (SBP) and pulse pressure (PP). Specifically, for every 10 μg/m3 increase in PM2.5, there was a 0.09 mmHg rise in PP. Additionally, one IQR increase in urinary 1-hydroxypyrene (1.06 μmol/mol creatinine) was associated with a 3.43 % elevation in PP. Similarly, an IQR increment of urine cobalt (2.31 μmol/mol creatinine) was associated with a separate 1.77 % and 4.71 % elevation of SBP and PP. Notably, platelet-to-lymphocyte ratio (PLR) played a mediating role in the elevation of SBP and PP induced by cobalt. Our multi-pollutants results showed that PAHs and cobalt were deleterious contributors to the elevated blood pressure. These findings deepen our understanding of the cardiovascular effects associated with PM2.5 constituents, highlighting the importance of increased vigilance in monitoring and controlling the harmful components in PM2.5.

Physical activity diminished adverse associations of obesity with lipid metabolism in the population of rural regions of China

The interactive effects of obesity and physical inactivity on lipid metabolism and prevalent dyslipidemia are scarcely reported in rural regions. 39029 subjects were obtained from the Henan Rural Cohort, and their metabolic equivalents (METs) of physical activity (PA) were computed. Independent associations of the obesity indices and PA with either lipid indices or prevalent dyslipidemia were analyzed by generalized linear models, and additive effects of obesity and PA on prevalent dyslipidemia were further quantified. Each obesity index was positively associated with total cholesterol, triglyceride, low-density lipoprotein or prevalent dyslipidemia but negatively associated with high-density lipoprotein, whereas the opposite association of PA with either each lipid index or prevalent dyslipidemia was observed. Joint association of PA and each obesity index with each lipid index and prevalent dyslipidemia was observed. Furthermore, the association of each obesity index in association with each lipid index was attenuated by increased PA levels.

The causal effect of air pollution on the risk of essential hypertension: a Mendelian randomization study

Background

Air pollution poses a major threat to human health by causing various illnesses, such as cardiovascular diseases. While plenty of research indicates a correlation between air pollution and hypertension, a definitive answer has yet to be found.

Methods

Our analyses were performed using the Genome-wide association study (GWAS) of exposure to air pollutants from UKB (PM2.5, PM10, NO2, and NOX; n = 423,796 to 456,380), essential hypertension from FinnGen (42,857 cases and 162,837 controls) and from UKB (54,358 cases and 408,652 controls) as a validated cohort. Univariable and multivariable Mendelian randomization (MR) were conducted to investigate the causal relationship between air pollutants and essential hypertension. Body mass index (BMI), alcohol intake frequency, and the number of cigarettes previously smoked daily were included in multivariable MRs (MVMRs) as potential mediators/confounders.

Results

Our findings suggested that higher levels of both PM2.5 (OR [95%CI] per 1 SD increase in predicted exposure = 1.24 [1.02-1.53], p = 3.46E-02 from Finn; OR [95%CI] = 1.04 [1.02-1.06], p = 7.58E-05 from UKB) and PM10 (OR [95%CI] = 1.24 [1.02-1.53], p = 3.46E-02 from Finn; OR [95%CI] = 1.04 [1.02-1.06], p = 7.58E-05 from UKB) were linked to an increased risk for essential hypertension. Even though we used MVMR to adjust for the impacts of smoking and drinking on the relationship between PM2.5 exposure and essential hypertension risks, our findings suggested that although there was a direct positive connection between them, it is not present after adjusting BMI (OR [95%CI] = 1.05 [0.87-1.27], p = 6.17E-01). Based on the study, higher exposure to PM2.5 and PM10 increases the chances of developing essential hypertension, and this influence could occur through mediation by BMI.

Conclusion

Exposure to both PM2.5 and PM10 is thought to have a causal relationship with essential hypertension. Those impacted by substantial levels of air pollution require more significant consideration for their cardiovascular health.

