provide an effect estimate adjusted for all Tier 1 confounders (i.e., not adjusted for age), nor the data to calculate such an adjusted estimate. Because this study did not report an unadjusted effect estimate either, we calculated the unadjusted RR from raw counts reported in the study record (see Appendix 7 in the supplementary data for details). The unadjusted RR was 1.77 (95 % CI 1.46–2.16) (Appendix 7 for forest plot).

We explored how each study impacted the pooled RR and I² heterogeneity indicator in a leave-one-out analysis (Table 7). Changes were generally small, however excluding 't Mannetje (2012) registered the largest increase in the pooled RR and the largest reduction in statistical heterogeneity (1.55, 95 % CI 1.35–1.77, I² 5 %). Leaving Lerchen et al. (1987) out resulted in the largest reduction in the pooled RR (1.44, 95 % CI 1.26–1.64, I² 18 %). The largest increase in statistical heterogeneity was observed when removing Corbin et al. (2011) (RR 1.48, 95 % CI 1.29–1.71, I² 28 %).

### 4.5.1.2. Cohort studies (supporting evidence).
Eight studies with over 1,171,445 participants (21,678 [1.9 %] females and at least 1,149,767 [98.1 %] males) from two WHO regions (Region of the Americas and European Region) reported estimates of the effect of any (or high) occupational exposure to welding fumes on acquiring trachea, bronchus, and lung cancer (incidence), compared with no (or low) occupational exposure to welding fumes. Six of these studies could be included in a quantitative meta-analysis. These studies were somewhat heterogeneous in terms of the definition of exposure (some studies considered occupation or job title of “welder” and some considered occupational exposure to welding fumes; see Table 4) and the comparator (some studies included people who had been exposed for less than a specified period of time as unexposed). All these studies examined lung cancer diagnosis only, except the Kromhout et al. (1992) study, which examined trachea, bronchus, and lung cancer diagnosis. However, we considered the studies sufficiently similar to warrant inclusion in the same meta-analysis. Compared with no (or low) occupational exposure to welding fumes, any (or high) occupational exposure to welding fumes increased the risk of acquiring trachea, bronchus, and lung cancer (RR 1.18, 95 % CI 1.08–1.29, 6 studies, ≥1,166,874 participants, I² 0 %; Fig. 6).

The findings from two cohort studies not included in this meta-analysis are presented in Table 8. Danielsen et al. (1993) and Danielsen et al. (2000) both reported an increased risk for participants with the work category of “welder”, but this was only statistically significant in those employed as a welder for > 5 years in Danielsen et al. (1993).

### 4.5.1.3. Synthesis across designs.
The prioritized body of evidence of case-control studies showed that, compared with no (or low) occupational exposure to welding fumes, any (or high) occupational exposure to welding fumes led to an estimated increase in trachea, bronchus, and lung cancer, providing an RR of 1.48 (95 % CI: 1.29–1.70). The evidence from the one case-control study and eight cohort studies excluded from the main meta-analysis are generally supportive of the findings from the main meta-analysis.

### 4.5.2. Died from trachea, bronchus, and lung cancer (mortality)

A total of eight studies (five case-control studies, three cohort studies) comprising 35,150 participants (at least 285 females [0.8 %] and 23,285 males [66.2 %]) reported estimates on the effect of any (or high) occupational exposure to welding fumes on the outcome of trachea, bronchus and/or lung cancer mortality, compared with no (or low) occupational exposure to welding fumes. Occupational exposure to welding fumes was generally assessed via administrative records or surveys (Table 4). We meta-analysed evidence from different study designs separately (as per our pre-published protocol; Pega et al. (2020a)). In our risk of bias assessment (see Section 4.4.2), we judged that case-control studies generally have a lower risk of confounding from tobacco smoking. Additionally, more of the case-control studies consider

exposure to asbestos for this outcome. Our main meta-analysis for this outcome is consequently that of the relevant case-control studies. We again also consider the evidence from the cohort studies as supporting evidence.

#### 4.5.2.1. Case-control studies (prioritised evidence).
Five studies comprising 14,825 participants (285 [1.9 %] females and 14,540 [98.1 %] males) from two WHO regions (Region of the Americas and European Region) reported estimates of the effect of any (or high) occupational exposure to welding fumes on dying of trachea, bronchus, and lung cancer (mortality), compared with no (or low) occupational exposure to welding fumes. Of these, three studies could be pooled in the same quantitative meta-analysis. The effect estimate from Yiin et al. (2007) was calculated using the Borenstein et al. (2009) method (see Appendix 8 in the Supplementary data for details of the calculation). We converted ORs to RR using the baseline risk in the unexposed population (i.e., 29.9 per 100,000 persons) reported for this outcome in the cohort studies included in this systematic review. As this was reported in two studies (Steenland et al. 1986; Steenland 2002), we selected the baseline risk from the more recent estimate and from the study with longer follow-up: Steenland (2002). The conversions are presented in Table 9. Compared with no (low) exposure to welding fumes, any (or high) occupational exposure welding fumes increased the risk of dying of trachea, bronchus, and lung cancer (RR 1.27, 95 % CI 1.04–1.56, 3 studies, 8,686 participants, I² 0 %; Fig. 7). We also used an alternative method to run the meta-analysis, in which we included ORs in the meta-analysis and then converted the pooled OR to a RR (Appendix 6 in the Supplementary data). This resulted in a pooled OR of 1.29 (95 % CI 1.03–1.61, I² 3 %) and a summary RR of 1.28 (95 % CI 1.02–1.60). We judged this to be comparable to pooled RR from the main meta-analysis.

The findings from the two cohort studies excluded from the meta-analysis are presented in Table 10. All three studies reported an increased OR following occupational exposure to welding fumes, but for Gottlieb (1980) this increase was limited to those who died at < 60 years of age. For those aged ≥ 60 years at death, Gottlieb (1980) reported lower odds of death in the exposed. The 95 % CI for both effect estimates

<caption>**Table 6**</caption>

Effect estimates (odds ratios converted to risk ratios) of the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer incidence reported in 23 case-control studies included in the main meta-analysis (median baseline risk: 0.025).

<table><thead><tr><th>Study ID</th><th>Odds ratio (95 % CI)<sup>a</sup></th><th>Converted risk ratio (95 % CI)</th></tr></thead><tbody><tr><td>Brenner, 2010</td><td>1.7 (1.0–3.0)</td><td>1.67 (0.96–2.89)</td></tr><tr><td>Brüske-Hohlfeld 2000</td><td>1.75 (1.14–2.61)</td><td>1.72 (1.14–2.60)</td></tr><tr><td>Buiatti 1985</td><td>2.8 (0.9–8.5)</td><td>2.68 (0.87–8.23)</td></tr><tr><td>Consonni 2010</td><td>0.94 (0.56–1.59)</td><td>0.94 (0.56–1.59)</td></tr><tr><td>Corbin 2011</td><td>1.43 (0.57–3.58)</td><td>1.41 (0.56–3.55)</td></tr><tr><td>Elci 2003</td><td>0.9 (0.5–1.7)</td><td>0.90 (0.49–1.66)</td></tr><tr><td>Fortes 2003</td><td>7.65 (0.59–99.8)</td><td>6.56 (0.5–85.31)</td></tr><tr><td>Guida 2011</td><td>1.66 (1.11–2.49)</td><td>1.63 (1.09–2.45)</td></tr><tr><td>Gustavsson 2000</td><td>1.52 (0.86–2.67)</td><td>1.50 (0.85–2.64)</td></tr><tr><td>Jockel 1998</td><td>1.87 (1.03–3.42)</td><td>1.83 (1.00–3.33)</td></tr><tr><td>Kazma 2012</td><td>0.37 (0.02–9.03)</td><td>0.38 (0.02–7.99)</td></tr><tr><td>Keller 1993</td><td>1.68 (1.03–2.76)</td><td>1.65 (1.01–2.70)</td></tr><tr><td>Lerchen 1987</td><td>3.2 (1.4–7.4)</td><td>3.03 (1.32–6.97)</td></tr><tr><td>López-Cima 2007</td><td>1.09 (0.66–1.80)</td><td>1.09 (0.66–1.80)</td></tr><tr><td>Morabia 1992</td><td>1.5 (0.8–2.7)</td><td>1.48 (0.81–2.72)</td></tr><tr><td>Pezzotto 1999</td><td>1.1 (0.4–3.1)</td><td>1.10 (0.39–3.05)</td></tr><tr><td>Richiardi 2004</td><td>1.77 (1.05–2.98)</td><td>1.74 (1.03–2.93)</td></tr><tr><td>Schoenberg 1987</td><td>2.5 (1.1–5.5)</td><td>2.41 (1.08–5.39)</td></tr><tr><td>Soskolne 2007</td><td>3.91 (1.03–14.95)</td><td>3.64 (0.96–13.89)</td></tr><tr><td>Stucker 2002</td><td>0.56 (0.18–1.7)</td><td>0.57 (0.18–1.74)</td></tr><tr><td>'t Mannetje 2012</td><td>1.18 (1.01–1.38)</td><td>1.17 (1.00–1.37)</td></tr><tr><td>Tse 2012</td><td>1.69 (1.11–2.58)</td><td>1.66 (1.09–2.53)</td></tr><tr><td>Vallières 2012</td><td>2.21 (1.10–4.41)</td><td>2.15 (1.07–4.30)</td></tr></tbody></table>

Footnote: <sup>a</sup> Presented to the decimal place reported in the study record or capped at two decimal places.
from Gottlieb (1980) were however wide. Overall, these studies provide some support for the findings from the meta-analysis.

We explored how each study impacted the pooled RR and heterogeneity indicator (I²) in a leave-one-out analysis (Table 11). Removing either Finkelstein (1995) or Yiin et al. (2007) resulted in a pooled RR of 1.48, whereas removing Ronco et al. (1988) resulted in a pooled RR of 1.25. Removing Ronco et al. (1988) lead to the same statistical heterogeneity (I² 0 %), whereas removing Yiin et al. (2007) and Finkelstein (1995) increased the statistical heterogeneity to I² 47 % and 35 %, respectively.

