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Table 1 Basic characteristics of studies included in the meta-analysis

From: Lung cancer mortality of residents living near petrochemical industrial complexes: a meta-analysis

ID

Comparison

Study period

The started operation year of PICs

Adjusted confounders

Country

Definition of petroleum area and reference area

Study group

(Number of subject)

Outcome selection

Industrial activity/

Substantial chemicals

Study design

Reference

A

Asian males,

exposure group vs. reference group

1982–1991

1968

(First–fourth naphtha cracking plants)b

Age

Taiwan

(32 counties)

Petroleum area: 16 counties with 2% or more of the population employed in petrochemical industrial complexes (PICs)

Reference area: 16 matched counties with less than 2% of the population employed in PICs

Exposure group:

Residents in 16 petroleum counties (N = 977,853)

Reference group:

Residents in 16 reference counties (N = 870,758)

Death registered in Bureau of Vital Statistics of the Taiwan Provincial Department of Health;

ICD-9 code = 162

Petrochemical manufacturing/

Vinyl chloride monomer, polycyclic aromatic hydrocarbons (PAH)

Cohort study

[18]

B

Asian females,

exposure group vs. reference group

1982–1991

1968

(First–fourth naphtha cracking plants)b

Age

Taiwan

(32 counties)

C

White males, Industrial Corridor vs. Louisiana

1990–1999

< 1970

Age

United States (Louisiana)

Petroleum area:

Industrial Corridor: the industrial area of the lower Mississippi River of South Louisiana (the highest density of petrochemical facilities in the United States)

Reference area:

Louisiana

Exposure group:

White male residents in Industrial Corridor (N = 186,727)a

Reference group:

White male residents in Louisiana (N = 1,385,055)a

Death data from the University of Pittsburgh’s Mortality and Population Data System;

ICD-9 code = 162

Producers of industrial and agricultural organic chemicals, plastics, synthetics, industrial inorganic chemicals/

Ammonia, methanol, phosphoric acid, nitrate compounds, formaldehyde, and PAH

Cohort study

[19]

D

White females, Industrial Corridor vs. Louisiana

1990–1999

< 1970

Age

United States (Louisiana)

Exposure group:

White female residents in Industrial Corridor (N = 194,376)a

Reference group:

White female residents in Louisiana (N = 1,454,083)a

E

Non-white males,

Industrial Corridor vs. Louisiana

1990–1999

< 1970

Age

United States (Louisiana)

Exposure group:

Non-white male residents in Industrial Corridor (N = 98,917)a

Reference group:

Non-white male residents in Louisiana (N = 646,311)a

F

Non-white females,

Industrial Corridor vs. Louisiana

1990–1999

< 1970

Age

United States (Louisiana)

Exposure group:

Non-white female residents in Industrial Corridor (N = 112,079)a

Reference group:

Non-white female residents in Louisiana (N = 734,504)a

G

White males,

Residents vs. Commuters

1960–2002

1960

(Gela plant)c

Age, calendar period, residence category or job category, and time since first employment

Italy (Sicily)

Petroleum area:

A large petrochemical plant built in the vicinity of the town of Gela, Sicily in 1960

Males workers employed in the Gela petrochemical plant in 1960–1993

Exposure group:

Residents: workers born in Gela (N = 1684) and in Sicilian municipalities with a probability of commuting defined by the gravity model as < 0.5 g (N = 709)

Reference group:

Commuters: workers born in Sicilian municipalities, excluding Gela with a probability of commuting

defined by the gravity model as > = 0.5 g (N = 3234)

Data from municipalities’ registry office;

ICD-9 code = 162

Oil refinery, thermoelectric power plants, producers of organic and inorganic chemicals/

Ethylene, acrylonitrile, sulfuric acid, ammonia, chlorine urea

Cohort study

[21]

H

Whites (both genders),

exposure group vs. reference group

1996–1997

1961

(Brindisi petrochemical plant)d

Age, sex, smoking, and education

Italy

(Brindisi)

Petroleum area:

The petrochemical plant located in Brindisi

Exposure group:

Residents in Brindisi and three neighboring municipalities(Carovigno, Torchiarolo, San Pietro Vernotico) who died from lung cancer (N = 95)

Reference group:

Random sample of residents in the same area who died from any other disease (N = 170)

Death register in Local Health Authority of Brindisi;

ICD-9 code = 162

Petrochemical plant/

N.R.

