1. Introduction
Persistent organic pollutants (POPs) are a heterogeneous group of toxic chemicals that are highly resistant to biological degradation with a high bioaccumulation potential in living organisms, so it is believed that internal body burden of certain POPs increases over life span [1,2]. This continuous exposure might pose relevant risks to human health, since POP exposure is suspected to increase the risk of certain chronic and highly prevalent conditions, e.g., type 2 diabetes, cardiovascular disease, or cancer [3]. POPs include diverse chemical groups such as Polychlorinated Biphenyls (PCBs), which have been used in industrial applications, and Organochlorine Pesticides (OCPs) used in agriculture [4].
Hexachlorocyclohexanes (HCHs) are OCPs with several chemical forms, such as α-, β-, δ-, and γ-HCH, the latter also named lindane, which exerts the most effective insecticidal properties [5]. Despite these four isomers being present in the technical HCH, α-HCH is the most prevalent [6]. However, β-HCH is more resistant to degradation, more prone to bioaccumulate in living organisms and consequently is the most abundant in human tissues [7]. In fact, its half-life in fatty tissues has been estimated in the range of 7–10 years [8]. Dicofol is another OCP which has been used as an acaricide in field crops [9]. Dicofol is synthesized from technical dichlorodiphenyltrichloroethane (DDT), sharing similar chemical structures [10], and containing DDT as an impurity [11].
Long-term human exposure to OCPs has been documented to be related to adverse effects on health, such as neurological, reproductive, and immunological disorders [12]. Moreover, it has been associated with an increased risk of several types of cancers, such as breast, prostate, lung, stomach, colorectal, and bladder [13,14,15,16], and even with type 2 diabetes [17]. Thus, the Spanish Government banned the use of HCH containing less than 99 percent of γ-isomer in 1994 [18] and dicofol in 2009, although the latter remained in use until 2010 [19]. Moreover, three HCH isomers (α-, β-, and γ) and dicofol were included in the list of POPs of concern at the Stockholm Convention in 2009 and 2013, respectively [20,21]. Nevertheless, despite the legal restrictions on their use and production, a number of POPs can be detected in virtually all humans [22,23].
Regardless of their potential relevance for human health, the abovementioned OCPs have remained relatively understudied in human biomonitoring (HBM) studies in comparison to other POPs such as DDT or hexachlorobenzene (HCB), probably because of lower detection limit in human samples.
HBM on α-, β-HCH, and dicofol has mainly focused on lipid-rich biological matrices, such as breast milk and the lipid fractions of serum and blood. Nevertheless, the concentrations in these matrices can be highly variable and not always reflect the total body burden [24]. In this regard, adipose tissue has been suggested as the most adequate matrix for estimating the long-term exposure to these chemicals [25]. However, HBM studies using adipose tissue are still relatively scarce, mostly because of the difficulties in accessibility [26,27,28,29,30,31,32].
In this context, this study represents a continuation of the previous work carried out by our research group, focused on the characterization of OCPs and other environmental pollutant exposures in humans, as well as their potential health outcomes [16,17,33,34,35,36]. The present study aimed to identify bioaccumulation patterns of α-, β-HCH, and dicofol in relation to sociodemographic, dietary, and lifestyle factors, in an adult cohort from Southern Spain.
2. Materials and Methods
2.1. Study Design, Characteristics of Participants, and Setting
The present cross-sectional research is framed within a larger cohort study focused on characterizing the influence of environmental factors on human health in the GraMo cohort (Granada province, Southern Spain). From July 2003 to June 2004, patients undergoing non-cancer-related surgery (41% hernias, 21% gallbladder diseases, 12% varicose veins, and 26% other conditions) in two public hospitals of Granada province (San Cecilio University Hospital in Granada city and Santa Ana Hospital in Motril) were invited to participate in the study. Both hospitals serve the population from the Center-Western and Southern areas of Granada province. The participants had to meet the following inclusion criteria: (1) age over 16 years, (2) absence of cancer diagnosis, (3) not receiving hormonal therapy, and (4) residence for the last 10 years prior to recruitment in the reference area of any of the two participant hospitals. Out of the 409 individuals contacted, a total of 387 (94.6%) participants accepted to participate in our study. Adipose tissue samples were collected from pelvic waist (50%), front abdominal wall (40%), and limbs (10%). A wider description of the GraMo cohort methodology, including characterization of other exposures, has been reported elsewhere [4,22,37,38].
All participants were informed about the study characteristics and signed a written informed consent before their inclusion in the study.
2.2. Sampling and α-, β-HCH, and Dicofol Analysis
Bioaccumulation of α-, β-HCH, and dicofol was estimated by analyzing their residues in adipose tissue samples collected at recruitment. 5–10 g of adipose tissue were obtained during routine surgery in the two participating hospitals. Samples were coded and stored immediately at −80 °C. Chemical analyses were performed by high-resolution gas chromatography with a mass spectrometry detector in tandem mode with a system Saturn 2000 ion trap (Varian, Walnut Creek, CA, USA) at Laboratorio Analítico Bioclínico (LAB) in Almería (Spain). The methodological aspects have been detailed elsewhere [39,40]. Lipid content in adipose tissue samples was quantified by gravimetry, as reported by Rivas et al. [40]. Normalized POP levels were expressed in nanograms per gram of lipid (ng/g lipid).
2.3. Data sources and Independent Variables
During the hospital stay, a structured questionnaire was administered face-to-face to each participant by trained interviewers to gather information on socio-demographic characteristics, lifestyles, diet, and health status. The questionnaire was validated in previous studies [41,42]. Body mass index (BMI) was calculated from height and weight and expressed as Kg/m2. A participant was considered a smoker at recruitment at ≥1 cig/day. The residence of a participant was classified in 6 sub-areas, according to their residence: Coast region, Motril, Granada city, Granada Metropolitan Area, Poniente, and Alpujarras. The sub-areas (Alhama, Baza, and Valle de Lecrín) with ≤6 participants were excluded from the analysis. Later, the residence was recategorized in the following 3 areas: (1) Motril city and coast region and both areas in the Mediterranean coast, with large agriculture zones and greenhouses where the use of pesticides is higher; (2) Granada city and Granada Metropolitan Area, as both are urban areas with a high amount of traffic and whose main economic activity is based on industry and tourism; (3) Poniente and Alpujarras, both rural areas with less population and an agricultural tradition [4] (Figure 1). Thus, the total pesticide use in Granada province over recruitment (years 2003 and 2004) remained virtually constant (1953.03 and 2053.73 tons, respectively) [43].
The dietary information on drinking water and consumption of meat, cold meats, fats, fish, eggs, milk, cheese, vegetables, legumes, fruit, bread, and pasta was obtained from a food frequency questionnaire. Water consumption referred to the quantity consumed regardless the type of water (bottled or not, or both). A participant was considered a consumer of a specific food item at a weekly consumption of ≥1 portion.
2.4. Statistical Analyses
OCP concentrations in adipose tissue were described as medians, and 25th and 75th percentiles, as well as percentages over the limit of detection (LOD).
Concentrations of β-HCH were natural-log transformed to reduce the skewed distribution, and their bioaccumulation pattern in relation to sociodemographic, dietary, and lifestyle factors were identified by means of multivariable linear regression, using a combination of backward and forward variable selection techniques. In this regard, beta coefficients indicate the average change in log-transformed pollutant concentrations associated to a 1-unit increase in the continuous predictor, or the average change in log-transformed concentrations in a given level of a categorical predictor compared to the reference level. Concentrations below the LOD (15.8%) were assigned a random value between 0 and LOD.
α-HCH and dicofol levels (% >LOD = 21.7 and 19.6%, respectively) were dichotomized (>LOD/<LOD) due to their relatively low number of samples with concentrations >LOD, and associated factors were explored by using unconditional binary logistic regression. Thus, the strength of the associations in these models are displayed as Odds Ratio (OR), i.e., odds of having detectable concentrations in a particular level of the predictor, compared to the odds of having detectable concentrations in the reference category of the predictor. In the case of continuous predictors, the OR could be interpreted as the change in the likelihood for having detectable dicofol levels per 1-unit increase in the predictor. Age, BMI, and sex (the latter in the non-stratified models) were always included in all models, regardless of their statistical significance, based on reported evidence of their association with OCP exposure. Independent variables were retained in the models based on their statistical significance, changes in R2 (linear regression) or pseudo-R2 (logistic regression), internal validity and coherence, and magnitude of effect estimates in order to explore the predictors of α-, β-HCH, and dicofol. In order to assess consistency between linear and logistic regression models, an additional sensitivity logistic regression analysis was performed using dichotomized β-HCH levels as the dependent variable to resemble the categorization for α-HCH and dicofol (80% vs. <20% of the sample). We also performed stratified analyses by sex, since several studies have evidenced differential OCP exposure levels and predictors in males and females in GraMo and other studies [22,30,38,44,45,46,47,48,49]. All statistical test were performed two-sided, and the level of statistical significance was set at p = 0.05. Stata 15 (Stata Corp., College Station, TX, USA, 2017) was used to perform all data analyses.
3. Results
3.1. Characteristics of the Study Population and Adipose Tissue OCP Concentrations
Characteristics of all study participants are summarized in Table 1. An additional description stratified by sex is provided as Supplementary Material (Table S1). From the 387 participants, there was a slightly higher number of males (50.9%). Mean age and BMI of the study population were 50.7 ± 17.1 years and 27.4 ± 5.4 kg/m2, respectively. The majority of the population (45.8%) lived in Motril city and Coast region.
Concentrations of β-HCH, α-HCH, and dicofol were detected in the adipose tissue of 84.2%, 21.7%, and 19.6% of the participants, respectively. Β-HCH showed the highest dispersion in their levels (25th: 3.7 and 75th: 21.4 ng/g lipid), whereas α-HCH and dicofol presented the lowest dispersion (25th: <LOD and 75th: <LOD) (Table 1). Stratified by sex, females showed higher β-HCH median levels (50th: 16.1 ng/g lipid) compared to males (50th: 7.3 ng/g lipid) (Supplementary Material, Table S1).
3.2. Predictors of Adipose Tissue α, β-HCH, and Dicofol Concentrations
The multivariable models exploring the predictors of β-HCH, α-HCH, and dicofol exposure explained, respectively, 42%, 41%, and 15% of the variability of adipose tissue levels (Table 2). After sex-stratification, the models explained, respectively, 45%, 39%, and 26% of the variability of females’ and 41%, 47%, and 14% of males’ concentrations (Supplementary Material, Tables S2 and S3).
Age, BMI, residence in Poniente and Alpujarras, mother’s occupation in agriculture during pregnancy, and water, white fish, and milk consumption were associated with increased β-HCH concentrations. On the other hand, lower β-HCH concentrations were related to males, residence close to an agriculture area, having worked for ≥10 years in agriculture, and beer consumption. Similar associations were found in the logistic regression models using dichotomized β-HCH levels as the dependent variable (Supplementary Material, Table S4). In sex-stratified analyses, age and BMI remained as significant predictors in both males and females. Among males, increased β-HCH levels were related to residence in Poniente and Alpujarras, mother’s occupation in agriculture during pregnancy, as well as white fish and water consumption. In addition, lower β-HCH levels were associated with beer consumption, residence near an agriculture area, and occupation for ≥ 10 years in agriculture. Among females, β-HCH levels were positively related to milk and cheese consumption, and negatively with residence close to agriculture areas.
