3.1 Study population
Of participants, 46.4% of children and adolescents were male and 53.6% were female, with a mean age of 12.5 ± 3.2 years old (Table 1). A total of 51.9% of mothers attained less than a high school degree, 24.7% attained equal to a high school degree, and 23.4% participated in college. The majority of food groups was generally categorized into tertiles, except for vegetable intake. A total of 49.9% of the participants were divided into the third tertile due to their high proportion of seven meals per week for vegetable consumption. The source of drinking water was mainly tap water (63.1%), followed by barreled water (22.1%), purified water (14.0%), and others (0.8%).
3.2 Concentrations of urinary OPE metabolites
Table 2 displayed the concentration distributions of urinary OPE metabolites in children and adolescents. Six OPE metabolites (TCEP, BCIPHIPP, BDCIPP, DPHP, BBOEP, and DoCP & DpCP) were detected in >70% of the urine samples, suggesting widespread exposure to OPEs for the study participants. BCIPHIPP, TCEP, DPHP, and BDCIPP were the primary four metabolites in the urine samples, with SG-corrected median concentrations of 0.37 ng/mL, 0.27 ng/mL, 0.22 ng/mL, and 0.19 ng/mL, respectively.
Table 2
Descriptive statistics for OPEs and their urinary metabolites.
Analytes | Parent compound | >LOD (%) | LOD | GM | Percentile | Max |
25th | 50th | 75th | 95th |
SG-corrected urine (ng/mL) |
TCEP | TCEP | 79.3 | 0.092 | 0.28 | 0.13 | 0.27 | 0.55 | 1.60 | 11.0 |
BCIPHIPP | TCIPP | 85.7 | 0.097 | 0.35 | 0.20 | 0.37 | 0.63 | 1.79 | 28.8 |
BDCIPP | TDCIPP | 78.1 | 0.064 | 0.18 | 0.07 | 0.19 | 0.41 | 1.04 | 6.06 |
DBP | TBP | 25.2 | 0.058 | 0.07 | <LOD | <LOD | 0.08 | 1.08 | 7.70 |
4-OH-DPHP | TPHP | 42.0 | 0.043 | 0.08 | <LOD | <LOD | 0.24 | 1.95 | 11.2 |
DPHP | TPHP/EHDPP | 91.7 | 0.036 | 0.24 | 0.10 | 0.22 | 0.49 | 2.03 | 25.5 |
BBOEP | TBOEP | 89.6 | 0.012 | 0.12 | 0.03 | 0.16 | 0.37 | 1.07 | 7.43 |
DoCP & DpCP | TCrP | 70.7 | 0.032 | 0.06 | 0.03 | 0.05 | 0.10 | 0.29 | 1.89 |
Handwipes (ng/wipe) |
TCEP | | 65.0 | 0.66 | 1.04 | 0.47 | 0.90 | 1.72 | 4.99 | 27.4 |
TCIPP | | 87.1 | 2.50 | 9.58 | 4.63 | 9.49 | 18.1 | 59.4 | 847 |
TDCIPP | | 81.1 | 0.80 | 2.09 | 1.01 | 2.02 | 3.85 | 13.2 | 64.3 |
TPHP | | 89.9 | 1.00 | 4.08 | 2.09 | 3.76 | 6.86 | 30.5 | 378 |
EHDPP | | 98.6 | 0.67 | 10.1 | 5.57 | 10.9 | 20.2 | 56.5 | 222 |
TBOEP | | 53.0 | 0.31 | 0.39 | <LOD | 0.32 | 0.55 | 1.59 | 448 |
TCrP | | 93.0 | 0.30 | 0.80 | 0.48 | 0.78 | 1.26 | 3.20 | 80.2 |
Note: SG, specific gravity; LOD, limit of detection; GM, geometric mean; Max, maximum. |
Median concentrations of urinary OPE metabolites in several studies were compared in Table S6. BCIPHIPP, BDCIPP, and DPHP are commonly analyzed urinary biomarkers of exposure to OPEs and are frequently detected in urine samples around the world. Compared to the concentrations in children or adolescents from the USA (Hoffman et al., 2018; Ospina et al., 2018), Belgium (Bastiaensen et al., 2021), Norway (Cequier et al., 2015), and Australia (He et al., 2018a; He et al., 2018b), these urinary metabolite concentrations in our study were relatively lower, but comparable to the results from other studies in China (Chen et al., 2018; Zhang et al., 2018a; Zhang et al., 2018b). BBOEP was detected in 90% of the urine samples. The concentration of BBOEP in our participants was higher than that in children from central and southern China (Chen et al., 2018; Zhang et al., 2018a), comparable to