Open Access Article
Solrunn
Hansen
*a,
Evert
Nieboer
b,
Natalia
Bravo
c,
Inger
Økland
d,
Silvinia
Matiocevich
e,
Marisa Viviana
Alvarez
f,
Stein Tore
Nilsen
g,
Joan O.
Grimalt
c and
Jon Øyvind
Odland
a
aDepartment of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, Box 6050 Langnes, NO-9037 Tromsø, Norway. E-mail: solrunn.hansen@uit.no; jon.øyvind.odland@uit.no; Tel: +47 77644836
bDepartment of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada. E-mail: nieboere@mcmaster.ca
cInstitute of Environmental Assessment and Water Research (IDAEA-CSIC), Department of Environmental Chemistry, Jordi Girona, 18, 08034 Barcelona, Catalonia, Spain. E-mail: natalia.bravo@idaea.csic.es; joan.grimalt@idaea.csic.es
dDepartment of Obstetrics and Gynecology, Stavanger University Hospital, P.O. Box 8100, N-4068 Stavanger, Norway. E-mail: inger.okland@sus.no
eBanco de Sangre, Clínica San Jorge, Onachanga 184, 9410 Ushuaia, Tierra del Fuego, Argentina. E-mail: matiocevichsilvina@hotmail.com
fHospital Público Materno Infantil de Salta, Sarmiento 1301, 4400 Salta, Argentina. E-mail: marisavivianaalvarez@gmail.com
gDepartment of Research, Stavanger University Hospital, P.O. Box 8100, N-4068 Stavanger, Norway. E-mail: stein.tore.nilsen@sus.no
First published on 29th September 2017
The EMASAR study is the first study to describe the body burden of OCs in Argentinian women after delivery. In total, 698 maternal serum samples from Salta (n = 498) and Ushuaia (n = 200) were collected in 2011–2012 and analyzed for a total of 7 polychlorinated biphenyls (PCBs) and 12 pesticide-related compounds. Only 11 of the compounds had detection rates above 60% in one or both places. Compared with Ushuaian women, those from Salta exhibited higher lipid-adjusted concentrations of p,p′-DDE, p,p′-DDT, β-HCH, and PCB 118 (p ≤ 0.003), with no differences in concentrations of PCB 153 and 138. After controlling for age, parity and heritage (born in the province or migrated there from other regions of Argentina), concentrations of p,p′-DDE, p,p′-DDT, β-HCH and all PCBs were significantly higher in Salta natives compared with Ushuaia natives or migrants (p ≤ 0.010). No variations between native and migrated Ushuaian women were observed other than for PCB 153 (6.1 versus 8.6 μg kg−1 lipid, p = 0.022). Age was generally associated positively with the body burden of nearly all OCs and parity negatively so, with p,p′-DDD, o,p′-DDT, and o,p′-DDD residues and α-HCH in Ushuaia being the exceptions. The regional differences in OC concentrations are explained by contrasting domestic sources, historical and current uses, industrial emissions, dietary patterns and lifestyle factors, as well as long-range-transport. The relatively high PCB 118/PCB 180 ratio observed for both Argentinian communities likely reflects the use of technical mixtures with congener-specific composition. In a comprehensive comparison with other countries, the Argentinian OC concentrations were mostly in the lower range. It is concluded that a latitude effect equivalent to that operative in the Arctic region seems unlikely.
Environmental significanceKnowledge about human exposure to organochlorine compounds (OCs) in Southern Hemisphere countries is limited. Polychlorinated biphenyls (PCBs) and pesticides in the sera of delivering women in Salta (a northwestern province) and Ushuaia (the most southern province) of Argentina reveal regional differences in concentrations and these are explained by contrasting domestic sources, historical and current uses, industrial emissions, dietary patterns, lifestyle factors and long-range-transport. A comprehensive comparison with other countries indicates that the Argentinian OC concentrations were mostly in the lower range. |
OCs are persistent, lipophilic, toxic and bioaccumulate in the food chain.3 The concentration of contaminants in maternal blood and breast milk provides important information on the exposure of the fetus and newborn, who are especially vulnerable. Endocrine disruption, reproductive effects, and impairment of immunologic development constitute worries and their adverse toxic effects may threaten human health (including trans-generational impairments).3
Knowledge about human exposure to OCs in South America is limited.12 The current study describes the body burden of OCs in Argentinian delivering women, and our findings are assessed in the context of comparable studies elsewhere. Our working hypothesis is that a phenomenon similar to the Arctic latitude-transport effect is not operative in the Southern Hemisphere.
