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Article

Sociodemographic and Lifestyle Factors Associated with Historical Exposure to Persistent Flame Retardant Concentrations in a Spanish Cohort

by
Eduardo Linares-Ruiz
1,
Celia Pérez-Díaz
1,2,
Francisco M. Pérez-Carrascosa
2,3,
Sara Gonzalez
4,
Juan José Ramos
4,
Inmaculada Salcedo-Bellido
1,2,5,* and
Juan Pedro Arrebola
1,2,5
1
Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain
2
Instituto de Investigación Biosanitaria de Granada ibs.GRANADA, 18012 Granada, Spain
3
Unidad de Gestión Clínica de Oncología Médica, Hospital Universitario de Jaén, 23007 Jaén, Spain
4
Centro Nacional de Sanidad Ambiental (CNSA), Instituto de Salud Carlos III, 28029 Madrid, Spain
5
CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, 28029 Madrid, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2026, 16(5), 2346; https://doi.org/10.3390/app16052346
Submission received: 30 December 2025 / Revised: 13 February 2026 / Accepted: 20 February 2026 / Published: 28 February 2026
(This article belongs to the Special Issue Exposure Pathways and Health Implications of Environmental Chemicals, 2nd Edition)
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The findings may contribute to the shaping of public health policies to identify population groups with elevated exposure to persistent flame retardants.

Abstract

The aim of this study was to estimate the historical exposure to a selection of polybrominated diphenyl ethers (PBDEs) and Dechlorane Plus (DP) concentrations and to identify the potential sociodemographic and lifestyle factors associated with this exposure. The study population (n = 134) was a subcohort of the GraMo Study, recruited in 2003–04 in Granada (Spain). Information on potential exposure-associated factors was collected through face-to-face interviews and a review of clinical records. Historical exposure was estimated by analyzing adipose tissue concentrations of 12 PBDEs and 2 DPs by means of gas chromatography coupled to a mass spectrometer. Data analyses included multivariable linear regression analyses. Median (interquartile range) pollutant concentrations ranged from 0.13 (0.09, 0.23) ng/g lipid for BDE-99 to 1.34 (0.92, 2.43) ng/g lipid for BDE-153. The body mass index was inversely associated with anti-DP, syn-DP, and BDE-153, -183, and -197 concentrations. Males exhibited higher levels of BDE-28, -47, -153, and -209 than females. Compared to non-manual workers, manual workers exhibited increased BDE-154, anti-DP, and syn-DP concentrations but lower BDE-28 levels. These findings highlight the elevated prevalence of PBDE/DP exposure and the heterogeneous exposure patterns observed across the study population. Further research is warranted to elucidate the long-term implications for human health.

1. Introduction

Persistent organic pollutants (POPs) are a myriad of chemicals that share a high resistance to degradation. As a result, they have a high potential for bioaccumulation in living organisms and biomagnification over the food chain [1,2]. In the general population, exposure to POPs occurs through multiple pathways, including dietary intake, particularly of animal-derived foods rich in lipids; ingestion and inhalation of contaminated indoor dust; inhalation of polluted indoor and outdoor air; and dermal contact with consumer products and treated materials [2,3,4]. Polybrominated diphenyl ethers (PBDEs) and Dechlorane Plus (DP) merit special attention among POPs because they are extensively used as halogenated flame retardants across many products (e.g., textiles, plastics, building materials and electronic devices) [5,6,7], and they have been found to accumulate in indoor dust and human tissues and travel long distances in the environment [8].
Polybrominated diphenyl ethers are a group of 209 congeners (designated BDE-1 to BDE-209) that have been widely used since the 1970s. PBDEs have been produced in different commercial mixtures, including Penta-BDE, Octa-BDE, and Deca-BDE [9,10]. Penta-BDE is predominantly composed of lower-brominated BDE congeners, with BDE-47 and -99 accounting for 38% and 49%, respectively; Octa-BDE refers to a mixture of PBDEs with 6–10 bromine substitutions (e.g., BDE-183); and Deca-BDE is composed primarily of BDE-209 (90%) [10]. DP was introduced in the market in the 1960s, and it was used as an alternative to PBDEs and the organochlorine pesticide Mirex [6,11]. Another halogenated flame retardant is DP, which was commercialized as a mixture of its two stereoisomers, with anti-DP predominant over syn-DP [11,12]. In this work, we decided to study PBDEs and DP together because, as mentioned above, they share similar applications, physicochemical properties, and exposure pathways.
Currently, most of the abovementioned chemicals have been listed for global elimination under different amendments to Annex A of the Stockholm Convention in 2009, 2017, and 2023 and are regulated by the European Union [13,14]. However, these pollutants are still frequently detected in the general population [4,15,16], with some of them considered as endocrine disrupting chemicals (EDCs), i.e., xenobiotics that can interfere with the endocrine system [17]. Frequent human exposure to low doses of EDCs has been linked to an elevated risk of developing several chronic non-communicable diseases, such as cancer, thyroid disease, as well as reproductive, neurobehavioral, and developmental disorders [18,19,20,21,22,23,24].
Considering the ubiquity of PBDEs/DP, human biomonitoring has emerged as a crucial tool to accurately evaluate individual chemical exposures, accounting for most exposure sources [25]. In addition, human biomonitoring allows the identification of trends in the exposure levels of the population [26]. In this regard, serum has been primarily used as the exposure matrix in most human biomonitoring studies [27,28,29,30,31,32]. Despite challenges in the sample collection, adipose tissue has been demonstrated to provide relevant information related to long-term exposure to moderately to highly lipophilic chemicals [3,33,34,35]. Thus, adipose tissue may help identify population groups with elevated accumulated exposure, thereby contributing to the adequate design of effective public health campaigns. Although prior literature has already studied legacy exposure to PBDEs/DP [36,37,38,39,40,41], few have measured these compounds in adipose tissue [42], and few have been conducted in Spain [43]. Moreover, hardly any study has comprehensively examined sociodemographic, occupational, dietary, and lifestyle determinants of PBDE/DP levels in adipose tissue. Our study addresses these gaps by quantifying PBDEs/DP in human adipose tissue from a Spanish cohort and by performing a detailed analysis of the factors associated with their concentrations.
Based on the abovementioned considerations, the objectives of this study were: (i) to quantify historical exposure to a selection of PBDEs and DP in a subsample of a Spanish adult cohort by measuring their concentrations in adipose tissue and (ii) to identify sociodemographic and lifestyle factors associated with the pollutant levels.