Results from the multivariable logistic models for adipose tissue α-HCH levels are displayed in Table 2. Age, BMI, milk consumption, and mother’s occupation in agriculture during pregnancy were associated with increased odds of having detectable α-HCH concentrations, whereas males and residents in Granada city and Granada Metropolitan Area, Poniente, and Alpujarras showed lower odds (Table 2). After sex-stratification, detectable α-HCH levels were positively associated with age in both sexes. In addition, BMI (in females), mother’s occupation in agriculture during pregnancy (in males), as well as meat consumption ≥2 portions/week (in males) were positively associated with increased odds of detectable α-HCH concentrations. Furthermore, residence in Granada city and Granada Metropolitan Area, Poniente, and Alpujarras showed a negative association with detectable α-HCH concentrations both in males and females. Living close to an agriculture area (in females) was negatively associated with α-HCH levels (Supplementary Material, Tables S2 and S3).
Finally, lower odds of detectable dicofol levels were found in smokers, white fish and water consumers, residents in Granada, Granada Metropolitan area, Poniente, Alpujarras, and those living close to an agriculture area (Table 2). In the sex-stratified analyses, white fish intake, and residence close to an agriculture area remained negatively associated with detectable dicofol levels in females, whereas negative associations were found for water intake and smoking in males. The previously observed negative association with residence in Granada city and Granada Metropolitan Area remained significant in both sexes (Supplementary Material, Tables S2 and S3).
In order to assess the potential confounding effect of adipose tissue origin on the results, sensitivity analyses were performed by adjusting every model by adipose tissue location (pelvic waist, front abdominal wall, limbs), with no relevant change in the observed associations (data not shown).
4. Discussion
In this study we observed markedly different bioaccumulation patterns in adipose tissue of the selected HCH isomers and dicofol, both in their magnitude and in the determinants of their concentrations. A cluster of factors might explain these findings, including dissimilar uses, chemical properties, and the different time frames when the use of these chemicals was permitted in the region. The present research was prompted by our previous findings on differential predictors of other OCPs concentrations in this cohort, as well as their potential long-term health effects that might be produced as a consequence of the exposure to individual chemicals, but also to mixtures of them [17,22,36,38,50]. Therefore, careful analysis of individual chemical concentrations, even those at low detection rates, is warranted as a first step for exposure assessment.
A summary of HBM studies on α-HCH, β-HCH, and dicofol concentrations published during the last 10 years is shown in Supplementary Material, Table S5. There are still a few HBM studies using adipose tissue [26,27,28,29,30,31,32], breastmilk [51,52,53,54,55,56,57], placenta [58], and meconium [59] as biological matrices to assess the OCPs exposure compared to the number of studies using serum [45,46,47,48,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94,95,96,97], blood [98,99,100,101,102,103,104,105,106], and plasma [5,49,107,108,109,110,111,112,113,114]. Moreover, two studies used two biological matrices such as serum and placenta [115] or serum and omentum fat [116]. In general, in comparison to those countries where α, β-HCH were no longer used at the recruitment moment [29,31,32,48], we found lower adipose tissue α, β-HCH concentrations in the GraMo cohort, although we also observed a β-HCH higher concentration in other studies [32,116]. Regarding dicofol, the levels in our population were higher than those found in a Chinese population, despite the fact that in both countries dicofol was not yet prohibited at the time of recruitment of participants [27]. Thus, the discrepancies found in levels could be explained by differences on lifestyles, diet, and occupational/environmental exposure among different populations, as described in previous research [117,118].
In general, concentrations of β-HCH were detected in a higher number of participants than dicofol and α-HCH, which could be due to the higher persistence in the environment compared to dicofol [119,120,121]. Indeed, the estimated amount of technical HCH used in Spain from 1948 to 1997 was between 100,000 to 1,000,000 million tones [122], whereas the dicofol usage in the year 2000 was 125,000 kg/year [123]. Among HCH isomers, adipose tissue β-HCH levels were found at a substantially higher detection rate than α-HCH, probably because it exerts a markedly high resistance to chemical degradation both in the environment as living organisms [124], as found in previous research [27,29,30,32]. In the same way, this was observed in several studies that used other biological matrices different to adipose tissue such as blood [99,100,101,102,103,106], serum [45,72,76,77,81,86,87,125], plasma [49,58,109], and breast milk [52,53,55,57].
In our study population, females had higher α- and β-HCH levels compared to males, which is in agreement with the results of multivariable models and some HBM studies using adipose tissue in Danish and Japanese populations [30,44]. These gender-related differences could be related to both social and physiological aspects. Indeed, cytochrome CYP450 (family of enzymes involved in OCP metabolism) activity has been reported to be lower in females than males [126,127]. Moreover, α- and β-HCH concentrations could be influenced by the amount of body fat [128]. These findings might also be related to specific gender-related roles and behaviors in the population [22]. For example, females working in agriculture activities traditionally have lower salaries, status, and receive less education on safety measures in comparison to males [129], thus being at a higher risk of pesticide exposure [130]. Despite maternal milk and giving birth being acknowledged as major excretion routes for POPs [5,47,131,132], these variables were not associated with adipose tissue concentrations in our population (data not shown). Nevertheless, our sample size was not large enough to stratify the analyses by breastfeeding or number of children.
Our observed differential associations of age with α- and β-HCH levels (positive) and dicofol (null) highlight the relevance of early exposures to OCPs. Interestingly, HCHs had been used since the 1940s [133], but were already banned at recruitment. On the contrary, dicofol production started in the 1990s [134] and was already in use in Spain at recruitment. Thus, in the case of HCHs, the results might relate to a “cohort effect”, by which older people born prior to prohibition of production and use of POPs could have a higher body burden of these chemicals compared to younger individuals [135], which is not the case for dicofol.
In line with the abovementioned, BMI was positively associated with adipose tissue α-, β-HCH concentrations, but not with dicofol. These results highlight the relevance of dietary exposure to persistent chemicals, particularly to those already banned, since individuals with increased BMI are likely to consume more fatty foods [6,28], which are in turn considered the main source of exposure in non-occupational settings [28,66]. This idea is supported by positive associations in our population of α and/or β-HCH levels with the consumption of fatty foods from animal origin such as milk, cheese, and fish. In fact, dicofol concentrations were not positively associated with dietary habits. Moreover, water consumption was positively related to the most persistent HCH congener (β-HCH), probably because high food ingestion is frequently associated with increased fluid consumption [136], such as water. The negative association of α-HCH with water consumption might be either a chance finding or influenced by third variables not accounted for in this study, since levels of this congener might also be related to recent occupational exposure.
Our observed negative and null associations of β-HCH and dicofol levels with occupational activities might be related to the banning of HCH in 1994 in Spain [18] 10 years prior recruitment time, so that agricultural activities were no longer a relevant exposure source. Indeed, this finding was confirmed with the lower β-HCH and dicofol levels in those who lived close to agriculture sites compared to those that did not. Lastly, we did not observe any clear association of OCP exposure with residence, probably due to the high heterogeneity in the participants’ residence. Therefore, more research on this last issue is needed, including larger populations.
The use of adipose tissue as an exposure assessment matrix represents a strength of the present study, since adipose tissue is likely to present lower point variability in comparison to other biological matrices [25]. Despite the relatively limited sample size, the majority of the associations in multivariable models seemed robust and plausible. Since the present research was conceived as an exploratory research in a specific population sample, further studies are warranted to confirm if our findings apply to other populations. Characterization of levels and sources of exposure is crucial in the ongoing process of exposure assessment in the GraMo cohort, and even more important considering previously reported associations of OCP with relevant health outcomes in GraMo [16,17,33,34,35,36]. This can be particularly relevant for chemicals such as dicofol and α-HCH, which are frequently overlooked in exposure-disease modeling based on their lower detection rates, but that might contribute to an overall mixture effect [137].
5. Conclusions
Our study revealed different bioaccumulation patterns of α, β-HCH, and dicofol in the analyzed population, probably related to their dissimilar periods of use. This should be considered in the evaluation of health implications of chemicals mixtures, since the specific relationship with potential confounders must be carefully considered in the models. In addition, our results emphasize the need for assessing the exposure to frequently overlooked pollutants, as well as the relevance of adipose tissue as a matrix for exposure assessment.
Conceptualization, J.P.A.; methodology, J.P.A.; formal analysis, I.S.-B. and E.A.; investigation, R.Q.-J. and J.P.A.; data curation, E.A. and C.P.-D.; writing—original draft preparation, I.S.-B.; writing—review and editing, I.S.-B., E.A., C.P.-D., A.S., F.V.-S., P.R., R.B.-R., R.E., F.M.P.-C., R.Q.-J., P.M.-O. and J.P.A.; supervision, project administration, funding acquisition, J.P.A. All authors have read and agreed to the published version of the manuscript.
This research was funded by research grants from CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Spain (PI16/01858, PI18/01573, PI20/01568).
The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board (or Ethics Committee) of “Comité de Ética de la Investigación Provincial de Granada” (Reference: 8/2016).
Informed consent was obtained from all subjects involved in the study.
The data presented in this study are available on request from the corresponding author.
These results would not have been achieved without the selfless collaboration of the staff from Santa Ana and San Cecilio Hospitals and the participants who took part in the study. Juan Pedro Arrebola is under contract within the Ramón y Cajal Program (RYC-2016-20155, Ministerio de Economía, Industria y Competitividad, Spain).
The authors declare no conflict of interest.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Enlarge this image.Figure 1. Map of Granada province (Southern Spain) with participants’ distribution by sub-areas.