Effect of exposures to multiple metals on blood pressure and hypertension in the elderly: a community-based study

A chronic disease, hypertension (HTN) is prevalent among the elderly. Exploring the factors that influence HTN and blood pressure (BP) changes is of great public health significance. However, mixed exposure to multiple serum metals has had less research on the effects on BP and HTN for the elderly. From April to August 2019, 2372 people participated in the community physical examination program for the elderly in Tongling City, Anhui Province. We measured BP and serum levels of 10 metals and collected basic demographic information. We analyzed the relationship between metal levels and changes in BP and HTN by the least absolute shrinkage and selection operator regression, Bayesian kernel machine regression model, and generalized linear model. In multiple models, lead (Pb) and cadmium (Cd) were still significantly associated with HTN occurrence after adjusting for potential confounders (Pb: ORquartile 4 VS quartile 1 = 1.20, 95% CI 1.01-1.43; Cd: ORquartile 4 VS quartile 1 = 1.37, 95% CI 1.16-1.62). In the male subgroup, results were similar to those of the general population. In the female group, Cd was positively correlated with HTN and systolic blood pressure, while Pb was not. According to this study, Pb and Cd were correlated with BP and HTN positively, and there was a certain joint effect. To some extent, our findings provide clues for the prevention of hypertension in the elderly.

Associations of the neighbourhood built and natural environment with cardiometabolic health indicators: A cross-sectional analysis of environmental moderators and behavioural mediators

BACKGROUND

Most studies examining the effects of neighbourhood urban design on cardiometabolic health focused solely on the built or natural environment. Also, they did not consider the roles of neighbourhood socio-economic status (SES) and ambient air pollution in the observed associations, and the extent to which these associations were mediated by physical activity and sedentary behaviours.

METHODS

We used data from the AusDiab3 study (N = 4141), a national cohort study of Australian adults to address the above-mentioned knowledge gaps. Spatial data were used to compute indices of neighbourhood walkability (population density, intersection density, non-commercial land use mix, commercial land use), natural environment (parkland and blue spaces) and air pollution (annual average concentrations of nitrogen dioxide (NO2) and fine particulate matter <2.5 μm in diameter (PM2.5)). Census indices were used to define neighbourhood SES. Clinical assessments collected data on adiposity, blood pressure, blood glucose and blood lipids. Generalised additive mixed models were used to estimate associations.

RESULTS

Neighbourhood walkability showed indirect beneficial associations with most indicators of cardiometabolic health via resistance training, walking and sitting for different purposes; indirect detrimental associations with the same indicators via vigorous gardening; and direct detrimental associations with blood pressure. The neighbourhood natural environment had beneficial indirect associations with most cardiometabolic health indicators via resistance training and leisure-time sitting, and beneficial direct associations with adiposity and blood lipids. Neighbourhood SES and air pollution moderated only a few associations of the neighbourhood environment with physical activity, blood lipids and blood pressure.

CONCLUSIONS

Within a low-density and low-pollution context, denser, walkable neighbourhoods with good access to nature may benefit residents' cardiometabolic health by facilitating the adoption of an active lifestyle. Possible disadvantages of living in denser neighbourhoods for older populations are having limited opportunities for gardening, higher levels of noise and less healthy dietary patterns associated with eating out.

Associations of long-term particulate matter exposure with cardiometabolic diseases: A systematic review and meta-analysis

BACKGROUND

This review aimed to establish a holistic perspective of long-term PM exposure and cardiometabolic diseases, identify long-term PM-related cardiovascular and metabolic risk factors, and provide practical significance to preventative measures.

METHOD

A combination of computer and manual retrieval was used to search for keywords in PubMed (2903 records), Embase (2791 records), Web of Science (5488 records) and Cochrane Library (163 records). Finally, a total of 82 articles were considered in this meta-analysis. Stata 13.0 was accustomed to inspecting the studies' heterogeneity and calculating the combined effect value (RR) by selecting the matching models. The subgroup analysis, sensitivity analysis and publication bias tests were also performed.