000 and features electronics manufacturing, fisheries, natural gas and oil extraction, sheep farming, and tourism. Salta (24.78° S, 65.42° S) is the capital of the northwestern-highland Salta province. The city has around 620
000 citizens, with agriculture and related industrial activities being the main economic activities (for additional details see Økland et al., 2017).13
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| Fig. 1 Age- and parity-adjusted maternal serum OC concentrations (μg kg−1 lipid, geomean) with 95% CI error bars, stratified by residence (Ushuaia and Salta) and maternal birthplace (native or migrated) for compounds with a detection frequency > 60%. City differences (Ushuaia versus Salta) at p < 0.001 except for PCB 153 (p = 0.081). The p-values for differences between native and migrated groups are provided in Table 2; for full names of the compounds, see Section 2.2. | ||
The field work was conducted in the period April 2011 to March 2012. Of the total 698 delivering women enrolled, the current study component is limited to 670 subjects (199 from Ushuaia and 471 from Salta). One person from Ushuaia and 27 from Salta were excluded due to the lack of serum lipid concentrations. Through interviews, participants completed questionnaires covering personal characteristics, socioeconomic factors, obstetrical and breastfeeding history, environmental, health and lifestyle conditions, and dietary intake. Non-fasting maternal blood samples, height and weight were obtained at 36 ± 12 hours following delivery (median 1 day, range 0–3 days). Details about the study profile, population anthropometric measurements and blood sampling procedures have been provided previously.13
EMASAR is a collaborative project between UiT The Arctic University of Norway, the Stavanger University Hospital (Norway) and the two Argentinian partners, namely Clínica San Jorge in Ushuaia (a private institution co-responsible with a public hospital for the in-hospital deliveries in the city and the surrounding region), and the Hospital Público Materno Infantil in Salta (a public institution responsible for all in-hospital deliveries in the city and the region).
The study (#2010/7317) was approved by the Ethics Committee of the Salta Medical Association and the Ministries of Health in both provinces. As required by law, the Norwegian Regional Committee for Medical and Health Research Ethics (REC North) approved the study (#2011/706), and it was conducted in accordance with the Helsinki declaration. Informed consent was obtained for any experimentation with human subjects in the study.
The analytical work was conducted at the Department of Environmental Chemistry, Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Catalonia, Spain. Serum samples were analysed for the following organochlorines (OCs): pentachlorobenzene (PeCB); α- and β-HCB (hexachlorobenzene); α-, β- δ- and γ-HCH (hexachlorocyclohexane); 1,1,1-trichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)ethane (o,p′-DDT); 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (p,p′-DDT); 1,1-dichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)ethane (o,p′-DDD); 1,1-dichloro-2,2-bis(p-chlorophenyl)ethane (p,p′-DDD); 1,1-dichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)ethylene (o,p′-DDE); 1,1-dichloro-2,2-bis(p-chlorophenyl) ethylene (p,p′-DDE); and polychlorinated biphenyl (PCB) congeners 28, 52, 101, 118, 138, 153 and 180. The analytical procedures employed have been described elsewhere by Bravo et al. (2017).14 Briefly, recovery standards TBB and PCB-209, n-hexane and concentrated H2SO4 were added to the serum samples (1 ml). After