that in adolescents from eastern China (Ding et al., 2019), but lower than the levels in children from Australia (He et al., 2018b). A larger amount of flame retardant usage or widespread exposure of OPEs may partly explain a higher urinary OPE metabolite concentrations in children from the developed countries. It was reported that the total OPE consumption in Europe and the USA was much higher than that in China for the same duration (Tao et al., 2021). The contamination levels of OPEs in indoor dust and air (Hou et al., 2021) and foods (Li et al., 2019a) are more pronounced in the developed countries. TCEP, as the parent compound of OPEs, could be detected in 80.5% of our participants. The concentration of urinary TCEP was comparable to that in adolescents from eastern China (Ding et al., 2019), but higher than that in children from Japan (Bastiaensen et al., 2019), Australia (He et al., 2018b), and Hong Kong, China (Li et al., 2019b). TCEP was found to be the most abundant OPEs in suspended particulate matters and gaseous phases (Ding et al., 2019; Mäkinen et al., 2009), and inhalation of TCEP was considered the greatest contributor of daily intake for TCEP (Xu et al., 2017a). Due to limited data available from multiple environmental compartments, whether a higher body burden of TCEP in children and adolescents of Liuzhou city is attributed to a higher contamination of TCEP in indoor air remains to be confirmed.
3.3 Concentrations of OPEs in hand wipes
The concentration distributions of OPEs in hand wipes from children and adolescents were shown in Table 2. Seven OPEs were detected in >50% of the hand wipe samples. EHDPP and TCIPP were detected at the highest median concentrations of 10.9 ng/wipe and 9.49 ng/wipe, respectively.
Concentrations of OPEs in hand wipes from various studies were summarized in Table S7. Two aryl phosphate compounds (TPHP and EHDPP) were ubiquitously detected in the general population. The median concentrations of TPHP and EHDPP in the present study were similar to those in a study of adults and children aged 1–5 years from South China (Tan et al., 2018), but slightly lower than the results reported from children aged 3–6 years in the USA (Hammel et al., 2020; Phillips et al., 2018). The detection frequency of TCrP in hand wipes is heterogeneous among different studies, but the median concentration of TCrP in our participants was comparable to that in toddlers or adults (Sugeng et al., 2017; Tao et al., 2018). Chlorinated alkyl phosphates (TCEP, TCIPP, and TDCIPP) were also frequently detected, with TCIPP having the highest median concentration of 9.49 ng/wipe among this subclass of compounds. This finding was different from other studies reporting TDCIPP as the most abundant in chlorinated alkyl phosphates, suggesting differential exposure in different subpopulations (Phillips et al., 2018), or a possible regional difference between domestic and foreign exposure (Stapleton et al., 2014; Tan et al., 2018). OPEs were detected in almost 100% of the hand wipe samples in our study, while the concentrations of OPEs, particularly TBOEP, were significantly lower than those in studies of children from other countries. TBOEP was 3–4 orders of magnitude lower than that reported from the USA (Phillips et al., 2018), Sweden (Larsson et al., 2018), and Norway (Xu et al., 2016), probably because ceramic flooring, not flooring treated with polish or wax is commonly used in schools in China (Zhao et al., 2020).
