Department of Environmental Health, Harvard T.H. Chan School of Public Health, 401 Park Drive, Boston, MA, 02215, USA.
Department of Biostatistics, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, 02115, USA.
J Expo Sci Environ Epidemiol. 2023 May;33(3):455-464. doi: 10.1038/s41370-023-00521-5. Epub 2023 Feb 1.
Knowing the geographical and temporal variation in radon concentrations is essential for assessing residential exposure to radon, the leading cause of lung cancer in never-smokers in the United States. Tens of millions of short-term radon measurements, which normally last 2 to 4 days, have been conducted during the past decades. However, these massive short-term measurements have not been commonly used in exposure assessment because of the conflicting evidence regarding their correlation with long-term measurements, the gold standard of assessing long-term radon exposure.
We aim to evaluate the extent to which a long-term radon measurement can be predicted by a collocated short-term radon measurement under different conditions.
We compiled a national dataset of 2245 pairs of collocated short- and long-term measurements, analyzed the predictability of long-term measurements with stratified linear regression and bootstrapping resampling.
We found that the extent to which a long-term measurement can be predicted by the collocated short-term measurement was a joint function of two factors: the temporal difference in starting dates between two measurements and the length of the long-term measurement. Short-term measurements, jointly with other factors, could explain up to 79% (0.95 Confidence Interval [CI]: 0.73-0.84) of the variance in seasonal radon concentrations and could explain up to 67% (0.95 CI: 0.52-0.81) of the variance in annual radon concentrations. The large proportions of variance explained suggest that short-term measurement can be used as convenient proxy for seasonal radon concentrations. Accurate annual radon estimation entails averaging multiple short-term measurements in different seasons.
Our findings will facilitate the usage of abundant short-term radon measurements, which have been obtained but was previously underutilized in assessing residential radon exposure.
Tens of millions of short-term radon measurements have been conducted but underutilized in assessing residential exposure to radon, the greatest cause of lung cancer in non-smokers. We investigate the correlations between collocated short- and long-term measurements in 2245 U.S. buildings and find that short-term measurements can explain ~75% of the variance in subsequent long-term measurements in the same buildings. Our results can facilitate the usage of massive short-term radon measurements that have been conducted to estimate the spatial and longitudinal distribution of radon concentrations, which can be used in epidemiological studies to quantify the health effects of radon.
了解氡浓度的地域和时间变化对于评估美国从不吸烟者中肺癌主要病因的氡暴露至关重要。在过去几十年中，已经进行了数千万次短期氡测量，通常持续 2 到 4 天。然而，由于这些短期测量与长期测量（评估长期氡暴露的金标准）的相关性存在相互矛盾的证据，因此这些大规模的短期测量并未被广泛用于暴露评估。
我们旨在评估在不同条件下，长期氡测量值通过短期氡测量值的预测程度。
我们汇编了一个包含 2245 对短期和长期短期测量值的全国性数据集，使用分层线性回归和引导重采样进行分析，以评估长期测量值的可预测性。
我们发现，长期测量值可以通过短期测量值的预测程度是两个因素的共同作用：两次测量的起始日期之间的时间差异和长期测量的长度。短期测量值与其他因素一起，可解释季节氡浓度变化的 79%（95%置信区间[CI]：0.73-0.84），可解释年氡浓度变化的 67%（95%CI：0.52-0.81）。如此高的可解释方差比例表明，短期测量值可以作为季节氡浓度的便捷代理。准确估计年氡浓度需要在不同季节平均多个短期测量值。
我们的研究结果将促进大量短期氡测量值的使用，这些测量值已经获得，但以前在评估住宅氡暴露方面利用不足。
已经进行了数千万次短期氡测量，但在评估氡暴露方面利用不足，而氡是不吸烟者患肺癌的最大原因。我们调查了美国 2245 座建筑物中短期和长期短期测量值之间的相关性，发现短期测量值可以解释同一建筑物中后续长期测量值的 75%左右的方差。我们的结果可以促进对已经进行的大量短期氡测量值的使用，这些测量值可以用来估计氡浓度的空间和纵向分布，这可以在流行病学研究中用于量化氡的健康影响。