RESULTS

Meta-analysis figured an association between PM and cardiometabolic diseases. PM2.5 (per 10 μg/m3 increase) boosted the risk of hypertension (RR = 1.14, 95 % CI: 1.09-1.19), coronary heart disease (CHD) (RR = 1.21, 95 % CI: 1.08-1.35), diabetes (RR = 1.16, 95 % CI: 1.11-1.21) and stroke (including ischemic stroke and hemorrhagic stroke). PM10 (per 10 μg/m3 increase) elevated the incidence of hypertension (RR = 1.11, 95 % CI: 1.07-1.16) and diabetes (RR = 1.26, 95 % CI: 1.08-1.47). PM1 (per 10 μg/m3 increase) exposure increased the risk of total dyslipidemia, yielding the RR of 1.10 (95 % CI: 1.01-1.18). Furthermore, the elderly, overweight and higher background pollutant level were potentially susceptible to related diseases.

CONCLUSION

There was a virtual connection between long-term exposure to PM and cardiometabolic diseases. PM2.5 or PM10 (per 10 μg/m3) increased the risk of hypertension, CHD, diabetes, stroke and dyslipidemia, causing cardiovascular "multimorbidity" in high-risk populations.

Exposure to ambient air pollution and lipid levels and blood pressure in an adult, Danish cohort

BACKGROUND

Air pollution is a well-recognized risk factor for cardiovascular disease. However, the mechanistic pathways underlying the association are not completely understood. Hence, further studies are required to shed light on potential mechanisms, through which air pollution may affect the development from subclinical to clinical cardiovascular disease.

OBJECTIVES

To investigate associations between short-term exposure to air pollution and high-density lipoprotein (HDL), non-high density lipoprotein (non-HDL), systolic and diastolic blood pressure.

METHODS

The study was conducted among 32,851 Danes from the Diet, Cancer and Health - Next Generations cohort, who had a blood sample taken and blood pressure measured. We measured HDL and non-HDL in the blood samples. We modelled exposure to fine particulate matter (PM_2.5), ultrafine particles (UFP), elemental carbon (EC) and nitrogen dioxide (NO₂) in time-windows from 24 h up to 90 days before blood sampling. Pollutants were modelled as total air pollution from all sources, and apportioned into contributions from non-traffic and traffic sources. We analyzed data using linear and logistic regression, with adjustment for socio-economic and lifestyle factors.

RESULTS

Air pollution exposure over 24 h to 30 days was generally adversely associated with lipid profile and blood pressure, e.g. for 30-day UFP-exposure, adjusted β-estimates were: -0.025 (-0.043; -0.006) for HDL, 0.086 (0.042; 0.130) for non-HDL, 2.45 (1.70; 3.11) for systolic and 1.56 (1.07; 20.4) for diastolic blood pressure, per 10,000 particles/cm³. The strongest associations were found for the non-traffic components of air pollution, and among those who were overweight/obese.

DISCUSSION

In this large study of air pollution and lipid levels and blood pressure, we found that 24-h to 30-day PM_2.5, UFP, EC and NO₂ concentrations were generally adversely associated with lipid profile and blood pressure, two important cardiovascular risk factors. The study suggests potential pathways, through which air pollution could affect the development of cardiovascular disease.

Exposure to air pollution and prevalence of metabolic syndrome: A nationwide study in China from 2011 to 2015

BACKGROUND

Evidence concerning the influence of air pollution on metabolic syndrome (MetS) is still limited. We aimed to investigate whether sustained exposure to air pollutants are associated with increased prevalence of MetS and its individual components.

METHODS

We conducted a cross-sectional study comprised of 14,097 individuals participated in the first or third survey of the CHARLS. The personal cumulative (3-year averaged) exposure concentrations of nitrogen dioxide (NO₂), particulate matter (PM) with a diameter of 1.0 μm or less (PM₁), PM with a diameter of 10 μm or less (PM₁₀) and PM with a diameter of 2.5 μm or less (PM_2.5) were estimated using a spatiotemporal random forest model at 0.1° × 0.1° spatial resolution based on residential address of each participant provided. We utilized logistic regression models to estimate the associations of the four air pollutants with the prevalence of MetS and its individual components, and performed interaction analyses to evaluate potential effect modifications by gender, health status, age and drinking status.