3.4 Exposure assessment
To investigate the total daily intake of OPEs, EDIs of individual OPEs were calculated and displayed in Table 3. Due to the lack of data on toxicokinetics of OPEs, only EDITCIPP, EDITDCIPP, EDITPHP, and EDITBOEP could be estimated in the present study. We only discussed the EDI values estimated based on Fue-S9-fraction, because Fue values from S9 fraction experiment contains both phase I and phase II metabolism (Van den Eede et al., 2013). The median EDIs of TCIPP and TPHP in our study were much lower than those reported in 0–5-year old children from central China (TCIPP: 94.9 ng/kg bw/day; TPHP: 267 ng/kg bw/day) (Zhang et al., 2018a) and 14–15-year old adolescents from Belgium (TCIPP: 57.4 ng/kg bw/day; TPHP: 197.7 ng/kg bw/day) (Bastiaensen et al., 2021), but comparable to the levels in 6–14-year old children from South China (TCIPP: 22.6 ng/kg bw/day; TPHP: 33.1 ng/kg bw/day) (Chen et al., 2018). For TDCIPP, the median EDI was similar to that in several studies of general population (Bastiaensen et al., 2021; Chen et al., 2018; Zhang et al., 2018a; Zhang et al., 2018b). The EDI of TBOEP were heterogeneous in different studies, but generally within the same range. Compared to the reference dose (RfD) made for human exposure to TCIPP (10000 ng/kg bw/day), TDCIPP (20000 ng/kg bw/day), TPHP (20000 ng/kg bw/day), and TBOEP (15000 ng/kg bw/day) (Poma et al., 2019), the high exposure levels (95th percentile EDIs) of the study participants were 2–3 orders of magnitude lower. Considering that RfD values were obtained based on toxicological data, the EDIs of individual OPEs in the present study could be over- or underestimated.
Table 3
Estimated daily intakes (ng/kg bw/day) of OPEs.
Compound | RfD a (ng/kg bw/day) | Dermal exposure | Total daily exposure | Proportion (%) |
S9 | HLM | S9 | HLM |
Median | 5th | 95th | Median | 5th | 95th | Median | 5th | 95th | Median | Median |
TCEP | | 0.31 | 0.10 | 1.83 | | | | | | | | |
TCIPP | 10000 | 2.63 | 0.40 | 22.9 | 27.6 | 5.34 | 140 | 23.4 | 4.53 | 119 | 10.1 | 11.9 |
TDCIPP | 20000 | 0.32 | 0.06 | 2.36 | 7.70 | 1.20 | 45.8 | 11.4 | 1.78 | 67.7 | 4.69 | 3.17 |
TPHP | 20000 | 0.98 | 0.16 | 10.3 | 31.7 | 4.50 | 340 | 14.7 | 2.09 | 158 | 3.25 | 7.02 |
TBOEP | 15000 | 0.09 | 0.27 | 17.2 | 28.4 | 1.57 | 191 | 5.61 | 0.31 | 37.8 | 0.36 | 1.84 |
EHDPP | | 3.10 | 0.04 | 0.45 | | | | | | | | |
TCrP | | 0.24 | 0.06 | 1.22 | | | | | | | | |
Σ7OPEs | | 10.7 | 2.32 | 49.7 | | | | | | | | |
Note: RfD, reference dose; HLM, human liver microsomes; S9, S9 fraction. |
a Adopted from Poma et al. (2019). |
To investigate the contribution of dermal exposure to OPEs, the OPE intake via skin wipes and its proportion to total daily intake were estimated (Table 3). The median DED of Σ7OPEs was 10.7 (5.56–19.3) ng/kg bw/day, in which TCIPP and EHDPP exposure via skin wipes were predominant contributors. The average proportion of OPE exposure via skin wipes ranged from 0.36% (TBOEP) to 10.1% (TCIPP) as total daily intake was estimated based on FUE-S9-fraction, suggesting a significant contribution of dermal absorption. In the present study, daily dermal exposure to OPEs of the study participants were higher than those estimated via hand wipes or house dust for adults (Cao et al., 2019; Huang et al., 2020; Liu et al., 2017; Xu et al., 2016), but lower than those estimated via house dust or air for toddlers (Huang et al., 2020; Liu et al., 2017). Different from other studies, we only considered the exposed surface area of hands and head as recommended by Pan et al. (2020). OPE uptake from dermal absorption could be higher if more skin area or whole body is included. Additionally, we adopted the absorption factors of TCEP (28%), TCIPP (25%), and TDCIPP (13%) from human ex vivo skin experiments to investigate the daily dermal exposure to OPEs, and utilized the average absorption rate (22%) of TCEP, TCIPP, and TDCIPP to estimate other OPEs (including TPHP, EHDPP, TBOEP, and TCrP).