### 4.5.2.2. Cohort studies (supporting evidence).
Three studies with 20,325 participants from two WHO regions (Region of the Americas and European Region) reported estimates of the effect of occupational exposure to welding fumes on dying of trachea, bronchus, and lung cancer, compared with no (or low) occupational exposure to welding fumes. In terms of study participants' sex, the studies comprised ≥ 8,745 [45.0 %] males; one study had no female participants, and in the other two studies the numbers of female and male participants were unclear. Steenland et al. (1986) reported an effect estimate with a p value, but no 95 % CI. Details of the back-calculation of the uncertainty measure can be found in Appendix 9 in the Supplementary data. All three studies could be included in the same quantitative meta-analysis. These studies that we pooled in our meta-analysis were somewhat heterogeneous in the exposure, with different minimum durations of working as a welder being included in the exposed group. Additionally, the Steenland et al. (1986) study reported that it examined lung cancer only, but did not report ICD codes to confirm this. ICD codes reported in the other two studies showed they examined trachea, bronchus, and lung cancer. Despite these differences between studies, we considered these studies similar enough to warrant inclusion in the same meta-analysis. Compared with no (or low) occupational exposure to welding fumes, any (or high) such occupational exposure increased the risk of dying of trachea, bronchus, and lung cancer (RR 1.25, 95 % CI 1.02–1.53, three studies, 20,325 participants, I² 0 %; Fig. 8).

### 4.5.2.3. Synthesis across designs.
Our synthesis of the prioritized body of

<caption>Table 7</caption>

Pooled effect estimates of the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer incidence in case-control studies, when each study is omitted from the main meta-analysis one at a time.

<table><thead><tr><th>Study excluded from meta-analysis</th><th>Pooled effect estimate (95 % confidence interval)</th><th>I² (%)</th></tr></thead><tbody><tr><td>None excluded (all studies)</td><td>1.48 (1.29–1.70)</td><td>24</td></tr><tr><td>Brenner, 2010</td><td>1.47 (1.27–1.70)</td><td>26</td></tr><tr><td>Brüske-Hohlfeld 2000</td><td>1.46 (1.26–1.69)</td><td>25</td></tr><tr><td>Buiatti 1985</td><td>1.46 (1.27–1.68)</td><td>24</td></tr><tr><td>Consonni 2010</td><td>1.51 (1.31–1.74)</td><td>22</td></tr><tr><td>Corbin 2011</td><td>1.48 (1.29–1.71)</td><td>28</td></tr><tr><td>Elci 2003</td><td>1.51 (1.31–1.73)</td><td>23</td></tr><tr><td>Fortes 2003</td><td>1.47 (1.28–1.69)</td><td>24</td></tr><tr><td>Guida 2011</td><td>1.47 (1.27–1.70)</td><td>26</td></tr><tr><td>Gustavsson 2000</td><td>1.48 (1.28–1.72)</td><td>27</td></tr><tr><td>Jöckel 1998</td><td>1.47 (1.27–1.69)</td><td>25</td></tr><tr><td>Kazma 2012</td><td>1.48 (1.29–1.71)</td><td>26</td></tr><tr><td>Keller 1993</td><td>1.47 (1.27–1.70)</td><td>26</td></tr><tr><td>Lerchen 1987</td><td>1.44 (1.26–1.64)</td><td>18</td></tr><tr><td>López-Cima 2007</td><td>1.51 (1.31–1.74)</td><td>25</td></tr><tr><td>Morabia 1992</td><td>1.48 (1.28–1.72)</td><td>27</td></tr><tr><td>Pezzotto 1999</td><td>1.49 (1.29–1.72)</td><td>27</td></tr><tr><td>Richiardi 2004</td><td>1.47 (1.27–1.70)</td><td>26</td></tr><tr><td>Schoenberg 1987</td><td>1.46 (1.27–1.67)</td><td>23</td></tr><tr><td>Soskolne 2007</td><td>1.46 (1.27–1.67)</td><td>22</td></tr><tr><td>Stücker 2002</td><td>1.49 (1.30–1.70)</td><td>21</td></tr><tr><td>'t Mannetje 2012</td><td>1.55 (1.35–1.77)</td><td>5</td></tr><tr><td>Tse 2012</td><td>1.47 (1.27–1.70)</td><td>26</td></tr><tr><td>Vallières 2012</td><td>1.46 (1.27–1.68)</td><td>23</td></tr></tbody></table>

evidence of case-control studies found that, compared with no (or low) occupational exposure to welding fumes, any (or high) occupational exposure to welding fumes led to an estimated increase in trachea, bronchus, and lung cancer mortality. The main meta-analysis produced an RR of 1.27 (95 % CI 1.04–1.56). We judged the evidence from the one case-control study and three cohort studies that we excluded from the main meta-analysis is generally supportive of the findings from the main meta-analysis.

<figure><img src="image_8.png" /><figcaption>Fig. 5. Forest plot with the main meta-analysis of the prioritized evidence (case-control studies), Outcome: Acquired trachea, bronchus, and lung cancer, Comparison: Any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes.</figcaption></figure>
## 4.6. Additional analyses

### 4.6.1. Subgroup analyses

Subgroup analyses were performed on data from the main meta-analysis. The forest plots and results of additional subgroup analyses are presented in Appendix 10 in the Supplementary data.

#### 4.6.1.1. Acquired trachea, bronchus, and lung cancer (incidence).
These analyses include subgrouping by WHO region, sex, occupation, and cancer site (Table 12). No evidence was found for meaningful subgroup differences by WHO region, cancer site or publication year. Regarding cancer site in the Gustavsson et al. (2000) study, the original study record specified that bronchus and lung cancers were studied, but the Kendzia et al. (2013) analysis, from which the effect estimate for this study was extracted, did not specify the exact cancer sites studied. Zero studies included only females, and the pooled estimate for studies including males only was similar to that of the main-meta-analysis. Limiting the meta-analysis to studies that only included participants with occupations coded as 7212 - welder in ISCO-08 (or equivalent) provided a pooled RR similar to that found in the main meta-analysis.

#### 4.6.1.2. Died from trachea, bronchus, and lung cancer (mortality).
We were able to conduct subgroup analyses by WHO region, sex, occupation, cancer site, and publication year (Table 13). These subgroup analyses found no evidence for meaningful subgroup differences by WHO region, cancer site or publication year. No study included only female participants; the pooled effect estimate for studies with only male participants was similar to that from the main meta-analysis. The pooled effect estimate for studies that included participants in occupations with the ISCO-08 code 7212 (or equivalent) only provided a pooled RR similar to that from the main meta-analysis.

### 4.6.2. Sensitivity analyses

Sensitivity analyses were also performed for data from the main meta-analysis. Their forest plots are presented in Appendix 11 in the Supplementary data.

#### 4.6.2.1. Acquired trachea, bronchus, and lung cancer (incidence).
The sensitivity analyses for incident trachea, bronchus, and lung cancer found no evidence for meaningful subgroup differences by risk of bias for conflict of interest, risk of confounding, use of documented or approximated ICD codes, adjustment for confounding by tobacco smoking and/or exposure to asbestos or assumed but unclear adjustment for Tier 1 confounders (Table 14). However, the pooled effect estimate was higher (RR 1.74, 95 % CI 1.45–2.09) for studies with “low”/ “probably low” risk of bias in all domains, compared with the pooled effect estimate for studies with “high”/”probably” high risk of bias in any domain (RR 1.29, 95 % CI 1.08–1.55; p value for subgroup differences 0.02). Additionally, there was no evidence for differences (p 0.61) between cohort studies reporting RR as the effect estimate (RR 1.24, 95 % CI 0.85–1.61) and cohort studies reporting hazard ratios (RR 1.15, 95 % CI 1.04–1.28).

<caption>**Table 8**</caption>

Results from studies excluded from the meta-analysis of the supporting evidence and reasons for their exclusion from this meta-analysis.

<table><thead><tr><th>Study ID</th><th>Effect estimate</th><th>Reason for exclusion from meta-analysis</th></tr></thead><tbody><tr><td>Danielsen 1993</td><td>RR for employment ≤ 5 years 1.8 (95 % CI 0.5–5.7)<br>RR for employment > 5 years 3.2 (95 % CI 1.3–8.1)</td><td>Only crude effect estimate reported and no data to calculate an adjusted effect estimate</td></tr><tr><td>Danielsen 2000</td><td>RR 1.90 (95 % CI 0.67–5.38)</td><td>Only crude effect estimate reported and no data to calculate an adjusted effect estimate</td></tr></tbody></table>

The meta-analysis using the inverse variance heterogeneity (IVhet) model (Doi et al. 2017) produced a similar but slightly lower pooled estimate than in the main meta-analysis (RR 1.38, 95 % CI 1.17–1.63).

We found information about the risk among never smokers in one of the prioritized studies (Brenner et al. 2010): an OR of 3.4 (95 % CI 1.1–10.4) for never smokers. This was larger than the prioritized effect estimate for the total population (i.e., ever and never smokers) used for the main meta-analysis for this study of 1.7 (95 % CI 1.0–3.0). It was not possible to draw any conclusions from this, as we were unable to back-calculate an OR for ever smokers, due to the addition of pack-years of smoking as a confounder in the analysis for the total population, and because this evidence comes from one study, in one location. Analyses by smoking status were provided in the pooled analysis by Kendzia et al. (2013), from which some effect estimates were taken. They reported that the OR for lung cancer among welders who were never-smokers was 2.34 (95 % CI 1.31–4.17); whereas the OR for lung cancer among welders who were ever-smokers was 1.33 (95 % CI 1.14–1.54) (29,947 participants, 15 studies). Additionally, interaction between welding and smoking was tested for. A p value of 0.22 and a relative excess risk due to interaction of 3.72 (95 % CI 1.19–6.25) were reported (29,947 participants, 15 studies), with the authors concluding no significant interaction. However, the individual effect estimates per study for welders and non-welders were not reported, so we were unable to reproduce this analysis or use these in our systematic review.

#### 4.6.2.2. Died from trachea, bronchus, and lung cancer (mortality).
Our sensitivity analyses for this outcome found no evidence for meaningful

<caption>**Table 9**</caption>

Effect estimates (odds ratios converted to risk ratios) of the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer mortality reported in three case-control studies included in the main meta-analysis (median baseline risk: 0.03).