2. Materials and Methods

2.1. Study Design and Population

This cross-sectional study was conducted on a subcohort of the GraMo cohort (Granada province, Southern Spain), which aims to identify environmental factors affecting the development of several chronic diseases. A thorough description of the GraMo cohort has been provided elsewhere [44,45,46,47,48]. Briefly, participants were recruited between July 2003 and June 2004 from two public hospitals: the Clínico San Cecilio University Hospital in the city of Granada and the Santa Ana Hospital in the coastal town of Motril. Granada province includes rural, semirural, and urban areas. The city of Granada (238,292 inhabitants in 2004) and its metropolitan area (213,709 inhabitants in 2004) are mainly economically based on the service sector and light industry and frequently experience atmospheric thermal inversion episodes, leading to peaks in air concentrations of industrial pollutants [49]. In contrast, Motril (55,078 inhabitants in 2004) and its surroundings are characterized by a high density of intensive agriculture, including greenhouse farming, and windier conditions due to their coastal location [44,50]. These two areas are separated by approximately 70 km (Figure 1). Participants were selected from patients who underwent non-cancer-related surgeries. The inclusion criteria were as follows: age older than 16 years, no cancer diagnosis, no hormonal disease related to the hypothalamic axis, no hormone therapy, and at least 10 years of living in the referral areas of the recruiting hospitals. In total, 387 of the 409 people contacted (94.6%) agreed to participate and provided biological samples. A total of 179 participants provided sufficient biological samples for PBDEs/DP analysis; among them, 134 (74.96%) had complete information about sociodemographic and lifestyle factors and constituted the study population in the present work (Figure 2).
Although the data collection for this cross-sectional study was conducted in 2003–04, the analysis of PBDEs and DP was carried out in 2024 following the subsequent funding received from the Instituto de Salud Carlos III, Spain (PI20/01568). The original study protocol and ethical aspects were approved by the ethics committee of each participating hospital in 2002, and the current study received approval from the Provincial Ethics Committee of Biomedical Research of Granada (Comité de Ética de Investigación Clínica de Granada, 8/2016 and 7/2020). All participants included in this study were duly informed and signed the corresponding informed consent.

2.2. Sociodemographic, Lifestyle and Clinical Information

Sociodemographic attributes, dietary habits, occupation, perceived health status and chemical exposure information were gathered from face-to-face interviews by trained staff during the participants’ hospital stay at recruitment. Dietary habits were assessed using a semi-quantitative questionnaire [51,52], including the following food groups: meat, cold meats, fats, fish, eggs, dairy products (excluding milk and cheese), milk, cheese, vegetables, legumes, fruits, bread, and pasta. A participant was considered a smoker at any level of daily tobacco consumption (≥1 cigarette/week), and an alcohol consumer at any level of weekly alcohol consumption (≥1 glass/week). Body mass index (BMI) was expressed as weight/height squared (kg/m2). Participants’ area of residence was classified as urban (>100,000 inhabitants), semirural (10,000–100,000 inhabitants), or rural (<10,000 inhabitants). Following the Goldthorpe social class classification [53], participants were assigned to six occupational categories. Because of sample size limitations, social classes I–III were grouped as manual workers, and social classes IV–V as non-manual workers. Although this classification is based on participants’ principal occupation at enrollment, participants had remained in the same role for a mean of 16 years. Thus, occupational exposure captures not only current workplace conditions but also long-term exposure associated with their occupation. Furthermore, occupational social class reflects the socioeconomic hierarchy and is closely linked to income, material resources, and lifestyle-related factors, including diet, physical activity, and health behaviors, which may further influence both environmental exposures and health outcomes [54,55].