3.5 Correlation between urine and hand wipes
We found that the TPHP and EHDPP levels in hand wipes were significantly correlated with their metabolite DPHP in urine (rs = 0.068–0.142, P < 0.05), whereas no significant correlations were observed between other OPEs in hand wipes and the corresponding urinary metabolites (Table 4). Hand wipes are theoretically a good integrated indicator of internal exposure, as they measured hand-to-mouth contact with dust and other exposure media (e.g., indoor consumer products), and may provide information on an individual’s activity pattern. Several studies have reported strong correlations between the TCIPP and TDCIPP amount in hand wipes and their urinary metabolites of BCIPHIPP and BDCIPP, respectively (Phillips et al., 2018; Tao et al., 2018), whereas our study did not confirm these previous findings, possibly because the levels of OPEs on hands could be affected by individual’s hand washing frequency and engaged activity before sampling (Larsson et al., 2018; Liu et al., 2017). However, hand washing frequency in our study was not related to the OPE concentrations in hand wipes (data not shown). Given that children and adolescents have a frequent contact with cell phone, the activity of cell phone touching was studied, as cell phones may act as a potential source of OPEs (Yang et al., 2019). There was no significant association between cell phone touching and the quantities of OPEs in hand wipes (data not shown).
Table 4
Spearman correlation coefficients for OPE and OPE metabolites levels measured in paired hand wipes and SG-corrected urine with >50% detection a.
Compound | TCEP | BCIPHIPP | BDCPP | DPHP | BBOEP | DoCP & DpCP |
TCEP | 0.034 | 0.016 | 0.073* | 0.058 | -0.072* | 0.011 |
TCIPP | -0.069 * | -0.048 | 0.022 | 0.042 | -0.003 | 0.013 |
TDCIPP | -0.007 | -0.059 | 0.016 | 0.018 | -0.144* | 0.002 |
TPHP | 0.033 | 0.047 | 0.097* | 0.068* | -0.010 | 0.043 |
EHDPP | -0.045 | -0.029 | 0.105* | 0.142* | 0.024 | 0.024 |
TBOEP | -0.030 | -0.039 | -0.010 | -0.004 | -0.016 | -0.054* |
TCrP | -0.048 | 0.035 | 0.035 | 0.062* | 0.087* | 0.001 |
Note: a Significant level are marked with bold text and asterisks (* P <0.05). |
In the present study, OPE intake via dermal absorption could partially explain the body burden of OPEs. To determine the potential predictors for urinary OPE metabolite concentrations, factors (sociodemographic variables, dietary patterns, and OPE levels in hand wipes) that may impact OPE exposure were all included in multivariable linear regression models (Table 5). After adjusting for sex, age, maternal education, and dietary patterns, a strong correlation continued to be found for EHDPP in the highest quartile in hand wipes and urinary DPHP (P < 0.001). Although the association between TPHP and DPHP was no longer significant, there was a suggestive dose response relationship between TPHP and DPHP (Fig. 1). Similarly, the levels of other OPEs in hand wipes were not related to their corresponding urinary metabolites in the multivariable models. These results implied that hand wipes could be an effective exposure metric for TPHP and EHDPP, whereas the exposure of other OPEs may be linked to additional predictors. Furthermore, we discussed the associations of sociodemographic and dietary variables with urinary OPE levels after adjusted for other variables in Table 5.
Table 5
Results of regression analyses for predicting urinary OPE metabolites a.