<table><thead><tr><th>Study ID</th><th>Odds ratio (95 % CI)</th><th>Converted risk ratio (95 % CI)</th></tr></thead><tbody><tr><td>Finkelstein 1995</td><td>1.07 (0.57–1.91)</td><td>1.07 (0.58–1.95)</td></tr><tr><td>Ronco 1988</td><td>2.93 (0.87–9.82)</td><td>2.77 (0.82–9.31)</td></tr><tr><td>Yiin 2007</td><td>1.28 (1.03–1.59)</td><td>1.27 (1.02–1.58)</td></tr></tbody></table>

<figure><img src="image_9.png" /><figcaption>**Fig. 6.** Forest plot with the meta-analysis of the supporting evidence (cohort studies), Outcome: Acquired trachea, bronchus, and lung cancer, Comparison: Any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Fig. 7.** Forest plot with the main meta-analysis of the prioritized evidence (case-control studies), Outcome: Died from trachea, bronchus, and lung cancer, Comparison: Any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes.</figcaption></figure>

<caption>**Table 10**</caption>

Results from studies excluded from the meta-analysis of the prioritized evidence and reasons for their exclusion from this meta-analysis.

<table><caption>**Table 11**</caption><thead><tr><th>Study ID</th><th>Effect estimate</th><th>Reason for exclusion from meta-analysis</th></tr></thead><tbody><tr><td>Gottlieb<br>1980</td><td>OR for age &lt; 60 years at death 1.89 (95 % CI 0.48–7.37)<br>OR for age ≥ 60 years at death 0.93 (95 % CI 0.25–3.46)</td><td>Adjustment was not made for the Tier 1 confounder of age. Instead, ORs were provided stratified on age, which combined would not have sufficiently controlled for age.</td></tr><tr><td>Lauritsen<br>1996</td><td>OR 3.20 (95 % CI 1.00–2.40)</td><td>Age was matched on but was not adjusted for.</td></tr></tbody></table>

Change in pooled effect estimate of the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer incidence in case-control studies, when each study is omitted from the main meta-analysis one at a time.

<table><thead><tr><th>Study excluded from meta-analysis</th><th>Point pooled estimate (95 % CI)</th><th>I² (%)</th></tr></thead><tbody><tr><td>None excluded (all studies)</td><td>1.27 (1.04–1.56)</td><td>0</td></tr><tr><td>Finkelstein 1995</td><td>1.48 (0.81–2.71)</td><td>35</td></tr><tr><td>Ronco 1998</td><td>1.25 (1.02–1.53)</td><td>0</td></tr><tr><td>Yiin 2007</td><td>1.48 (0.61–3.59)</td><td>47</td></tr></tbody></table>

subgroup differences by risk of bias in any domain, risk of bias for conflict of interest, risk of confounding, use of documented or approximated ICD codes or adjustment for confounding by tobacco smoking and/or exposure to asbestos (Table 15). We also carried out a sensitivity analysis to remove Yiin et al. (2007), as the effect estimate was calculated using the Borenstein et al. (2009) method. This resulted in a pooled effect estimate of 1.48 (0.61–3.58; see Table 11). We judged this to be potentially different to the pooled RR from the main meta-analysis (i.e., 1.27, 95 % CI 1.04–1.56).

Additionally, we carried out two sensitivity analyses relating to cohort studies. There were no differences between cohort studies reporting RR as the effect estimate (RR 1.24, 95 % CI 0.98–1.57) and cohort studies reporting hazard ratios (RR 1.28, 95 % CI 0.88–1.86; p 0.87). Furthermore, as the 95 % CI was back-calculated for Steenland et al. (1986), we carried out a sensitivity analysis, removing this cohort study from the meta-analysis of cohort studies reporting on trachea,

bronchus, and lung cancer mortality. This resulted in a pooled effect estimate of 1.24 (95 % CI 0.98–1.57), compared with the effect estimates of 1.25 (95 % CI 1.02–1.53) when Steenland et al. (1986) was included, which we judged to be very similar.

## 4.7. Quality of evidence

### 4.7.1. Acquired trachea, bronchus, and lung cancer (incidence)

#### 4.7.1.1. Downgrade domain – Risk of bias.
We judged there to be some concern over the risk of bias in the domain called “risk of bias due to exposure assessment”. On the one hand, the sensitivity analysis that we conducted on this domain showed no subgroup difference between studies judged to be at “high”/”probably high” and those judged to be at “low”/”probably low” risk of bias in this domain (see Table A11.1.2 in Appendix 11), and studies that were larger in size (and contribution to the main meta-analysis) and those that were prioritized evidence that contributed to the main meta-analysis were judged to be generally at lower risk of bias in this domain. On the other hand, we judged this risk of bias to have potentially attenuated the effect estimate towards the null, which would be equally concerning as an overestimation of the effect size, since the aim of the meta-analysis is risk quantification (to produce a RR that is as accurate as possible that will be used to produce estimates of the burden of disease, if any), rather than establishing harmfulness (carcinogenicity)/direction of the effect. We had no or only minor concerns for risk of bias in all other domains. With that in mind, we had serious, but not very serious, concerns for risk of bias and downgraded the quality of evidence by only one level in this downgrade domain.

#### 4.7.1.2. Downgrade domain – Indirectness.
The included studies covered populations in 21 countries in three WHO regions. Most included studies primarily or only covered males, but we judged this to not be concerning because it is likely representative of the population of workers exposed to welding fumes who we judged to also be primarily males. Additionally, we were unaware of any evidence suggesting that there is a biological difference in the effect of occupational exposure to welding fumes on the outcome between males and females (i.e., no effect modification by sex). The included studies also covered populations across several decades of time. The exposures and populations in the included studies reasonably well capture the exposure and global population of interest to this systematic review. We, therefore, had no or

<figure><img src="image_11.png" /><figcaption>**Fig. 8.** Forest plot with the meta-analysis of the supporting evidence (cohort studies), Outcome: Died from trachea, bronchus, and lung cancer, Comparison: Any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes.</figcaption></figure>
<caption>**Table 12**</caption>

Summary of results from subgroup analyses for outcome of Acquired trachea, bronchus, and lung cancer.

<table><thead><tr><th>Subgroup</th><th>Pooled effect estimate for subgroup</th><th>Test for subgroup differences</th></tr></thead><tbody><tr><td><strong>WHO region</strong></td><td></td><td>p = 0.18</td></tr><tr><td>Americas (7 studies)</td><td>1.79 (1.40–2.30)</td><td></td></tr><tr><td>Europe (16 studies)</td><td>1.36 (1.13–1.62)</td><td></td></tr><tr><td>Western Pacific (2 studies)</td><td>1.62 (1.09–2.39)</td><td></td></tr><tr><td><strong>Sex</strong></td><td></td><td>p = N/A</td></tr><tr><td>Males only (22 studies)</td><td>1.47 (1.27–1.70)</td><td></td></tr><tr><td><strong>Occupation</strong></td><td></td><td>p = N/A</td></tr><tr><td>ISCO-08 7212 or equivalent (16 studies)</td><td>1.51 (1.29–1.78)</td><td></td></tr><tr><td><strong>Cancer site</strong></td><td></td><td>p = 0.92</td></tr><tr><td>Lung (16 studies)</td><td>1.46 (1.22–1.75)</td><td></td></tr><tr><td>Bronchus and lung (1 study)</td><td>1.49 (0.85–2.63)</td><td></td></tr><tr><td>Trachea, bronchus, and lung (6 studies)</td><td>1.56 (1.21–2.00)</td><td></td></tr><tr><td><strong>Publication year</strong></td><td></td><td>p = 0.09</td></tr><tr><td>Published in 1980s (3 studies)</td><td>2.69 (1.61–4.49)</td><td></td></tr><tr><td>Published in 1990s (4 studies)</td><td>1.58 (1.16–2.16)</td><td></td></tr><tr><td>Published in 2000s (8 studies)</td><td>1.39 (1.04–1.85)</td><td></td></tr><tr><td>Published in 2010s (3 studies)</td><td>1.36 (1.13–1.64)</td><td></td></tr></tbody></table>

Footnote: p values in the table relate to tests for subgroup differences.

only minor concerns for indirectness and did not downgrade the quality of evidence.

**4.7.1.3. Downgrade domain – Inconsistency.** We judged statistical heterogeneity to be low, since the $I^2$ of 24 % for the main meta-analysis of the prioritized evidence is relatively low. The leave-one-out analysis also did not result in large changes in the already low $I^2$, with the exception being that leaving out the 't Mannetje 2012 study ('t Mannetje, 2012) resulted in a reduction of the $I^2$ to 5 %. We therefore had no or only minor concerns for inconsistency and did not downgrade the quality of evidence.

**4.7.1.4. Downgrade domain – Imprecision.** We judged that the main meta-analysis was able to estimate the effect with good precision given

<caption>**Table 13**</caption>

Summary of results from subgroup analyses for outcome of Died from trachea, bronchus, and lung cancer.

<table><thead><tr><th>Subgroup</th><th>Pooled effect estimate for subgroup</th><th>Test for subgroup differences</th></tr></thead><tbody><tr><td><strong>WHO region</strong></td><td></td><td>p = 0.20</td></tr><tr><td>Americas (2 studies)</td><td>1.25 (1.02–1.53)</td><td></td></tr><tr><td>Europe (1 study)</td><td>2.77 (1.13–1.62)</td><td></td></tr><tr><td><strong>Sex</strong></td><td></td><td>p = N/A</td></tr><tr><td>Males only (2 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td><strong>Occupation</strong></td><td></td><td>p = N/A</td></tr><tr><td>ISCO-08 7212 or equivalent (2 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td><strong>Cancer site</strong></td><td></td><td>p = 0.74</td></tr><tr><td>Lung (2 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td>Trachea, bronchus, and lung (1 study)</td><td>1.27 (1.02–1.58)</td><td></td></tr><tr><td><strong>Publication year</strong></td><td></td><td>p = 0.39</td></tr><tr><td>Published in 1980s (1 study)</td><td>2.77 (0.82–9.35)</td><td></td></tr><tr><td>Published in 1990s (1 study)</td><td>1.07 (0.58–1.97)</td><td></td></tr><tr><td>Published in 2000s (1 study)</td><td>1.27 (1.02–1.58)</td><td></td></tr></tbody></table>

Footnote: p values in the table relate to tests for subgroup differences.

that the 95 % CI around the pooled effect estimate was relatively narrow. The 95 % CI ranged from an increase by 29 % to an increase to 70 %. We also judged the 95 % CI of the effect estimate in absolute terms to suggest good precision, with between 32.1 and 42.3 incident cases per 100,000 among exposed workers, compared with 24.9 incident cases per 100,000 among unexposed workers. This indicates a range between a large increase (7.2 additional incident cases/100,000 persons) and a very large increase in risk (17.4 additional incident cases/100,000 persons), suggesting a precise estimate, in absolute terms. We therefore had no or only minor concerns for imprecision and did not downgrade the quality of evidence.