2.3. Laboratory Analyses

All standards were purchased from Wellinton Laboratories (Guelph, ON, Canada). The concentrations of 12 brominated flame retardants [bromodiphenyl ether (BDE) -28, -47, -99, -100, -153, -154, -183, -196, -197, -203, -209 and 1,3,5-tribromo-2-[2-(2,4,6-tribromophenoxy) ethoxy] benzene (BTBPE)] and 2 DP isomers (syn-DP and anti-DP) were analyzed in adipose tissue samples. First, 5–10 g adipose tissue samples were collected during each participant’s surgery. The samples were immediately coded and frozen at −80 °C until chemical analyses.
The sample preparation procedure was adapted from methods previously described [56,57]. Briefly, adipose tissue samples (in general, between 150 and 250 mg) were spiked with an internal standard (BDE-79 and BDE-138) and, after 30 min equilibration time, transferred to a 10 mL glass tube for extraction. In order to ensure complete disintegration of the sample and facilitate deeper penetration of the solvents [58], adipose tissue was, in the first stage, crushed and homogenized with an Ultra-Turrax® (T25, IKA, Barcelona, Spain) using 4 mL of n-hexane:acetone (1:1) as solvent extraction. Then, ultrasound-assisted extraction was carried out in an ultrasonic bath for 15 min at 40 °C. The extract obtained after centrifugation (4000 rpm, 4 °C, 10 min) was evaporated at 40 °C with a gentle flow of nitrogen up to 0.5 mL. The extract was cleaned in a multilayer silica gel column, packed in a 6 mL empty glass column and formed by 0.8 g of activated silica gel, 3 g of silica modified with sulfuric acid (44%, w/w), and 0.3 g of anhydrous sodium sulfate. Analytes were eluted with 8 mL of n-hexane and 6 mL of dichloromethane (DCM) (1:1, v/v). The extract was evaporated to dryness and finally reconstituted with 100 µL of 13C-labeled BDE-209 solution in isooctane.
Based on a previous study [59], instrumental analysis was performed by gas chromatography (GC) (HP 7890A Series, Hewlett-Packard, Palo Alto, CA, USA) equipped with a multimode inlet (MMI) and coupled to a single quadrupole mass spectrometer in negative chemical ionization mode (NCI-MS, 5975C Agilent Santa Clara, CA, USA). This MS soft-ionization is widely used for the determination of polybrominated compounds because it provides less fragmentation and high sensitivity, i.e., up to 15 times higher than electron ionization (EI-MS) [60,61]. Thus, 5 µL was injected in large volume injection (LVI), and chromatography separation was carried out by a DB-5MS column (15 m × 0.25 mm × 0.10 µm, Agilent). The GC oven temperature was programmed from 80 °C (held for 2.6 min) to 200 °C at 30 °C/min, then up to 275 °C at 5 °C/min, and finally to 315 °C (6 min) at 50 °C/min. Helium was used as the carrier gas, ramping the flow from 1.5 mL/min (19.8 min) up to 4.5 mL/min (9 min) to avoid BDE-209 column degradation. A mass spectrometer used methane as a reagent gas and 70 eV of electron energy. Transfer line, quadrupole, and ion source temperatures were set at 300, 150, and 150 °C, respectively. Quantification was performed in selected ion monitoring (SIM).
Quantification based on nine-point calibration curves from 0.05 to 20.00 ng/mL, except for BDE-209, i.e., 0.5–200 ng/mL, with satisfactory linearity (R2 > 0.996) was obtained. For internal quality control purposes, procedure blanks and quality controls at 0.1 ng/mL and 1 ng/mL (1 and 10 ng/mL for BDE 209) processed in the same way as the samples were included in every analytical series, i.e., twelve samples. As confirmation criteria, retention times and the maintenance of the ratio of the two selected ions within 15% of the standard value were used.
The lipid content in adipose tissue samples was quantified by gravimetry, as reported by Rivas et al. [61], which was used for normalizing PBDE/DP concentrations, as reported by Phillips et al. [62]. The final concentrations were then expressed as nanograms per gram of lipid (ng/g lipid).
Limits of quantitation (LOQ) for the PBDE congeners, BTBPE and DPs ranged from 0.0029 to 0.0785 ng/g lipid (Supplementary Material, Table S1). The chromatography laboratory at the Centro Nacional de Sanidad Ambiental has participated in the HBM4EU QA/QC program, resulting in its qualification as an EU laboratory for the analysis of PBDE and DPs in human serum.

2.4. Statistical Analyses

Descriptive analyses included absolute values and percentages for categorical variables; mean, standard deviation (SD), and median and interquartile range (IQR, 25th and 75th percentiles) for continuous variables. Chemical concentrations were reported in ng/kg lipid for clarity in the descriptive analysis, whereas these variables were entered as ng/g lipid in the regression models to improve the interpretability of the model’s coefficients.
For PBDEs and DP with quantification rates above 70%, values below the LOD were imputed by assigning a random number between 0 and the LOQ. BTBPE, BDE-196, and BDE-203 were excluded from analyses because their quantification rates were below 70%. Concentrations were natural log-transformed to relax the linearity assumption. Consequently, the beta coefficients (β) reflect the average change in the natural log-transformed pollutant concentration (ng/g lipid) associated with a 1-unit increase in continuous independent variables. For categorical variables, β indicates the average difference in the log-transformed concentrations between that category and the reference category. Associations of sociodemographic, lifestyle, occupation and perceived chemical exposure (independent variables) with PBDEs and both DP isomers (dependent variables) were identified using multivariable linear regression with manual stepwise forward–backward model variable selection. First, variables were selected based on the available literature and biological plausibility as potential factors of PBDEs/DP exposure [63,64,65,66,67]. Then, we used a two-stage selection procedure (Supplementary Material, Figure S1):
  • Forward selection stage: Independent variables with a p-value ≤ 0.20 were retained in the same multivariable model.
  • Backward elimination stage: Independent variables with p-value ≥ 0.10 and/or substantial increase in Bayesian information criterion (BIC) (ΔBIC ≥ 10, in accordance with Raftery’s approach [68]) were excluded from the model.
Statistical analyses were performed using R Statistical Software v4.5.0 (R Core Team 2025) [69]. Linear regressions were performed using base R, and descriptive tables were generated using the “gtsummary” package (v2.2.0) [70].

