Literature DB >> 27248007

Erratum: "Associations of Fine Particulate Matter Species with Mortality in the United States: A Multicity Time-Series Analysis".

Lingzhen Dai, Antonella Zanobetti, Petros Koutrakis, Joel D Schwartz.   

Abstract

Entities:  

Year:  2016        PMID: 27248007      PMCID: PMC4892900          DOI: 10.1289/EHP301

Source DB:  PubMed          Journal:  Environ Health Perspect        ISSN: 0091-6765            Impact factor:   9.031


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Environ Health Perspect 122(8):837–842 (2014), http://dx.doi.org/10.1289/ehp.1307568 In Table S1, the authors incorrectly inverted the titles of the column headers for temperature and PM2.5. In the original supplemental materials, the last two column headings were titled Temperature (°C) and PM2.5 (µg/m3), but should have been PM2.5 (µg/m3) and Temperature (°C), respectively. The authors also noticed the following misspelling: Saint Diego, CA, should be spelled San Diego, CA. These corrections to Table S1 appear in this erratum. These typographical errors do not affect the information presented in the article. The authors regret the errors. City specific summary (mean ± SD) of all-cause mortality, PM2.5, and temperature, 2000–2006.
Table S1

City specific summary (mean ± SD) of all-cause mortality, PM2.5, and temperature, 2000–2006.