RESULTS

Sustained exposure to air pollutants is associated with increased prevalence of MetS. For every 10 μg/m³ increase in NO₂, PM₁, PM₁₀ and PM_2.5, the adjusted odds ratio (OR) of MetS was 2.276 (95 % CI: 2.148, 2.412), 1.207 (95 % CI: 1.155, 1.263), 1.027 (95 % CI: 1.006, 1.048) and 1.027 (95 % CI: 0.989, 1.066), respectively. For MetS components, we observed significant associations between NO₂, PM₁, PM₁₀ and central obesity, high blood pressure, elevated fasting glucose and low high-density lipoprotein cholesterol. For example, the adjusted OR of low high-density lipoprotein cholesterol for every 10 μg/m³ increase in NO₂ was 1.855 (95 % CI: 1.764, 1.952). We also identified that age could significantly modified the association between NO₂ and prevalence of MetS.

CONCLUSIONS

Chinese adults sustained exposure to higher concentrations of air pollutants are associated with increased prevalence of MetS and its components.

Associations of long-term exposure to air pollution, physical activity with blood pressure and prevalence of hypertension: the China Health and Retirement Longitudinal Study

Background

Long-term exposure to air pollution and physical activity (PA) are linked to blood pressure and hypertension. However, the joint effect of air pollution and PA on blood pressure and hypertension are still unknown in Chinese middle-aged and older adults.

Methods

A total of 14,622 middle-aged and older adults from the China Health and Retirement Longitudinal Study wave 3 were included in this study. Ambient air pollution [particulate matter with diameter ≤ 2.5 μm (PM_2.5), or ≤10 μm (PM₁₀), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbonic oxide (CO)] were estimated using satellite-based spatiotemporal models. PA was investigated using International Physical Activity Questionnaire. Generalized linear models were used to examine the associations of air pollution, PA score with blood pressure [systolic blood pressure (SBP), diastolic blood pressure (DBP), and mean arterial pressure (MAP)], and the prevalence of hypertension. Subgroup analysis was conducted to investigate the effects of air pollution on blood pressure and the prevalence of hypertension in different PA groups.

Results

The results showed that for each inter-quartile range (IQR) increase in PM_2.5 (25.45 μg/m³), PM₁₀ (40.56 μg/m³), SO₂ (18.61 μg/m³), NO₂ (11.16 μg/m³), CO (0.42 mg/m³) and PA score (161.3 MET/h-week), the adjusted odd ratio (OR) of hypertension was 1.207 (95% confidence interval (CI): 1.137, 1.281), 1.189 (95%CI: 1.122, 1.260), 1.186 (95%CI: 1.112, 1.266), 1.186 (95%CI: 1.116, 1.260), 1.288 (95%CI: 1.223, 1.357), 0.948 (95%CI: 0.899, 0.999), respectively. Long-term exposure to PM_2.5, PM₁₀, SO₂, NO₂, and CO was associated with increased SBP, DBP, and MAP levels. For example, each IQR increase in PM_2.5 was associated with 1.20 mmHg (95%CI: 0.69, 1.72) change in SBP, 0.66 mmHg (95%CI: 0.36, 0.97) change in DBP, and 0.84 mmHg (95%CI: 0.49, 1.19) change in MAP levels, respectively. Each IQR increase in PA score was associated with -0.56 mmHg (95%CI: -1.03, -0.09) change in SBP, -0.32 mmHg (95%CI: -0.59, -0.05) change in DBP, and -0.33 mmHg (95%CI: -0.64, -0.02) change in MAP levels, respectively. Subgroup analysis found that the estimated effects in the sufficient PA group were lower than that in the insufficient PA group.

Conclusion

Long-term exposure to air pollutants is associated with increased blood pressure and hypertension risk, while high-level PA is associated with decreased blood pressure and hypertension risk. Strengthening PA might attenuate the adverse effects of air pollution on blood pressure and hypertension risk.