Characteristics of the study population (n = 387).
| Variable | |||
|---|---|---|---|
| Sex, n (%) | |||
| Females | 190 (49.1) | ||
| Males | 197 (50.9) | ||
| Age (years), mean ± SD | 50.7 ± 17.1 | ||
| Body mass index (Kg/m2), mean ± SD | 27.4 ± 5.4 | ||
| Normal weight (<25 kg/m2), n (%) | 137 (35.4) | ||
| Overweight (25-≤30 kg/m2), n (%) | 167 (43.2) | ||
| Obesity (>30 kg/m2), n (%) | 83 (21.4) | ||
| Residence, n (%) | |||
| Coast, Motril | 176 (45.5) | ||
| Granada city, Granada Metropolitan Area | 135 (34.9) | ||
| Poniente, Alpujarras | 65 (16.8) | ||
| Others | 8 (2.1) | ||
| Missing | 3 (0.8) | ||
| Residence near to agricultural area ≤2000 m (yes), n (%) | 216 (55.8) | ||
| Residence near to greenhouse ≤2000 m (yes), n (%) | 72 (18.6) | ||
| Occupation in agriculture (≥10 years) (yes), n (%) | 145 (37.5) | ||
| Occupation in industry (≥10 years) (yes), n (%) | 55 (14.2) | ||
| Mother’s occupation during pregnancy, n (%) | |||
| Housewife | 279 (72.1) | ||
| Agricultural worker | 51 (13.2) | ||
| Others | 57 (14.7) | ||
| Current smoker (yes), n (%) | 126 (32.6) | ||
| White fish consumption (yes), n (%) | 304 (79.2) | ||
| Meat consumption | |||
| ≤2 portions/week | 140 (36.2) | ||
| >2 portions/week | 243 (62.8) | ||
| Missing | 4 (1.0) | ||
| Milk consumer (yes), n (%) a | 339 (90.4) | ||
| Cheese consumer (yes), n (%) a | 359 (93.3) | ||
| Vegetable consumption, n (%) | |||
| <2 portions/week | 105 (27.1) | ||
| ≥2 portions/week | 278 (71.8) | ||
| Missing | 4 (1.0) | ||
| Beer consumption (glasses/week), mean ± SD | 3.1 ± 7.9 | ||
| Water consumption (glasses/day), mean ± SD | 5.6 ± 3.9 | ||
| Variable, ng/g lipid | 25th | 50th | 75th |
| β-HCH | 3.7 | 10.6 | 21.4 |
| α-HCH | <LOD | <LOD | <LOD |
| Dicofol | <LOD | <LOD | <LOD |
| Variable | n (%) | ||
| β-HCH (>LOD) | 326 (84.2) | ||
| α-HCH (>LOD) | 84 (21.7) | ||
| Dicofol (>LOD) | 76 (19.6) | ||
β-HCH: β-Hexachlorocyclohexane; α-HCH: α-Hexachlorocyclohexane; LOD: limit of detection; SD: standard deviation. a: Consumer is referred to intake of any amount of milk or cheese per week.
Predictors of adipose tissue β-HCH, α-HCH, and dicofol concentrations in GraMo cohort (n = 387).
| β-HCH a |
α-HCH b |
Dicofol b |
||||
|---|---|---|---|---|---|---|
| β (95% CI) | p-Value | OR (95% CI) | p-Value | OR (95% CI) | p-Value | |
| Age (years) | 0.06 (0.05, 0.07) | <0.001 | 1.10 (1.06, 1.12) | <0.001 | 0.99 (0.97, 1.00) | 0.185 |
| Sex | ||||||
| Females | 1.00 (ref.) | 1.00 (ref.) | 1.00 (ref.) | |||
| Males | −0.67 (−1.02, −0.33) | <0.001 | 0.27 (0.12, 0.59) | 0.001 | 1.18 (0.64, 2.17) | 0.594 |
| Body mass index (Kg/m2) | 0.07 (0.04, 0.10) | <0.001 | 1.10 (1.02, 1.17) | 0.013 | 1.01 (0.96, 1.07) | 0.649 |
| Residence | ||||||
| Coast, Motril city | 1.00 (ref.) | 1.00 (ref.) | 1.00 (ref.) | |||
| Granada city, Granada Metropolitan Area | −0.12 (−0.50, 0.26) | 0.540 | 0.03 (0.01, 0.09) | <0.001 | 0.18 (0.09, 0.39) | <0.001 |
| Poniente, Alpujarras | 0.59 (0.12, 1.06) | 0.013 | 0.16 (0.06, 0.41) | <0.001 | 0.31 (0.12, 0.76) | 0.011 |
| Residence near to agricultural area ≤2000 m | ||||||
| No | 1.00 (ref.) | 1.00 (ref.) | 1.00 (ref.) | |||
| Yes | −0.64 (−0.98, −0.30) | <0.001 | 0.52 (0.24, 1.13) | 0.098 | 0.52 (0.28, 0.96) | 0.035 |
| Residence near to greenhouse area ≤2000 m | ||||||
| No | 1.00 (ref.) | |||||
| Yes | 0.50 (0.23, 1.10) | 0.083 | ||||
| Mother’s occupation during pregnancy | ||||||
| Housewife | 1.00 (ref.) | 1.00 (ref.) | 1.00 (ref.) | |||
| Agricultural worker | 0.76 (0.26, 1.27) | 0.003 | 3.27 (1.35, 7.94) | 0.009 | 0.53 (0.21, 1.32) | 0.171 |
| Others | 0.21 (−0.26, 0.67) | 0.384 | 1.07 (0.33, 3.50) | 0.907 | 1.02 (0.43, 2.38) | 0.969 |
| Occupation in agriculture ≥ 10 years | ||||||
| No | 1.00 (ref.) | 1.00 (ref.) | ||||
| Yes | −0.49 (−0.87, −0.10) | 0.013 | 1.54 (0.79, 2.99) | 0.207 | ||
| Occupation in industry ≥ 10 years | ||||||
| No | 1.00 (ref.) | |||||
| Yes | 0.12 (−0.34, 0.59) | 0.605 | ||||
| Water consumption (glasses/day) | 0.05 (0.01, 0.10) | 0.020 | 1.08 (0.98, 1.18) | 0.124 | 0.91 (0.83, 0.99) | 0.024 |
| Beer consumption (glasses/week) | −0.02 (−0.04, 0.00) | 0.037 | 0.95 (0.88, 1.03) | 0.238 | ||
| Current smoker | ||||||
| No | 1.00 (ref.) | |||||
| Yes | 0.49 (0.25, 0.99) | 0.048 | ||||
| White fish consumption | ||||||
| No | 1.00 (ref.) | 1.00 (ref.) | ||||
| Yes | 0.47 (0.06, 0.87) | 0.025 | 0.38 (0.19, 0.74) | 0.004 | ||
| Meat consumption | ||||||
| <2 portions/week | 1.00 (ref.) | 1.00 (ref.) | 1.00 (ref.) | |||
| ≥2 portions/week | 0.17 (−0.16, 0.50) | 0.313 | 1.48 (0.72, 3.06) | 0.288 | 0.69 (0.38, 1.28) | 0.239 |
| Milk consumer c | ||||||
| No | 1.00 (ref.) | 1.00 (ref.) | ||||
| Yes | 0.70 (0.14, 1.27) | 0.014 | 3.50 (1.03, 11.88) | 0.045 | ||
| Cheese consumer c | ||||||
| No | 1.00 (ref.) | |||||
| Yes | 0.56 (−0.07, 1.19) | 0.081 | ||||
| Vegetables consumption | ||||||
| <2 portions/week | 1.00 (ref.) | 1.00 (ref.) | ||||
| ≥2 portions/week | −0.28 (−0.64, 0.08) | 0.121 | 0.67 (0.31, 1.48) | 0.324 | ||
a: Multivariable linear regression analysis. Dependent variable: log-transformed concentrations (ng/g lipid). b: Multivariable logistic regression analysis. Dependent variable: dichotomized concentrations (>limit of detection vs. <limit of detection). c: Consumer is referred to intake of any amount of milk or cheese per week. β-HCH: beta-hexachlorocyclohexane; α-HCH: alpha-hexachlorocyclohexane. β: Beta coefficient; CI: Confidence interval; OR: Odds Ratio; Ref.: reference category.
Supplementary Materials
The following supporting information can be downloaded at:
References
1. Pacyna-Kuchta, A.D.; Wietrzyk-Pełka, P.; Węgrzyn, M.H.; Frankowski, M.; Polkowska, Ż. A Screening of Select Toxic and Essential Elements and Persistent Organic Pollutants in the Fur of Svalbard Reindeer. Chemosphere; 2020; 245, 125458. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2019.125458] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31846790]