3. Results and Discussion

3.1. Description of the Study Population and Adipose Tissue Pollutant Concentrations

The main characteristics of the study population are summarized in Table 1. This subcohort included slightly fewer females than males. The mean BMI in our cohort was 27.9 kg/m2. This was higher than the average BMI reported for the Andalusian population in 2003 [71], likely because our hospital-based cohort included participants with obesity-related conditions. In our population, approximately one-third of the participants were smokers at recruitment, and 69.9% of males and 29.5% of females reported being alcohol consumers. These results are similar to those reported for the Andalusian population [71]. In our study, manual workers were predominant, while a higher proportion of females (but not males) resided in semirural areas vs. urban and rural areas.
PBDE/DP concentrations in adipose tissue are summarized in Table 1. Males showed consistently higher levels of PBDEs than females. PBDE/DP detection frequencies ranged from 82.8% (BDE-209) to 100.0% (BDE-99, -153, -154, and -183 and anti-DP) (Supplementary Material, Table S2). In accordance with previous studies, BDE-153 was the predominant congener [10,30,32,72,73,74,75,76,77,78,79]; in other studies, the most prevalent congener was BDE-47 [42,63,80]. Our findings may be explained by the following factors: (i) increased relative exposure to BDE-153 compared to other PBDEs and (ii) slower metabolism in humans [10,30]. In fact, lower-brominated BDEs, such as BDE-153, have been found to have longer half-lives and are therefore more likely to accumulate at higher concentrations in human tissues. Congruently, in our study, BDE-209, with a relatively high degree of bromination, was found at the lowest detection rates [81].
No differences in bioaccumulation were observed between the two DP isomers. In our study, anti-DP was the predominant form with an average anti-DP fraction (anti-DP/total DP) of 0.75 ± 0.11, consistent with the reported proportions in commercial DP products ranging between 0.60 and 0.80 [82], and in prior studies in humans (sample size ranging from 20 to 105), with anti-DP fractions ranging between 0.71 and 0.79 [11,36,83,84]. These findings may suggest no stereoselectivity in the entry into the human body or metabolism and primarily legacy exposure. However, in highly exposed occupational roles, populations with lower anti-DP fractions have been reported [85,86].