Relationship between Built-Up Environment, Air Pollution, Activity Frequency and Prevalence of Hypertension-An Empirical Analysis from the Main City of Lanzhou

In the process of promoting the strategy of a healthy China, the built environment, as a carrier of human activities, can effectively influence the health level of residents in the light of its functional types. Based on the POI data of four main urban areas in Lanzhou, this paper classifies the built environment in terms of function into four types. The association between different types of built environments and the prevalence of hypertension was investigated by using the community as the study scale, and activity frequency, air pollution and green space were used as mediating variables to investigate whether they could mediate the relationship between built environments and hypertension. The results indicate that communities with a high concentration of commercial service facilities, road and traffic facilities and industrial facilities have a relatively high prevalence of hypertension. By determining the direct, indirect and overall effects of different functional types of built environment on the prevalence of hypertension, it was learned that the construction of public management and service facilities can effectively mitigate the negative effects of hypertension in the surrounding residents. The results of the study contribute to the rational planning of the structure of the built environment, which is beneficial for optimizing the urban structure and preventing and controlling chronic diseases such as hypertension.

Healthier Lifestyles Attenuated Association of Single or Mixture Exposure to Air Pollutants with Cardiometabolic Risk in Rural Chinese Adults

There is little research on how long-term exposure to independent and multiple air pollutants changes cardiometabolic risk in adults. In addition, previous studies focused on only the effect of one or two lifestyles on cardiometabolic risk. The evidence on the interactive effects of the lifestyle score and exposure to independent and mixtures of air pollutants on cardiometabolic risk is lacking. A total of 33,638 rural residents were included in the cross-sectional study. The three-year average concentrations of air pollutants for participants were predicted by using a satellite-based prediction. The air pollution score was created to assess the combined exposure of four air pollutants (PM1, PM2.5, PM10, and NO2). A gender−age-specific cardiometabolic risk score was calculated. Multivariable-adjusted linear regression and quantile g-computation were used to investigate the associations between air pollutants and cardiometabolic risk. Interaction plots were applied to describe the interactive effects of air pollution and the healthy lifestyle score on cardiometabolic risk. Per interquartile range (IQR) unit increases in PM1, PM2.5, PM10, or NO2 were associated with 0.162 (95% CI: 0.091, 0.233), 0.473 (95% CI: 0.388, 0.559), 0.718 (95% CI: 0.627, 0.810), and 0.795 (95% CI: 0.691, 0.898) unit increases in cardiometabolic risk score (all p < 0.05), respectively. A 0.854 (95% CI: 0.768, 0.940) unit increase in cardiometabolic risk was associated with each IQR increase in air pollution score. Furthermore, the strengths of associations of PM1, PM2.5, PM10, NO2, and the air pollution score on cardiometabolic risk score were attenuated with the healthy lifestyle score increase. In addition, there was no statistical significance after the lifestyle score equal to four scores for the effect of PM1 on the cardiometabolic risk score. In conclusions, individual or joint air pollutants were associated with an increased cardiometabolic risk. Improving the healthy lifestyle may be an effective method to improve cardiometabolic health in highly polluted rural regions.

Interaction of biomass fuels use and metals exposure on hypertension: A prospective cohort study in rural areas along the Yangtze River, China

Humans maybe simultaneously exposed to multiple-metals and indoor air pollution in daily life. However, limited prospective studies have assessed the interaction between multiple metals exposure and biomass fuels use on hypertension in China. The prospective cohort study in rural areas along the Yangtze River included 2625 adults in 2014-2015, and they were followed up till 2019. Among 1248 rural residents who were without hypertension at baseline, 377 hypertension events (30.21%) were observed after 4.5 years of average follow-up time. First-morning urine samples of residents were collected at baseline, the association between urinary metals level and hypertension were assessed using quantile g-computation. Additionally, we also examined the effect of biomass fuels use, fuels switching, and cookstove ventilation on the association of metals exposure with hypertension. Quantile g-computation analyses showed a positive joint effect of 17 metals on hypertension, with the odds ratio (OR) of 1.68 (95% CI: 0.89, 3.14) when increasing all seventeen metals by one quartile, and cadmium, lithium, copper contributed the largest positive weights. Biomass fuels use can interact with cadmium exposure on hypertension with OR for interaction of 1.28 (95%CI: 1.00, 1.73), and increase the association between copper, manganese and zinc exposure and systolic blood pressure, lithium exposure and diastolic blood pressure at the follow-up visit. Moreover, switching from biomass fuels to clean fuels during follow up, cookstove ventilation can alleviate the risk of higher blood pressure from metals exposure. In rural areas along the Yangtze River, China, biomass fuels use for cooking can interact with multiple-metals exposure on hypertension. Residents who switched from biomass fuels to clean fuels and who used ventilation had a lower risk of hypertension. Further cohort studies are needed to clarify the mechanism of combined effects of metals exposure and biomass fuels use on the human health.