2. United Nations Environmental Programme (UNEP). Available online: https://www.pops.int (accessed on 7 March 2021).
3. Alharbi, O.M.L.; Basheer, A.A.; Khattab, R.A.; Ali, I. Health and Environmental Effects of Persistent Organic Pollutants. J. Mol. Liq.; 2018; 263, pp. 442-453. [DOI: https://dx.doi.org/10.1016/j.molliq.2018.05.029]
4. Echeverría, R.; Vrhovnik, P.; Salcedo-Bellido, I.; Pérez-Carrascosa, F.M.; Gómez-Peña, C.; Fiket, Ž.; Martin-Olmedo, P.; Olea, N.; Fernández, M.F.; Arrebola, J.P. Associations of Residential and Occupational History with the Distribution of Persistent Pollutants Mixtures in Adipose Tissue Samples. Environ. Res.; 2021; 194, 110687. [DOI: https://dx.doi.org/10.1016/j.envres.2020.110687] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33385390]
5. Reid, A.; Callan, A.; Stasinska, A.; Heyworth, J.; Phi, D.T.; Odland, J.O.; Hinwood, A. Maternal Exposure to Organochlorine Pesticides in Western Australia. Sci. Total Environ.; 2013; 449, pp. 208-213. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2013.01.067] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23428750]
6. Olivero-Verbel, J.; Guerrero-Castilla, A.; Ramos, N.R. Biochemical Effects Induced by the Hexachlorocyclohexanes. Rev. Environ. Contam. Toxicol.; 2011; 212, pp. 1-28. [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21432053]
7. Traina, M.E.; Rescia, M.; Urbani, E.; Mantovani, A.; Macrì, C.; Ricciardi, C.; Stazi, A.V.; Fazzi, P.; Cordelli, E.; Eleuteri, P. et al. Long-Lasting Effects of Lindane on Mouse Spermatogenesis Induced by in Utero Exposure. Reprod. Toxicol.; 2003; 17, pp. 25-35. [DOI: https://dx.doi.org/10.1016/S0890-6238(02)00101-6]
8. Zou, E.; Matsumura, F. Long-Term Exposure to Beta-Hexachlorocyclohexane (Beta-HCH) Promotes Transformation and Invasiveness of MCF-7 Human Breast Cancer Cells. Biochem. Pharmacol.; 2003; 66, pp. 831-840. [DOI: https://dx.doi.org/10.1016/S0006-2952(03)00394-0]
9. Qiu, X.; Zhu, T.; Yao, B.; Hu, J.; Hu, S. Contribution of Dicofol to the Current DDT Pollution in China. Environ. Sci. Technol.; 2005; 39, pp. 4385-4390. [DOI: https://dx.doi.org/10.1021/es050342a]
10. Ahmad, A.; Ahmad, M. Deciphering the Toxic Effects of Organochlorine Pesticide, Dicofol on Human RBCs and Lymphocytes. Pestic. Biochem. Physiol.; 2017; 143, pp. 127-134. [DOI: https://dx.doi.org/10.1016/j.pestbp.2017.08.007]
11. Qiu, X.; Zhu, T. Using the o,px-DDT/p,p′-DDT Ratio to Identify DDT Sources in China. Chemosphere; 2010; 81, pp. 1033-1038. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2010.08.049]
12. Ara, T.; Nisa, W.-U.; Aziz, R.; Rafiq, M.T.; Gill, R.A.; Hayat, M.T.; Afridi, U. Health Risk Assessment of Hexachlorocyclohexane in Soil, Water and Plants in the Agricultural Area of Potohar Region, Punjab, Pakistan. Environ. Geochem. Health; 2021; 43, pp. 1-17. [DOI: https://dx.doi.org/10.1007/s10653-021-00847-9] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/33624225]
13. Abolhassani, M.; Asadikaram, G.; Paydar, P.; Fallah, H.; Aghaee-Afshar, M.; Moazed, V.; Akbari, H.; Moghaddam, S.D.; Moradi, A. Organochlorine and Organophosphorous Pesticides May Induce Colorectal Cancer; A Case-Control Study. Ecotoxicol. Environ. Saf.; 2019; 178, pp. 168-177. [DOI: https://dx.doi.org/10.1016/j.ecoenv.2019.04.030] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31004929]
14. Jayaraj, R.; Megha, P.; Sreedev, P. Organochlorine Pesticides, Their Toxic Effects on Living Organisms and Their Fate in the Environment. Interdiscip. Toxicol.; 2016; 9, pp. 90-100. [DOI: https://dx.doi.org/10.1515/intox-2016-0012] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28652852]
15. Mortazavi, N.; Asadikaram, G.; Ebadzadeh, M.-R.; Kamalati, A.; Pakmanesh, H.; Dadgar, R.; Moazed, V.; Paydar, P.; Fallah, H.; Abolhassani, M. Organochlorine and Organophosphorus Pesticides and Bladder Cancer: A Case-Control Study. J. Cell. Biochem.; 2019; 120, pp. 14847-14859. [DOI: https://dx.doi.org/10.1002/jcb.28746]
16. Arrebola, J.P.; Fernández, M.F.; Martín-Olmedo, P.; Molina-Molina, J.M.; Sánchez-Pérez, M.J.; Sánchez-Cantalejo, E.; Molina-Portillo, E.; Expósito, J.; Bonde, J.P.; Olea, N. Adipose Tissue Concentrations of Persistent Organic Pollutants and Total Cancer Risk in an Adult Cohort from Southern Spain: Preliminary Data from Year 9 of the Follow-Up. Sci. Total Environ.; 2014; 500–501, pp. 243-249. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2014.08.043]
17. Barrios-Rodríguez, R.; Pérez-Carrascosa, F.M.; Gómez-Peña, C.; Mustieles, V.; Salcedo-Bellido, I.; Requena, P.; Martín-Olmedo, P.; Jiménez-Moleón, J.J.; Arrebola, J.P. Associations of Accumulated Selected Persistent Organic Pollutants in Adipose Tissue with Insulin Sensitivity and Risk of Incident Type-2 Diabetes. Environ. Int.; 2021; 155, 106607. [DOI: https://dx.doi.org/10.1016/j.envint.2021.106607]
18. Boletín Oficial del Estado (BOE). Orden de 4 de Febrero de 1994 Por La Que Se Prohíbe La Comercialización Y Utilización De Plaguicidas De Uso Ambiental Que Contienen Determinados Ingredientes Activos Peligrosos. 1994; 5132.Available online: https://www.boe.es/diario_boe/txt.php?id=BOE-A-1994-3824 (accessed on 1 November 2021).
19. Hart, E.; Coscollà, C.; Pastor, A.; Yusà, V. GC–MS Characterization of Contemporary Pesticides in PM10 of Valencia Region, Spain. Atmos. Environ.; 2012; 62, pp. 118-129. [DOI: https://dx.doi.org/10.1016/j.atmosenv.2012.08.006]
20. United Nations Environmental Programme (UNEP). Proposal to list dicofol in annexes a, b and/or c to the stockholm convention on persistent organic pollutants note. Proceedings of the Stockholm Convention’s Persistent Organic Pollutants; Rome, Italy, 27–30 October 2014; pp. 1-13.
21. United Nations Environmental Programme (UNEP). Report of the Conference of the Parties of the Stockholm Convention on Persistent Organic Pollutants on the Work of Its Fourth Meeting; UNEP/POPS/COP.4/38. 2009; Available online: http://chm.pops.int/portals/0/repository/cop4/unep-pops-cop.4-38.english.pdf (accessed on 23 November 2021).
22. Arrebola, J.P.; Fernández, M.F.; Olea, N.; Ramos, R.; Martin-Olmedo, P. Human Exposure to p,p’-Dichlorodiphenyldichloroethylene (p,p’-DDE) in Urban and Semi-Rural Areas in Southeast Spain: A Gender Perspective. Sci. Total Environ.; 2013; 458–460, pp. 209-216. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2013.04.001]
23. Mercado, L.A.; Freille, S.M.; Vaca-Pereira, J.S.; Cuellar, M.; Flores, L.; Mutch, E.; Olea, N.; Arrebola, J.P. Serum Concentrations of p,p′-Dichlorodiphenyltrichloroethane (p,p′-DDE) in a Sample of Agricultural Workers from Bolivia. Chemosphere; 2013; 91, pp. 1381-1385. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2012.12.023]
24. Cano-Sancho, G.; Labrune, L.; Ploteau, S.; Marchand, P.; Le Bizec, B.; Antignac, J.-P. The Challenging Use and Interpretation of Circulating Biomarkers of Exposure to Persistent Organic Pollutants in Environmental Health: Comparison of Lipid Adjustment Approaches in a Case Study Related to Endometriosis. Chemosphere; 2018; 200, pp. 388-396. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2018.02.120]
25. Mustieles, V.; Arrebola, J.P. How Polluted Is Your Fat? What the Study of Adipose Tissue Can Contribute to Environmental Epidemiology. J. Epidemiol. Community Health; 2020; 74, pp. 401-407. [DOI: https://dx.doi.org/10.1136/jech-2019-213181] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/32019765]
26. Ociepa-Zawal, M.; Rubis, B.; Wawrzynczak, D.; Wachowiak, R.; Trzeciak, W.H. Accumulation of Environmental Estrogens in Adipose Tissue of Breast Cancer Patients. J. Environ. Sci. Health Part A Toxic Hazard. Subst. Environ. Eng.; 2010; 45, pp. 305-312. [DOI: https://dx.doi.org/10.1080/10934520903468038] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20390871]
27. Wang, N.; Shi, L.; Kong, D.; Cai, D.; Cao, Y.; Liu, Y.; Pang, G.; Yu, R. Accumulation Levels and Characteristics of Some Pesticides in Human Adipose Tissue Samples from Southeast China. Chemosphere; 2011; 84, pp. 964-971. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2011.05.062] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21722941]
28. Bräuner, E.V.; Raaschou-Nielsen, O.; Gaudreau, E.; LeBlanc, A.; Tjønneland, A.; Overvad, K.; Sørensen, M. Predictors of Polychlorinated Biphenyl Concentrations in Adipose Tissue in a General Danish Population. Environ. Sci. Technol.; 2011; 45, pp. 679-685. [DOI: https://dx.doi.org/10.1021/es102489c] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21141999]
29. Malarvannan, G.; Dirinck, E.; Dirtu, A.C.; Pereira-Fernandes, A.; Neels, H.; Jorens, P.G.; Gaal, L.V.; Blust, R.; Covaci, A. Distribution of Persistent Organic Pollutants in Two Different Fat Compartments from Obese Individuals. Environ. Int.; 2013; 55, pp. 33-42. [DOI: https://dx.doi.org/10.1016/j.envint.2013.02.012]
30. Watanabe, M.X.; Kunisue, T.; Ueda, N.; Nose, M.; Tanabe, S.; Iwata, H. Toxicokinetics of Dioxins and Other Organochlorine Compounds in Japanese People: Association with Hepatic CYP1A2 Expression Levels. Environ. Int.; 2013; 53, pp. 53-61. [DOI: https://dx.doi.org/10.1016/j.envint.2012.12.008]
31. Waliszewski, S.M.; Caba, M.; Saldarriaga-Noreña, H.; Martínez, A.J.; Meza, E.; Quintana, R.V.; Zepeda, R. Organochlorine Pesticide Level Differences among Female Inhabitants from Veracruz, Puebla and Tabasco, Mexico. Bull. Environ. Contam. Toxicol.; 2014; 93, pp. 233-237. [DOI: https://dx.doi.org/10.1007/s00128-014-1309-3]
32. Achour, A.; Derouiche, A.; Barhoumi, B.; Kort, B.; Cherif, D.; Bouabdallah, S.; Sakly, M.; Rhouma, K.B.; Touil, S.; Driss, M.R. et al. Organochlorine Pesticides and Polychlorinated Biphenyls in Human Adipose Tissue from Northern Tunisia: Current Extent of Contamination and Contributions of Socio-Demographic Characteristics and Dietary Habits. Environ. Res.; 2017; 156, pp. 635-643. [DOI: https://dx.doi.org/10.1016/j.envres.2017.04.021]
33. Arrebola, J.P.; Fernández, M.F.; Martin-Olmedo, P.; Bonde, J.P.; Martín-Rodriguez, J.L.; Expósito, J.; Rubio-Domínguez, A.; Olea, N. Historical Exposure to Persistent Organic Pollutants and Risk of Incident Hypertension. Environ. Res.; 2015; 138, pp. 217-223. [DOI: https://dx.doi.org/10.1016/j.envres.2015.02.018]
34. Arrebola, J.P.; Ocaña-Riola, R.; Arrebola-Moreno, A.L.; Fernández-Rodríguez, M.; Martin-Olmedo, P.; Fernández, M.F.; Olea, N. Associations of Accumulated Exposure to Persistent Organic Pollutants with Serum Lipids and Obesity in an Adult Cohort from Southern Spain. Environ. Pollut.; 2014; 195, pp. 9-15. [DOI: https://dx.doi.org/10.1016/j.envpol.2014.08.003] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25173983]
35. Arrebola, J.P.; Pumarega, J.; Gasull, M.; Fernandez, M.F.; Martin-Olmedo, P.; Molina-Molina, J.M.; Fernández-Rodríguez, M.; Porta, M.; Olea, N. Adipose Tissue Concentrations of Persistent Organic Pollutants and Prevalence of Type 2 Diabetes in Adults from Southern Spain. Environ. Res.; 2013; 122, pp. 31-37. [DOI: https://dx.doi.org/10.1016/j.envres.2012.12.001] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23290489]
36. Mustieles, V.; Fernández, M.F.; Martin-Olmedo, P.; González-Alzaga, B.; Fontalba-Navas, A.; Hauser, R.; Olea, N.; Arrebola, J.P. Human Adipose Tissue Levels of Persistent Organic Pollutants and Metabolic Syndrome Components: Combining a Cross-Sectional with a 10-Year Longitudinal Study Using a Multi-Pollutant Approach. Environ. Int.; 2017; 104, pp. 48-57. [DOI: https://dx.doi.org/10.1016/j.envint.2017.04.002] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28414931]
37. Arrebola, J.P.; Fernandez, M.F.; Porta, M.; Rosell, J.; de la Ossa, R.M.; Olea, N.; Martin-Olmedo, P. Multivariate Models to Predict Human Adipose Tissue PCB Concentrations in Southern Spain. Environ. Int.; 2010; 36, pp. 705-713. [DOI: https://dx.doi.org/10.1016/j.envint.2010.05.004]
38. Arrebola, J.P.; Martin-Olmedo, P.; Fernandez, M.F.; Sanchez-Cantalejo, E.; Jimenez-Rios, J.A.; Torne, P.; Porta, M.; Olea, N. Predictors of Concentrations of Hexachlorobenzene in Human Adipose Tissue: A Multivariate Analysis by Gender in Southern Spain. Environ. Int.; 2009; 35, pp. 27-32. [DOI: https://dx.doi.org/10.1016/j.envint.2008.05.009] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/18653237]
39. Vidal, J.L.M.; Frías, M.M.; Frenich, A.G.; Olea-Serrano, F.; Olea, N. Determination of Endocrine-Disrupting Pesticides and Polychlorinated Biphenyls in Human Serum by GC-ECD and GC-MS-MS and Evaluation of Contributions to the Uncertainty of the Results. Anal. Bioanal. Chem.; 2002; 372, pp. 766-775. [DOI: https://dx.doi.org/10.1007/s00216-002-1272-4] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/12012187]
40. Rivas, A.; Fernandez, M.F.; Cerrillo, I.; Ibarluzea, J.; Olea-Serrano, M.F.; Pedraza, V.; Olea, N. Human Exposure to Endocrine Disrupters: Standardisation of a Marker of Estrogenic Exposure in Adipose Tissue. Apmis; 2001; 109, pp. 185-197. [DOI: https://dx.doi.org/10.1034/j.1600-0463.2001.090302.x]
41. Buckland, G.; González, C.A.; Agudo, A.; Vilardell, M.; Berenguer, A.; Amiano, P.; Ardanaz, E.; Arriola, L.; Barricarte, A.; Basterretxea, M. et al. Adherence to the Mediterranean Diet and Risk of Coronary Heart Disease in the Spanish EPIC Cohort Study. Am. J. Epidemiol.; 2009; 170, pp. 1518-1529. [DOI: https://dx.doi.org/10.1093/aje/kwp282] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/19903723]
42. Gonzalez, C.A.; Riboli, E. Diet and Cancer Prevention: Contributions from the European Prospective Investigation into Cancer and Nutrition (EPIC) Study. Eur. J. Cancer; 2010; 46, pp. 2555-2562. [DOI: https://dx.doi.org/10.1016/j.ejca.2010.07.025]
43. Mullor, M.M.R. Estudio Andaluz de Prevalencia de Diversas Patologíaas en Áreas con Distinto Nivel de Utilización de Plaguicidas; Editorial de la Universidad de Granada: Granada, Spain, 2009.