3.2. Factors Associated with PBDE and DP Concentrations in Adipose Tissue

As described in the Section 2, we fitted a model for each individual pollutant by entering all the variables found relevant during its individual forward–backward selection. For clarity purposes, each model’s data are split into three tables, corresponding to sociodemographic (Table 2), perceived exposures (Table 3) and dietary (Table 4) variables.
Overall, we observed apparently robust, statistically significant inverse associations between BMI and concentrations of PBDEs and DP. We also found robust positive associations between males and PBDEs (Table 2); perceived exposure to paints and PBDEs levels, notably BDE-47 and BDE-99 (Table 3); and fish consumption and PBDEs, specifically BDE-183 and -197 (Table 4). These findings will be more extensively discussed below.
Regarding sociodemographic and anthropometric characteristics (Table 2), males showed higher BDE-28, -47, -153 and -209 adipose tissue concentrations than females. Furthermore, sensitivity analyses examining the association between PBDEs/DP and breastfeeding (dichotomized) showed inverse, although non-significant, trends, except for BDE-28. Our results are in agreement with those from previous studies [30,32,72,87,88,89,90,91], since the observed lower levels of PBDEs in females may be the result of a clearance process during pregnancy and breastfeeding, as Bramwell et al. hypothesized [32]. Internal flame retardant levels may be reduced during breastfeeding due to the high affinity of flame retardants for lipid-rich structures. In addition, PBDEs cross the placenta and can selectively accumulate in the fetus and the umbilical cord [91,92]. These processes are consistent with previous studies that have detected flame retardants in breast milk [10,93,94], and umbilical cord blood [92,95,96,97].
We hypothesize that the higher PBDE concentrations in males vs. females in our study population may be related, at least in part, to lifestyle differences, as previously observed for other POPs in the GraMo cohort [44,46,98]. Indeed, in our study, males reported an increased consumption of fatty food from animal origin, such as pork (23.3% vs. 6.6%), while chicken consumption was predominant in females (41.0% vs. 26.0%). Additionally, 20.55% of males and 1.64% of females acknowledged involvement in industrial activities, such as operators of installations, machinery assemblers, craftsmen, and workers in industry, construction, and mining.
Interestingly, age was inversely linked to BDE-47 and -99. These findings are consistent with prior studies reporting inverse associations of age with BDE-47 and -99, with lower levels for middle-aged adults compared to younger or older adults [89,99]. This may be explained by the relatively recent manufacture and environmental release of PBDEs; younger individuals have therefore spent most of their lives exposed to higher environmental concentrations, whereas older adults were largely unexposed for much of their lives [89,99].
The BMI was negatively associated with BDE-153, -183, -197 and syn- and anti-DP (Table 2). A sensitivity analysis with BMI categorized into three categories (<25 kg/m2, 25–30 kg/m2 and ≥30 kg/m2) corroborated this negative trend. In particular, 25–30 kg/m2 vs. <25 kg/m2 showed significant negative β coefficients ranging from −0.37 to −0.50 for BDE-183, -197, and both syn- and anti-DP. The association for BDE-153 was also inverse but did not reach statistical significance (β = −0.27, p-value = 0.092). Similar inverse associations for BDE-153 were described in previous studies using serum as the matrix for exposure assessment [29,32,88,100]. This negative trend may be attributed to a dilution effect of PBDEs in obese individuals, as initially proposed by Wolff et al. [29,101]. This might be particularly relevant in our population, with 39.6% overweight and 27.6% obese individuals.
Manual workers showed lower BDE-28 and higher BDE-154, anti-DP, and syn-DP concentrations compared to non-manual workers (Table 2). These findings are consistent with previous studies identifying specific manual activities, such as industrial manufacturing, construction, and e-waste recycling, as sources of PBDE exposure [102,103,104].
Regarding perceived exposure (Table 3), higher BDE-28, -47, -99, -100 and -153 levels were associated with perceived exposure to paints. Furthermore, elevated BDE-154 and -183 concentrations were associated with perceived exposure to solvents. In addition, some paints, which often contain PBDEs in their composition [7,105,106], have shown positive correlations with these pollutants, as reported in a Korean study that used umbilical cord blood as a biological matrix [107].
Lower concentrations of BDE-47, -153, and -154 were associated with perceived exposure to toxic metals (Table 3). Toxic metals can co-occur in the same PBDE sources, such as recycling sites or industrial activities [108]. Thus, perceived exposure to toxic metals does not appear to be a useful indicator of highly PBDE/DP-exposed individuals. We hypothesize that the negative associations observed may be explained by greater implementation or adherence to safety measures among individuals who perceive themselves as being at risk, as shown in previous studies [109,110,111]. This interpretation, although highly speculative, opens the door to future population-based interventions to confirm whether increasing awareness of exposure is effective for reducing the body burden.
Higher BDE-99 levels were observed in former smokers but not in current smokers (Table 3). Lower BDE-209 levels were associated with alcohol consumption. Both tobacco and alcohol can upregulate the cytochrome P450 family [112,113,114,115]; in particular, tobacco consumption induces CYP2B6 [116], which is thought to be the main metabolic pathway of BDE-99 [117,118,119]. Thus, smoking would be expected to enhance the metabolic clearance of BDE-99. However, we did not observe reduced BDE-99 levels among current smokers. Additionally, BDE-209 metabolic pathways remain incompletely understood [117,120]. We cannot provide a definitive explanation and cannot exclude the possibility that this finding arose by chance.
Regarding dietary variables (Table 4), higher BDE-197 levels were associated with oily fish consumption and elevated BDE-183 and -197 with consumption ≥ 2 portions/week. This may be due to the fact that fish has previously been identified as the main dietary source of PBDEs [67,121,122]. BDE-28 was also linked to meat consumption frequency larger than two portions per week. This is consistent with previous epidemiological studies that have associated meat consumption with PBDE levels [30,67,75]. However, in our population, an inverse association was found for BDE-99 and eggs (Table 4). Considering the limited biological plausibility and the exploratory nature of this study, we consider that this might be a chance finding or even a result of a confounding effect of a third uncontrolled variable in the models, since BDE-99 has been reported as the dominant congener in eggs [123].
Other fatty products from animal origin, such as dairy products, have been established as a source of organic pollutants [124]. In our study, higher BDE-153 concentrations were associated with cheese consumption and daily milk consumption.
In our study, lower BDE-153 levels were associated with vegetable consumption. This is consistent with prior research reporting lower PBDE levels among individuals following vegetarian versus omnivorous diets [30]. In addition, consumption of dietary fiber, characteristic of plant-based diets, may reduce the intestinal absorption of organic pollutants [125,126].
Nonetheless, higher BDE-197 concentrations were positively linked with fruit consumption. Other congeners have been related to fruit through industrial processes such as “hydro-cooling”, which involves the use of BDE-209-coated pallets [7,28]. Nevertheless, this finding has no precedent and, therefore, warrants further confirmation.
This study has potential limitations to take into account in the interpretation of the results. Firstly, the study size, and especially the sex-stratified subsamples, was relatively small, although it was sufficient to detect trends warranting confirmation in larger cohorts. Secondly, although our hospital-based design may limit generalizability, the study population resembles the general adult population of the study area in several important aspects, such as sex distribution and prevalence of major lifestyle factors such as smoking and alcohol consumption [50]. Of note, PBDEs and DP levels are unlikely to be influenced by our heterogeneous selection criteria (including conditions such as gallbladder disease, varicose veins, or hernias). The large number of analyses increases the risk of false positives due to multiple comparisons. Nevertheless, this study is exploratory and aims to identify population subgroups with higher PBDE/DP exposure; therefore, our findings will require confirmation in future studies. Thirdly, the chemical exposure profile has changed over time, with some compounds now restricted and others newly introduced. Nevertheless, we consider that the exposure characterization presented in this work is highly relevant for two reasons. On the one hand, many of the compounds studied, although restricted, are still frequently detected in the population due to their high persistence and ubiquity, therefore posing public health concerns. On the other hand, this study represents a crucial first step toward longitudinal investigations of the health effects of this exposure, which are currently being conducted in the GraMo cohort.
This study has notable strengths. As previously mentioned, the use of adipose tissue for exposure assessment provides a highly accurate measure of long-term PBDE accumulation. This matrix also reduces intra-sample variability compared to other biological specimens, such as serum, thereby minimizing random error and lowering the sample size needed to detect associations [33]. Furthermore, adipose tissue might be particularly relevant in hospital-based studies conducted in countries with universal public healthcare systems such as Spain, where routine clinical or surgical procedures provide opportunities to collect adipose tissue samples from large and heterogeneous population samples. In addition, this study was performed within the well-characterized GraMo cohort, which provides detailed sociodemographic, lifestyle, metabolic, and exposure information for participants. Notably, our study is among the largest to utilize adipose tissue for PBDE/DP exposure assessment in adults. Importantly, our chemical analyses covered a wide range of PBDE congeners and both stereoisomers of DP, with concentrations quantified using validated and high-quality analytical methods that reduce exposure misclassification.