Adverse associations of different obesity measures and the interactions with long-term exposure to air pollutants with prevalent type 2 diabetes mellitus: The Henan Rural Cohort study

BACKGROUND

Obesity and ambient air pollution are independent risk factors of type 2 diabetes mellitus (T2DM), however, the evidence regarding their joint associations on T2DM was sparsely studied in low-middle income countries.

METHODS

A total of 38,841 participants were selected from Henan Rural Cohort study which was carried out during 2015-2017. Obesity was identified by body mass index (BMI), WC (waist circumstance), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BFP (body fat percent), and VFI (visceral fat index). Three-year averaged-concentrations of NO₂, PM₁, PM_2.5, and PM₁₀ were assessed by using the method of spatiotemporal model incorporated into the satellites data. The independent associations of obesity indicators and exposure to air pollutants on fasting blood glucose (FBG) and T2DM were assessed by generalized linear and logistic regression model, respectively, and their interaction associations on T2DM were quantified by using relative excess risk due to interaction (RERI), attributable proportion due to interaction (AP), and synergy index (S).

RESULTS

Positive associations of six obesity measures and four air pollutants with FBG levels and prevalent T2DM were observed. Obese participants measured by BMI plus high exposure to NO₂, PM₁, PM_2.5 and PM₁₀ were related to a 2.96-fold (2.66-3.29), 2.87-fold (2.58-3.20), 2.98-fold (2.67-3.32) and 3.01-fold (2.70-3.35) increased risk for prevalent T2DM, respectively; similarity of joint associations of the other obesity measures and air pollutants on T2DM were observed. The additive associations of different obesity measures and air pollutants with prevalent T2DM were further found.

CONCLUSIONS

The synergistic associations of obesity and air pollutants on FBG levels and prevalent T2DM were observed, indicating that obese participants were at high risk for prevalent T2DM in highly polluted rural regions.

Association between Particulate Matter Pollution Concentration and Hospital Admissions for Hypertension in Ganzhou, China

Fine particulate matter (PM_2.5) and respirable particulate matter (PM₁₀) are two major air pollutants with toxic effects on the cardiovascular system. Hypertension, as a chronic noncommunicable cardiovascular disease, is also a risk factor for several diseases. We applied generalized linear models with a quasi-Poisson link to assess the effect of air pollution exposure on the number of daily admissions for patients with hypertension. In addition, we established a two-pollutant model to evaluate PM_2.5 and PM₁₀ hazard effect stability by adjusting the other gaseous pollutants. Results showed that during the study period, 24 h mean concentrations of ambient PM_2.5 and PM₁₀ at 38.17 and 59.84 μg/m³, respectively, and a total of 2,611 hypertension hospital admissions were recorded. Air pollution concentrations significantly affected the number of hospitalizations for hypertension approximately 2 months after exposure. For each 10 μg/m³ increase in PM_2.5 and PM₁₀ in single-pollutant models, the number of hospitalizations for hypertension increased by 7.92% (95% CI: 5.48% to 10.42%) and 4.46% (95% CI: 2.86% to 5.65%), respectively, at the lag day with the strongest effect. NO₂, O₃, CO, and SO₂ had different significant effects on the number of hospitalizations over the same time period, and PM_2.5 and PM₁₀ still showed robust significant effects after adjustment of gas pollutants through a two-pollutant model. These findings may contribute to a better understanding of the health effects of ambient particulate matter.