info@biomedres.us   +1 (502) 904-2126   One Westbrook Corporate Center, Suite 300, Westchester, IL 60154, USA   Site Map
ISSN: 2574 -1241

Impact Factor : 0.548

  Submit Manuscript

Research ArticleOpen Access

Is it Possible that the Connection Between Solar Lentigines and Type 2 Diabetes Mellitus Can Result from a Common Cause – Solar Alpha Particle Streams? Volume 58- Issue 4

Nikolay Takuchev*

  • Ph.D., Associate professor, Trakia University, Bulgaria

Received: September 03, 2024; Published: September 19, 2024

*Corresponding author: Nikolay Takuchev, Ph.D., Associate professor, Trakia University, Stara Zagora, Bulgaria

DOI: 10.26717/BJSTR.2024.58.009196

Abstract PDF

ABSTRACT

Between the incidence of solar lentigo (benign dark skin spots) and type-2 diabetes, there is a statistically proven positive correlation – diabetics have more solar lentigo. Both depend on prolonged exposure to solar radiation. Still, there is a logical contradiction – while the frequency of solar lentigo increases among those exposed to protracted solar radiation, diabetes among them is less common, and it would follow that the two diseases are negatively, not positively, correlated. The controversy can be resolved if it is accepted that both diseases depend on a hitherto unaccounted-for common risk factor related to solar radiation other than electromagnetic radiation composed of visible (light) and ultraviolet radiation. With examples from mortality statistics in Europe and the Mediterranean, combined with data from satellite observations, it is shown that it is possible that the common risk factor sought is high-energy solar alpha radiation reaching the Earth’s orbit. By some mechanism, streams of positively charged particles with high energy entering the Earth’s orbit increase mortality on the planet’s surface. The increase in mortality is in a zone of maximum risk in the Northern Hemisphere, parallel to the equator and bounded by the parallels of 30° and 50° north latitude. Examples are given for the European Union mortality from endocrine, nutritional, and metabolic diseases, in particular diabetes mellitus, confirming the described phenomenon. A hypothetical mechanism based on observational evidence has been proposed, according to which this dangerous phenomenon is due to solar alpha particles of high energy sufficient to overcome the atmosphere’s resistance and reach the Earth’s surface in a limited area of maximum death impact.

Keywords: Mortality; Diabetes Mellitus; Satellites GOES; Cosmic Alpha Radiation; EUROSTAT

Introduction

Type 2 Diabetes Mellitus causes death and disability. It was the ninth leading cause of death in 2017 [1]. Some external impacts on the human organism, such as exposure to sunlight and ultraviolet radiation, could reduce the risk of type-2 diabetes [2-5]. The same influencing factors cause solar lentigo – benign hyper-pigmented macules on the skin, more commonly seen in older persons [6,7], associate the appearance of spots on the skin with photo-damage and the aging process as a result of chronic ultraviolet exposure, resulting in increased melanin production. A statistically significant correlation was observed between the presence of cutaneous lentigo and type-2 diabetes. Since both diseases are supposedly related to exposure to sunlight – light and ultraviolet radiation – one would expect the correlation between these two diseases to be negative – lentigo increases with exposure to sunlight and diabetes decreases. It seems paradoxical, but the two diseases are positively correlated [8,9]. The presence of lentigo on the skin of patients with type-2 diabetes was statistically significantly more than that of control groups, more pronounced in women. The presence of lentigo may be used as an indicator of a patient’s metabolic status or it may be a symptom of undiagnosed diabetes [8]. The mechanisms of development of skin lentigo among patients with type-2 diabetes mellitus are unknown. It has to be concluded that these diseases are linked, possibly through a common risk factor, connected with solar radiation, but it is not electromagnetic radiation – visible (light) and ultraviolet radiation.