4. Conclusions

Our study revealed that exposure to PBDEs and DP in the GraMo cohort, as estimated through the analysis of adipose tissue samples, was ubiquitous in the study population, with pollutant levels ranging between 73.1 ng/kg lipid for BDE-28 and 1335.2 ng/kg lipid for BDE-153. Based on the consistency and robustness of the findings, sex, BMI, and self-reported exposure to paints and solvents were identified as the main factors associated with exposure. These results might help better target public health interventions by identifying modifiable factors associated with the exposure. However, due to the exploratory nature of this study, our findings need to be confirmed by further research.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/app16052346/s1, Figure S1: Manual step forward–backward model variables selection; Table S1: Limit of quantification of PBDEs/DP; Table S2: Baseline detection of PBDEs/DP of study population.

Author Contributions

E.L.-R., formal analysis, investigation and writing—original draft; C.P.-D., data curation and writing—review and editing; F.M.P.-C., data curation and writing—review and editing; S.G., investigation, writing—review and editing; J.J.R., investigation, writing—review and editing; I.S.-B., conceptualization, supervision and writing—review and editing; J.P.A., conceptualization, funding acquisition, supervision and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

Research was funded by research grants from the CIBER de Epidemiología y Salud Pública (CIBERESP), Instituto de Salud Carlos III, Spain (PI16/01858), co-funded by the European Union (FEDER). Celia Pérez-Díaz is under contract PFIS (FI21/00269, Predoctoral Health Research Training Contracts, Instituto de Salud Carlos III, Spain).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of each hospital and subsequently by the ethics committee, “the Provincial Ethics Committee of Biomedical Research of Granada (Comité de Ética de Investigación Clínica de Granada)” (8/2016 and 7/2020).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Acknowledgments

These findings would not have been possible without the generous support of the staff at Santa Ana and San Cecilio Hospitals and the participation of our study volunteers. This article will form part of the doctoral thesis developed by Eduardo Linares-Ruiz in the context of the “Programa de Doctorado de Medicina Clínica y Salud Pública” of the University of Granada (Spain).

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
BDEBromodiphenyl ether
BICBayesian information criterion
BMIBody mass index
BTBPE1,3,5-tribromo-2-[2-(2,4,6-tribromophenoxy) ethoxy] benzene
CIConfidence interval
DMCDichloromethane
DPDechlorane plus
EDCEndocrine disruptor chemical
IQRInterquartile range
LOQLimit of quantification
LVILarge volume injection
MMIMultimode inlet
PBDEsPolibromodiphenyl ethers
POPsPersistent organic pollutants
SDStandard deviation
SNHSSpanish National Health Survey
SIMSelected ion monitoring
βBeta coefficient