OPE metabolites | Variables | %change (95% CI) |
TCEP | Age | |
| 6–11 years (Ref) | |
| 12–15 years | 97.6 (68.5, 132) * |
| 16–18 years | 34.4 (13.5, 59.2) * |
| Sex | |
| Male (Ref) | |
| Female | -14.3 (-24.9, -2.31) * |
| Drinking water | |
| Tap water (Ref) | |
| Barreled water | 2.39 (-13.2, 20.7) |
| Purified water | -8.67 (-24.8, 10.8) |
| Others | -58.2 (-80.3, -10.9) * |
BCIPHIPP | Age | |
| 6–11 years (Ref) | |
| 12–15 years | 41.7 (22.1, 64.4) * |
| 16–18 years | 18.0 (0.86, 38.0) * |
| Drinking water | |
| Tap water (Ref) | 30.4 (11.8, 52.0) * |
| Barreled water | 16.7 (-2.51, 39.8) |
| Purified water | -22.5 (-61.7, 57.0) |
| Others | |
BDCIPP | Age | |
| 6–11 years (Ref) | |
| 12–15 years | -4.24 (-19.0, 13.2) |
| 16–18 years | -48.4 (-56.6, -38.5) * |
| Beans (times/week) | |
| ≤1 (Reference) | |
| 2 | 2.11 (-15.0, 22.6) |
| ≥3 | -19.7 (-32.4, -4.61) * |
DPHP | Age | |
| 6–11 years (Ref) | |
| 12–15 years | 5.96 (-12.4, 28.2) |
| 16–18 years | -42.1 (-52.5, -29.4) * |
| Meat (times/week) | |
| ≤2 (Ref) | |
| 3–5 | -18.9 (-33.3, -1.43) * |
| ≤6 | -9.52 (-26.9, 12.0) |
| Vegetables (times/week) | |
| ≤4 (Ref) | |
| 2 | 13.3 (-10.3, 43.2) |
| ≥3 | 23.7 (0.51, 52.1) * |
BBOEP | Age | |
| 6–11 years (Ref) | |
| 12–15 years | -21.6 (-38.9, 0.65) |
| 16–18 years | -6.74 (-28.1, 21.0) |
| Sex | |
| Male (Ref) | |
| Female | 22.3 (0.75, 48.5) * |
| Maternal education | |
| Less than high school (Ref) | |
| High school | 22.2 (-4.40, 56.1) |
| College or above | 50.9 (17.5, 93.6) * |
| Drinking water | |
| Tap water (Ref) | |
| Barreled water | 5.11 (-17.6, 34.1) |
| Purified water | -27.3 (-45.3, -3.46) * |
| Others | 33.1 (-56.4, 306) |
Note: a Significant level are marked with bold text and asterisks (* P <0.05). |
3.6 Urinary OPE metabolites and sociodemographic characteristics
It was not surprising that the urinary BDCIPP, DPHP, and BBOEP concentrations were inversely associated with age (categorical variable), because children have rapid metabolic and ventilation rates and large ratio of surface area to body weight, in addition to frequent hand-to-mouth activity (Miller et al., 2002; Tulve et al., 2002). Nevertheless, the levels of urinary TCEP and BCIPHIPP in the study participants aged 12–15 years were highest, followed by adolescents aged 16–18 years, and children aged 6–11 years were lowest. Contradictory to previous studies (Bastiaensen et al., 2019; He et al., 2018b; Van den Eede et al., 2015), we observed positive assocations of urinary TCEP and BCIPHIPP concentrations with age. To our knowledge, we did not observe a determinant activity pattern in which senior students had an increased potential for exposure to OPEs compared to schoolchildren, while a recent study found that urinary TCEP and BCIPHIPP levels were high in adolescents aged 12–15 years in eastern China (Ding et al., 2019). The concentration of urinary TCEP were high in males, while urinary BBOEP was high in females, indicating differences in metabolism and exposure patterns between genders (Hoffman et al., 2015). Maternal education level was a proxy for socioeconomic status that was positively associated with the urinary BBOEP in our participants. A potential explanation of this result is that newer furniture and electronics entered into these highly educated mothers’ households, which led to the transition of indoor exposure patterns from PBDEs to OPEs (Percy et al., 2020).
3.7 Urinary OPE metabolites and dietary patterns
High vegetable intake in the past week (≥7 times) was associated with a 23.7% higher DPHP concentration in urine compared to the lowest vegetable intake (≤4 times) [%change = 23.7; 95% confidence interval (CI): 0.51, 52.1]. Medium meat intake (3–5 times) was associated with a 18.9% lower DPHP concentration, although there was lack of statistical significance for the highest meat intake category (≥6 times). In comparison with frequently consumed tap water, barreled water was associated with a 30.4% increased BCIPHIPP concentration in urine, purified water drinking was related to a 27.3% lower BBOEP concentration, and other drinking water was associated with a 58.2% lower TCEP concentration.
High vegetable intake was suspected to be an important factor that influence the concentrations of urinary OPE metabolites, which was first reported in children and adolescents. Zhang et al. (2016) detected 75 commonly consumed foods sampled from 4 representative areas in China and found that vegetables were severely contaminated by TCEP and TEHP. TPHP and EHDPP were not abundant OPEs in vegetables, thus, we could not conclude that the higher DPHP concentration in urine was attributed to the high contamination of its parent compounds in vegetables. However, a study in Australia reported the ubiquitous occurrence of DPHP in vegetables. The contamination level of DPHP (median: 0.99 ng/g wet weight) in vegetables was obviously higher than its parent compound TPHP (He and Wang, 2018). Considering the ubiquitously co-existence of organophosphate di-esters (di-OPEs) and tri-esters (tri-OPEs) in various environmental compartments (Björnsdotter et al., 2018; Hou et al., 2017; Tan et al., 2019), the direct intake of di-OPEs from foodstuffs cannot be ignored.
