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Environmental Pollution: Statistical Approach on Mobile Tower Radiation.

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Mobile phone radiation (Electromagnetic Field - EMF) may cause oxidative stress and neurodegenerative disorders. Generalized Linear Models effectively analyze mobile tower radiation data, highlighting the need for further research into EMF health effects.

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Area of Science:

  • Environmental Health
  • Neuroscience
  • Biophysics

Background:

  • The widespread use of mobile phones raises concerns about Electromagnetic Field (EMF) exposure and its potential health impacts.
  • EMF exposure from mobile phones and telecom towers is linked to oxidative stress, potentially leading to brain degeneration.
  • Government initiatives aim to bridge the information gap regarding EMF emissions and their scientific evidence.

Purpose of the Study:

  • To investigate the influence of EMF on oxidative stress.
  • To examine the relationship between EMF exposure and neurodegenerative disorders.

Main Methods:

  • An analytical study utilizing a supervised machine learning approach, specifically Generalized Linear Models (GLM).
  • Data was sourced from open-access information in two Indian states.
  • Statistical analysis focused on understanding mobile tower radiation patterns.

Main Results:

  • Confidence Intervals (CI) for measured radiation values were calculated for Andhra Pradesh and Telangana across 2018-2019 and 2019-2020.
  • Andhra Pradesh: 95% CI [0.0045 to 0.0111] (2018-19) and 95% CI [0.0016 to 0.0028] (2019-20).
  • Telangana: 95% CI [0.0500 to 0.0763] (2018-19) and 95% CI [0.0189 to 0.4345] (2019-20).

Conclusions:

  • Generalized Linear Models (GLM) are identified as the optimal statistical tool for analyzing mobile tower radiation.
  • The study underscores the importance of statistical modeling in assessing EMF exposure risks.