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Applsci 16 02346 g001
Figure 1. Map of Granada province with participants’ distribution.
Figure 1. Map of Granada province with participants’ distribution.
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Figure 2. Study population selection.
Figure 2. Study population selection.
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Table 1. Baseline main characteristics of the study population with measures of PBDEs/DP (ng/kg lipid).
Table 1. Baseline main characteristics of the study population with measures of PBDEs/DP (ng/kg lipid).
VariableAll (n = 134)Females (n = 61)Males (n = 73)
n (%)n (%)n (%)
Sex = Female61 (45.5%)61 (100.0%)0 (0.0%)
Residence
   Urban24 (17.9%)6 (9.8%)18 (24.7%)
   Semirural59 (44.0%)39 (63.9%)20 (27.4%)
   Rural51 (38.1%)16 (26.2%)35 (47.9%)
Social occupational class = manual workers104 (77.6%)48 (78.7%)56 (76.7%)
Alcohol consumers69 (51.5%)18 (29.5%)51 (69.9%)
Smoking habit
    No smoker51 (38.1%)38 (62.3%)13 (17.8%)
    Former smoker34 (25.4%)10 (16.4%)24 (32.9%)
    Smoker49 (36.6%)13 (21.3%)36 (49.3%)
Sample collection’s surgery
   Hernia63 (47.0%)16 (26.2%)47 (64.4%)
   Gallbladder20 (14.9%)14 (23.0%)6 (8.2%)
   Benign tumor/hyperplasia14 (10.4%)10 (16.4%)4 (5.5%)
   Other37 (27.6%)21 (34.4%)16 (21.9%)
Mean (SD 1)Mean (SD 1)Mean (SD 1)
Age (years)50 (17.3)51 (17.3)50 (17.4)
BMI 3 (kg/m2)27.9 (5.6)27.6 (5.7)28.0 (5.6)
Median (IQR 2)Median (IQR 2)Median (IQR 2)
BDE 4-2873.1 (35.0, 127.2)58.6 (31.8, 115.9)93.7 (41.5, 136.0)
BDE 4-47353.0 (203.5, 546.7)266.2 (179.4, 456.3)393.6 (276.8, 579.4)
BDE 4-99130.8 (89.9, 230.7)117.4 (81.4, 184.8)140.5 (102.0, 294.6)
BDE 4-100301.4 (173.0, 453.4)287.3 (159.3, 403.0)313.6 (194.6, 455.7)
BDE 4-1531335.2 (918.2, 2432.2)1205.1 (842.7, 1831.0)1501.5 (994.5, 3116.0)
BDE 4-154429.7 (306.6, 678.7)412.0 (277.8, 583.1)483.3 (325.6, 689.6)
BDE 4-183419.2 (247.2, 595.7)412.3 (248.5, 581.8)420.0 (242.2, 677.8)
BDE 4-197564.5 (338.5, 990.9)560.1 (342.7, 974.0)569.0 (321.0, 1001.1)
BDE 4-209614.4 (308.2, 1052.4)543.7 (190.9, 1006.4)693.3 (342.0, 1121.0)
Syn-DP 582.9 (39.9, 163.9)79.7 (37.2, 147.4)84.4 (42.8, 182.1)
Anti-DP 5247.0 (157.7, 417.6)274.3 (179.6, 350.3)226.7 (148.5, 481.5)
1 Standard deviation; 2 25th and 75th percentiles; 3 body mass index; 4 brominated diphenyl ether; 5 Dechlorane Plus. Pollutant concentrations are expressed as ng/kg lipid in order to improve readability. Participants were categorized as alcohol consumers if their intake exceeded one drink per week.
Table 2. Summary of the multivariable linear regression models exploring factors associated with PBDE and DP adipose tissue concentrations (n = 134). Sociodemographic and anthropometric variables.
Table 2. Summary of the multivariable linear regression models exploring factors associated with PBDE and DP adipose tissue concentrations (n = 134). Sociodemographic and anthropometric variables.
BDE-28 1BDE-47 1BDE-99 1BDE-100 1BDE-153 1BDE-154 1BDE-183 1BDE-197 1BDE-209 1Syn-DP 2Anti-DP 2
β 3 (95% CI) 4
Sex = male0.37 (0.02, 0.71)0.47 (0.12, 0.82) 0.42 (0.05, 0.79) 1.06 (0.27, 1.84)
Age (years) −0.01 (−0.02, 0.00)−0.01 (−0.02, 0.00) −0.01 (−0.02, 0.00)
BMI 5 (kg/m2) −0.04 (−0.07, −0.01) −0.03 (−0.05, −0.01)−0.05 (−0.07, −0.02) −0.04 (−0.07, −0.01)−0.04 (−0.06, −0.02)
Occupation = manual worker−0.54 (−0.95, −0.13) 0.33 (0.01, 0.64) 0.51 (0.07, 0.94)0.38 (0.06, 0.69)
Residence
Urban 6 Ref.
Semirural 7 −0.16 (−0.51, 0.20)
Rural 8 −0.36 (−0.72, 0.00)
1 Bromodiphenyl ether; 2 Dechlorane Plus; 3 beta; 4 confidence interval; 5 body mass index; 6 (>100,000 inhabitants); 7 (100,000–10,000 inhabitants); 8 (<10,000 inhabitants); estimates in bold indicate p-value < 0.05. Dependent variable pollutant concentrations (ng/g lipid) were natural log-transformed for the analyses. The coefficients displayed in the table represent models adjusted for the variables included in the other tables. For improving interpretability, the model coefficients are split into three tables, corresponding to sociodemographic (this table), perceived exposures (Table 3) and dietary (Table 4) variables.
Table 3. Summary of the multivariable linear regression models exploring factors associated with each PBDE and DP adipose tissue concentrations (n = 134): perceived exposures.
Table 3. Summary of the multivariable linear regression models exploring factors associated with each PBDE and DP adipose tissue concentrations (n = 134): perceived exposures.
BDE-28 1BDE-47 1BDE-99 1BDE-100 1BDE-153 1BDE-154 1BDE-183 1BDE-197 1BDE-209 1Syn-DP 2Anti-DP 2
Perceived Exposure toβ 3 (95% CI) 4
Paints = Yes0.61 (0.16, 1.06)0.85 (0.40, 1.30)0.80 (0.41, 1.19)0.56 (0.05, 1.08)0.67 (0.22, 1.13)
Solvents = Yes 0.42 (0.02, 0.82)0.58 (0.18, 0.98)0.44 (−0.01, 0.89)
Toxic metals = Yes −0.74 (−1.27, −0.22)−0.38 (−0.82, 0.06) −1.05 (−1.58, −0.52)−0.38 (−0.75, −0.01)
Alcohol consumption = Yes −0.80 (−1.59, −0.02)0.32 (−0.04, 0.69)
Smoking habit
No smoker Ref.
Former smoker 0.48 (0.11, 0.85)
Smoker 0.16 (−0.19, 0.50)
1 Bromodiphenyl ether; 2 dechlorane plus; 3 beta; 4 confidence interval; estimates in bold indicate p-value < 0.05. Dependent variable pollutant concentrations (ng/g lipid) were natural log-transformed for the analyses. For improving interpretability, the model coefficients are split into three tables, corresponding to sociodemographic (Table 2), perceived exposures (this table) and dietary (Table 4) variables.
Table 4. Summary of the multivariable linear regression models exploring factors associated with each PBDE and DP adipose tissue concentrations (n = 134): dietary.
Table 4. Summary of the multivariable linear regression models exploring factors associated with each PBDE and DP adipose tissue concentrations (n = 134): dietary.
BDE-28 1BDE-47 1BDE-99 1BDE-100 1BDE-153 1BDE-154 1BDE-183 1BDE-197 1BDE-209 1Syn-DP 2Anti-DP 2
β 3 (95% CI) 4
Fish consumption ≥ 2 portions/week 0.38 (0.11, 0.65)0.38 (0.08, 0.69)
Oily fish consumption = Yes 0.45 (0.14, 0.77)
Meat consumption > 2 portions/week0.45 (0.11, 0.80)
Vegetable consumption > 2 portions/week 0.42 (−0.07, 0.91)−0.54 (−0.96, −0.12) −0.35 (−0.70, 0.00)
Fruit consumption > 2 portions/week 0.36 (−0.01, 0.74)0.46 (0.04, 0.88) 0.50 (−0.01, 1.01)
Bread consumption > 1 portion/week 0.35 (−0.07, 0.77)
Cheese consumption > 2 portions/week 0.49 (0.16, 0.82)
Number of glasses of milk per day 0.20 (0.06, 0.35)
Egg consumption
≤1 portion/week Ref.
2 portions/week −0.35 (−0.70, −0.01)
2 portions/week −0.34 (−0.72, 0.05)
1 Bromodiphenyl ether; 2 dechlorane plus; 3 beta; 4 confidence interval; estimates in bold indicate p-value < 0.05. Dependent variable pollutant concentrations (ng/g lipid) were log-transformed for the analyses. For improving interpretability, the model coefficients are split into three tables, corresponding to sociodemographic (Table 2), perceived exposures (Table 3) and dietary (this table) variables.
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Linares-Ruiz, E.; Pérez-Díaz, C.; Pérez-Carrascosa, F.M.; Gonzalez, S.; Ramos, J.J.; Salcedo-Bellido, I.; Arrebola, J.P. Sociodemographic and Lifestyle Factors Associated with Historical Exposure to Persistent Flame Retardant Concentrations in a Spanish Cohort. Appl. Sci. 2026, 16, 2346. https://doi.org/10.3390/app16052346