Negative associations between food consumption and urinary metabolite concentrations are challenging to interpret and are rarely reported. Eggs, fish, and meat which are categorized as animal-based foods, had the lowest contamination concentrations of OPEs compared to other food groups (Li et al., 2019a). The very low OPE concentrations in the animal-based foods might be due to the rapid metabolism and/or excretion of OPEs (Greaves et al., 2016; Poma et al., 2018). It seems reasonable that increased meat and egg consumption were associated with lower urinary metabolite concentrations. Although a small study of toddlers in the USA (n=41) suggested that meat and fish consumption were related to higher DPHP and BDCIPP concentrations in urine, these associations were not statistically significant (Thomas et al., 2017). Moreover, a previous study showed that the OPE levels in bean products were negligible (Ding et al., 2018), thus, an inverse association between high consumption of beans and the urinary BDCIPP concentration is also possible.
Tap water is the most common and cheapest drinking water in China and contains abundant OPEs, particularly halogeno-OPEs, compared to other water sources (e.g., barreled water, bottled water, purified water, and well water) (Ding et al., 2015). A possible hypothesis is that purified water, barreled water, and other drinking water may be associated with lower concentrations of urinary OPE metabolites. Due to the limited number of participants in the other drinking water group, the result that other drinking water was associated with a lower TCEP concentration in urine should be interpreted with caution. However, it is unexpected that barreled water drinking was associated with an increase in urinary BCIPHIPP. Li et al. (2019c) analyzed the concentrations of OPEs in tap water samples from 79 cities in China, in which the contamination of OPEs in tap water from Liuzhou (the sample site of our study) was not severe. In addition, most barreled water-producing manufacturers are regional, and different manufacturing techniques are used according to the enterprise scale and cost. In the sample site of our study, regional barreled water could be a potential source of exposure to OPEs for residents. Considering the limited data on drinking water around the world, more research on different types of drinking water is needed.
3.8 Limitation and strength
The main strengths of our study include the large sample size for an exposure study of OPEs and the focus on the vulnerable population of children and adolescents. This is a relatively comprehensive study that examines the relationship between urinary OPE metabolites and dietary factors. The dietary factors include the consumption rate of seven common food groups and the sources of daily drinking water. Additionally, the OPE levels in hand wipes were included in the multivariable linear regression models given that dermal contact with dust is commonly considered an important exposure pathway for humans.
Several limitations exist. First, organophosphate diesters could be generated from bio-transformation of OPEs, as well as environmental degradation of parent OPEs and industrial production (Liu et al., 2021). Meanwhile, some of organophosphate diesters are metabolized by various OPEs. For example, DPHP could be generated from TPHP (Su et al., 2014), EHDPP (Shen et al., 2019), and resorcinol bis(diphenylphosphate) (RDP) metabolism (Ballesteros-Gómez et al., 2015). Therefore, the suitability of usage of organophosphate diesters as metabolites of OPEs are needed further assessment. Second, given that other newly discovered OPEs exhibit great detection frequencies and are abundant in multiple environmental matrices (e.g., bis-(2-ethylhexyl)-phenyl phosphate (BEHPP), tris(2,4-di-tertbutylphenyl) phosphate (TDTBPP)), these novel OPEs should be monitored in the forthcoming studies. Third, we could not examine long-term exposure to OPEs using a cross-sectional study, and many of OPEs are rapidly metabolized in the human body; thus, a spot urine sample could not be representative of the average body burden of our participants. Fourth, single hand wipe sample could be a potential weakness for OPE measurements, as it is unknown how OPE levels vary in a single person over time. Herein, we measured OPEs in urine and hand wipe samples, whereas the inclusion of other exposure metrics (e.g., passive air samples and indoor dust) may provide additional information on exposure to OPEs. Last, in the present study, food items combined with food frequency questionnaires were used to estimate human dietary intake of OPEs, but this method only provides an approximately estimate of dietary habits during a designed period of sample time (Xu et al., 2017a).