Another possible risk factor, connected with solar radiation is streams of solar alpha particles with high enough energy, allowing them to penetrate through the atmosphere to the Earth’s surface. The mentioned streams are of short duration – from minutes to a few days and reach the Earth’s surface in a limited area the size of a medium- sized country, which is why they can hardly be registered on the Earth’s surface. Below are arguments in favor of the claim that the mentioned streams of solar alpha particles are also a risk factor, increasing the mortality from type-2 Diabetes Mellitus. In a series of publications [10-33], a dangerous phenomenon of cosmic origin for humanity was described – the presence of a high correlation between the flows of positively charged particles with high kinetic energy recorded from satellites in the Earth orbit and mortality on the Earth’s surface from many diseases. The main focus of the mentioned publications was on the effect of solar alpha radiation on mortality from diseases, killer number one of mankind – those of the circulatory system. The harmful effects of solar alpha radiation are also observed on many other organs and systems in the human organism, turning this invisible effect into one of the main sources of death for humanity. The mentioned dangerous phenomenon of cosmic origin is unevenly spread on the planet’s surface. Europe and the Mediterranean are among the most affected.

However, in [1-24] are described many examples, where this phenomenon is also observable in several countries from the Northern Hemisphere – Asia, America, and even Africa. The European Union has a tradition of maintaining reliable mortality statistics, in which the discussed multifaceted influence of solar alpha radiation on mortality stands out clearly. Below, based on data from mortality statistics in the European Union, the unexpected association between solar alpha radiation and mortality from endocrine, nutritional, and metabolic diseases, type-2 diabetes mellitus in particular, is shown. The described phenomenon is not observed in the statistical data of large countries such as the USA, Russia, and China. This (at least for the USA [19]) is due to masking the phenomenon in the general statistics for the large country if the cause acts on a limited area smaller than the country and for a limited time – lasting much less than data averaging periods for statistical purposes. The mortality statistic of the European Union is suitable for the study because it is based on statistical regions, smaller than a country, but still big enough, to include a statistically sufficient number of inhabitants. This phenomenon would be expected to influence mortality in countries south of the Equator, but mortality statistics for them are scarce, unreliable, or absent, preventing reliable inferences about such an influence in the Southern Hemisphere.

Material and Methods

Mortality Data

The analysis below is based on an authoritative source of health data – EUROSTAT [34]. In the study, the parameter annual mortality rate – number of deaths per 100,000 inhabitants was used as a characteristic of mortality. EUROSTAT offers free access to data on mortality rates from causes in the countries of the European Union, the European Economic Area, and the candidate countries for membership in the union. Geographically, these countries occupy Europe and the Mediterranean. Data are grouped by NUTS (Nomenclature Des Unités Territoriales Statistiques in French, the nomenclature of territorial units for statistics). In the study, were used mortality data from the Eurostat shortlist in which mortality rates are grouped by causes of death into 92 groups, mostly diseases. The groups are related to the classes in the International Disease Classifier ICD-10, (10th revision). The shortlist contains mortality data for EU countries (NUTS-1) and EU regions (NUTS-2, smaller areas of the larger NUTS-1 countries). Currently (2023) the shortlist includes mortality rate data for the interval 2011 – 2020. Annual mortality rate data were extracted for 354 European regions (NUTS-2) separately from each of the shortlist groups for the interval 2011 – 2019 (the last pre-pandemic year).

Satellite Data

Satellite data on corpuscular radiation – protons and alpha particles recorded by the satellites of the series GOES (Geostationary Operational Environmental Satellites) were obtained from a NOAA site [35]. The satellites of the GOES series fly in geostationary orbit (above the Earth’s equator), at an altitude of 36,000 kilometers above the Earth’s surface, make one lap in 24 hours, that is, they “hang” over a certain point on the Earth’s surface and are not shade by the Earth at their circumference around it. Data on alpha-particle and proton fluxes (unit: (number of particles).cm-2.s-1.sr-1.MeV-1) with energies of the range 3.8 – 21.3 MeV were used. The fluxes were recorded by the satellite high-energy particle detectors: 1. Energetic Particles Sensor (EPS), and 2. Energetic Proton, Electron, and Alpha Detector (EPEAD). The data are available averaged over a 5-minute interval, during which there are up to 25 reports of the instrument.