Case- control study

[22]

I

White males,

Teesside (zone A,B,C) vs. Sunderland (zone S)

1981–1991

1965

(Teesside refinery)f

5-year age group

United Kingdom

(Teesside)

Petroleum area:

Teesside (one of western Europe’s largest steel and petrochemical complexes)

Exposure group:

Residents in 19 housing estates in Teesside (zones A,B,C) (N = 77,330)

Reference group:

Residents in 8 housing estates in Sunderland (zone S) (N = 43,485)

Death data from the former Northern Regional Health

Authority

Petrochemical complex, steel complex, coking, and chemical operations/

N.R.

Cohort study

[7]

J

White females,

Teesside (zone A,B,C) vs. Sunderland (zone S)

1981–1991

1965

(Teesside refinery)f

5-year age group

United Kingdom

(Teesside)

K

White males,

residents living within 10 km circle vs. in Rome

1987–1993

1965

(Rome refinery plant)e

5-year age group, four levels of socioeconomic index

Italy

(Rome)

Petroleum area:

Circle of 10 km radius around the petrochemical refinery which began operation in the early 1960s in the area of Malagrotta, a suburb of Rome

Exposure group:

Males living within a 10 km radius of the plants (N = 165,074)

Reference group: Males in 6108 census tracts in Rome (N = N.R.)

Data from the geographical information mortality system;

ICD-9 code = 162

Waste disposal, waste incinerators, petrochemical refinery/ Particulates, hydrogen chloride, chlorinated dibenzo-p-dioxins, dibenzofurans, PAH, chlorinated benzene, chlorinated phenols, and phthalates

Cohort study

[8]

L

White females,

residents living within 10 km circle vs. in Rome

1987–1993

1965

(Rome refinery plant)e

5-year age group, four levels of socioeconomic index

Italy

(Rome)

Exposure group:

Females living within a 10 km radius of the plants (N = 176,315)

Reference group: Females in 6108 census tracts in Rom (N = N.R.)

M

White (both genders)

within 3 km vs. England and Wales

1981–1991

1963

(Baglan Bay petrochemical plant)

Age, sex, index of deprivation, and region

United Kingdom

(West Glamorgan)

Petroleum area:

Circle of 3 km radius centered on the petrochemical plant

Exposure group:

Residents living within circle of 3 km radius centered on the petrochemical plant, and death before 74 years old (N = 26,206)

Reference group:

Residents in England and Wales, and death before 74 years old (N = N.R.)

Death data from the Small Area Health Statistics Unit and 1981 census;

ICD-9 code = 162

Baglan Bay Chemicals/ Alcohols, styrene, olefins, benzene, vinyl chloride and polyvinyl chloride

Cohort study

[23]

  1. N number of subject, N.R. not reported, ICD International Classification of Diseases
  2. aSource of data: 1990 Census of Population: General Population Characteristics, Louisiana. https://www2.census.gov/library/publications/decennial/1990/cp-1/cp-1-20.pdf (Accessed 10 Mar 2017)
  3. bSource of data: The industrial heritage in Taiwan (In Chinese), National Science and Technology Museum, Taiwan, http://iht.nstm.gov.tw/form/index-1.asp?m=2&m1=3&m2=76&gp=21&id=7 (Accessed 13 Apr 2017)
  4. cSource of data: Pasetto R, Comba P, Pirastu R. Lung cancer mortality in a cohort of workers in a petrochemical plant: occupational or residential risk? Int J Occup Environ Health. 2008;14(2):124–8
  5. dSource of data: Petrolchimico di Brindisi (1969–1972) (In Italian), Tatiana Schirinzi, http://www.nove.firenze.it/petrolchimico-brindisi/ (Accessed 14 Apr 2017)
  6. eSource of data: Rome Refinery, A Barrel Full, http://abarrelfull.wikidot.com/rome-refinery (Accessed 13 Apr 2017)
  7. f Source of data: Teesside Refinery, https://www.revolvy.com/main/index.php?s=Teesside%20Refinery (Accessed 19 Jul 2017)
  8. gSoure of data: Signorino G, Pasetto R, Gatto E, Mucciardi M, La Rocca M, Mudu P. Gravity models to classify commuting vs. resident workers. An application to the analysis of residential risk in a contaminated area. Int J Health Geogr 2011,10:11