44. Bräuner, E.V.; Raaschou-Nielsen, O.; Gaudreau, E.; Leblanc, A.; Tjønneland, A.; Overvad, K.; Sørensen, M. Predictors of Adipose Tissue Concentrations of Organochlorine Pesticides in a General Danish Population. J. Expo. Sci. Environ. Epidemiol.; 2012; 22, pp. 52-59. [DOI: https://dx.doi.org/10.1038/jes.2011.39]
45. Freire, C.; Koifman, R.J.; Sarcinelli, P.N.; Rosa, A.C.S.; Clapauch, R.; Koifman, S. Long-Term Exposure to Organochlorine Pesticides and Thyroid Status in Adults in a Heavily Contaminated Area in Brazil. Environ. Res.; 2013; 127, pp. 7-15. [DOI: https://dx.doi.org/10.1016/j.envres.2013.09.001]
46. Narduzzi, S.; Fantini, F.; Blasetti, F.; Rantakokko, P.; Kiviranta, H.; Forastiere, F.; Michelozzi, P.; Porta, D. Predictors of Beta-Hexachlorocyclohexane Blood Levels among People Living Close to a Chemical Plant and an Illegal Dumping Site. Environ. Health; 2020; 19, pp. 1-9. [DOI: https://dx.doi.org/10.1186/s12940-020-0562-7] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/31969154]
47. Porta, M.; Gasull, M.; Puigdomènech, E.; Garí, M.; de Basea, M.B.; Guillén, M.; López, T.; Bigas, E.; Pumarega, J.; Llebaria, X. et al. Distribution of Blood Concentrations of Persistent Organic Pollutants in a Representative Sample of the Population of Catalonia. Environ. Int.; 2010; 36, pp. 655-664. [DOI: https://dx.doi.org/10.1016/j.envint.2010.04.013] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20569985]
48. Ramos, J.J.; Huetos, O.; González, S.; Esteban, M.; Calvo, E.; Pérez-Gómez, B.; Castaño, A. Bioambient.es. Organochlorinated Pesticides Levels in a Representative Sample of the Spanish Adult Population: The Bioambient.Es Project. Int. J. Hyg. Environ. Health; 2017; 220, pp. 217-226. [DOI: https://dx.doi.org/10.1016/j.ijheh.2016.10.005] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28277312]
49. Wang, H.-S.; Chen, Z.-J.; Wei, W.; Man, Y.-B.; Giesy, J.P.; Du, J.; Zhang, G.; Wong, C.K.-C.; Wong, M.-H. Concentrations of Organochlorine Pesticides (OCPs) in Human Blood Plasma from Hong Kong: Markers of Exposure and Sources from Fish. Environ. Int.; 2013; 54, pp. 18-25. [DOI: https://dx.doi.org/10.1016/j.envint.2013.01.003]
50. Artacho-Cordón, F.; León, J.; Sáenz, J.M.; Fernández, M.F.; Martin-Olmedo, P.; Olea, N.; Arrebola, J.P. Contribution of Persistent Organic Pollutant Exposure to the Adipose Tissue Oxidative Microenvironment in an Adult Cohort: A Multipollutant Approach. Environ. Sci. Technol.; 2016; 50, pp. 13529-13538. [DOI: https://dx.doi.org/10.1021/acs.est.6b03783]
51. Aerts, R.; Van Overmeire, I.; Colles, A.; Andjelković, M.; Malarvannan, G.; Poma, G.; Den Hond, E.; Van de Mieroop, E.; Dewolf, M.-C.; Charlet, F. et al. Determinants of Persistent Organic Pollutant (POP) Concentrations in Human Breast Milk of a Cross-Sectional Sample of Primiparous Mothers in Belgium. Environ. Int.; 2019; 131, 104979. [DOI: https://dx.doi.org/10.1016/j.envint.2019.104979]
52. Castillo-Castañeda, P.C.; Gaxiola-Robles, R.; Méndez-Rodríguez, L.C.; Labrada-Martagón, V.; Zenteno-Savín, T. Antioxidantes, Especies Reactivas de Oxígeno y Daño Oxidativo Asociado a La Presencia de Plaguicidas Organoclorados En La Leche Materna. Nutr. Hosp.; 2016; 33, pp. 422-430. [DOI: https://dx.doi.org/10.20960/nh.127]
53. Dimitriadou, L.; Malarvannan, G.; Covaci, A.; Iossifidou, E.; Tzafettas, J.; Zournatzi-Koiou, V.; Kalantzi, O.-I. Levels and Profiles of Brominated and Chlorinated Contaminants in Human Breast Milk from Thessaloniki, Greece. Sci. Total Environ.; 2016; 539, pp. 350-358. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2015.08.137]
54. Mamontova, E.A.; Tarasova, E.N.; Mamontov, A.A. PCBs and OCPs in Human Milk in Eastern Siberia, Russia: Levels, Temporal Trends and Infant Exposure Assessment. Chemosphere; 2017; 178, pp. 239-248. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2017.03.058]
55. Eroğlu, K.; Daş, Y.K.; Gölbaşi, Z.; Şimşek, Z.; Koruk, F.; Atmaca, E. Persistent Organic Chlorinated Compound Residues in the Breast Milk of Female Seasonal Agricultural Workers. J. Occup. Environ. Med.; 2018; 60, pp. 860-866. [DOI: https://dx.doi.org/10.1097/JOM.0000000000001362]
56. Song, S.; Ma, X.; Pan, M.; Tong, L.; Tian, Q. Excretion Kinetics of Three Dominant Organochlorine Compounds in Human Milk within the First 6 Months Postpartum. Environ. Monit. Assess.; 2018; 190, 457. [DOI: https://dx.doi.org/10.1007/s10661-018-6850-9] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29995278]
57. Lu, D.; Wang, D.; Ni, R.; Lin, Y.; Feng, C.; Xu, Q.; Jia, X.; Wang, G.; Zhou, Z. Organochlorine Pesticides and Their Metabolites in Human Breast Milk from Shanghai, China. Environ. Sci. Pollut. Res. Int.; 2015; 22, pp. 9293-9306. [DOI: https://dx.doi.org/10.1007/s11356-015-4072-z] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25595932]
58. Toichuev, R.M.; Zhilova, L.V.; Paizildaev, T.R.; Khametova, M.S.; Rakhmatillaev, A.; Sakibaev, K.S.; Madykova, Z.A.; Toichueva, A.U.; Schlumpf, M.; Weber, R. et al. Organochlorine Pesticides in Placenta in Kyrgyzstan and the Effect on Pregnancy, Childbirth, and Newborn Health. Environ. Sci. Pollut. Res. Int.; 2018; 25, pp. 31885-31894. [DOI: https://dx.doi.org/10.1007/s11356-017-0962-6] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/29247409]
59. Jeong, Y.; Lee, S.; Kim, S.; Choi, S.-D.; Park, J.; Kim, H.-J.; Lee, J.J.; Choi, G.; Choi, S.; Kim, S. et al. Occurrence and Prenatal Exposure to Persistent Organic Pollutants Using Meconium in Korea: Feasibility of Meconium as a Non-Invasive Human Matrix. Environ. Res.; 2016; 147, pp. 8-15. [DOI: https://dx.doi.org/10.1016/j.envres.2016.01.033]
60. Luzardo, O.P.; Badea, M.; Zumbado, M.; Rogozea, L.; Floroian, L.; Ilea, A.; Moga, M.; Sechel, G.; Boada, L.D.; Henríquez-Hernández, L.A. Body Burden of Organohalogenated Pollutants and Polycyclic Aromatic Hydrocarbons in Romanian Population: Influence of Age, Gender, Body Mass Index, and Habitat. Sci. Total Environ.; 2019; 656, pp. 709-716. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2018.11.404]
61. Grimalt, J.O.; Carrizo, D.; Garí, M.; Font-Ribera, L.; Ribas-Fito, N.; Torrent, M.; Sunyer, J. An Evaluation of the Sexual Differences in the Accumulation of Organochlorine Compounds in Children at Birth and at the Age of 4 Years. Environ. Res.; 2010; 110, pp. 244-250. [DOI: https://dx.doi.org/10.1016/j.envres.2010.01.005]
62. Lu, Y.; Zhou, S.-B.; Li, B.-X. Exposure to Environmental Hexachlorocyclohexane (HCH) and Dichlorodiphenyltrichloroethane (DDT) among Rural Children in North Eastern China. Biomed. Environ. Sci.; 2010; 23, pp. 230-233. [DOI: https://dx.doi.org/10.1016/S0895-3988(10)60057-8]
63. Son, H.-K.; Kim, S.-A.; Kang, J.-H.; Chang, Y.-S.; Park, S.-K.; Lee, S.-K.; Jacobs, D.R.; Lee, D.-H. Strong Associations between Low-Dose Organochlorine Pesticides and Type 2 Diabetes in Korea. Environ. Int.; 2010; 36, pp. 410-414. [DOI: https://dx.doi.org/10.1016/j.envint.2010.02.012]
64. Weldon, R.H.; Webster, M.; Harley, K.G.; Bradman, A.; Fenster, L.; Davis, M.D.; Hubbard, A.; Barr, D.B.; Holland, N.; Eskenazi, B. Serum Persistent Organic Pollutants and Duration of Lactation among Mexican-American Women. J. Environ. Public Health; 2010; 2010, 861757. [DOI: https://dx.doi.org/10.1155/2010/861757]
65. Cao, L.-L.; Yan, C.-H.; Yu, X.-D.; Tian, Y.; Zhao, L.; Liu, J.-X.; Shen, X.-M. Relationship between Serum Concentrations of Polychlorinated Biphenyls and Organochlorine Pesticides and Dietary Habits of Pregnant Women in Shanghai. Sci. Total Environ.; 2011; 409, pp. 2997-3002. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2011.04.040]
66. Ibarluzea, J.; Alvarez-Pedrerol, M.; Guxens, M.; Marina, L.S.; Basterrechea, M.; Lertxundi, A.; Etxeandia, A.; Goñi, F.; Vioque, J.; Ballester, F. et al. Sociodemographic, Reproductive and Dietary Predictors of Organochlorine Compounds Levels in Pregnant Women in Spain. Chemosphere; 2011; 82, pp. 114-120. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2010.09.051] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20965545]