Data Processing

The correlation coefficients [36] were calculated between the annual averaged alpha radiation flux and the annual mortality rate separately for 354 NUTS-2 European regions, and for each of the three EUROSTAT shortlist death causes: “Endocrine, nutritional and metabolic diseases (E00-E90)” (EUROSTAT shortlist number 34), “Diabetes mellitus” (EUROSTAT shortlist number 35), and “Other endocrine, nutritional and metabolic diseases (remainder of E00-E90)” (EUROSTAT shortlist number 36). From data for the 354 NUTS-2 European regions maps were created showing (with black isolines) the distribution of the annual mortality for 2012, the year with the highest solar activity (and mortality) in the studied time interval 2011 – 2019. Data on latitude and longitude [Google Earth] of the centroids of the NUTS-2 regions included in the study were used in the map. Mapping was performed with Golden Software Surfer10. The kriging interpolation procedure was used. With red isolines, the map shows the distribution across Europe and the Mediterranean of the correlation coefficient between the annual mortality rate from each of the studied three causes with the annually averaged alpha particle flux for the studied period 2011 – 2019. In mathematical statistics, the level of statistical significance [36] is a parameter indicating the degree of reliability of the calculated correlation coefficient. The smaller the value of this parameter, the more reliably the correlation coefficient is established, i.e. the more reliably a cause-and-effect relationship has been established, in the case between the annual flux of solar alpha radiation and mortality from the studied cause from the EUROSTAT shortlist. The correlation coefficient and the level of statistical significance are related.

For the 9 years included in the study, a minimum correlation coefficient of 0.668 corresponds to a statistical significance level of 0.05 [36]. In scientific studies, a level of statistical significance no greater than 0.05 is accepted as a criterion for the reliability of the correlation coefficient. The red isolines on the correlation coefficient distribution in the maps enclose the regions with statistically significant values of the correlation coefficients equal and above a significance level of 0.05. Correlation coefficients with a significance level above 0.05 are of high reliability (the higher the number, the lower the significance level) i.e. the existence of a causal relationship between cosmic alpha radiation and mortality from the studied cause can be considered reliably established in the mentioned areas enclosed by red isolines on the correlation coefficient. If there is a coincidence for some of the maxima for mortality rate and correlation coefficients, then in the region of these maxima, the impact of alpha radiation contributes noticeably to the mortality from the studied cause. To the extent that the hypothetical mechanism proposed below explaining the observed phenomenon assumes that charged particles of high energy pass through the atmosphere and reach the Earth’s surface, the energy required for this was calculated from databases and calculators PSTAR and ASTAR [37,38]. Geomagnetic field data were obtained from the INTERMAGNET site [39].

Results

The described dangerous phenomenon is observed in the form of dependence between the annual average flux of radiation from positively charged particles with high kinetic energy, recorded by satellites in orbit around the Earth, and the annual mortality rate in the statistics of several countries from all continents in the Northern Hemisphere. The countries in whose mortality statistics the phenomenon is observed are located in a zone parallel to the equator with approximate boundaries along the parallels of 30° and 50° north latitudes. It is observed in the annual mortality statistics of small countries. It is not noticeable in the statistics of large countries in the same zone. It can be inferred that the impact on the Earth’s surface is shortlived and over a limited area the size of a small country, but is masked in large country statistics because it does not affect the entire area of the large country at the same time. This conclusion is confirmed for the USA, for which there is data on mortality in individual states [19]. For particle energies of the order of 3.8 – 21.3 MeV, the year-averaged fluxes of protons and alpha particles are highly correlated, i.e. the studied phenomenon of lethality is noticeable in both the mean proton flux and the mean alpha particle flux data. In the examples below an averaged stream of high-energy alpha particles is included as the incident radiation. Figure 1 shows for the Europe and Mediterranean the distribution of the mortality rate for “Diabetes mellitus” (black isolines) and the distribution of the statistically significant correlation coefficient between solar alpha particle fluxes and the mortality rate for “Diabetes mellitus” (red isolines).