#CityAll-cause mortality per 100,000 in population (No.)PM2.5 (µg/m3)Temperature (°C)
1Akron, OH2.6 ± 0.715.8 ± 8.410.0 ± 10.1
2Atlanta, GA1.6 ± 0.316.5 ± 7.417.0 ± 8.0
3Bakersfield, CA1.9 ± 0.616.6 ± 14.018.7 ± 7.7
4Bath, NY2.0 ± 1.19.4 ± 6.78.9 ± 10.2
5Birmingham, AL2.9 ± 0.715.8 ± 8.117.4 ± 8.4
6Boston, MA2.3 ± 0.411.9 ± 6.710.9 ± 9.5
7Baton Rouge, LA2.0 ± 0.713.2 ± 6.020.1 ± 7.4
8Cedar Rapids, IA3.0 ± 1.511.0 ± 7.29.4 ± 11.4
9Charlotte, NC1.7 ± 0.514.9 ± 6.815.7 ± 8.3
10Charleston, SC5.7 ± 2.212.0 ± 5.718.9 ± 7.6
11Chicago, IL2.5 ± 0.315.2 ± 8.210.3 ± 10.6
12Cincinnati, OH2.5 ± 0.616.8 ± 8.212.4 ± 9.7
13Cleveland, OH2.7 ± 0.415.2 ± 8.810.5 ± 10.0
14Columbus, OH2.0 ± 0.516.1 ± 8.311.8 ± 10.1
15Corpus Christ, TX2.0 ± 0.810.2 ± 4.123.4 ± 5.8
16Dallas, TX1.6 ± 0.312.5 ± 5.819.4 ± 8.8
17Davenport, IA4.3 ± 1.612.2 ± 7.111.1 ± 11.1
18Dayton, OH2.5 ± 0.716.2 ± 8.311.2 ± 10.3
19Des Moines, IA1.9 ± 0.710.3 ± 6.410.9 ± 11.4
20Detroit, MI2.2 ± 0.315.4 ± 9.110.4 ± 10.4
21Dodge, WI2.8 ± 1.610.9 ± 7.68.2 ± 11.6
22Elizabeth, NJ2.2 ± 0.714.4 ± 8.613.1 ± 9.7
23El Paso, TX1.5 ± 0.510.0 ± 5.118.5 ± 8.8
24Erie, PA2.5 ± 1.012.8 ± 8.110.1 ± 9.9
25Essex, NY0.3 ± 0.26.2 ± 5.56.0 ± 11.0
26Fresno, CA1.8 ± 0.519.0 ± 15.318.3 ± 7.7
27Fort Lauderdale, FL2.4 ± 0.48.4 ± 4.022.8 ± 4.9
28Gettysburg, PA2.5 ± 1.313.2 ± 8.311.5 ± 9.7
29Grand Rapids, MI1.1 ± 0.313.6 ± 8.79.1 ± 10.5
30Greenville, SC2.5 ± 1.315.0 ± 6.916.2 ± 8.1
31Harrisburg, PA2.5 ± 1.015.4 ± 9.312.1 ± 9.8
32Houston, TX1.5 ± 0.212.8 ± 5.521.1 ± 7.3
33Indianapolis, IN2.2 ± 0.516.2 ± 8.212.0 ± 10.3
34Kansas City, KS2.5 ± 0.511.9 ± 6.013.2 ± 10.7
35Knoxville, TN3.1 ± 0.915.3 ± 7.115.3 ± 8.7
36Los Angeles, CA1.6 ± 0.217.8 ± 10.317.2 ± 3.4
37Louisville, KY2.5 ± 0.715.6 ± 7.914.6 ± 9.7
38Little Rock, AR2.3 ± 0.813.9 ± 6.717.2 ± 9.1
39Memphis, TN2.1 ± 0.513.2 ± 6.617.5 ± 9.0
40Miami, FL2.1 ± 0.39.1 ± 4.325.0 ± 3.7
41Middletown, OH2.1 ± 0.816.0 ± 8.19.8 ± 10.4
42Milwaukee, WI3.1 ± 0.613.4 ± 8.19.2 ± 10.5
43Minneapolis, MN1.9 ± 0.411.6 ± 7.38.4 ± 12.2
44Nashville, TN2.2 ± 0.613.9 ± 6.715.7 ± 9.0
45New Haven, CT3.8 ± 0.913.4 ± 8.110.4 ± 10.1
46New York City, NY1.8 ± 0.214.5 ± 8.413.4 ± 9.6
47Oklahoma City, OK2.4 ± 0.79.9 ± 5.217.2 ± 9.4
48Omaha, NE2.0 ± 0.710.3 ± 6.011.2 ± 11.5
49Port Arthur, TX11.3 ± 4.511.1 ± 5.520.8 ± 7.1
50Philadelphia, PA7.4 ± 1.914.1 ± 8.213.5 ± 9.6
51Phoenix, AZ1.8 ± 0.311.2 ± 7.124.1 ± 8.9
52Pittsburgh, PA3.0 ± 0.615.6 ± 10.110.9 ± 9.8
53Portland, OR4.2 ± 0.98.8 ± 6.012.2 ± 6.2
54Providence, RI5.1 ± 1.110.9 ± 6.511.0 ± 9.5
55Provo, UT3.7 ± 1.89.5 ± 8.712.0 ± 10.5
56Raleigh, NC1.4 ± 0.514.1 ± 6.615.8 ± 8.7
57Riverside, CA4.1 ± 0.717.4 ± 11.419.1 ± 5.8
58Sacramento, CA2.0 ± 0.412.3 ± 10.316.3 ± 6.4
59Salt Lake City, UT1.4 ± 0.411.3 ± 10.911.9 ± 10.5
60State College, PA1.8 ± 1.012.9 ± 8.410.4 ± 9.8
61Scranton, PA8.7 ± 2.212.0 ± 7.910.0 ± 10.0
62San Diego, CA1.8 ± 0.312.6 ± 7.317.6 ± 3.3
63Seattle, WA1.7 ± 0.39.4 ± 5.811.4 ± 5.6
64San Jose, CA1.3 ± 0.313.2 ± 11.016.4 ± 4.7
65Springfield, MA2.7 ± 0.812.3 ± 7.610.2 ± 10.1
66Saint Louis, MO2.4 ± 0.514.0 ± 7.214.2 ± 10.4
67Tampa, FL2.2 ± 0.511.3 ± 5.123.0 ± 5.4
68Toledo, OH2.5 ± 0.814.9 ± 8.410.5 ± 10.4
69Tucson, AZ2.3 ± 0.66.1 ± 2.421.2 ± 7.8
70Tulsa, OK2.4 ± 0.711.3 ± 6.017.1 ± 9.7
71Washington, PA3.1 ± 1.314.6 ± 7.911.7 ± 9.7
72Washington DC1.9 ± 0.514.9 ± 8.214.5 ± 9.3
73Wilmington, DE2.0 ± 0.714.9 ± 8.312.6 ± 9.5
74Winston, NC2.3 ± 0.914.5 ± 7.415.2 ± 8.6
75Youngstown, OH2.9 ± 0.915.1 ± 8.09.6 ± 9.9
  1 in total

1.  The occurrence of COVID-19 is associated with air quality and relative humidity.

Authors:  Ling Tong; Lu Ji; Dan Li; Huihui Xu
Journal:  J Med Virol       Date:  2021-10-21       Impact factor: 20.693

  1 in total

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