67. Park, S.K.; Son, H.K.; Lee, S.K.; Kang, J.H.; Chang, Y.S.; Jacobs, D.R.; Lee, D.H. Relationship between Serum Concentrations of Organochlorine Pesticides and Metabolic Syndrome among Non-Diabetic Adults. J. Prev. Med. Public Health; 2010; 43, pp. 1-8. [DOI: https://dx.doi.org/10.3961/jpmph.2010.43.1.1] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20185977]
68. Kaushik, C.P.; Sharma, N.; Kumar, S.; Kaushik, A. Organochlorine Pesticide Residues in Human Blood Samples Collected from Haryana, India and the Changing Pattern. Bull. Environ. Contam. Toxicol.; 2012; 89, pp. 587-591. [DOI: https://dx.doi.org/10.1007/s00128-012-0709-5] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22772832]
69. Azandjeme, C.S.; Delisle, H.; Fayomi, B.; Ayotte, P.; Djrolo, F.; Houinato, D.; Bouchard, M. High Serum Organochlorine Pesticide Concentrations in Diabetics of a Cotton Producing Area of the Benin Republic (West Africa). Environ. Int.; 2014; 69, pp. 1-8. [DOI: https://dx.doi.org/10.1016/j.envint.2014.04.002] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24769438]
70. Hassine, S.B.; Hammami, B.; Ameur, W.B.; El Megdiche, Y.; Barhoumi, B.; El Abidi, R.; Driss, M.R. Concentrations of Organochlorine Pesticides and Polychlorinated Biphenyls in Human Serum and Their Relation with Age, Gender, and BMI for the General Population of Bizerte, Tunisia. Environ. Sci. Pollut. Res. Int.; 2014; 21, pp. 6303-6313. [DOI: https://dx.doi.org/10.1007/s11356-013-1480-9] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23338993]
71. Braun, J.M.; Kalkbrenner, A.E.; Just, A.C.; Yolton, K.; Calafat, A.M.; Sjödin, A.; Hauser, R.; Webster, G.M.; Chen, A.; Lanphear, B.P. Gestational Exposure to Endocrine-Disrupting Chemicals and Reciprocal Social, Repetitive, and Stereotypic Behaviors in 4- and 5-Year-Old Children: The HOME Study. Environ. Health Perspect.; 2014; 122, pp. 513-520. [DOI: https://dx.doi.org/10.1289/ehp.1307261]
72. Freire, C.; Koifman, R.J.; Sarcinelli, P.N.; Rosa, A.C.S.; Clapauch, R.; Koifman, S. Association between Serum Levels of Organochlorine Pesticides and Sex Hormones in Adults Living in a Heavily Contaminated Area in Brazil. Int. J. Hyg. Environ. Health; 2014; 217, pp. 370-378. [DOI: https://dx.doi.org/10.1016/j.ijheh.2013.07.012]
73. Guo, H.; Jin, Y.; Cheng, Y.; Leaderer, B.; Lin, S.; Holford, T.R.; Qiu, J.; Zhang, Y.; Shi, K.; Zhu, Y. et al. Prenatal Exposure to Organochlorine Pesticides and Infant Birth Weight in China. Chemosphere; 2014; 110, pp. 1-7. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2014.02.017]
74. Itoh, H.; Iwasaki, M.; Kasuga, Y.; Yokoyama, S.; Onuma, H.; Nishimura, H.; Kusama, R.; Yoshida, T.; Yokoyama, K.; Tsugane, S. Association between Serum Organochlorines and Global Methylation Level of Leukocyte DNA among Japanese Women: A Cross-Sectional Study. Sci. Total Environ.; 2014; 490, pp. 603-609. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2014.05.035]
75. Lam, T.; Williams, P.L.; Lee, M.M.; Korrick, S.A.; Birnbaum, L.S.; Burns, J.S.; Sergeyev, O.; Revich, B.; Altshul, L.M.; Patterson, D.G. et al. Prepubertal Organochlorine Pesticide Concentrations and Age of Pubertal Onset among Russian Boys. Environ. Int.; 2014; 73, pp. 135-142. [DOI: https://dx.doi.org/10.1016/j.envint.2014.06.020]
76. Li, C.; Cheng, Y.; Tang, Q.; Lin, S.; Li, Y.; Hu, X.; Nian, J.; Gu, H.; Lu, Y.; Tang, H. et al. The Association between Prenatal Exposure to Organochlorine Pesticides and Thyroid Hormone Levels in Newborns in Yancheng, China. Environ. Res.; 2014; 129, pp. 47-51. [DOI: https://dx.doi.org/10.1016/j.envres.2013.12.009] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24529002]
77. Saoudi, A.; Fréry, N.; Zeghnoun, A.; Bidondo, M.-L.; Deschamps, V.; Göen, T.; Garnier, R.; Guldner, L. Serum Levels of Organochlorine Pesticides in the French Adult Population: The French National Nutrition and Health Study (ENNS), 2006–2007. Sci. Total Environ.; 2014; 472, pp. 1089-1099. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2013.11.044] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24361744]
78. Savitz, D.A.; Klebanoff, M.A.; Wellenius, G.A.; Jensen, E.T.; Longnecker, M.P. Persistent Organochlorines and Hypertensive Disorders of Pregnancy. Environ. Res.; 2014; 132, pp. 1-5. [DOI: https://dx.doi.org/10.1016/j.envres.2014.03.020] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/24742720]
79. Steenland, K.; Mora, A.M.; Barr, D.B.; Juncos, J.; Roman, N.; Wesseling, C. Organochlorine Chemicals and Neurodegeneration among Elderly Subjects in Costa Rica. Environ. Res.; 2014; 134, pp. 205-209. [DOI: https://dx.doi.org/10.1016/j.envres.2014.07.024] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25173053]
80. Bjerregaard-Olesen, C.; Long, M.; Ghisari, M.; Bech, B.H.; Nohr, E.A.; Uldbjerg, N.; Henriksen, T.B.; Olsen, J.; Bonefeld-Jørgensen, E.C. Temporal Trends of Lipophilic Persistent Organic Pollutants in Serum from Danish Nulliparous Pregnant Women 2011–2013. Environ. Sci. Pollut. Res. Int.; 2017; 24, pp. 16592-16603. [DOI: https://dx.doi.org/10.1007/s11356-017-8992-7] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28432626]
81. Wang, Q.; Yuan, H.; Jin, J.; Li, P.; Ma, Y.; Wang, Y. Organochlorine Pesticide Concentrations in Pooled Serum of People in Different Age Groups from Five Chinese Cities. Sci. Total Environ.; 2017; 586, pp. 1012-1019. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2017.02.082]
82. Coakley, J.; Bridgen, P.; Bates, M.; Douwes, J.; ’t Mannetje, A. Chlorinated Persistent Organic Pollutants in Serum of New Zealand Adults, 2011–2013. Sci. Total Environ.; 2018; 615, pp. 624-631. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2017.09.331]
83. González-Alzaga, B.; Lacasaña, M.; Hernández, A.F.; Arrebola, J.P.; López-Flores, I.; Artacho-Cordón, F.; Bonde, J.P.; Olea, N.; Aguilar-Garduño, C. Serum Concentrations of Organochlorine Compounds and Predictors of Exposure in Children Living in Agricultural Communities from South-Eastern Spain. Environ. Pollut.; 2018; 237, pp. 685-694. [DOI: https://dx.doi.org/10.1016/j.envpol.2017.10.109]
84. Kim, J.-T.; Kang, J.-H.; Chang, Y.-S.; Lee, D.-H.; Choi, S.-D. Determinants of Serum Organochlorine Pesticide and Polychlorinated Biphenyl Levels in Middle-Aged Korean Adults. Environ. Sci. Pollut. Res.; 2018; 25, pp. 249-259. [DOI: https://dx.doi.org/10.1007/s11356-017-0382-7]
85. Harmouche-Karaki, M.; Matta, J.; Helou, K.; Mahfouz, Y.; Fakhoury-Sayegh, N.; Narbonne, J.-F. Serum Concentrations of Selected Organochlorine Pesticides in a Lebanese Population and Their Associations to Sociodemographic, Anthropometric and Dietary Factors: ENASB Study. Environ. Sci. Pollut. Res. Int.; 2018; 25, pp. 14350-14360. [DOI: https://dx.doi.org/10.1007/s11356-017-9427-1]
86. Bravo, N.; Hansen, S.; Økland, I.; Garí, M.; Álvarez, M.V.; Matiocevich, S.; Odland, J.-Ø.; Grimalt, J.O. Influence of Maternal and Sociodemographic Characteristics on the Accumulation of Organohalogen Compounds in Argentinian Women. The EMASAR Study. Environ. Res.; 2017; 158, pp. 759-767. [DOI: https://dx.doi.org/10.1016/j.envres.2017.07.033] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28753526]
87. Zhao, B.; Shen, H.; Liu, F.; Liu, S.; Niu, J.; Guo, F.; Sun, X. Exposure to Organochlorine Pesticides Is an Independent Risk Factor of Hepatocellular Carcinoma: A Case-Control Study. J. Expo. Sci. Environ. Epidemiol.; 2012; 22, pp. 541-548. [DOI: https://dx.doi.org/10.1038/jes.2011.29] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21915153]
88. Bjermo, H.; Darnerud, P.O.; Lignell, S.; Pearson, M.; Rantakokko, P.; Nälsén, C.; Barbieri, H.E.; Kiviranta, H.; Lindroos, A.K.; Glynn, A. Fish Intake and Breastfeeding Time Are Associated with Serum Concentrations of Organochlorines in a Swedish Population. Environ. Int.; 2013; 51, pp. 88-96. [DOI: https://dx.doi.org/10.1016/j.envint.2012.10.010] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23201820]
89. Morales, E.; Gascon, M.; Martinez, D.; Casas, M.; Ballester, F.; Rodríguez-Bernal, C.L.; Ibarluzea, J.; Marina, L.S.; Espada, M.; Goñi, F. et al. Associations between Blood Persistent Organic Pollutants and 25-Hydroxyvitamin D3 in Pregnancy. Environ. Int.; 2013; 57–58, pp. 34-41. [DOI: https://dx.doi.org/10.1016/j.envint.2013.03.011]