vortexing and centrifugation, repeated extraction of the serum n-hexane layer followed and the combined extracts were reduced to near dryness. The remaining solution was quantitatively transferred to gas chromatograph (GC) vials using four 25 μl rinses of isooctane and the injection standard PCB-142 (20 μl) was added. Instrumental analysis was performed by gas chromatography with electron capture detection. Compound identification was confirmed by analysis with a GC coupled to a mass spectrometer. A blank was analysed for every 6 samples. The recoveries of the surrogate standards were 76 ± 13% and 82 ± 14% for PCB-30 and PCB-200, respectively. The measured concentrations of the compounds were adjusted for the recoveries of these standards. The limits of detection were calculated as three times the standard deviation of the noise measured next to the chromatographic peaks of each analyte: they ranged from 0.01 to 0.027 μg l−1 (Table 1). Moreover, the analytical methods fared well (within 20% variability of the consensus values) in the AMAP Ring Test Proficiency Program for Persistent Organic Pollutants in human serum conducted by the Centre de Toxicologie Institut National de Santé Publique du Québec.15
| Compounda | LODa | Ushuaia (n = 199) | Salta (n = 471) | p-Valueb | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| % ≥ LOD | GM | AM | Median | Min | Max | % ≥ LOD | GM | AM | Median | Min | Max | |||
| a For the full names of the compounds see Section 2.2; the limit of detection (LOD) is in μg l−1. b Mann Whitney test for compounds with a detection frequency > 60%. c Detection frequency < 20%. | ||||||||||||||
| PCB28 | 0.010 | 32.7 | 1.3 | 2.1 | 0.9 | 0.3 | 14.2 | 24.0 | 1.2 | 1.7 | 0.9 | 0.4 | 17.4 | |
| PCB52 | 0.005 | 38.2 | 1.04 | 2.84 | 0.47 | 0.21 | 37.9 | 33.1 | 0.94 | 2.68 | 0.50 | 0.22 | 59.3 | |
| PCB101 | 0.001 | 56.3 | 0.70 | 2.59 | 0.72 | 0.06 | 25.2 | 16.1 | 0.18 | 0.46 | 0.13 | 0.06 | 16.1 | |
| PCB118 | 0.011 | 64.8 | 3.1 | 5.6 | 3.8 | 0.5 | 66.9 | 79.0 | 5.7 | 9.1 | 7.1 | 0.6 | 163 | <0.001 |
| PCB138 | 0.002 | 97.0 | 6.32 | 8.84 | 7.06 | 0.13 | 45.4 | 97.0 | 6.36 | 9.91 | 7.04 | 0.18 | 172 | 0.900 |
| PCB153 | 0.008 | 97.0 | 9.13 | 12.19 | 9.80 | 0.48 | 51.7 | 94.3 | 8.08 | 11.60 | 8.80 | 0.48 | 144 | 0.091 |
| PCB180 | 0.011 | 36.7 | 1.7 | 3.2 | 1.0 | 0.4 | 38.2 | 30.1 | 1.7 | 3.4 | 1.1 | 0.5 | 62.5 | |
| p,p′-DDT | 0.005 | 89.4 | 3.22 | 14.29 | 3.47 | 0.31 | 1950 | 97.0 | 6.83 | 12.32 | 6.32 | 0.31 | 334 | <0.001 |
| p,p′-DDE | 0.013 | 99.0 | 38.5 | 196.5 | 32.7 | 1.2 | 23 800 |
100 | 80.2 | 228.3 | 69.0 | 3.69 | 12 100 |
<0.001 |
| p,p′-DDD | 0.002 | 81.4 | 1.63 | 2.89 | 2.41 | 0.13 | 71.5 | 52.0 | 0.60 | 1.17 | 0.67 | 0.09 | 23.3 | |
| o,p′-DDT | 0.005 | 66.3 | 1.61 | 2.71 | 2.22 | 0.26 | 15.3 | 15.7 | 0.55 | 0.94 | 0.43 | 0.20 | 30.5 | |
| o,p′-DDE | 0.013 | 47.7 | 2.2 | 3.4 | 1.4 | 0.5 | 22.5 | 15.3 | 1.4 | 2.2 | 1.2 | 0.6 | 57.5 | |
| o,p′-DDD | 0.007 | 68.8 | 2.31 | 4.02 | 2.97 | 0.32 | 29.9 | 24.2 | 0.95 | 1.56 | 0.66 | 0.30 | 21.3 | |
| ∑DDT | 60.0 | 223.8 | 49.9 | 8.1 | 25 900 |
99.5 | 246.5 | 83.2 | 9.7 | 12 400 |
<0.001 | |||
| PeCB | 0.006 | 22.6 | 0.72 | 1.18 | 0.52 | 0.20 | 11.8 | 4.20 | —c | —c | 0.51 | 0.26 | 9.7 | |
| HCB | 0.027 | 80.9 | 10.0 | 19.0 | 9.8 | 1.4 | 499 | 57.1 | 5.9 | 8.9 | 7.1 | 1.5 | 102 | |
| α-HCH | 0.007 | 86.9 | 4.42 | 7.64 | 4.84 | 0.37 | 59.9 | 33.5 | 1.44 | 4.77 | 0.67 | 0.32 | 47.2 | |
| β-HCH | 0.010 | 61.3 | 6.0 | 21.2 | 7.8 | 0.5 | 281 | 71.3 | 9.4 | 31.0 | 13.7 | 0.5 | 483 | 0.003 |
| δ-HCH | 0.020 | 17.6 | 2.1 | 3.7 | 1.7 | 0.7 | 45.7 | 19.5 | 2.7 | 6.0 | 1.8 | 0.9 | 74.4 | |
| γ-HCH | 0.013 | 19.1 | —c | —c | 1.1 | 0.4 | 24.7 | 1.1 | —c | —c | 1.1 | 0.6 | 26.6 | |
