Chronic Intermittent Hypoxia and Blood Pressure: Is There Risk for Hypertension in Healthy Individuals?

High Alt Med Biol. 2016 Mar;17(1):5-10. doi: 10.1089/ham.2015.0067. Epub 2015 Nov 5.

Abstract

Aim: The aim of the current study was to assess a year-long impact of chronic intermittent exposure to hypoxia on blood pressure (BP) in healthy working middle-aged adults.

Materials and methods: Data from pre-employment and annual screening of high-altitude mining company (elevation 4000 meters above sea level) were obtained for 472 workers aged 34.1 ± 7.8 years, working 2-week shifts, followed by 2 weeks of rest at low altitude (cumulative exposure 6 months). Overall systolic, diastolic BP change (ΔBP) were calculated, and tested in multivariate regression models in the entire group, as well as in different strata of BP.

Results: Baseline systolic BP reduced from 123.2 ± 11.3 to 116.3 ± 13.1 mmHg (ΔBP 6.8 mmHg), diastolic BP from 76.7 ± 8.4 to 74.9 ± 8.4 mmHg (ΔBP -1.7 mmHg) (p < 0.001), both measured at low altitude before and after one year of exposure to chronic intermittent hypoxia. The greater the baseline BP, the more pronounced was BP decrease. In the most prevalent combined group of normal and high normal BP, both systolic and diastolic BP reduced after one year of high altitude exposure (p < 0.01). In multivariate adjusted models, none of exposures of interest were associated with ΔBP.

Conclusions: One-year intermittent exposure to hypobaric hypoxia in new hires for high-altitude mining company was not associated with BP increase.

Keywords: blood pressure; hypoxia; intermittent hypoxia; occupational; screening.

MeSH terms

  • Adult
  • Altitude
  • Altitude Sickness / complications*
  • Altitude Sickness / physiopathology
  • Blood Pressure / physiology
  • Female
  • Healthy Volunteers
  • Humans
  • Hypertension / etiology*
  • Male
  • Mass Screening / statistics & numerical data
  • Mining*
  • Multivariate Analysis
  • Occupational Diseases / etiology*
  • Occupational Exposure / adverse effects*
  • Occupational Health / statistics & numerical data
  • Regression Analysis
  • Risk Factors