90. Mrema, E.J.; Rubino, F.M.; Mandic-Rajcevic, S.; Sturchio, E.; Turci, R.; Osculati, A.; Brambilla, G.; Minoia, C.; Colosio, C. Exposure to Priority Organochlorine Contaminants in the Italian General Population. Part 1. Eight Priority Organochlorinated Pesticides in Blood Serum. Hum. Exp. Toxicol.; 2013; 32, pp. 1323-1339. [DOI: https://dx.doi.org/10.1177/0960327113485255]
91. Porta, D.; Fantini, F.; De Felip, E.; Blasetti, F.; Abballe, A.; Dell’Orco, V.; Fano, V.; Ingelido, A.M.; Narduzzi, S.; Forastiere, F. A Biomonitoring Study on Blood Levels of Beta-Hexachlorocyclohexane among People Living Close to an Industrial Area. Environ. Health; 2013; 12, 57. [DOI: https://dx.doi.org/10.1186/1476-069X-12-57]
92. Upson, K.; De Roos, A.J.; Thompson, M.L.; Sathyanarayana, S.; Scholes, D.; Barr, D.B.; Holt, V.L. Organochlorine Pesticides and Risk of Endometriosis: Findings from a Population-Based Case-Control Study. Environ. Health Perspect.; 2013; 121, pp. 1319-1324. [DOI: https://dx.doi.org/10.1289/ehp.1306648]
93. Porta, M.; Lopez, T.; Panades, M.G.; Rodríguez-Sanz, M.; Garí, M.; Pumarega, J.; Borrell, C.; Grimalt, J. Distribution of Blood Concentrations of Persistent Organic Pollutants in a Representative Sample of the Population of Barcelona in 2006, and Comparison with Levels in 2002. Sci. Total Environ.; 2012; 423, pp. 151-161. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2012.02.001]
94. Mørck, T.A.; Erdmann, S.E.; Long, M.; Mathiesen, L.; Nielsen, F.; Siersma, V.D.; Bonefeld-Jørgensen, E.C.; Knudsen, L.E. PCB Concentrations and Dioxin-like Activity in Blood Samples from Danish School Children and Their Mothers Living in Urban and Rural Areas. Basic Clin. Pharmacol. Toxicol.; 2014; 115, pp. 134-144. [DOI: https://dx.doi.org/10.1111/bcpt.12214]
95. Zubero, M.B.; Aurrekoetxea, J.J.; Murcia, M.; Ibarluzea, J.M.; Goñi, F.; Jiménez, C.; Ballester, F. Time Trends in Serum Organochlorine Pesticides and Polychlorinated Biphenyls in the General Population of Biscay, Spain. Arch. Environ. Contam. Toxicol.; 2015; 68, pp. 476-488. [DOI: https://dx.doi.org/10.1007/s00244-014-0107-6]
96. do Nascimento, F.P.; Kuno, R.; Lemes, V.R.R.; Kussumi, T.A.; Nakano, V.E.; Rocha, S.B.; de Oliveira, M.C.C.; de Albuquerque Kimura, I.; Gouveia, N. Organochlorine Pesticides Levels and Associated Factors in a Group of Blood Donors in São Paulo, Brazil. Environ. Monit. Assess.; 2017; 189, 380. [DOI: https://dx.doi.org/10.1007/s10661-017-6072-6] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/28685370]
97. Thomas, A.; Toms, L.-M.L.; Harden, F.A.; Hobson, P.; White, N.M.; Mengersen, K.L.; Mueller, J.F. Concentrations of Organochlorine Pesticides in Pooled Human Serum by Age and Gender. Environ. Res.; 2017; 154, pp. 10-18. [DOI: https://dx.doi.org/10.1016/j.envres.2016.12.009] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/27992738]
98. Pathak, R.; Ahmed, R.S.; Tripathi, A.K.; Guleria, K.; Sharma, C.S.; Makhijani, S.D.; Banerjee, B.D. Maternal and Cord Blood Levels of Organochlorine Pesticides: Association with Preterm Labor. Clin. Biochem.; 2009; 42, pp. 746-749. [DOI: https://dx.doi.org/10.1016/j.clinbiochem.2008.11.007]
99. Dhananjayan, V.; Ravichandran, B.; Rajmohan, H.R. Organochlorine Pesticide Residues in Blood Samples of Agriculture and Sheep Wool Workers in Bangalore (Rural), India. Bull. Environ. Contam. Toxicol.; 2012; 88, pp. 497-500. [DOI: https://dx.doi.org/10.1007/s00128-012-0546-6] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22323047]
100. Kanazawa, A.; Miyasita, C.; Okada, E.; Kobayashi, S.; Washino, N.; Sasaki, S.; Yoshioka, E.; Mizutani, F.; Chisaki, Y.; Saijo, Y. et al. Blood Persistent Organochlorine Pesticides in Pregnant Women in Relation to Physical and Environmental Variables in The Hokkaido Study on Environment and Children’s Health. Sci. Total Environ.; 2012; 426, pp. 73-82. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2012.02.073] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22503674]
101. Rudge, C.V.C.; Sandanger, T.; Röllin, H.B.; Calderon, I.M.P.; Volpato, G.; Silva, J.L.P.; Duarte, G.; Neto, C.M.; Sass, N.; Nakamura, M.U. et al. Levels of Selected Persistent Organic Pollutants in Blood from Delivering Women in Seven Selected Areas of São Paulo State, Brazil. Environ. Int.; 2012; 40, pp. 162-169. [DOI: https://dx.doi.org/10.1016/j.envint.2011.07.006]
102. Sharma, E.; Mustafa, M.; Pathak, R.; Guleria, K.; Ahmed, R.S.; Vaid, N.B.; Banerjee, B.D. A Case Control Study of Gene Environmental Interaction in Fetal Growth Restriction with Special Reference to Organochlorine Pesticides. Eur. J. Obstet. Gynecol. Reprod. Biol.; 2012; 161, pp. 163-169. [DOI: https://dx.doi.org/10.1016/j.ejogrb.2012.01.008] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22310945]
103. Dewan, P.; Jain, V.; Gupta, P.; Banerjee, B.D. Organochlorine Pesticide Residues in Maternal Blood, Cord Blood, Placenta, and Breastmilk and Their Relation to Birth Size. Chemosphere; 2013; 90, pp. 1704-1710. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2012.09.083]
104. Singh, N.; Chhillar, N.; Banerjee, B.; Bala, K.; Basu, M.; Mustafa, M. Organochlorine Pesticide Levels and Risk of Alzheimer’s Disease in North Indian Population. Hum. Exp. Toxicol.; 2013; 32, pp. 24-30. [DOI: https://dx.doi.org/10.1177/0960327112456315]
105. Zong, G.; Valvi, D.; Coull, B.; Göen, T.; Hu, F.B.; Nielsen, F.; Grandjean, P.; Sun, Q. Persistent Organic Pollutants and Risk of Type 2 Diabetes: A Prospective Investigation among Middle-Aged Women in Nurses’ Health Study II. Environ. Int.; 2018; 114, pp. 334-342. [DOI: https://dx.doi.org/10.1016/j.envint.2017.12.010]
106. Sharma, A.; Gill, J.P.S.; Bedi, J.S. Monitoring of Pesticide Residues in Human Blood from Punjab, India. Bull. Environ. Contam. Toxicol.; 2015; 94, pp. 640-646. [DOI: https://dx.doi.org/10.1007/s00128-015-1522-8] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25773703]
107. Arguin, H.; Sánchez, M.; Bray, G.A.; Lovejoy, J.C.; Peters, J.C.; Jandacek, R.J.; Chaput, J.-P.; Tremblay, A. Impact of Adopting a Vegan Diet or an Olestra Supplementation on Plasma Organochlorine Concentrations: Results from Two Pilot Studies. Br. J. Nutr.; 2010; 103, pp. 1433-1441. [DOI: https://dx.doi.org/10.1017/S000711450999331X] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/20030906]
108. Sawada, N.; Iwasaki, M.; Inoue, M.; Itoh, H.; Sasazuki, S.; Yamaji, T.; Shimazu, T.; Tsugane, S. Japan Public Health Center Based Prospective (JPHC) Study Group. Plasma Organochlorines and Subsequent Risk of Prostate Cancer in Japanese Men: A Nested Case-Control Study. Environ. Health Perspect.; 2010; 118, pp. 659-665. [DOI: https://dx.doi.org/10.1289/ehp.0901214]
109. Channa, K.R.; Röllin, H.B.; Wilson, K.S.; Nøst, T.H.; Odland, J.Ø.; Naik, I.; Sandanger, T.M. Regional Variation in Pesticide Concentrations in Plasma of Delivering Women Residing in Rural Indian Ocean Coastal Regions of South Africa. J. Environ. Monit.; 2012; 14, pp. 2952-2960. [DOI: https://dx.doi.org/10.1039/c2em30264k] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23047303]
110. Valera, B.; Ayotte, P.; Poirier, P.; Dewailly, E. Associations between Plasma Persistent Organic Pollutant Levels and Blood Pressure in Inuit Adults from Nunavik. Environ. Int.; 2013; 59, pp. 282-289. [DOI: https://dx.doi.org/10.1016/j.envint.2013.06.019] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/23872387]
111. Adlard, B.; Davis, K.; Liang, C.L.; Curren, M.S.; Rodríguez-Dozal, S.; Riojas-Rodríguez, H.; Hernández-Ávila, M.; Foster, W.; Needham, L.; Wong, L.-Y. et al. Persistent Organic Pollutants (POPs) and Metals in Primiparous Women: A Comparison from Canada and Mexico. Sci. Total Environ.; 2014; 500–501, pp. 302-313. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2014.08.074] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25233368]
112. Li, J.; Wang, P.; Shi, S.; Xue, J. Background Biomonitoring of Residue Levels of 137 Pesticides in the Blood Plasma of the General Population in Beijing. Environ. Monit. Assess.; 2018; 190, 315. [DOI: https://dx.doi.org/10.1007/s10661-018-6694-3]
113. Curren, M.S.; Davis, K.; Liang, C.L.; Adlard, B.; Foster, W.G.; Donaldson, S.G.; Kandola, K.; Brewster, J.; Potyrala, M.; Van Oostdam, J. Comparing Plasma Concentrations of Persistent Organic Pollutants and Metals in Primiparous Women from Northern and Southern Canada. Sci. Total Environ.; 2014; 479–480, pp. 306-318. [DOI: https://dx.doi.org/10.1016/j.scitotenv.2014.01.017]