Figure 1

biomedres-openaccess-journal-bjstr

The figure shows that the places with the highest diabetes mellitus mortality are situated mainly between the 40th and 50th parallel in France, Italy, and Austria, and the islands of Sardinia and Corsica. A noticeable effect of alpha radiation on diabetes mortality is found in the region of western Spain, Germany, and Istanbul, where areas of increased mortality (for 2012, black isolines) overlap with those with a statistically significant correlation of mortality with alpha radiation flux (red isolines). Figures 2-9 show the correlated changes in mortality from endocrine, nutritional, and metabolic diseases with alpha radiation flux for these areas. The figures show the time dependence in the interval 2011 – 2019 of two numerical sequences:

1. of the recorded annual fluxes of alpha particles from satellites of the GOES series – 10, 11, 12, 13, and 14, and
2. of the annual mortality rate of Eurostat shortlist cause classes “Endocrine, nutritional and metabolic diseases (E00-E90)”, “Diabetes mellitus”, and “Other endocrine, nutritional and metabolic diseases (remainder of E00-E90)” for the NUTS-2 regions of the European Union.
The high correlation between the two numerical sequences can be seen, indicating the existence of a causal relationship between them.

Figure 2

biomedres-openaccess-journal-bjstr

Figure 3

biomedres-openaccess-journal-bjstr

Figure 4

biomedres-openaccess-journal-bjstr

Figure 5

biomedres-openaccess-journal-bjstr

Figure 6

biomedres-openaccess-journal-bjstr

Figure 7

biomedres-openaccess-journal-bjstr

Figure 8

biomedres-openaccess-journal-bjstr

Figure 9

biomedres-openaccess-journal-bjstr

Discussion

The given examples convincingly prove the existence of an influence of cosmic radiation flux on endocrine, nutritional, and metabolic disease mortality. The problem of the mechanism of the described influence remains unclear. A hypothesized mechanism of this influence is outlined below, answering many of the questions that arise.

1. An observed phenomenon – mortality from many diseases in the statistics of many countries located mainly in the 30° N – 50°N band, is strongly correlated with fluxes of positively charged particles with energy of the order of 4 – 21 MeV, recorded by the GOES series satellites in Earth orbit.

2. The recorded alpha particle flows are mostly pulses with a duration of less than 5 minutes (the averaging interval of the recording device) to a few days.

3. Proposed hypothesis – positively charged particles with high energy penetrate through the Earth’s atmosphere to the Earth’s surface and damage human health, causing death mainly in elderly people with an already damaged metabolism, immune and circulatory system.

4. As the average altitude of the affected countries increases, the particle flux-correlated mortality shows an increasing trend [13,19]. It is probably due to the more intense radiation flux penetrating the thinner atmosphere over the mountainous region of Earth’s surface – an argument favoring the hypothesis.

5. The source of the flows of positively charged particles is the Sun – mortality increases with observable processes on the Sun – from SME directed to Earth (a phenomenon on the solar surface that could be observed with other astronomical means) [13]. The Alpha Magnetic Spectrometer (AMS-02) on the International Space Station measures cosmic rays, excluding those of solar origin (only galactic cosmic rays – when the spectrometer is shielded from the Sun by the station’s solar panels). In particular, it measures the flow of 3He and 4He (alpha particles) in cosmic rays. The measurements show [40] increasing annual flux of alpha particles in cosmic rays for the interval of years from 2011 to 2017 (last available data), while the flux of GOES registered (solar?) alpha particles for the same interval of years is decreasing (Figures 2-9). Indirect evidence for the Sun as a source of high-energy alpha particles is that this assumption convincingly explains the downstream processes that ultimately lead to death.