Chemical analyses of the serum lipid profile (Økland et al., 2017)13 were done enzymatically at the respective hospitals. Total lipid contents were calculated from the cholesterol and triglyceride concentrations: total lipids = 90 + 1.3 (cholesterol + triglyceride) mg dl−1.16
10 transformation, the OC distributions remained skewed positively to the right and were not normally distributed according to the Kolmogorov–Smirnov test and Q–Q residual plots. We therefore employed non-parametric statistics (the Mann–Whitney U test) for comparisons of OC concentrations between the two study sites. For related compounds, Levene's test demonstrated equal variances between the two study sites. In a univariate general linear model (UGML) adjusted for the continuous variables age and parity (excluding stillbirths), acceptable case-wise diagnostics were possible even though abruptions of normality were evident based on histograms, the Kolomogorov–Smirnov test and residual plots. Parity (excluding stillbirths) and months of lactation were highly correlated (Spearman's ρ = 0.937), with the former displaying the highest correlation with OC concentrations; it was thus selected in the modelling. Nevertheless, lactation yielded similar results (not reported). To harmonize the group size, and thus the distribution, bootstrapping with 2000 estimates was selected. Between city comparisons (Ushuaia versus Salta) and maternal birthplaces involved four groups: (i) born and living in Ushuaia (natives, n = 61); (ii) living in Ushuaia, but born in another province within Argentina (migrated, n = 128); (iii) living and born in Salta (natives, n = 409); and (iv), living in Salta but born in another province within Argentina (n = 38). In the regression model, the coefficients for the OCs were estimates of the mean difference in log-transformed concentrations between each group (city or heritage) and the reference level. The regression coefficients were back-transformed (10β) to reflect the ratios of change in concentrations, and in the text are described as % change = (10β − 1) × 100. The significant levels were set at p < 0.05. Finally, the ratios within the DDT group were calculated to distinguish ongoing chronic exposure versus dietary exposure or distant past exposure.3,18
Several significant statistical differences (p ≤ 0.010) were observed when considering residence history in terms of being native born or migrants to the two regions of Argentina (Table 2). Relative to Salta natives, those of Ushuaia had 27% lower concentrations of PCB 138 and 32% of PCB 153; and migrants into Ushuaia also exhibited reduced concentrations of PCB 118 and PCB 138 (respectively, by 47% and 25%), but not so for PCB 153. In addition, Ushuaian migrants had 46% less serum PCB 118 than those in Salta. The p,p′-DDE and p,p′-DDT concentrations for Ushuaian natives and migrants were less substantive by 60% and 70% when compared to the respective groups in Salta (Table 3). Ushuaia migrants had 58% lower concentrations of β-HCH compared to Saltanean natives (post hoc analysis). Intra-city differences in OC concentrations between native and migrated women in Salta did not reach statistical significance; nor for Ushuaians, with the exception that PCB concentrations in native citizens were on average 29% lower (Table 2; also see Table S4†). Age had a positive influence on OC concentrations and parity a negative one (p < 0.05). The statistical significance for these variables was lost for Ushuaia residents when examining each community separately (e.g., Table S5†), but persisted for all OCs in Salta (data not shown).