**4.7.1.5. Downgrade domain – Publication bias.** We judged both the funnel plot (Fig. 9) and the Doi plot (Fig. 10) to show no signs of major asymmetry. Moreover, the LFK index statistic from the Doi plot was 1.41, which can be interpreted as indicative of only “minor asymmetry”. We therefore had no or only minor concerns for publication bias and did not downgrade the quality of evidence.

**4.7.1.6. Upgrade domain – Large effect size.** Based on the criteria we adopted for a large effect size, the effect estimate of an RR of 1.48 from the main meta-analysis for this outcome exceeded the fixed 1.25 cut-off. The E-value was 2.32 for the pooled RR (Appendix 12). The major risk factors that could confound the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer are tobacco smoking and occupational exposure to asbestos. We could not find evidence that reported the prevalence of occupational exposure to asbestos among welders and non-welders, so used tobacco smoking as the

<caption>**Table 14**</caption>

Summary of results from sensitivity analyses on effect estimates for trachea, bronchus, and lung cancer incidence.

<table><thead><tr><th>Subgroup for sensitivity analysis</th><th>Pooled effect estimate for subgroup</th><th>Test for subgroup differences</th></tr></thead><tbody><tr><td><strong>"High"/"probably high" risk of bias in any domain</strong></td><td></td><td>p = 0.02</td></tr><tr><td>Any "High"/"probably high" (12 studies)</td><td>1.29 (1.08–1.55)</td><td></td></tr><tr><td>All "Low"/"probably low" (11 studies)</td><td>1.74 (1.45–2.09)</td><td></td></tr><tr><td><strong>Risk of bias for misclassification of the exposure</strong></td><td></td><td>p = 0.32</td></tr><tr><td>"High"/"probably high" (12 studies)</td><td>1.35 (1.07–1.71)</td><td></td></tr><tr><td>"Low"/"probably low" (11 studies)</td><td>1.57 (1.31–1.89)</td><td></td></tr><tr><td><strong>Risk of bias for conflict of interest</strong></td><td></td><td>p = 0.99</td></tr><tr><td>"High"/"probably high" (1 studies)</td><td>1.48 (0.80–2.71)</td><td></td></tr><tr><td>"Low"/"probably low" (22 studies)</td><td>1.48 (1.28–1.72)</td><td></td></tr><tr><td><strong>Risk of confounding</strong></td><td></td><td>p = 0.42</td></tr><tr><td>"High"/"probably high" (3 studies)</td><td>1.03 (0.43–2.49)</td><td></td></tr><tr><td>"Low"/"probably low" (20 studies)</td><td>1.49 (1.29–1.72)</td><td></td></tr><tr><td><strong>With documented or approximated ICD codes</strong></td><td></td><td>p = 0.84</td></tr><tr><td>Yes (5 studies)</td><td>1.45 (1.13–1.88)</td><td></td></tr><tr><td>No (18 studies)</td><td>1.50 (1.27–1.78)</td><td></td></tr><tr><td><strong>Adjustment for tobacco smoking and/or exposure to asbestos</strong></td><td></td><td>p = 0.79</td></tr><tr><td>Tobacco smoking only (20 studies)</td><td>1.47 (1.23–1.76)</td><td></td></tr><tr><td>Both (3 studies)</td><td>1.53 (1.20–1.96)</td><td></td></tr><tr><td><strong>Studies where Tier 1 adjustment was assumed but unclear</strong></td><td></td><td>p = 0.22</td></tr><tr><td>Assumed but unclear (1 study)</td><td>2.41 (1.08–5.83)</td><td></td></tr><tr><td>Specified (22 studies)</td><td>1.45 (1.27–1.67)</td><td></td></tr></tbody></table>

Footnote: p values in the table relate to tests for subgroup differences.
reference confounder. Applying a bias factor, calculated based on the associations between tobacco smoking, and both the exposure and the outcome resulted in an “unconfounded RR” of 1.19, meaning that the reference confounder could reduce the observed RR to a value of 1.19 (i.e., not null). Unmeasured residual confounding could have a similar effect as tobacco smoking. Therefore, we judged the pooled effect estimate for this outcome to be large in size and consequently upgraded the quality of evidence by one level.

### 4.7.1.7. Upgrade domain – Dose response effect.
We did not consider the existing evidence from included studies that reported effect estimates for different levels (or doses or intensities) of cumulative exposure to consistently indicate a dose-response relationship. The only included such study that reported a formal statistical test for a dose-response relationship found evidence for a positive trend where a higher level of cumulative exposure also had a higher RR (p for test of trend 0.02; Guida et al. (2011); Table 16). The other studies that reported relevant analyses did not report statistical tests for such trends and also used a range of different proxies for level of cumulative exposure, so we were unable to draw meaningful conclusions from these regarding the presence or not of a dose-response relationship (Table 16). We therefore judged there to be no suggestion of a dose-response and did not upgrade the quality of evidence for this outcome in this upgrade domain.

### 4.7.1.8. Upgrade domain – Residual confounding and bias not plausibly explaining the effect.
We did not consider residual confounding or bias to be plausible and therefore did not upgrade the quality of evidence in this upgrade domain.

### 4.7.1.9. Final rating.
We started the assessment at a rating of “moderate quality of evidence” for human observational studies as per the Navigation Guide methodology (see Section 3.10). We downgraded the quality of evidence by one level for serious concerns for risk of bias in the

<caption>**Table 15**</caption>

Summary of results from the sensitivity analyses on the effect estimates for trachea, bronchus, and lung cancer mortality.

<table><thead><tr><th>Subgroup for sensitivity analysis</th><th>Pooled effect estimate for subgroup</th><th>Test for subgroup differences</th></tr></thead><tbody><tr><td><strong>"High"/"probably high" risk of bias in any domain</strong></td><td></td><td>p = N/A</td></tr><tr><td>Any "High"/"probably high" (3 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td>All "Low"/"probably low" (0 studies)</td><td>N/A</td><td></td></tr><tr><td><strong>Risk of bias for misclassification of the exposure</strong></td><td></td><td>p = N/A</td></tr><tr><td>"High"/"probably high" (3 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td>"Low"/"probably low" (0 studies)</td><td>N/A</td><td></td></tr><tr><td><strong>Risk of bias for conflict of interest</strong></td><td></td><td>p = N/A</td></tr><tr><td>"High"/"probably high" (0 studies)</td><td>N/A</td><td></td></tr><tr><td>"Low"/"probably low" (3 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td><strong>Risk of confounding</strong></td><td></td><td>p = 0.17</td></tr><tr><td>"High"/"probably high" (2 studies)</td><td>1.07 (0.58–1.97)</td><td></td></tr><tr><td>"Low"/"probably low" (1 study)</td><td>2.77 (0.82–9.35)</td><td></td></tr><tr><td><strong>With documented or approximated ICD codes</strong></td><td></td><td>p = N/A</td></tr><tr><td>Yes (0 studies)</td><td>N/A</td><td></td></tr><tr><td>No (3 studies)</td><td>1.48 (0.61–3.58)</td><td></td></tr><tr><td><strong>Adjustment for tobacco smoking and/or exposure to asbestos</strong></td><td></td><td>p = 0.17</td></tr><tr><td>Neither (2 studies)</td><td>1.07 (0.58–1.97)</td><td></td></tr><tr><td>Both (1 study)</td><td>2.77 (0.82–9.35)</td><td></td></tr></tbody></table>

domain of risk of bias due to exposure assessment and upgraded the quality of evidence by one level for a large effect size. In summary, we started at moderate quality of evidence, and downgraded by one level and upgraded by one level. In conclusion, the final rating of quality of evidence is “moderate quality of evidence”; further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.

### 4.7.2. Died from trachea, bronchus, and lung cancer (mortality)

#### 4.7.2.1. Downgrade domain – Risk of bias.
We judged there to be concerns over the risk of bias in the domains called “risk of bias due to exposure assessment” and “risk of confounding”. For exposure assessment bias, we, however, judged the risk of this bias to have attenuated the effect estimate towards the null, leading to an underestimation of the effect size; this increased our confidence in the effect detected. Our sensitivity analysis on this risk of bias domain found no evidence for a difference between studies judged to be at “high”/”probably high” and the one study judged to be at “probably low” risk of bias in this domain (see Table A11.2.2 in Appendix 11 in the Supplementary data). The study Yiin et al. (2007) that was largest in sample size and contributed the greatest weight to the main meta-analysis was judged to be at relatively lower risk of bias in this domain, however it was judged to be at “probably high” risk of bias due to selection of participants into the study. For confounding, our sensitivity analysis found no evidence for a difference between studies judged to be at “high”/”probably high” and the one study judged to be at “probably low” risk of confounding (see Table A11.2.4 in Appendix 11 in the Supplementary data). However, we judged the largest study with the greatest weight in the main meta-analysis to be of “probably high” risk of confounding as it used birth cohort as a proxy for tobacco smoking. We had no or only minor concerns for risk of bias in all other domains. In conclusion, we therefore had serious concerns for risk of bias and downgraded the quality of evidence by one level in this downgrade domain.

#### 4.7.2.2. Downgrade domain – Indirectness.
The included studies covered populations in two WHO regions and five countries, all of which are high-income countries. Most included studies primarily or only covered males, but we judged this to not be concerning, because it is likely representative of the population of workers exposed to welding fumes who we judged to also be primarily males. Additionally, we were unaware of any evidence suggesting that there is a biological difference in the effect of occupational exposure to welding fumes on the outcome between males and females (i.e., no effect modification by sex). However, the studies covered only industrial sectors within manufacturing (or the sector covered was unclear), and although several decades were covered by the studies, none of these were recent decades. We, therefore, had serious, but not very serious, concerns for indirectness. We downgraded the quality of evidence by one level.

#### 4.7.2.3. Downgrade domain – Inconsistency.
Regarding inconsistency, we judged the statistical heterogeneity to be low, since the I² for the main meta-analysis of the prioritized evidence is 0 %. The leave-one-out analysis resulted in large increases in the I² and the effect estimate. The 95 % CI includes the null for two of the included studies. While we judged that there was no evidence of serious inconsistency, we note that few studies are included in the main meta-analysis and that one of the studies is largely driving the meta risk estimate. The supporting evidence indicated increased risks among the exposed as well. We, therefore, had no or only minor concerns for inconsistency. We did not downgrade the quality of evidence for inconsistency.

