Using an Internet Penetration Algorithm and multiple sequential linear regressions to establish excess cancer incidence and cancer radiation and other aetiologies, by Dr Chris Barnes, Bangor Scientific and Educational Consultants, Bangor, Gwynedd.  E-mail doctor.barnes@univ.bangor.ac.uk

 

Abstract

An exciting new technique is developed and validated for exploring cancer aetiology.  Over and above the combinations of aging and modern living ( diet, environment and lack of exercise) as  defined by the new so called ‘internet penetration algorithm’ , excess cases of cancer in Europe and Australia are shown to be quite strongly due to indoor gamma radiation  and excess cases the world over are shown to be due to alcohol and lack of sunlight.  Possibly up to 36% of world cancers could be avoided if people simply had adequate vitamin D status.  In the author’ s opinion it is high time the media hype on dangers of sun exposure were played down or ended.

    

 

Introduction

 

I have recently established that percentage Internet Penetration per Capita is a highly accurate predictor of World cancer incidence, R circa .9. The value of this regression factor increases further and quite dramatically if nations which don’t consume alcohol are removed from the sample up to a limiting value of about .96.

 

I have proposed elsewhere that this perhaps surprisingly high regression value is due to the fact that internet penetration is an excellent pointer of both a nation’s wealth and hence a tendency to have an aging population    prone to cancer for numerous reasons including but not exclusively; poor melatonin and vitamin D status due to mainly working indoors and in radio frequency fields and artificial light, poor diet including processed food nitrosamines, trans fats etc.  and being exposed to emissions form furnishings such as formaldehyde and  phthalates and being generally physically inactive.      

 

An ideal facet of the regression is that it enables one to generate an expected value of cancer incidence for a given population with a given internet penetration per capita   Hence to calculate excess cases (positive or negative) over and above this value.

 

Experimental and Data Sets

In this present study the linear regressed data set of the previous world study (ref)  was used to generate a master algorithm for cancer incidence on the basis of internet penetration per capita. The function is

 

I= 37.6 + 2.27* P     

 

Where I = Incidence per 100,000 and P= percentage penetration

 

The number of excess cases (X) are than give simply by the actual number of cases per hundred thousand observed (O) minus the calculated incidence (I). 

X= O-I

 

 

Unfortunately, accurate data on natural radiation sources is only known for certain countries in the world other than those due to very radioactive hotspots.  The best data set available seemed to be that detailing just Europe and Australia.  Thus the Cancer/Radiation aetiology study can only be limited to these countries.   The average annual radiation doses are shown below in Figure 1.

 

Figure 1

 

 

The total data set is reprinted from XL below

Penetration

O

Country

I

X

Radon

Total Gamma

Indoor G

94

256

FINLAND

250.98

5.02

0.65

0.4

86

324

FRANCE 

232.82

91.18

0.7

0.5

57

163

GREECE

166.99

-3.99

0.65

0.33

81

307

IRELAND

221.47

85.53

0.5

0.5

60

278

ITALY

173.8

104.2

1.1

0.7

96

318

NORWAY

255.52

62.48

0.67

0.46

74

249

SPAIN

205.58

43.42

0.55

0.47

88

287

SWITZ

237.36

49.64

0.65

0.4

89

273

UK

239.63

33.37

0.45

0.38

89

323

AUS

239.63

83.37

1.4

0.4

 

 

 The number of excess cases X  for all the countries on the list was then separately regressed against relative Radon concentration, total Indoor and  Outdoor Gamma Ray availability and the Total Indoor Gamma Ray availability.

 

Results and Discussion

 

Indoor Gamma, figure 2,  showed the best correlation with a regression factor R= circa .75. 

 

 

 

      

Figure 2

 

 

 

 

For the summation of total Gamma availability, figure 3,  the Regression factor was somewhat less at  R=.47.

 

 

 

Figure 3

 

For radon concentration, figure 4,  the data  was anti-correlated which is perhaps initially somewhat surprising but will be explained below. 

