Micro-environmental personal radio-frequency electromagnetic field exposures in Melbourne: A

Environmental Research · 2024 · Mixed · Insufficient evidence

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MixedInsufficient evidencePaper 152

Study snapshot

PublicationEnvironmental Research · 2024

Study typeexposure_assessment

Reported directionMixed

Evidence ratingInsufficient

Abstract

Micro-environmental personal radio-frequency electromagnetic field exposures in Melbourne: A longitudinal trend analysis Bhatt CR, Henderson S, Sanagou M, Brzozek C, Thielens A, Benke G, Loughran S. Micro-environmental personal radio-frequency electromagnetic field exposures in Melbourne: A longitudinal trend analysis. Environ Res. 2024 Mar 13;251(Pt 2):118629. doi: 10.1016/j.envres.2024.118629 Highlights • RF-EMF exposure may be affected by changes in telecommunication technologies. • Personal RF-EMF exposure assessments were undertaken in 2015/16 and 2022. • Quantile regression models were used to compare exposure levels and overall trend. • Median total exposure level at follow-up did not change over time. • Overall trend of total exposure at follow-up increased. Abstract Background A knowledge gap exists regarding longitudinal assessment of personal radio-frequency electromagnetic field (RF-EMF) exposures globally. It is unclear how the change in telecommunication technology over the years translates to change in RF-EMF exposure. This study aims to evaluate longitudinal trends of micro-environmental personal RF-EMF exposures in Australia. Methods The study utilised baseline (2015-16) and follow-up (2022) data on personal RF-EMF exposure (88 MHz-6 GHz) measured across 18 micro-environments in Melbourne. Simultaneous quantile regression analysis was conducted to compare exposure data distribution percentiles, particularly median (P50), upper extreme value (P99) and overall exposure trends. RF-EMF exposures were compared across six exposure source types: mobile downlink, mobile uplink, broadcast, 5G-New Radio, Others and Total (of the aforementioned sources). Frequency-specific exposures measured at baseline and follow-up were compared. Total exposure across different groups of micro-environment types were also compared. Results For all micro-environmental data, total (median and P99) exposure levels did not significantly change at follow-up. Overall exposure trend of total exposure increased at follow-up. Mobile downlink contributed the highest exposure among all sources showing an increase in median exposure and overall exposure trend. Of seven micro-environment types, five of them showed total exposure levels (median and P99) and overall exposure trend increased at follow-up. Open access paper: sciencedirect.com

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AI evidence extraction

Structured fields below were generated from the paper’s abstract and metadata to make the evidence easier to inspect. Automated extraction may be incomplete or incorrect; verify important details against the original paper.

Study typeexposure_assessment

Effect directionmixed

PopulationNot supplied

Sample sizeNot supplied

ExposureRF · baseline 2015-16 and follow-up 2022

Evidence strengthInsufficientConfidence: 74% · Peer reviewed: yes

Main findings

Across all micro-environmental data, total exposure levels at follow-up did not significantly change for the median (P50) or P99. The overall exposure trend of total exposure increased at follow-up. Mobile downlink was the highest contributing source and showed an increase in median exposure and overall exposure trend; five of seven micro-environment types showed increases in total exposure levels (median and P99) and overall exposure trend at follow-up.

Outcomes measured

Personal RF-EMF exposure levels (88 MHz–6 GHz) across 18 micro-environments
Exposure distribution percentiles (median/P50, P99)
Overall exposure trend over time
Source-specific exposures (mobile downlink, mobile uplink, broadcast, 5G-New Radio, others, total)
Micro-environment type comparisons (7 types mentioned)

View raw extracted JSON

{
  "study_type": "exposure_assessment",
  "exposure": {
    "band": "RF",
    "source": "personal exposure across micro-environments; sources analyzed include mobile downlink, mobile uplink, broadcast, 5G-New Radio, others",
    "frequency_mhz": null,
    "sar_wkg": null,
    "duration": "baseline 2015-16 and follow-up 2022"
  },
  "population": null,
  "sample_size": null,
  "outcomes": [
    "Personal RF-EMF exposure levels (88 MHz–6 GHz) across 18 micro-environments",
    "Exposure distribution percentiles (median/P50, P99)",
    "Overall exposure trend over time",
    "Source-specific exposures (mobile downlink, mobile uplink, broadcast, 5G-New Radio, others, total)",
    "Micro-environment type comparisons (7 types mentioned)"
  ],
  "main_findings": "Across all micro-environmental data, total exposure levels at follow-up did not significantly change for the median (P50) or P99. The overall exposure trend of total exposure increased at follow-up. Mobile downlink was the highest contributing source and showed an increase in median exposure and overall exposure trend; five of seven micro-environment types showed increases in total exposure levels (median and P99) and overall exposure trend at follow-up.",
  "effect_direction": "mixed",
  "limitations": [],
  "evidence_strength": "insufficient",
  "confidence": 0.74,
  "peer_reviewed_likely": "yes",
  "keywords": [
    "RF-EMF",
    "personal exposure",
    "micro-environments",
    "longitudinal trend",
    "Melbourne",
    "Australia",
    "quantile regression",
    "mobile downlink",
    "mobile uplink",
    "broadcast",
    "5G-New Radio",
    "88 MHz-6 GHz"
  ],
  "suggested_hubs": [
    {
      "slug": "5g-policy",
      "weight": 0.32,
      "reason": "Includes 5G-New Radio as an exposure source category in longitudinal personal exposure assessment."
    }
  ]
}

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AI-extracted fields are generated from the abstract and metadata and may be incomplete or incorrect. This material is for informational purposes and is not medical advice.

Identifiers and source

DOI: 10.1016/j.envres.2024.118629
PubMed: Not supplied

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