#### 4.7.2.4. Downgrade domain – Imprecision.
Overall, we judged that precision is relatively low in this body of evidence. Precision was not achieved in the relative effect estimate, with the 95 % CI of the RR ranging
from a very small or small increase by 4% (considering that we assume a
25 % change to indicate a large effect (van Kempen et al. 2018)) to a
very large increase by 56 %. We also judged the 95 % CI of the effect
estimate in absolute terms to suggest poor precision, with between 31.1
and 46.6 deaths per 100,000 among exposed workers, compared with
29.9 deaths per 100,000 among unexposed workers. This indicates a
range between no meaningful difference (1.2 additional deaths/100,000
persons) and a large increase in risk (16.7 additional deaths/100,000
persons), suggesting an imprecise estimate, in absolute terms. We had
serious concerns for imprecision, and therefore downgraded the quality
of evidence in this downgrade domain.

**4.7.2.5. Downgrade domain – Publication bias.** We judged there to be no evidence of publication bias, even though we did not identify protocols for any included studies. We, therefore, had no or only minor concerns for publication bias and did not downgrade the quality of evidence.

**4.7.2.6. Upgrade domain – Large effect size.** The pooled effect estimate of 1.27 for this outcome was similar to the 1.25 cut-off value. The E-value was 1.84 for this pooled RR (Appendix 12). Applying a bias factor, calculated based on the associations between tobacco smoking and both the exposure and the outcome, resulted in an “unconfounded RR” of 1.02. The, meaning that that the reference confounder could reduce the observed RR to a value of 1.02 (i.e., close to null). Unmeasured residual confounding could have a similar effect as confounding by tobacco smoking. Therefore, we did not judge there to be evidence to upgrade the quality of evidence for a large effect size.

**4.7.2.7. Upgrade domain – Dose-response effect.** We judged that there was also no evidence for a dose-response effect. The one study (Lauritsen and Hansen 1996) reporting level of exposure was excluded from the prioritized evidence and did not report a test of trend, making it difficult to assess the evidence of a dose-response effect from this study. We therefore did not upgrade the quality of evidence for this outcome in this upgrade domain.

**4.7.2.8. Upgrade domain – Residual confounding and bias not plausibly explaining the effect.** We did not consider residual confounding or bias to be plausible. We did not upgrade the quality of evidence in this upgrade domain.

**4.7.2.9. Final rating.** We started the assessment at a rating of “moderate quality of evidence” for human observational studies, applying the Navigation Guide methodology (see Section 3.10). We downgraded the quality of evidence by one level each for serious concerns for risk of bias, indirectness, and imprecision, respectively, and did not upgrade it. In summary, we started at “moderate quality of evidence”, and downgraded by three levels.. In conclusion, we judged this body of evidence to be of “low quality of evidence”; further research is very likely to have an important impact on our confidence in the effect estimate and is likely to change the estimate.

4.8. Strength of evidence

4.8.1. Acquired trachea, bronchus, and lung cancer (incidence)

**4.8.1.1. Quality of evidence.** We judged this body of evidence on this outcome to be of “moderate quality of evidence”. To that end, we have downgraded the quality of evidence by one level for serious concerns for risk of bias (in the domain of risk of bias due to exposure assessment) and upgraded it by one level for a large effect size.

**4.8.1.2. Direction of effect estimate.** We judged the pooled effect estimate from the main meta-analysis of the prioritized evidence to indicate a clear increase in risk. The pooled effect estimate from the main meta-analysis was large in size and estimated with good precision. The individual studies included in this main meta-analysis also consistently reported an increase in risk. Supporting evidence from non-prioritized included studies also reported effect estimates in the same direction. Not one single included study reported a point estimate that indicated a reduced risk. We therefore judged the body of evidence on this outcome to indicate an increased risk consistently and clearly. In conclusion, chance, bias, and confounding could be ruled out in concluding that occupational exposure to welding fumes leads to an increase in incident trachea, bronchus, and lung cancer.

**4.8.1.3. Confidence in the effect estimate.** We are also confident in the effect estimate, which is supported by evidence on causal pathways and biological plausibility. We judged the effect to be of a large size, estimated precisely, and indicating a meaningfully increased risk. Our leave-one-out analysis for this outcome (incidence) showed that the

<figure><img src="image_12.png" /><figcaption>**Fig. 9.** Funnel plot for the studies included in the main meta-analysis of the prioritized evidence (case-control studies), Outcome: Acquired trachea, bronchus, and lung cancer, Comparison: Any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes.</figcaption></figure>
<figure><img src="image_13.png" /><figcaption>Fig. 10. Doi plot with LFK index for the studies included in the main meta-analysis of the prioritized evidence (case-control studies), Outcome: Acquired trachea, bronchus, and lung cancer, Comparison: Any (or high) occupational exposure to welding fumes, compared with no (or low) occupational exposure to welding fumes.</figcaption></figure>

<caption>**Table 16**</caption>

Effect estimates from studies reporting on the association between occupational exposure to welding fumes, in terms of cumulative exposure, and trachea, bronchus, and lung cancer incidence.

<table><thead><tr><th>Study ID</th><th>Included in main meta-analysis</th><th>Exposure definition</th><th>Level of exposure</th><th>Adjusted odds ratio (95% confidence interval)</th><th>P value for trend (as reported)</th></tr></thead><tbody><tr><td rowspan="2">Danielsen 1993</td><td rowspan="2">No – unadjusted</td><td>Length of employment as a welder (years) compared with other shipyard production workers (with 10-year lag time)</td><td>Unexposed ≤ 5 > 5</td><td>1.0 (-)</td><td rowspan="2">Not reported</td></tr><tr><td>Length of employment as a welder (years) compared with other shipyard production workers</td><td>Unexposed < 2 2–4 5–14 ≥ 15</td><td>1.0 (-) 2.42 (0.73–8.01) 0.66 (0.09–4.85) 0.56 (0.08–4.17) 1.90 (0.67–5.38)</td></tr><tr><td>Guida 2011</td><td>Yes</td><td>Duration of regular welding (years)</td><td>No welding ≤ 10 > 10</td><td>1.0 (-) 1.53 (0.91–2.55) 1.96 (0.98–3.92)</td><td>0.02</td></tr><tr><td rowspan="2">Gustavsson 2000</td><td rowspan="2">Yes – but these cumulative exposure estimates are from a different analytical model than that used in the main meta-analysis</td><td rowspan="2">Duration of exposure to welding fumes (years)</td><td>0 > 0–9 10–29 ≥ 30</td><td>1.0 (-) 1.70 (0.97–2.96) 1.45 (0.96–2.20) 1.25 (0.82–1.90)</td><td rowspan="2">Not reported</td></tr><tr><td>Lifetime exposure to welding (cumulated hours)</td><td>Never 0–1,000 1,000–6,000 > 6,000</td><td>1.0 (-) 1.38 (0.91–2.09) 1.14 (0.73–1.79) 1.10 (0.73–1.66)</td></tr><tr><td>Siew 2008</td><td>No – cohort study</td><td>Cumulative exposure to welding fumes (mg/m³ – years)</td><td>None Low (0.1–10) Medium (10.1–49.9) High (≥50)</td><td>1.0 (-) 1.09 (1.05–1.14)</td><td>Not reported</td></tr></tbody></table>

Footnotes: One study that was included in the main meta-analysis reported an analysis on duration of exposure: Guida 2011 (Guida et al. 2011; Matrat et al. 2016). This analysis considered duration of work in an occupation of regular welder and provides support for a dose-response relationship, with the OR for those who were welders for > 10 years higher than the OR for those who were welders for ≤ 10 years (p for the trend 0.02). Although the effect estimates used in the main meta-analysis for Jöckel et al. (1998) and Gustavsson et al. (2000) were taken from Kendzia et al. (2013), the original Jöckel et al. (1998), and Gustavsson et al. (2000) study records also presented an analysis by cumulated hours exposed to welding fumes. Additionally, the association in terms of cumulative exposure was presented in Danielsen et al. (1993), Danielsen et al. (2000), and Siew et al. (2008). None of these studies reported a test for trend.

effect estimate remained consistently high no matter which individual included study was removed from the main meta-analysis. Moreover, our many sensitivity analyses also did not find any evidence of bias or other problems. Supporting evidence also reported effects in the same direction.

### 4.8.1.4. Other compelling attributes.
The IARC classification of welding fumes as a Group 1 carcinogen is a compelling attribute (International Agency for Research on Cancer 2018). This assessment comprehensively integrated mechanistic, animal, and human evidence streams into the final assessment. Additionally, this assessment concluded that there was also limited evidence for the carcinogenicity of welding fumes on cancer
of the kidney (International Agency for Research on Cancer, 2018).

4.8.1.5. **Final rating.** We judged the strength of evidence for this outcome as "sufficient evidence of harmfulness"; for human evidence a positive relationship is observed between exposure and outcome where chance, bias, and confounding, can be ruled out with reasonable confidence. See Table 3 for the full definitions of the strength of evidence ratings.

### 4.8.2. *Died from trachea, bronchus, and lung cancer (mortality)*

4.8.2.1. **Quality of evidence.** We judged the body of evidence to be of "low quality of evidence" for this outcome. We downgraded the quality of evidence by three levels, namely-one level each for serious concerns for risk of bias (in the domains of risk of bias due to exposure assessment and risk of confounding), indirectness and imprecision, respectively.

4.8.2.2. **Direction of effect estimate.** We judged the pooled effect estimate from the main meta-analysis of the prioritized evidence (i.e., an RR of 1.27) to indicate a clear increase in risk (as for the incidence outcome; see Section 4.8.1.2). The pooled point estimate from the main meta-analysis indicated a large effect and was estimated with reasonable precision. All three individual studies included in this main meta-analysis also reported point estimates indicating increased risk. Supporting evidence from non-prioritized included studies also reported increased risks. The only exception was that Gottlieb (1980) reported a point estimate that indicated a small decrease in risk (OR 0.93), at least for the cohort of people aged ≥ 60 years at death. We therefore judged the body of evidence on this outcome to, overall, indicate an increased risk. We have some certainty of this direction of the effect.