114. Trejo-Acevedo, A.; Rivero-Pérez, N.E.; Flores-Ramírez, R.; Orta-García, S.T.; Varela-Silva, J.A.; Pérez-Maldonado, I.N. Assessment of the Levels of Persistent Organic Pollutants and 1-Hydroxypyrene in Blood and Urine Samples from Mexican Children Living in an Endemic Malaria Area in Mexico. Bull. Environ. Contam. Toxicol.; 2012; 88, pp. 828-832. [DOI: https://dx.doi.org/10.1007/s00128-012-0593-z]
115. Yin, S.; Zhang, J.; Guo, F.; Zhao, L.; Poma, G.; Covaci, A.; Liu, W. Transplacental Transfer of Organochlorine Pesticides: Concentration Ratio and Chiral Properties. Environ. Int.; 2019; 130, 104939. [DOI: https://dx.doi.org/10.1016/j.envint.2019.104939]
116. Louis, G.M.B.; Chen, Z.; Peterson, C.M.; Hediger, M.L.; Croughan, M.S.; Sundaram, R.; Stanford, J.B.; Varner, M.W.; Fujimoto, V.Y.; Giudice, L.C. et al. Persistent Lipophilic Environmental Chemicals and Endometriosis: The ENDO Study. Environ. Health Perspect.; 2012; 120, pp. 811-816. [DOI: https://dx.doi.org/10.1289/ehp.1104432] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/22417635]
117. Bates, M.N.; Thomson, B.; Garrett, N. Reduction in Organochlorine Levels in the Milk of New Zealand Women. Arch. Environ. Health Int. J.; 2002; 57, pp. 591-597. [DOI: https://dx.doi.org/10.1080/00039890209602093] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/12696658]
118. Petrik, J.; Drobna, B.; Pavuk, M.; Jursa, S.; Wimmerova, S.; Chovancova, J. Serum PCBs and Organochlorine Pesticides in Slovakia: Age, Gender, and Residence as Determinants of Organochlorine Concentrations. Chemosphere; 2006; 65, pp. 410-418. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2006.02.002] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/16530805]
119. Abhilash, P.C.; Jamil, S.; Singh, V.; Singh, A.; Singh, N.; Srivastava, S.C. Occurrence and Distribution of Hexachlorocyclohexane Isomers in Vegetation Samples from a Contaminated Area. Chemosphere; 2008; 72, pp. 79-86. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2008.01.056]
120. Anand, M.; Taneja, A. Organochlorine Pesticides Residue in Placenta and Their Influence on Anthropometric Measures of Infants. Environ. Res.; 2020; 182, 109106. [DOI: https://dx.doi.org/10.1016/j.envres.2019.109106]
121. Reddy, N.S.; Reddy, N.L.; Nissy, S.M.; Pallavi, G.; Vangalapati, M. Degradation of Dicofol by Synthesized ZnO Nanoparticles as Catalyst. Mater. Today Proc.; 2020; 26, pp. 1694-1700. [DOI: https://dx.doi.org/10.1016/j.matpr.2020.02.358]
122. Li, Y.F. Global Technical Hexachlorocyclohexane Usage and Its Contamination Consequences in the Environment: From 1948 to 1997. Sci. Total Environ.; 1999; 232, pp. 121-158. [DOI: https://dx.doi.org/10.1016/S0048-9697(99)00114-X]
123. Van der Gon, H.D.; Van het Bolscher, M.; Visschedijk, A.; Zandveld, P. Emissions of Persistent Organic Pollutants and Eight Candidate POPs from UNECE–Europe in 2000, 2010 and 2020 and the Emission Reduction Resulting from the Implementation of the UNECE POP Protocol. Atmos. Environ.; 2007; 41, pp. 9245-9261. [DOI: https://dx.doi.org/10.1016/j.atmosenv.2007.06.055]
124. Murthy, H.M.R.; Manonmani, H.K. Aerobic Degradation of Technical Hexachlorocyclohexane by a Defined Microbial Consortium. J. Hazard. Mater.; 2007; 149, pp. 18-25. [DOI: https://dx.doi.org/10.1016/j.jhazmat.2007.03.053]
125. Bravo, N.; Grimalt, J.O.; Chashchin, M.; Chashchin, V.P.; Odland, J.-Ø. Drivers of Maternal Accumulation of Organohalogen Pollutants in Arctic Areas (Chukotka, Russia) and 4,4′-DDT Effects on the Newborns. Environ. Int.; 2019; 124, pp. 541-552. [DOI: https://dx.doi.org/10.1016/j.envint.2019.01.049] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/30690245]
126. McTernan, P.G.; Anderson, L.A.; Anwar, A.J.; Eggo, M.C.; Crocker, J.; Barnett, A.H.; Stewart, P.M.; Kumar, S. Glucocorticoid Regulation of P450 Aromatase Activity in Human Adipose Tissue: Gender and Site Differences. J. Clin. Endocrinol. Metab.; 2002; 87, pp. 1327-1336. [DOI: https://dx.doi.org/10.1210/jcem.87.3.8288] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/11889205]
127. Silbergeld, E.K.; Flaws, J.A. Environmental Exposures and Women’s Health. Clin. Obstet. Gynecol.; 2002; 45, pp. 1119-1128. [DOI: https://dx.doi.org/10.1097/00003081-200212000-00019] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/12438889]
128. López-Flores, I.; González-Alzaga, B.; Casal, A.; Lacasaña, M. Exposición Laboral a Plaguicidas y Efectos En Salud: Contribución de Factores Biológicos y Sociales; Sanín-Aguirre, L.H.; Cedillo, L.; Guevara-Godínez, R.M. Género Salud y Ambiente Laboral: Chihuahua, Mexico, 2009.
129. García, A.M. Pesticide Exposure and Women’s Health. Am. J. Ind. Med.; 2003; 44, pp. 584-594. [DOI: https://dx.doi.org/10.1002/ajim.10256] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/14635235]
130. Robinson, E.; Nguyen, H.T.; Isom, S.; Quandt, S.A.; Grzywacz, J.G.; Chen, H.; Arcury, T.A. Wages, Wage Violations, and Pesticide Safety Experiencied by Migrant Farmaworkers in North Carolina. New Solut.; 2011; 21, pp. 251-268. [DOI: https://dx.doi.org/10.2190/NS.21.2.h] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/21733804]
131. Arrebola, J.P.; Mutch, E.; Rivero, M.; Choque, A.; Silvestre, S.; Olea, N.; Ocaña-Riola, R.; Mercado, L.A. Contribution of Sociodemographic Characteristics, Occupation, Diet and Lifestyle to DDT and DDE Concentrations in Serum and Adipose Tissue from a Bolivian Cohort. Environ. Int.; 2012; 38, pp. 54-61. [DOI: https://dx.doi.org/10.1016/j.envint.2011.08.006]
132. Wolff, M.S.; Deych, E.; Ojo, F.; Berkowitz, G.S. Predictors of Organochlorines in New York City Pregnant Women, 1998–2001. Environ. Res.; 2005; 97, pp. 170-177. [DOI: https://dx.doi.org/10.1016/j.envres.2004.07.014]
133. Li, Y.F.; Bidleman, T.F.; Barrie, L.A.; McConnell, L.L. Global Hexachlorocyclohexane Use Trends and Their Impact on the Arctic Atmospheric Environment. Geophys. Res. Lett.; 1998; 25, pp. 39-41. [DOI: https://dx.doi.org/10.1029/97GL03441]
134. Tao, S.; Li, B.G.; He, X.C.; Liu, W.X.; Shi, Z. Spatial and Temporal Variations and Possible Sources of Dichlorodiphenyltrichloroethane (DDT) and Its Metabolites in Rivers in Tianjin, China. Chemosphere; 2007; 68, pp. 10-16. [DOI: https://dx.doi.org/10.1016/j.chemosphere.2006.12.082]
135. Porta, M.; Puigdomènech, E.; Ballester, F.; Selva, J.; Ribas-Fitó, N.; Llop, S.; López, T. Monitoring Concentrations of Persistent Organic Pollutants in the General Population: The International Experience. Environ. Int.; 2008; 34, pp. 546-561. [DOI: https://dx.doi.org/10.1016/j.envint.2007.10.004]
136. Szlyk, P.C.; Sils, I.V.; Francesconi, R.P.; Hubbard, R.W. Patterns of Human Drinking: Effects of Exercise, Water Temperature, and Food Consumption. Aviat. Space Environ. Med.; 1990; 61, pp. 43-48.
137. Kortenkamp, A. Low Dose Mixture Effects of Endocrine Disrupters and Their Implications for Regulatory Thresholds in Chemical Risk Assessment. Curr. Opin. Pharmacol.; 2014; 19, pp. 105-111. [DOI: https://dx.doi.org/10.1016/j.coph.2014.08.006] [PubMed: https://www.ncbi.nlm.nih.gov/pubmed/25244397]
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Details
; Amaya, Esperanza 2 ; Pérez-Díaz, Celia 3
; Soler, Anabel 4 ; Vela-Soria, Fernando 5 ; Requena, Pilar 3 ; Barrios-Rodríguez, Rocío 1
; Echeverría, Ruth 4
; Pérez-Carrascosa, Francisco M 6
; Quesada-Jiménez, Raquel 2 ; Martín-Olmedo, Piedad 7
; Juan Pedro Arrebola 1 1 Departamento de Medicina Preventiva y Salud Pública, Universidad de Granada, 18071 Granada, Spain;
2 Instituto de Investigación Biosanitaria (ibs. GRANADA), 18014 Granada, Spain;
3 Departamento de Medicina Preventiva y Salud Pública, Universidad de Granada, 18071 Granada, Spain;
4 Departamento de Medicina Preventiva y Salud Pública, Universidad de Granada, 18071 Granada, Spain;
5 Instituto de Investigación Biosanitaria (ibs. GRANADA), 18014 Granada, Spain;
6 Departamento de Medicina Preventiva y Salud Pública, Universidad de Granada, 18071 Granada, Spain;
7 Instituto de Investigación Biosanitaria (ibs. GRANADA), 18014 Granada, Spain;