| Groups | n | PCB 153 | p-Value | CI 95% | PCB 138 | p-Value | CI 95% | PCB 118 | p-Value | CI 95% | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GM | Ratio | GM | Ratio | GM | Ratio | |||||||||||
| a Univariate analyses of variance models based on detection frequencies above 60% in each population group and bootstrap with p-values and 95% CI based on 2000 samples. b Blanks indicate detection frequencies below 60%, and the corresponding data were excluded from the analyses. c Bonferroni post hoc pairwise comparisons: for PCB 153, the Ushuaia natives/Ushuaia migrated concentration ratio was 0.71, p = 0.022; for PCB 118, the Ushuaia migrated/Salta migrated ratio was 0.54, p = 0.004; and for both p,p′-DDT and p,p′-DDE, the Ushuaia natives and Ushuaia migrated/Salta migrated ratios were ∼0.40, p < 0.001. | ||||||||||||||||
| Ushuaia natives | 61 | 6.07 | 0.68 | 0.008 | 0.52 | 0.91 | 5.14 | 0.73 | 0.010 | 0.57 | 0.93 | |||||
| Ushuaia migrated | 128 | 8.55 | 0.96 | 0.679 | 0.81 | 1.14 | 5.25 | 0.75 | 0.008 | 0.61 | 0.91 | 3.13 | 0.53 | <0.001 | 0.42 | 0.67 |
| Salta natives | 409 | 8.87 | Ref. | 7.01 | Ref. | 5.93 | Ref. | |||||||||
| Salta migrated | 38 | 7.36 | 0.83 | 0.200 | 0.61 | 1.13 | 6.62 | 0.94 | 0.625 | 0.77 | 1.19 | 5.83 | 0.98 | 0.929 | 0.68 | 1.40 |
| Age, year | 1.05 | <0.001 | 1.03 | 1.06 | 1.06 | <0.001 | 1.04 | 1.07 | 1.02 | 0.013 | 1.01 | 1.04 | ||||
| Parity | 0.82 | <0.001 | 0.76 | 0.87 | 0.78 | <0.001 | 0.72 | 0.84 | 0.88 | 0.001 | 0.81 | 0.95 | ||||
| Groups | n | p,p′-DDT | p-Value | CI 95% | p,p′-DDE | p-Value | CI 95% | β-HCH | p-Value | CI 95% | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| GM | Ratio | GM | Ratio | GM | Ratio | |||||||||||
| Ushuaia natives | 61 | 2.88 | 0.41 | <0.001 | 0.30 | 0.53 | 28.4 | 0.31 | <0.001 | 0.22 | 0.43 | |||||
| Ushuaia migrated | 128 | 3.00 | 0.42 | <0.001 | 0.35 | 0.51 | 28.2 | 0.30 | <0.001 | 0.24 | 0.38 | 4.7 | 0.42 | <0.001 | 0.28 | 0.62 |
| Salta natives | 409 | 7.06 | Ref. | 92.9 | Ref. | 11.2 | Ref. | |||||||||
| Salta migrated | 38 | 6.93 | 0.98 | 0.864 | 0.78 | 1.24 | 73.5 | 0.79 | 0.206 | 0.56 | 1.14 | 13.9 | 1.23 | 0.424 | 0.71 | 2.11 |
| Age, year | 1.03 | 0.001 | 1.01 | 1.04 | 1.08 | <0.001 | 1.06 | 1.10 | 1.09 | <0.001 | 1.06 | 1.12 | ||||
| Parity | ![]() |
![]() |
0.92 | 0.012 | 0.86 | 0.97 | ![]() |
0.65 | <0.001 | 0.60 | 0.70 | 0.56 | <0.001 | 0.50 | 0.64 | |
| PCB 118 | PCB 138 | PCB 153 | p,p′-DDT | p,p′-DDE | p,p′-DDD | o,p′-DDD | o,p′-DDT | HCB | α-HCH | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
| a Results are presented for compounds with a detection frequency > 60%. ** Significant correlation at the 0.01 or * 0.05 level (2-tailed). | |||||||||||
| Ushuaia (n = 199) | PCB 138 | 0.632** | |||||||||
| PCB 153 | 0.595** | 0.758** | |||||||||
| p,p′-DDT | 0.222** | 0.339** | 0.301** | ||||||||
| p,p′-DDE | 0.259** | 0.510** | 0.465** | 0.381** | |||||||
| p,p′-DDD | 0.073 | −0.106 | 0.118 | 0.172* | −0.046 | ||||||
| o,p′-DDD | 0.417** | 0.180* | 0.148* | 0.046 | 0.084 | 0.177* | |||||
| o,p′-DDT | 0.103 | −0.008 | 0.142 | 0.197** | 0.021 | 0.646** | 0.119 | ||||
| HCB | 0.192** | 0.348** | 0.233** | 0.249** | 0.464** | −0.002 | −0.070 | 0.011 | |||
| α-HCH | 0.099 | −0.060 | 0.114 | −0.115 | −0.064 | 0.534** | 0.305** | 0.401** | −0.046 | ||
| β-HCH | 0.292** | 0.388** | 0.445** | 0.151* | 0.474** | −0.073 | 0.029 | 0.050 | 0.321** | −0.068 | |
| Salta (n = 471) | PCB 138 | 0.589** | |||||||||
| PCB 153 | 0.592** | 0.899** | |||||||||
| p,p′-DDT | 0.223** | 0.420** | 0.343** | ||||||||
| p,p′-DDE | 0.124** | 0.414** | 0.384** | 0.564** | |||||||
| β-HCH | 0.288** | 0.411** | 0.379** | 0.312** | 0.553** | 0.205** | |||||
![]() | ||