4.8.2.3. **Confidence in the effect estimate.** The pooled effect estimate was driven primarily by one study (Yiin et al. 2007), as the leave-one-out analyses also found. The body of prioritized evidence only comprised three studies. The lower 95 % CI limit is 1.04, which – while meaningful at the population level – is a small increase in risk only. We cannot rule out chance due to the small number of studies (three) included in the main meta-analysis. Additionally, the risks of bias in selection of participants into the study and bias due to exposure misclassification cannot be ruled out. Risk of confounding could also not be ruled out in these studies. Our confidence in the effect estimate is low.

4.8.2.4. **Other compelling attributes.** The IARC classification of welding fumes as a Group 1 carcinogen is again also a compelling attribute for this outcome (International Agency for Research on Cancer 2018). The IARC assessment comprehensively considered and integrated mechanistic, animal, and human evidence streams, and also reported limited evidence for the carcinogenicity of welding fumes on cancer of the kidney (International Agency for Research on Cancer 2018).

4.8.2.5. **Final rating.** We judged the strength of evidence for this outcome as "limited evidence of harmfulness"; for human evidence; a positive relationship is observed between exposure and outcome where chance, bias, and confounding cannot be ruled out with reasonable confidence (Table 3 for the rating's full definition).

# 5. Discussion

## 5.1. Summary of evidence

As shown in the table of summary of findings (Table 17), our systematic review and meta-analysis found "moderate quality of evidence" for the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer incidence. There was consistent evidence of an increased risk. The body of evidence was rated as of "moderate

quality of evidence" due to the potential for risk of bias due to exposure misclassification. Most studies reported a crude exposure classification of ever versus never based on occupation or job title of "welder". This exposure assignment likely underestimates the prevalence of occupational exposure to welding fumes as this method does not account for persons in other occupations or job titles that may be performing welding tasks and/or occupationally exposed to welding fumes. This strengthens our confidence in the effect estimate. We concluded that there was "sufficient evidence of harmfulness" of occupational exposure to welding fumes for acquiring trachea, bronchus, and lung cancer, from the human evidence stream. Additionally, we judged the evidence we found to be of "low quality of evidence" for the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer mortality. We concluded that there was "limited evidence of harmfulness" from human evidence for dying from trachea, bronchus, and lung cancer, because chance, bias, and confounding could not be ruled out with reasonable confidence.

Subgroup and sensitivity analyses did not suggest any differences between subgroups for either outcome. The only exception was that the sensitivity analysis for the outcome of trachea, bronchus, and lung cancer incidence of the effect estimate for studies with a "high"/"probably high" risk of bias rating in any domain (RR 1.29, 95 % CI 1.08–1.55) was lower than that for studies with a "low"/"probably low" risk of bias in all domains (RR 1.74, 95 % CI 1.45–2.09; p value for subgroup differences 0.02). Some methodologists, however, caution against stratification by risk of bias (Stone et al. 2019).

## 5.2. Comparison to previous systematic reviews

In IARC Monograph Volume 118, a working group of individual experts convened by WHO's IARC has concluded based on a synthesis of evidence streams of mechanistic, animal, and human studies that "Welding fumes are carcinogenic to humans and cause cancer of the lung (Group 1)" (International Agency for Research on Cancer 2018). Exposure to welding fumes is therefore already an established risk factor for human health (International Agency for Research on Cancer 2018).

The four relevant previous reviews and/or meta-analyses (Sjogren et al. 1994; Moulin 1997; Ambroise et al. 2006; International Agency for Research on Cancer 2018; Honaryar et al. 2019) have all reported that exposure to welding fumes is associated with an increased risk of lung cancer incidence and/or mortality. They reported increases in risk ranging from 1.17 to 1.94 (depending on the type of study considered, and combining effect estimates across incidence and mortality). The lower 95 % CI limits also always indicated an increased risk in all reviews and/or meta-analyses (ranging from 1.04 to 1.53). Our systematic review and meta-analysis on the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer supports these previous findings.

However, the relevant previous reviews and/or meta-analyses combined different study types (e.g., combined case-control with cohort studies) and/or different outcomes (i.e., combined incidence with mortality outcome measures) in their pooled analyses. Furthermore, the aim of our review was to provide a pooled estimate of the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer (Pega et al. 2020a), whereas relevant previous reviews and/or meta-analyses captured any exposure to welding fumes (even if in practice most commonly these were occupational ones) and only lung cancer (even if this may sometimes have included bronchus as a site, at least in older studies), respectively. Therefore, our systematic review and meta-analysis is not – strictly speaking – comparable with those from previous reviews and/or meta-analyses. Nevertheless, the pooled effect estimates we produced for the outcomes of trachea, bronchus, and lung cancer incidence (RR 1.48, 95 % CI 1.29–1.70) and mortality (RR 1.27, 95 % CI 1.04–1.56) are in the same direction (increase in risk) and of similar size (a moderate to large increase) as those reported in the previous reviews and/or meta-analyses. The findings from this
systematic review and meta-analysis are thus still aligned with and support the conclusions reached in the previous relevant reviews and/or meta-analyses.

## 5.3. Limitations and strengths of this systematic review

### 5.3.1. Limitations

Our systematic review and meta-analysis has several limitations. First, even though the search strategy included many academic and grey literature databases, potentially eligible studies may have been missed (e.g., those published in languages other than those we collectively covered, or those only indexed in additional databases like CINAHL, which could be included in future updates of the systematic review). However, this is unlikely given that consultation with subject matter experts did not lead to the identification of any additional eligible studies. Given the large number of included studies and consequently large number of included study participants, the overall findings would not have been affected by eligible studies that our literature search (which would likely be relatively smaller in sample size).

Second, in several studies, exposure was assigned using occupation or job title as proxies or measured by asking participants to self-report their occupational exposures. Objective assessments of occupational exposure to welding fumes using personal monitoring devices may have provided more accurate, valid, and reliable estimates from which to assess the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer, but these were not available in any included study. However, direct, objective exposure measurements are realistically only feasible in prospective cohort and intervention studies; indirect, subjective measurements (e.g., use of occupation, job title or job tasks as a proxy for exposure) or direct but subjective (self-reported) exposure to welding fumes are the most common and still acceptable assessment methods in case-control study designs assessing retrospective lifetime occupational exposure history. Further, the use of occupation or job title of “welder” as a proxy to occupational exposure to welding fumes may misclassify those occupationally exposed to welding fumes (e.g., themselves involved in welding tasks or exposed at the workplace from another workers’ welding) but who were not “welders”. Nevertheless, the risk of bias assessment recognized this limitation and was considered in the final evaluations of the quality and strength of the bodies of evidence.

Third, no eligible study was found on the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer prevalence. Relatively few studies were identified for the outcome of mortality from trachea, bronchus, and lung cancer, with only three eligible for inclusion in the main meta-analysis for this outcome. Additionally, no study estimated the exposure’s effect on both incidence and mortality, so it was not possible to look at these two outcomes within the same population. This limits the comprehensiveness of the available body of evidence.

Fourth, the health outcome of interest in this review is trachea, bronchus, and lung cancer, in line with the relevant WHO Global Health Estimates category (World Health Organization 2018), but most included studies stated that they investigated “lung cancer” only. Some studies reported on “lung cancer” as their outcome of interest, but the ICD codes that they then specified in the study records for this outcome were those for two or more of trachea, bronchus, and lung cancer. Since ICD-10 (World Health Organization 2015) classifies lung and bronchus cancer as part of the same cancer site, if a study reports on “lung cancer” and that it used the relevant ICD code for “bronchus and lung cancer”, it is unclear if the study covered the site of lung only or both sites of lung and bronchus, presenting possible discrepancies in reporting of outcomes in such studies.

### 5.3.2. Strengths

Our systematic review and meta-analysis also has a number of strengths. First, some relevant previous reviews and/or meta-analyses

have not reported clearly whether all the steps of a systematic review have been performed, but our systematic review and meta-analysis have done so, including use of a pre-published protocol (Pega et al. 2020a), which represents a substantial improvement in systematic review methods on the subject. Some relevant previous reviews and/or meta-analyses have also not comprehensively reported the analytic steps of the review and/or meta-analysis for comparisons of any (or high) occupational exposure to welding fumes with no (or low) occupational exposure to welding fumes. That our systematic review and meta-analysis has done this provides another improvement in accuracy of systematic review and meta-analytic evidence on this topic.

Second, previous reviews and/or meta-analyses on this topic have not sought to differentiate trachea, bronchus, and lung cancer prevalence from incidence from mortality as separate outcomes, but our systematic review and meta-analysis improves accuracy by differentiating these different outcomes.

Third, our systematic review and meta-analysis differed from previous work in that studies that may have included welders in the comparator (e.g., general population) were excluded per WHO/ILO methodology. This exclusion of a potentially contaminated reference group avoided potential bias of the pooled effect estimates towards the null.

Fourth, whereas some previous review and meta-analytic evidence has not comprehensively assessed risk of bias and quality of evidence using established systematic review frameworks with dedicated tools and approaches, we have rigorously applied the Navigation Guide framework in this systematic review and meta-analysis, which should have ensured comprehensiveness, rigor, and transparency.

Fifth, in previous reviews and/or meta-analyses, the strength of evidence was not commonly assessed. The IARC Monograph Volume 118 (International Agency for Research on Cancer 2018) did assess strength of evidence as part of its hazard identification (as reported above). In our systematic review and meta-analysis, we have applied pre-specified, pre-published criteria (Pega et al. 2020a) to rate the strength of evidence for each included outcome.

Sixth, in our systematic review and meta-analysis, we conducted many sensitivity analyses to investigate the robustness of our results. For example, we conducted an additional sensitivity analysis using the alternative IVhet estimator for the main meta-analysis for acquired trachea, bronchus, and lung cancer.

Finally, to our knowledge, this is the first systematic review and meta-analysis on this topic conducted specifically for an occupational burden of disease study, here for the WHO/ILO Joint Estimates. It can provide a model for future systematic reviews and meta-analyses that will help ensure that such global health estimates adhere fully with the GATHER Guidelines for Accurate and Transparent Health Estimates Reporting (Stevens et al. 2016).

