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Geomagnetic Field Effects on Living Systems

As shown in Figure 6.15 (Jaruševičius et al., 2018), in the male group, the weekly correlation coef­

fcients are similar to the female group, however, all coefcients are negative. Unlike females, they

observed non-signifcant changes in Sγ range, which may indicate slightly diferent sensitivity of difer­

ent sexes to the GMF changes.

As shown in Figure 6.16 (Jaruševičius et al., 2018), they found that a correlation between the number

of STEMI cases and <63 y.o. males was maintained in all MF frequency ranges. Diferences between

both halves of the year were signifcant. Tese results revealed that diferent frequency ranges have dif­

ferent correlations with the presence of myocardial infarctions and the correlations varied in diferent

age groups as well as in males and females, which may indicate diverse organism sensitivity to the GMF.

Tey supposed that diferent people may have diferent sensitivity to diferent frequencies of MFs, but

there may be potential diferences due to age, gender, and health status.

In addition, the same Lithuania research team reported the following conclusions: (1) signifcant cor­

relation between acute coronary syndrome and the local GMF changes was revealed; (2) the acute coro­

nary syndrome is positively correlated with the local GMF in Sγ range in females through the year; (3) a

higher MF in Sβ and Sγ ranges is associated with higher incidences of acute coronary syndrome through

the year in females; (4) the higher MF in Sγ range is associated with higher incidences of acute coronary

syndrome through the year in females and through the second half of the year in males (Žiubrytė et al.,

2018).

In another aspect, in international stroke incidence studies, a joint research team examined the rela­

tionship between the number of frst strokes and geomagnetic activity (Feigin et al., 2014). Data for

stroke patients (over 11,000 total patients) were pooled from multiple studies in Europe, Australia, and

New Zealand between 1981 and 2004 (Feigin et al., 2014). Geomagnetic activity data were obtained from

the US National Oceanic and Atmospheric Administration (NOAA) (Feigin et al., 2014). As for main

results, it has been suggested that the risk increases to an average of 1.9 times in those over 75 years old,

especially in the case of a strong magnetic storm (Feigin et al., 2014). It is unclear why magnetic storms

increase strokes, but previous studies have shown that magnetic storms afect the human body such as

increased BP (Stoupel et al., 1995; Ghione et al., 1998), fuctuations in HR (Stoupel et al., 1994), and blood

viscosity/coagulability related to the risk of blood clots (Stoupel, 2002). All of which are risk factors for

stroke. Te research project team proposes that people with a high risk of stroke should be cautious dur­

ing severe/extremely magnetic storms, such as avoiding heavy or excessive drinking and being careful

not to become dehydrated (Feigin et al., 2014).

With reference to the correlation between the geomagnetic storm and BP, Watanabe et al. (2001)

reported correlations of geomagnetic activity with systolic BP (SBP) and DBP at Daini hospital in Tokyo.

Te authors observed an inverse relationship between Wolf Number (WN) and the variability in SBP

and, to a lesser extent, DBP. Te WN, or relative sunspot number, is an index of the entire visible disk of

the Sun, which is determined each day without reference to previous days. Te relative sunspot number

is defned as:

R

k f +10g)

(6.1)

= (

where g is the number of groups of sunspots and f is the total number of distinct spots. Te scaling fac­

tor k depends on the sensitivity of the observing equipment and is usually less than unity (Hargreaves,

1992). Te data used in this study were from one individual who self-measured his BP and HR at inter­

vals of 15–30 minutes from August 1987 to July 1998, and beyond. Te subject was 35 at the start of the

11-year data set and was clinically healthy. A direct association between HR and WN was found to be

solar cycle stage-dependent, while an inverse relationship was consistently found between WN and HR

variability (HRV) (Watanabe et al., 2001). Tis seems to suggest that high levels of solar activity, and

therefore high levels of geomagnetic disturbance, cause HRV to decrease. Cornélissen et al. (2002) also

report that magnetic storms cause HRV to decrease; Chernouss et al. (2001) confrm this result but state

that the response varies signifcantly between diferent individuals.