| Fig. 2 Worldwide comparisons of serum or plasma p,p′-DDT and p,p′-DDE (μg kg−1 lipid, geomean) of pregnant or delivering women for the 2004–2014 period. *p,p′-DDT, not reported due to high numbers of non-detections. For details and references, see the text and ESI S6 a and b.† | ||
![]() | ||
| Fig. 3 Worldwide comparisons of serum or plasma β-HCH and HCB (μg kg−1 lipid, geomean) of pregnant or delivering women for the 2004–2014 period. *Not reported due to high numbers of non-detections. For details and references, see the text and ESI S6c and d.† | ||
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| Fig. 4 Worldwide comparisons of serum or plasma PCB 153 (μg kg−1 lipid, geomean) of pregnant or delivering women for the 2004–2014 period. For details and references, see the text and ESI S6e.† | ||
The Argentinian p,p′-DDT concentrations observed (Fig. 2) were lower than in countries with a previous or current history of DDT usage.17,19,22,27,29 Comparable p,p′-DDT levels to those in Salta have been observed in Mexico,28 Northern Greenland and Faroe Island3 and the non-malaria Indian Ocean area in South Africa.19 The Ushuaian levels were slightly higher than those found in Alaska and Iceland.3 Finally, our observed concentrations of DDT-related compounds were higher (p,p′-DDE), comparable (p,p′-DDT) or lower (p,p′-DDD) than those reported for an adult population of Buenos Aires in 2006.12
Relative to Ushuaia, the higher concentrations of p,p′-DDT (and thus also p,p′-DDE) in Salta are in agreement with the nearly ten-fold higher use of insecticides in the home and perhaps in agriculture.13 Several decades ago this compound was used for malaria vector control in the northwestern regions.4 The current presence of low levels p,p′-DDT and the relatively high concentrations of its derivative p,p′-DDE point to past comprehensive use and ongoing entry into the local food web.4,6,7,9 The observed p,p′-DDE/p,p′-DDT ratio of around 20 in the two communities (Table S4†) is consistent with historical use of the latter.18 Nevertheless, chronic or more recent exposure to DDT cannot be excluded as one in five women in both communities had ratios below 5. The o,p′-DDT/p,p′-DDT ratio is a useful index in regions with active use of dicofol.30 In Ushuaia, the relatively high o,p′-DDT/p,p′-DDT ratio of 1.09 compared to 0.29 in Salta (Table S4†) suggests some recent DDT input,18 and is likely related to dicofol use.30–32 Atmospheric release of dicofol in the province of Mendoza in western-central Argentina has also been reported,9 and this insecticide still appears to be in use.10 Furthermore, long-range transport of the relatively volatile Dicofol from neighboring regions and countries, or other southern continents, might also have some influence.33,34
Before the use of pure lindane (γ-HCH) technical mixtures were used, which encompassed isomeric compositions of 60–70% α-HCH, 5–12% β-HCH and 10–15% γ-HCH.36 Generally speaking, data on human maternal body burdens of α-HCH are scarce and are low or below the detection limit for mothers in China,27 Australia,23 Canada and Mexico.28 Our Argentinian levels (Table 1), particularly those in Ushuaia, are comparable in magnitude to those reported in South Africa (2 μg kg−1 lipid)37 and China (5.2 μg kg−1 lipid).38 As depicted in Fig. 3, the observed β-HCH concentrations were higher than those from Canada, Greenland and Alaska,3 comparable to those from Mexico,28 Korea20 and South Africa,39 but lower than those reported for the Faroe Island3 and Spain.24 The high concentrations observed in China are consistent with its extensive organochlorine pesticide production and use.27 The generally low β-HCH concentrations among Arctic populations contrast those of other OCs, and perhaps reflect decades of worldwide restrictions and prohibitions.