## 6. Use of evidence for burden of disease estimation

This systematic review and meta-analysis was conducted by WHO and ILO, supported by a large number of individual experts, for the WHO/ILO Joint Estimates (Pega et al. 2021a,b; World Health Organization and International Labour Organization 2021a,b). More specifically, it provides the crucial evidence base for the organizations to consider producing estimates of the burden of deaths and DALYs from trachea, bronchus, and lung cancer that is attributable to occupational exposure to welding fumes. The systematic review found a large body of evidence from several case-control studies for comparison of persons with any (or low) occupational exposure to welding fumes with those with no (or low) occupational exposure to these fumes for the incidence of trachea, bronchus, and lung cancer. We judged this body of evidence to be of “moderate quality of evidence” and to provide “sufficient evidence of harmfulness”. The systematic review found a smaller body of evidence from case-control studies for comparison of persons occupationally exposed to welding fumes with those occupationally unexposed
<caption>**Table 17**</caption>

Table of summary of findings.

Trachea, bronchus, and lung cancer among workers with any (or high) occupational exposure to welding fumes compared with among workers with no (or low) occupational exposure to welding fumes

Population: workers

Settings: all countries and work settings

Exposure: any (or high) occupational exposure to welding fumes

Comparison: no (or low) occupational exposure to welding fumes

<table><thead><tr><th rowspan="3">Outcome</th><th colspan="2">Illustrative comparative risks</th><th rowspan="3">Relative effect<br>(95 % CI)</th><th rowspan="3">No. of<br>participants<br>(studies)</th><th rowspan="3">Navigation Guide ( Woodruff and Sutton 2014)<br>quality of the<br>evidence rating</th><th rowspan="3">Navigation Guide strength<br>of evidence<br>rating</th><th rowspan="3">Comments</th></tr><tr><th colspan="2">(95 % CI)</th></tr><tr><th>Assumed<br>risk</th><th>Corresponding<br>risk</th></tr></thead><tbody><tr><td>Has trachea, bronchus,<br>and lung cancer<br>(prevalence)</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>-</td><td>No eligible study found.</td></tr><tr><td>Acquired trachea,<br>bronchus, and lung<br>cancer (incidence)<br>(assessed using medical<br>records)<sup>a</sup></td><td>24.9 per<br>100,000</td><td>36.9 per<br>100,000<br>(32.1–42.3)</td><td>RR 1.48<br>(1.29–1.70)</td><td>57,931<br>participants<br>(23 studies)</td><td>Moderate quality of<br>evidence<sup>c,d</sup></td><td>Sufficient<br>evidence of<br>harmfulness</td><td>The pooled effect estimate from the eight case-control studies (main meta-analysis) indicated that occupational exposure to welding fumes lead to a clinically meaningful increase in risk of trachea, bronchus, and lung cancer incidence. Evidence was supported by eight cohort studies that were included in a meta-analysis, along with one case-control study and two cohort studies that were not included in a meta-analysis.</td></tr><tr><td>Died from trachea,<br>bronchus, and lung<br>cancer (mortality)<br>(assessed using<br>administrative records,<br>such as death certificates)<sup>b</sup></td><td>29.9 per<br>100,000</td><td>37.9 per<br>100,000<br>(31.1–46.6)</td><td>RR 1.27<br>(1.04–1.56)</td><td>8,686<br>participants<br>(3 studies)</td><td>Low quality of<br>evidence<sup>e</sup></td><td>Limited<br>evidence of<br>harmfulness</td><td>The pooled effect estimate from three case-control studies (main meta-analysis) indicated that occupational exposure to welding fumes lead to a clinically meaningful increase in risk of trachea, bronchus, and lung cancer mortality. Some support was provided by three cohort studies that were included in a meta-analysis, along with two case-control studies that were not included in a meta-analysis.</td></tr></tbody><tfoot><tr><td colspan="8">CI: confidence interval; RR: risk ratio</td></tr></tfoot></table>

Navigation Guide quality of evidence ratings

**High quality:** Further research is very unlikely to change our confidence in the estimate of effect.

**Moderate quality:** Further research is likely to have an important impact on our confidence in the estimate of effect and may change the estimate.

**Low quality:** Further research is very likely to have an important impact on our confidence in the estimate of effect and is likely to change the estimate.

Navigation Guide strength of evidence ratings

**Sufficient evidence of harmfulness:** The available evidence usually includes consistent results from well-designed, well-conducted studies, and the conclusion is unlikely to be strongly affected by the results of future studies. For human evidence a positive relationship is observed between exposure and outcome where chance, bias, and confounding, can be ruled out with reasonable confidence.

**Limited evidence of harmfulness:** The available evidence is sufficient to determine the effects of the exposure, but confidence in the estimate is constrained by such factors as: the number, size or quality of individual studies, the confidence in the effect or inconsistency of findings across individual studies. As more information becomes available, the observed effect could change, and this change may be large enough to alter the conclusion. For human evidence a positive relationship is observed between exposure and outcome where chance, bias, and confounding cannot be ruled out with reasonable confidence.

**Inadequate evidence of harmfulness:** Studies permit no conclusion about a toxic effect. The available evidence is insufficient to assess effects of the exposure. Evidence is insufficient because of: the limited number or size of studies, low quality of individual studies or inconsistency of findings across individual studies. More information may allow an estimation of effects.

**Evidence of lack of harmfulness:** The available evidence includes consistent results from well-designed, well-conducted studies, and the conclusion is unlikely to be strongly affected by the results of future studies. For human evidence more than one study showed no effect on the outcome of interest at the full range of exposure levels that humans are known to encounter, where bias and confounding can be ruled out with reasonable confidence. The conclusion is limited to the age at exposure and/or other conditions and levels of exposure studied.

Footnotes:

<footnote>a For the outcome of trachea, bronchus, and lung cancer incidence, we took the median baseline risk in the unexposed population reported for this outcome in the cohort studies included in this systematic review (Danielsen et al. 1993; Danielsen et al. 2000; Siew et al. 2008; Wong et al. 2017).</footnote>

<footnote>b For the outcome of trachea, bronchus, and lung cancer mortality, the baseline risk was taken from Steenland (2002).</footnote>

<footnote>c Downgraded by one level, because we had serious concerns for risk of bias.</footnote>

<footnote>d Upgraded by one level as we judged the effect estimate to be large in size.</footnote>

<footnote>e Downgraded by three levels, because we had serious concerns for each of: risk of bias, indirectness, and imprecision.</footnote>
to this risk factor for mortality from trachea, bronchus, and lung cancer. This body of evidence was judged to be of "low quality of evidence" and to provide "limited evidence of harmfulness".

Producing estimates of the burden of trachea, bronchus, and lung cancer attributable to occupational exposure to welding fumes appears evidence-based and warranted. Applying the standards outlined previously (Pega et al. 2021a; World Health Organization and International Labour Organization 2021a), the parameters reviewed (including the pooled RR from the main meta-analysis) from the body of evidence regarding trachea, bronchus, and lung cancer incidence appear suitable as input data for WHO/ILO modelling of work-related burden of disease.

## 7. Conclusions

We judged the existing bodies of evidence as "sufficient evidence of harmfulness" for occupational exposure to welding fumes and trachea, bronchus, and lung cancer incidence, and as "limited evidence of harmfulness" for occupational exposure to welding fumes and trachea, bronchus, and lung cancer mortality. The RR for the comparisons between those occupationally exposed and unexposed to welding fumes is suitable as input data for the WHO/ILO Joint Estimates.

The quality of evidence could be improved in future research studies to improve the available bodies of evidence on the effect of occupational exposure to welding fumes on trachea, bronchus, and lung cancer prevalence, incidence, and mortality in three ways. First, the main concerns for risk of bias were related to the domain called "risk of bias due to exposure misclassification". All studies measured occupational exposure indirectly, either through self-reported data on occupation, job title, job tasks or exposures; reports from supervisors, spouses, colleagues or other third parties; or administrative records. Ideally, future studies would assess occupational exposure to welding fumes directly. The risk of trachea, bronchus, and lung cancer from occupational exposure to welding fumes would be affected by numerous factors (e.g., ventilation and use of protective equipment). Any two welders may not be occupationally exposed to welding fumes at the same level, despite both being considered "exposed" if, for example, occupation or job title is used to assign exposure status. Direct measures of exposure would enable more specific and sensitive exposure assignment, with potential for improved RRs becoming available for use in burden of disease estimation through future updates of this systematic review and meta-analysis. Second, future research should investigate all three outcomes (i.e., prevalence, incidence, and mortality) in the same study, so it is possible to estimate the exposure effect on these three outcomes within the same population over time. Third, it should be noted that the current bodies of evidence cover only three WHO Regions: the Region of the Americas, the European Region, and the Western Pacific Region. There may be some differences in protections for workers and levels of occupational exposure to welding fumes between countries in these regions compared with other WHO regions. While the current bodies of evidence have been judged to provide sufficient evidence for the production of WHO/ILO Joint Estimates, more studies covering more WHO regions and more countries would be beneficial for burden of disease estimation in the future.

## 8. Differences between protocol and systematic review

* We further developed the conceptual framework presented in the protocol (Pega et al. 2020a) in two ways. First, we added as effect modifiers: tobacco smoking, exposure to asbestos, base metals welded, welding technique process, duration of welding tasks and related activities, the position of the welder, degree of ventilation of the occupational setting, and the use of personal protective equipment. Second, we removed as mediators: base metals welded, welding technique process, duration of welding tasks and related activities, the position of the welder, degree of ventilation of the occupational setting, and the use of personal protective equipment.

This brings the conceptual framework in better alignment with the statistical and epidemiological definitions of effect modifiers and mediators, respectively.

* In the section "Types of exposures", we changed our definition of the risk factor levels from "Any occupational exposure to welding fumes" in the protocol to "Any (or high) occupational exposure to welding fumes" in the systematic review and from "No occupational exposure to welding fumes" to "No (or low) occupational exposure to welding fumes", respectively. The reason was that this revised definition was more realistic and better aligned with prior definitions of risk factor levels used in burden of disease studies (Concha-Barrientos et al. 2004; World Health Organization 2021).

* In the section "Types of exposures", we changed the definition of the theoretical minimum risk exposure level from "No occupational exposure to welding fumes" in the protocol to "No (or low) occupational exposure to welding fumes" in the systematic review. This reflected the changes made to the definition of the relevant risk factor level (see above bullet point).

* We added in sections "Types of comparators" and "Types of effect measures" that standardized RRs or standardized ORs, where the rate or odds of mortality or incidence among the exposed population were compared with the rates or odds amongst the general population, were excluded from the systematic review.