6. Positively charged solar particles capable of penetrating through the Earth’s atmosphere to the Earth’s surface are high-energy alpha particles. Calculators PSTAR [37] and ASTAR [38] calculate the penetration parameters of protons, respectively alpha particles in different substances, in particular in air. Calculations with data for a homogeneous atmosphere – an atmospheric model with constant density, temperature, and pressure decreasing with height [13] show that only particles whose energy is above 2.4 GeV for protons and over 6.2 GeV for alpha particles can penetrate the Earth’s atmosphere to the surface. There are no registered protons above 0.7 GeV, but there are registered alpha particles with energy above 3.4 GeV, hypothetically also those with energy above 6.2 GeV [13,19,21], i.e. the particles that penetrate to the Earth’s surface are probably high-energy alpha particles. Only flows of alpha particles with a magnitude of at least (1000 particles). cm-2.s-1.sr-1.MeV-1 is correlated with the mortality of the Earth’s surface.

7. It is assumed that the alpha particles recorded by the satellites were emitted simultaneously in a common explosive process on the solar surface (flares?) with the hypothetical fast alpha particles. It can be calculated that particles with an energy of 7 GeV need 8.87 min to reach the Earth’s surface from the Sun’s surface, and registered by satellites particles with energies of 5 – 10 MeV travel about 2 hours. The registered alpha particles do not have enough energy to penetrate the atmosphere, unlike the hypothetical fast alpha particles that reach the surface of the Earth in minutes from the center of the solar disk. However, the registered alpha particles are an indicator that two hours earlier there was an irradiation of the Earth’s surface with fast (unregistered) alpha particles.

8. Although alpha particle streams irradiate the entire illuminated part of the atmosphere, penetration of fast alpha particles to the surface occurs only in a limited area of the surface (death spot), for which two conditions favoring penetration are combined:

a. The Sun is culminating for the center of the death spot. During the year, the apparent position of the Sun relative to the point of observation shifts, so that the maximum angle of elevation of the Sun’s disk above the horizon (solar culmination at the time of local noon) changes depending on the date. The point on the Earth’s surface where the solar disk is at its culmination when the satellite registers the alpha particle flow – the point of registration, can be determined from the date (latitude), and the time – the hours and minutes of registration of the alpha particle flow (latitude), and the hours and minutes of registration of the alpha particle flow (longitude). The center of the dead spot can be calculated – it is approximately 30° east of the registration point [19]. The Earth’s angular velocity is 15° per hour.

b. For the center of the death spot, a coincidence is in effect – the direction of the geomagnetic vector coincides with the direction of the alpha particle intrusion – the alpha particle movement is not affected by the deflecting magnetic force. Such a coincidence occurs twice a year for latitudes in the band from 28°N to 48°N [13]. For latitudes outside this band, such a coincidence is impossible, the fast alpha particles do not reach the Earth’s surface, or their flux on the surface decreases fast with their moving away from the band.

The moment of occurrence of a flow of fast alpha particles cannot be predicted, but the dates of increased risk for a given point on the Earth’s surface between 30°N – 50°N can be calculated by the latitude of the location [19]. For example, for Tuscany, Italy (See Figure 7), with latitude 43.5°N, the dates with maximum risk are April 22 – 29 and August 14 – 21. In these intervals, the inclination of the geomagnetic vector for Tuscany (60°, constant angle, depending on the geographical position of the observation point) is close in magnitude to or coincides with the culmination of the Sun (the Earth’s atmosphere is thinnest at the moment of the Sun’s culmination, and there is no deflecting magnetic force for alpha particles if they intrude at this time from the Sun). The increased risk of health incidents outdoors around local noon is a further argument for the healthfulness of the indoor midday break (‘siesta’) practiced in Mediterranean countries. The predominant part of the recorded pulses of alpha particles form unnatural series with fixed periods and relatively constant magnitudes, which allows the hypothesis of their artificial origin [21].