The observed HCB, α-HCH and β-HCH concentrations likely reflect regional diversities in past emissions. HCB is still released into the Argentinian environment as a by-product of pesticide use, various industrial activities, open burning processes, waste disposal and landfills.9 The 3-fold higher α-HCH levels in Ushuaia, and its lack of a relationship with HCB, PCBs, p,p′-DDT and p,p′-DDE (Table 3) may reflect source-specific pathways. It is known that α-HCH is retained less in nature and humans than β-HCH.36 Their comparable concentrations in Ushuaia mothers remain unexplained, as is the observation in China that α-HCH levels exceeded those of β-HCH.38 Atmospheric long-range transportation of this semi-volatile HCH to colder climates may be relevant. Furthermore, the relatively higher exposure to the water-insoluble β-HCH in Salta suggests greater historical local usage of HCH pesticides compared with more central and southern remote areas. The positive correlations of β-HCH at both sites with both PCBs and p,p′-DDE (see Table 3) suggest common sources of exposure, while the scarcity of γ-HCH is consistent with its lower bioaccumulation potential and more rapid degradation in nature.36 By contrast, a study in South Africa showed almost non-detectable maternal concentrations of HCB, α-HCH and β-HCH and a complete predominance of γ-HCH – this was explained by on-going use of lindane.37
Despite prohibitions, Argentinian electric power-generation equipment, aged industrial plants, stockpiles and the other sources already mentioned continue to be sources of PCBs and continue to impact the environment and thus the food chain.9,11 However from a global perspective, the Argentinian production and use of PCBs have been low. It is estimated that only 3% of the total global historical use of PCB occurred in the Southern Hemisphere, with Argentina contributing 0.1%.40 This is consistent with the data for PCB 153 in Fig. 4.
Age as a positive predictor of serum OC concentrations and parity and previous breastfeeding as negative ones are well understood.35,44 Because of the relatively long half-lives (in years) of OCs (typically > 7 years),45 body burdens increase over time. OC storage in lipid tissues and loss via breastfeeding explain the observed negative impact of parity.
In Argentina, dietary foodstuffs are typically produced within the nation, but with regional differences. Extensive importation of foods into Ushuaia suggests an additional contrasting factor. OCs are often associated with animal lipid-rich aquatic and terrestrial food web sources, including dairy products and eggs, or even fruit, vegetables and grains.35,41,46 As indicated by others6 and confirmed in our recent publication,13 fish contributed only 10–15% of the Argentinian diet. Argentinian studies have also suggested that freshwater species contain OCs due to the pollution of rivers.6,11 Consumption of fatty meats and freshwater fish has been identified as a dietary predictor variable of OCs in Argentinian women.47 Such sources would likely affect the inland residents of Salta more.
Salta province in the north has a subtropical climate, while Tierra del Fuego is at a lower latitude and has a cooler climate. Its prevailing winds are from the south-west, and thus a latitude effect equivalent to that operative in the Arctic region seems unlikely. However, Ushuaia's expanding industry, economy, population and tourism constitute environmental challenges that include heavily polluted waterfronts and limited waste-disposal systems.8
Low detection frequencies for some compounds might have introduced some bias into the statistical analyses. A few cases of extreme values of DDTs were also found, but sensitivity analyses supported their inclusion. We acknowledge that our comparisons of our data with those of multiple studies are subject to uncertainties related to varying methodological and analytical variances. However, most of the publications referred to employed the AMAP study approach, and the respective laboratories have participated in the mentioned Inter-laboratory Ring test.3 Our use of lipid-adjusted concentrations in our comparisons might have helped to minimize bias such as that associated with different pregnancy sampling periods.18,44
Footnotes |
| † Electronic supplementary information (ESI) available. See DOI: 10.1039/c7em00278e |
| ‡ Full names of the abbreviations used are provided in Section 2.2. |
| This journal is © The Royal Society of Chemistry 2017 |