* Added was also in section "Types of effect measures" that: For case-control studies matched by Tier 1 confounding variables (i.e., age and sex), we applied the following eligibility criteria. As Pearce has pointed out, "Matching in a case-control study does not control for confounding by the matching factors" and "A matched design may require controlling for the matching factors in the analysis" (p1) (Pearce 2016). Pearce argues that matching does not remove confounding, and it is still necessary to control for confounding by the matching factors, and in fact "the matching process in a case-control study changes the association between the matching factor and the outcome, and can create an association even if there were none before the matching was conducted" (p2) (Pearce 2016). Therefore, if a case-control study matched by Tier 1 confounders but did not adjust for these matching variables (e.g., in a regression analysis), we included this study in the systematic review, but excluded it from the meta-analysis. Additionally, Pearce states that "A "standard" (unconditional) analysis may be most valid and appropriate, and a "matched" (conditional) analysis may not be required or appropriate". (p1) (Pearce 2016). Therefore, we included effect estimates regardless of conditionality of analysis.

* We added in section "Types of effect measures" that, for the Kendzia et al. (2013) individual participant data analysis, we referred to the original study records of included studies to systematically identify the best effect estimate for the included studies.

* For studies that were included in IARC Monograph 118 (International Agency for Research on Cancer 2018) or a subsequent meta-analysis (Honaryar et al. 2019), we planned in our protocol to use existing data extractions for some selected data such as RRs and study characteristics, but in the systematic review we conducted separate data extractions for all included studies to ensure optimal fit with our specific systematic review objectives.

* In the protocol, we intended to request missing data from the principal study author by email or phone, using the contact details provided in the principal study record, but in the end did not do so, because we preferred to use peer-reviewed, published data only.

* For risk of bias assessment, we planned to use a modification of a previous method to identify and assess undisclosed financial interests of authors (Forsyth et al. 2014). Where no financial disclosure or conflict of interest statements were available, we planned to search the name of all authors in other study records gathered for this study and published in the prior 36 months and in other publicly available declarations of interests. However, this step was not carried out due to lack of working group capacity.
* For risk of bias assessment, we further developed our pre-specified criteria for assessment of risk of bias due to exposure misclassification. For studies that assigned exposure based on an occupation or a job title of “welder” alone, risk of bias in this domain was considered to be relatively higher than for studies that assigned exposure based on a job task of “welding” or that employed a welding-specific questionnaire or more complex exposure matrix.

* We added specification of methods for back-calculating measures of variance for effect estimates for which the point estimate was reported without a measure of variance, but with a statistic from which the variance could be derived.

* We also added specification that we used the Borenstein et al. (2009) methods for calculating a summary effect estimate from two or more individual effect estimates extracted from comparisons of different levels of exposure with the same comparator.

* Our protocol did not plan to conduct a subgroup analysis by cancer site, but in the systematic review we did conduct and report such an analysis, because reported cancer sites differed across studies included in the main meta-analysis, and we wanted to investigate if this had introduced heterogeneity in this meta-analysis.

* Additionally, our protocol did not plan to conduct a subgroup analysis by publication year, but this was added it following a suggestion made during the peer-review process.

* We also added a sensitivity analysis for meta-analyses with studies for which the measure of variance was derived, rather than reported. In such sensitivity analyses, the study with a derived variance was excluded to see if adding this study had made any difference.

* Added was also a sensitivity analysis of studies judged to be of "high"/"probably high" risk of bias from exposure misclassification, compared with studies at "low"/"probably low" risk of bias in this domain.

* Added was further also a sensitivity analysis for cohort studies, comparing those that reported RRs as the effect estimate with those that reported hazard ratios, because we saw the need to explore if the type of effect estimate impacted the results of such meta-analyses.

* Added was also a sensitivity analysis for case-control studies with ORs converted to RRs before conducting the quantitative meta-analysis, compared with case-control studies with ORs pooled in the quantitative meta-analysis and then the pooled OR being converted to a RR. This enabled us to assess if the point at which OR-to-RR conversions were made impacted the final, pooled RR estimate.

* We also added sensitivity analyses in which we removed studies whose effect estimates were calculated using the method developed by Borenstein et al. (2009) or whose measures of variance for effect estimates were back-calculated.

* We added a further sensitivity analysis with studies for which we back-calculated the standard error from a p value, compared with studies for which we back-calculated the standard error from a 95 % CI.

* We had planned to potentially conduct a sensitivity dose-response meta-analysis of studies that reported categorical risk estimates. This would have enabled us to investigate potential threshold effects. We did not conduct such analyses, however, as the working group did not have the capacity for them.

* Additionally, following peer-review, we added sensitivity analyses in which we conducted meta-analyses with RR to look at relative risks among non-smokers or /never-smokers, compared to meta-analyses with RR among smokers. However, there was insufficient information available in studies to carry out this sensitivity analysis.

* In addition to producing Egger's funnel plots to access publication bias as per protocol, we also produced Doi plots and LFK indices, enabling us to base our assessment on a more comprehensive set of metrics for detecting publication bias.

* For quality of evidence assessment, we did not quantify what effect size we would judge as indicative of a "large effect size" and "very large effect size" for upgrading the quality of evidence in our protocol. Initially, in the systematic review we applied a change in RR by ≥ 25 % (i.e., an RR of ≤ 0.75 or ≥ 1.25) as indicative of a large effect size, based on a prior systematic review from the WHO/ILO Joint Estimates (Teixeira et al. 2021b) that had adopted this limit value from WHO guidelines on exposure to environmental noise (van Kempen et al. 2018). However, during the peer-review process it was suggested that we could adopt the strategy used in a recent WHO evidence review on the effect of long-term air pollution on mortality (Huangfu and Atkinson 2020), which calculated the so-called E-values and considered a reference confounder to assess the likelihood of residual confounding (Verbeek et al. 2021). Since, neither of the two approaches is beyond reproach, we applied them both judiciously and in tandem. We therefore relied on two approaches to determine whether the quality of evidence should be upgraded for a large effect size.

## Financial support

All authors are salaried staff members of their respective institutions. This publication was prepared with financial support to the World Health Organization from the National Institute for Occupational Safety and Health of the Centres for Disease Control and Prevention of the United States of America (Grant 1E11OH0010676-02; Grant 6NE11OH010461-02-01; and Grant 5NE11OH010461-03-00); the German Federal Ministry of Health (BMG Germany) under the BMG-WHO Collaboration Programme 2020–2023 (WHO specified award ref. 70672); and the Spanish Agency for International Cooperation (AECID) (WHO specified award ref.71208). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

## Sponsors

The sponsors of this systematic review are the World Health Organization and the International Labour Organization.

## Author contributions

Conceived the idea for this systematic review: FP, Ivan Ivanov (WHO), Nancy Leppink (ILO).

Coordinated the entire series of systematic reviews: FP, Yuka Ujita (ILO).

Selected the lead reviewers and gathered the review team: FP, NCM, Ivan Ivanov, Nancy Leppink, Yuka Ujita.

Were the lead reviewers of this systematic review: DL, AMD.

Led the design of the systematic review including developed the standard methods: FP.

Contributed substantially to the design of the systematic review: DL, NCM, NC, NG, RLM, MMS.

Conducted the search: MMS.

Selected studies: DL, AMD, NC, AD, NG, S-KK, AM, RLM, MMS, AS, SZ.

Extracted data: DL, AMD, NC, AD, NG, S-KK, AM, RLM, MMS, AS, SZ.

Assessed risk of bias: DL, AMD, NC, AD, NG, S-KK, AM, RLM, MMS, AS, SZ.

Conducted the meta-analyses: DL, AMD, NCM, NG, FP.

Assessed quality and strength of evidence: DL, AMD, NC, AD, NG, AM, RLM.

Facilitated the quality and strength of evidence assessments: FP, NCM.

Developed the standards and wrote the template for all systematic reviews in the series: FP.

Wrote the first draft of the manuscript using the template: FP, NCM.

Revised the manuscript critically for important intellectual content: All authors.

Ensured tailoring of the systematic review for WHO/ILO estimation
purposes: FP, NCM.

Ensured harmonization across systematic reviews in the series: FP, NCM.

Approved the final version of the systematic review to be published: All authors.

Agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved: All authors.

## Disclaimer

The authors alone are responsible for the views expressed in this article and they do not necessarily represent the views, decisions or policies of the institutions with which they are affiliated.

## CRediT authorship contribution statement

**Dana Loomis:** Conceptualization, Investigation, Methodology, Project administration, Supervision, Validation, Writing – review & editing.
**Angel M. Dzhambov:** Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – review & editing.
**Natalie C. Momen:** Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Supervision, Validation, Visualization, Writing – review & editing.
**Nicholas Chartres:** Investigation, Methodology, Validation, Writing – review & editing.
**Alexis Descatha:** Data curation, Investigation, Validation, Writing – review & editing.
**Neela Guha:** Data curation, Formal analysis, Investigation, Methodology, Validation, Writing – review & editing.
**Seong-Kyu Kang:** Investigation, Validation, Writing – review & editing.
**Alberto Modenese:** Investigation, Validation, Writing – review & editing.
**Rebecca L. Morgan:** Investigation, Methodology, Validation, Writing – review & editing.
**Seoyeon Ahn:** Investigation, Validation, Writing – review & editing.
**Martha S. Martínez-Silveira:** Data curation, Investigation, Validation, Writing – review & editing.
**Siyu Zhang:** Investigation, Validation, Writing – review & editing.
**Frank Pega:** Conceptualization, Data curation, Formal analysis, Investigation, Funding acquisition, Methodology, Project administration, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing.

## Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Data availability

No data was used for the research described in the article.

## Acknowledgments

We thank Dr Paul Whaley (Editor, Systematic Reviews, *Environment International*; and Lancaster University) for the editorial review and guidance. Dr Kurt Straif (at the time: WHO IARC) contributed to the early stages of this systematic review. Dr Yuka Ujita and then Dr Halim Hamzaoui were the ILO focal point for the WHO/ILO Joint Estimates. Dr Nathan DeBono (WHO IARC), Bayan Hosseini (WHO IARC), Dr Ann Olsson (WHO IARC), and Professor Lesley Stayner (WHO IARC) provided comments on an earlier version of the manuscript.

## Appendix A. Supplementary material

Supplementary data to this article can be found online at https://doi.org/10.1016/j.envint.2022.107565.

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