Figure 4

 

 

Discussion

Taking agriculture and the construction industry as the main sources of outdoor work only 11% of European individuals work outdoors.  There is no significant correlation between Gamma radiation indoors and Gamma radiation outdoors in figure 1.  Furthermore because on average more individuals work indoors and all individuals other than shift workers are indoors during the overnight period, therefore on the basis that Gamma radiation causes DNA damage and mutations more of this should be seen indoors.  This is borne out in the observed highest Regression factor, figure 2. 

 

The R^2 value for gamma indoors implies that 56% of  excess European and Australian cancers over and above those predicted by the Internet Penetration algorithm are due to Indoor Gamma radiation.             

 

Excess cancers are negatively correlated against Radon concentration. Radon is essentially an Alpha and to some extent Beta  Emitter.

 

Here's the process:

 

Radon has mainly been associated with Lung cancers but I have recently also shown a strong correlation with malignant melanoma.   Alpha particles must be inhaled to initiate lung cancer but Beta particles being stopped by the dermis could be implicated in Melanoma     However, both lung and melanoma cancers only form a minority percentage of the total of all cancers considered in the original algorithm and both are strongly   correlated with other factors.    

 

Other aetiologies                                      

 

1.      Alcohol

Figure 5 :  Effect of alcohol R= .54

 

2.      Solar UV index

 

Figure 6  Effect of sunshine R=-.61

 

Discussion of other aetiologies

1.      Alcohol

 

The R^2 for figure 5 suggests that globally some 29% of cancer incidence could be alcohol related.  One reference ………quotes that up to 21% of cancer deaths worldwide could potentially be related to alcohol.   These figures are quite comparable, hence tending to support/justify the new technique  developed here.

 

 

2.      Solar U/V

 

The result based on R^2 figure 6 suggests that up to 36% of cancers worldwide could be avoided by exposure to a high solar UV index.  A high UV index is synonymous with people having a good vitamin D status.   Also if they get more sun in the morning they are likely to have a good serotonin and 5-MTT status, hence good melatonin status at night.       

 

Nair and Masseh (2012) have suggested that up to 50% of people worldwide could have vitamin D insufficiency and over 1 billion ( about   14%) could have severe deficiency.  Only 51% of children play outside at least once a day ( ref)  and thus vitamin D shortage probably commences at an early age.  This is being accentuated by the almost hysterical media hype that sunshine is supposed to be so destructive for everybody and the main culprit in malignant melanoma.  I have previously shown an association between melanoma and Radon and an association between melanoma and a lack of sunshine in spring and autumn.  Further Hallberg and Johansson have showed a strong association between melanoma and radio broadcasting technologies    http://avaate.org/IMG/pdf/melanoma_fm.pdf

 

I have stressed the importance of vitamin D as an anti-cancer agent elsewhere.  Once again this newly developed technique  and its hypotheses  would appear to be supported/justified.

 

 

Conclusions

Using an Internet Penetration Algorithm developed in one of my earlier publications and multiple sequential linear regressions I have established excess European and Australian cancer incidence in terms of a radiation aetiology and I have shown that only Gamma rays indoors are statistically significant in the case of all cancers. 56% of  excess European and Australian cancers over and above those predicted by the Internet Penetration algorithm are due to Indoor Gamma radiation.         

 

I have further employed the technique to examine the effect of alcohol on world cancers.  Potentially up to  29% of all cancers could be in some way alcohol related.   The figure is some 30% higher than that established elsewhere.   The usual arguments that alcohol impurities such as acetaldehyde are chemical carcinogens probably apply  together with the fact that alcohol dissolves the carcinogens in tobacco smoke   and forms, for them, a more efficient vector into the body.    My guess is the additional figure may be wrapped firstly in the fact that alcohol reduces vitamin adsorption and secondly that it increases promiscuity adding particularly to the developing world burden of STI’s which are linked to cancers of the cervix.   

 

 

Finally,  I have established that up to   36% of cancers worldwide could be avoided by exposure to a high solar UV index.  A high UV index is tantamount with good vitamin D status.   Also if people get more sun in the morning they are likely to have a good serotonin and 5-MTT status, hence good melatonin status at night.    Both these circadian hormones in addition to vitamin D are powerful antioxidants and anti-cancer agents.    

 

 

 

References