References

  1. Fried L P, Tangen C M, Walston J, Newman A B, Hirsch C, et al. (2001) Frailty in older adults: evidence for a phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56(3): M146-M156.
  2. (2018) ACSM's Guidelines for Exercise Testing and Prescription. Lippincott Williams & Wilkins. American College of Sports Medicine.
  3. Peterson M D, Sen A, Gordon P M (2010) Resistance exercise for the aging adult: clinical benefits and prescription guidelines. American Journal of Medicine 123(6): 510-517.
  4. Liu C J, Latham N K (2009) Progressive resistance strength training for improving physical function in older adults. Cochrane Database of Systematic Reviews (3).
  5. Chodzko Zajko W J, Proctor D N, Fiatarone Singh M A, Minson C T, Nigg C R, et al. (2009) Exercise and physical activity for older adults. Medicine and Science in Sports and Exercise 41(7): 1510-1530.
  6. Phillips S M (2014) A brief review of critical processes in exercise-induced muscular hypertrophy. Sports Medicine 44(Suppl 1): 71-77.
  7. Cruz Jentoft A J, Baeyens J P, Bauer J M, Boirie Y, Cederholm T, et al. (2010) Sarcopenia: European consensus on definition and diagnosis. Age and Ageing 39(4): 412-423.
  8. Ned Y, Wu M J, Becker B J, Tenenbaum G (2005) Physical activity and psychological well-being in advanced age: a meta-analysis of intervention studies. Psychology and Aging 20(2): 272-284.
  9. Peterson M D, Sen A, Gordon P M (2010) Resistance exercise for the aging adult: clinical benefits and prescription guidelines. American Journal of Medicine 123(6): 510-517.
  10. Liu C J, Latham N K (2009) Progressive resistance strength training for improving physical function in older adults. Cochrane Database of Systematic Reviews (3).
  11. Fiatarone M A, O Neill E F, Ryan N D, Clements K M, Solares G R, et al. (1994) Exercise training and nutritional supplementation for physical frailty in very elderly people. New England Journal of Medicine 330(25): 1769-1775.
  12. Aprahamian I (2017) Effects of a 12-week resistance training program on muscle strength, power, and functional performance in older adults. Journal of Geriatric Physical Therapy 40(3): 123-130.
  13. Phillips S M (2014) A brief review of critical processes in exercise-induced muscular hypertrophy. Sports Medicine 44(Suppl 1): 71-77.
  14. Cruz Jentoft A J, Baeyens J P, Bauer J M, Boirie Y, Cederholm T, et al. (2010) Sarcopenia: European consensus on definition and diagnosis. Age and Ageing 39(4): 412-423.
  15. Hakkinen K, Alen M, Kraemer W J, Gorostiaga E, Izquierdo M, et al. (1998) Neuromuscular adaptations during concurrent strength and endurance training versus strength training. European Journal of Applied Physiology and Occupational Physiology 78(1): 99-105.
  16. Chodzko Zajko W J, Proctor D N, Fiatarone Singh M A, Minson C T, Nigg C R, et al. (2009) Exercise and physical activity for older adults. Medicine and Science in Sports and Exercise 41(7): 1510-1530.
  17. Ivan P (2018) Molecular mechanisms underlying the benefits of strength training in older adults. Journal of Gerontology: Biological Sciences 73(6): 789-797.
  18. Ned Y, Wu M J, Becker B J, Tenenbaum G (2005) Physical activity and psychological well-being in advanced age: a meta-analysis of intervention studies. Psychology and Aging 20(2): 272-284.
  19. Montgomery R M, Aprahamian I (2018) Fragilidade e Doença de Parkinson. Thesis.
  20. (2018) ACSM's Guidelines for Exercise Testing and Prescription. Lippincott Williams & Wilkins. American College of Sports Medicine.
  21. Fiatarone M A, O Neill E F, Ryan N D, Clements K M, Solares G R, et al. (1994) Exercise training and nutritional supplementation for physical frailty in very elderly people. New England Journal of Medicine 330(25): 1769-1775.
  22. Fried L P, Tangen C M, Walston J, Newman A B, Hirsch C, et al. (2001) Frailty in older adults: evidence for a phenotype. The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56(3): M146-M156.
  23. Hakkinen K, Alen M, Kraemer W J, Gorostiaga E, Izquierdo M, et al. (1998) Neuromuscular adaptations during concurrent strength and endurance training versus strength training. European Journal of Applied Physiology and Occupational Physiology 78(1): 99-105.