A randomized cross-over trial investigating differences in 24-h personal air and skin temperatures using wearable sensors between two climatologically contrasting settings

Abstract

The influence of elevated air temperatures recorded in various urban microenvironments in adversely impacting biologically relevant disease end points has not yet been extensively tackled. This study is a post hoc analysis of the TEMP pilot trial, a randomized 2 × 2 cross-over trial that examined changes in metabolic and stress hormonal profiles of healthy adults in two settings (urban vs. rural) with distinctly different climatological characteristics during the Mediterranean summer. This analysis aimed to study the association between the 24-h personal air or skin temperature sensor measurements and the diary-based location type (indoors vs. outdoors) in urban (seaside) vs. rural (higher in altitude) microenvironments. Out of 41 eligible participants, a total of 37 participants were included in this post-hoc TEMP trial analysis. Wearable sensors recorded personal air temperature, skin temperature, and activity (as a surrogate marker of physical activity) in each setting, while a time-stamped personal diary recorded the types of indoor or outdoor activities. Temperature peaks during the 24-h sampling period were detected using a peak finding algorithm. Mixed effect logistic regression models were fitted for the odds of participant location (being indoors vs. outdoors) as a function of setting (urban vs. rural) and sensor-based personal temperature data (either raw temperature values or number of temperature peaks). During the study period (July–end of September), median [interquartile range, IQR] personal air temperature in the rural (higher altitude) settings was 1.5 °C lower than that in the urban settings (27.1 °C [25.4, 29.2] vs. 28.6 °C [27.1, 30.5], p < 0.001), being consistent with the Mediterranean climate. Median [IQR] personal air temperature in indoor (micro)environments was lower than those in outdoors (28.0 °C [26.4, 30.3] vs 28.5 °C [26.8, 30.7], p < 0.001). However, median [IQR] skin temperature was higher in indoor (micro)environments vs. outdoors (34.8 °C [34.0, 35.6] and 33.9 °C [32.9, 34.8], p < 0.001) and the number of both personal air and skin temperature peaks was higher indoors compared to outdoors (median [IQR] 3.0 [2.0,4.0] vs 1.0 [1.0,1.3], p < 0.007, for the skin sensors). A significant association between the number of temperature peaks and indoor location types was observed with either the personal air sensor (OR 3.1; 95% CI 1.2–8.2; p = 0.02) or the skin sensor (OR 3.7; 95% CI 1.4–9.9; p = 0.01), suggesting higher number of indoor air temperature fluctuations. Amidst the global climate crisis, more population health studies or personalized medicine approaches that utilize continuous tracking of individual-level air/skin temperatures in both indoor/outdoor locations would be warranted, if we were to better characterize the disease phenotype in response to climate change manifestations.

Diurnal Nonlinear Recurrence Metrics of Skin Temperature and Their Association with Metabolic Hormones in Contrasting Climate Settings: A Randomized Cross-Over Trial

“…This was an additional analysis of the original TEMP trial [ 10 , 11 ] that used wearable sensors to measure diurnal (24-h long, one-minute intervals) skin temperature temporal profiles of healthy, non-obese individuals crossing from one setting to another (urban to mountainous and vice versa) after a 7-day long stay in each setting during the Mediterranean summer. A notable difference of about 8–10 °C in daily max air temperature between the urban and mountainous settings during the study period was observed using governmental station measurement data.…”

“…The growing availability and lower cost of wearable sensors allows for improving exposure measurement errors by providing individual-level measurements that are closer to the true personal exposure value. The choice of wearable sensors finds increasing use in environmental epidemiology studies, especially in those applying the human exposome framework and its exposomic tools, utilizing sensor data for multiple exposure stressors [ 10 , 11 , 12 ].…”

“…The deployment of such wearable sensors allows for capturing the exposure variance in 24-h skin temperature measurements as a result of human mobility and activity across different indoor and outdoor (micro)environments [ 10 ]. A diurnally varying temperature profiling was observed indoors for the majority of participants with a higher number of temperature peaks recorded indoors than outdoors [ 10 ]. Skin temperature is known to respond quite quickly to changes in ambient temperatures (within seconds) [ 13 ].…”

“…The need for a deeper analysis of the daily patterns of skin temperature fluctuations emerged from the findings of the main analysis of the TEMP trial [ 10 , 11 ]. The main TEMP analysis showed alterations in metabolic hormones (e.g., leptin) associated with a short-term stay (5–7 days) in climatologically cooler areas than those observed in geographically adjacent urban settings (~1-h driving distance) during a typical Mediterranean summer [ 10 , 11 ]. Towards this, an additional analysis of the pilot TEMP study dataset was set up, using the finely resolved time series data that were available, based on the wearable sensor-based skin temperature measurements.…”

A review on the application of the exposome paradigm to unveil the environmental determinants of age-related diseases

“…An increasing number of personal sensors are being developed to monitor heart rate, blood sugar concentrations, blood pressure, muscle activity, temperature, and sweat production [98]. Remarkable advances in novel algorithms in wearable technologies are allowing for accurate acquisition of personal temperature exposures, chemical and biological exposures, and clinical laboratory measurements to explore individual-level 24-h exposures in various microenvironments in exposome studies [99][100][101][102]. Koelmel et al captured the changes in gas-and particulate-phase airborne chemicals to which individuals were exposed and determined which exposures posed the greatest risk to health.…”