AMA Style

Linares-Ruiz E, Pérez-Díaz C, Pérez-Carrascosa FM, Gonzalez S, Ramos JJ, Salcedo-Bellido I, Arrebola JP. Sociodemographic and Lifestyle Factors Associated with Historical Exposure to Persistent Flame Retardant Concentrations in a Spanish Cohort. Applied Sciences. 2026; 16(5):2346. https://doi.org/10.3390/app16052346

Chicago/Turabian Style

Linares-Ruiz, Eduardo, Celia Pérez-Díaz, Francisco M. Pérez-Carrascosa, Sara Gonzalez, Juan José Ramos, Inmaculada Salcedo-Bellido, and Juan Pedro Arrebola. 2026. "Sociodemographic and Lifestyle Factors Associated with Historical Exposure to Persistent Flame Retardant Concentrations in a Spanish Cohort" Applied Sciences 16, no. 5: 2346. https://doi.org/10.3390/app16052346

APA Style

Linares-Ruiz, E., Pérez-Díaz, C., Pérez-Carrascosa, F. M., Gonzalez, S., Ramos, J. J., Salcedo-Bellido, I., & Arrebola, J. P. (2026). Sociodemographic and Lifestyle Factors Associated with Historical Exposure to Persistent Flame Retardant Concentrations in a Spanish Cohort. Applied Sciences, 16(5), 2346. https://doi.org/10.3390/app16052346

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