Association of size-fractionated indoor particulate matter and black carbon with heart rate variability in healthy elderly women in Beijing

Abstract Background Quantitative assessment of individual body adaptability to physical training performed with the purposes of health maintenance is particularly necessary in the elderly age, to avoid the risk of overstrain induced by inappropriate exercises workload and physical stress. For that purpose, heart rate monitors and heart rate variability (HRV) analysis are nowadays commercially available. However, their reliability to guide individualized fitness training in elderly people needs to be tested, knowing that users might not have medical education. Objective To preliminary quantify autonomic nervous system (ANS) responses to graded physical effort and recovery in healthy elderly basing on the parasympathetic nervous system (PNSi), the sympathetic nervous system (SNSi) and the stress (STRi) indices, derived by short-term and time-varying HRV analysis. Methods ECG of a 75 healthy male subject was monitored, from April to November 2020, during three times/week training sessions with a professional bike–ergometer. Each session consisted of 10 minutes baseline rest, 5 minutes warm-up, 30 minutes work and 10 minutes recovery. According to age, the training workload was graded from low (65–75 watt/min), to moderate (75–85 watt/min), semi-intensive (85–95 watt/min) and intensive (95–110 watt/min). For this pilot study, ECG data of only 40 training sessions (10 sessions for each workload to evaluate reproducibility) were analyzed with Kubios Premium software (version 3.4.1), in the time (TD) and frequency (FD) domains, with nonlinear (NL) methods and with time-varying (TV) algorithms. Short-time HRV was calculated from 2-minutes intervals. The PNSi, SNSi and STRi induced by each workload were averaged and compared. Results Average values of PNSi, SNSi and STRi were significantly different (p<0.05) among training sessions carried out with different workloads (Table 1A) and among measurements obtained at rest, at every 5 minutes step of each 30 minutes training session, and at 1 and 5 minutes of recovery (Table 1B). Interestingly, the correlation between SNSi and STRi was strictly linear (R= 0,98), whereas that between PNSi and STRi was better fitted by a cubic function (R=0,82 with cubic vs 0.68 with linear function), when evaluated either as a function of the sessions' workloads (Figure 1A), or of four time-intervals of each training session (Figure 1B). PNSi and SNSi were inversely correlated, with cross-point at about 15 minutes of training and 75 watt/min workload. Conclusions The calculation of PNSi, SNSi and STRi from HRV analysis is an efficient method for quick and simplified quantitative assessment of dynamic ASN adaptation to effort-induced stress from HRV analysis. If confirmed, the method may be useful for safer and even remote monitoring of training/rehabilitation in elderly. However, more detailed evaluation of spectral and NL parameters may be necessary to interpret more complex patterns of abnormal cases. FUNDunding Acknowledgement Type of funding sources: None. Table 1 Figure 1

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Personal exposure to particulate matter and heart rate variability among informal electronic waste workers at Agbogbloshie: a longitudinal study

BMC Public Health ◽

10.1186/s12889-021-12241-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Afua A. Amoabeng Nti ◽

Thomas G. Robins ◽

John Arko Mensah ◽

Duah Dwomoh ◽

Lawrencia Kwarteng ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Particulate Matter ◽

Electronic Waste ◽

Ambient Air ◽

Repeated Measurements ◽

Ambient Air Pollution ◽

Continuous Exposure ◽

Cardiac Autonomic Dysfunction ◽

Increased Risk

Abstract Background Informal electronic waste recycling activities are major contributors to ambient air pollution, yet studies assessing the effects or relationship between direct/continuous exposure of informal e-waste workers to particulate matter and cardiovascular function are rare. Methods Repeated measurements of fractions of PM2.5, PM10–2.5, and PM10 in personal air of informal e-waste workers, (n = 142) and a comparable group (n = 65) were taken over a period of 20 months (March 2017 to November, 2018). Concurrently, 5-min resting electrocardiogram was performed on each participant to assess resting heart rate variability indices. Linear mixed-effects models were used to assess the association between PM fractions and cardiac function. Results SDNN, RMSSD, LF, HF and LH/HF ratio were all associated with PM. Significant associations were observed for PM2.5 and Mean NN (p = 0.039), PM10 and SDNN (p = 0.035) and PM 10–2.5 and LH/HF (p = 0.039). A 10 μg/m3 increase in the concentrations of PM 2.5, PM10–2.5, and PM10 in personal air was associated with reduced HRV indices and increased resting HR. A 10 μg/m3 per interquartile (IQR) increase in PM10–2.5 and PM10, decreased SDNN by 11% [(95% CI: − 0.002- 0.000); (p = 0.187)] and 34% [(95% CI: − 0.002-0.001); (p = 0.035)] respectively. However, PM2.5 increased SDNN by 34% (95% CI: − 1.32-0.64); (p = 0.493). Also, 10 μg/m3 increase in PM2.5, PM10–2.5 and PM10 decreased RMSSD by 27% [(− 1.34–0.79); (p = 0.620)], 11% [(− 1.73, 0.95); (p = 0.846)] and 0.57% [(− 1.56–0.46); (p = 0.255%)]. Conclusion Informal e-waste workers are at increased risk of developing cardiovascular disease from cardiac autonomic dysfunction as seen in reduced HRV and increased heart rate.

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