Research ArticleCLIMATE CHANGE

Nighttime temperature and human sleep loss in a changing climate

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Science Advances  26 May 2017:
Vol. 3, no. 5, e1601555
DOI: 10.1126/sciadv.1601555
  • Fig. 1 Nights of insufficient sleep increase with nighttime temperature anomalies.

    (A) Relationship between average monthly nighttime temperature anomalies and 765,000 respondents’ reported number of monthly nights with insufficient sleep from 2002 to 2011. As temperature anomalies become more positive, nights with insufficient sleep become more frequent. Points represent the average of respondents’ monthly number of nights with insufficient sleep for each 0.5°C nighttime temperature anomaly bin. The line represents a smoothing of the raw data using a cubic spline fit. Shaded error bounds represent the 95% confidence interval of this fit. (B) Distribution of 2002–2011 average monthly nighttime temperature anomalies from the daily nighttime temperature normals of 1981–2010.

  • Fig. 2 The effect of nighttime temperature anomalies is most acute during the summer and among lower-income respondents and the elderly.

    (A) Marginal effects from our main model specification run on samples stratified by season (rescaled to an effect per 100 individuals). The effects observed in the summertime sample are over double the magnitude of those observed in other seasons. (B) Marginal effects associated with splitting the sample by median income. Those with under $50,000 per year have notably higher responses to nighttime temperature anomalies. (C) Sample by age, showing that the effects of nighttime temperature anomalies on sleep are larger in the elderly. Marginal effects significantly different from zero at the α = 0.05 level are presented in red. Error bars are SEM (see regression tables in the Supplementary Materials).

  • Fig. 3 Climate change may amplify human sleep loss.

    (A) Distributions of nighttime temperature anomalies calculated from 21 downscaled climate models for the cities in our sample in 2010, 2050, and 2099. Nighttime temperature anomalies from the 1981–2010 city nighttime temperature normals increase in both magnitude and variation by 2050 and 2099 as compared to 2010. (B) City-level forecasts for the impact of climate change on monthly nights of insufficient sleep per 100 individuals. To incorporate downscaled climate model uncertainty, we calculate an estimated change for an ensemble of 21 climatic models for 219 cities, producing nearly 4600 estimates for both 2050 and 2099. The change between 2010 and 2050 is represented by golden lines, whereas the predicted change between 2050 and 2099 is represented by red lines. The black dashed lines plot the median predicted change between each period. (C) Mean predicted change in sleep for each period across all climate models (rescaled to an effect per 100 individuals). Error bars are SEM and incorporate downscaled climate model uncertainty.

  • Fig. 4 Geographic dispersion of the predicted effects of climate change–induced nighttime warming on human sleep.

    This figure presents the 25-km × 25-km grid cell forecasts of the potential impact of nighttime warming on monthly nights of insufficient sleep per 100 individuals. Downscaled climatic model data are averaged across the 21 models in the ensemble and then coupled with our historical model parameter β to produce an estimated change in insufficient sleep in each geographic location for the periods of 2050 and 2099. Areas of the western and northern United States—where nighttime temperatures are projected to increase most acutely—may experience the largest future changes in sleep.

Supplementary Materials

  • Supplementary material for this article is available at http://advances.sciencemag.org/cgi/content/full/3/5/e1601555/DC1

    table S1. Monthly nighttime temperature anomalies and monthly nights of insufficient sleep.

    table S2. Varying time and location controls.

    table S3. Regressions by season.

    table S4. Regressions by income level.

    table S5. Regressions by age.

    table S6. Average nighttime temperature regressions.

    table S7. Demographic controls.

    table S8. Negative binomial regressions.

    table S9. Monthly nighttime temperature anomalies and any nights of insufficient sleep (0/1).

    table S10. Monthly nighttime temperature anomalies (PRISM) and monthly nights of insufficient sleep.

    fig. S1. Permutation test.

    fig. S2. Cities and stations.

  • Supplementary Materials

    This PDF file includes:

    • table S1. Monthly nighttime temperature anomalies and monthly nights of insufficient sleep.
    • table S2. Varying time and location controls.
    • table S3. Regressions by season.
    • table S4. Regressions by income level.
    • table S5. Regressions by age.
    • table S6. Average nighttime temperature regressions.
    • table S7. Demographic controls.
    • table S8. Negative binomial regressions.
    • table S9. Monthly nighttime temperature anomalies and any nights of insufficient sleep (0/1).
    • table S10. Monthly nighttime temperature anomalies (PRISM) and monthly nights of insufficient sleep.
    • fig. S1. Permutation test.
    • fig. S2. Cities and stations.

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