Printer Friendly

Maternal Peripartum Serum DDT/E and Urinary Pyrethroid Metabolite Concentrations and Child Infections at 2 Years in the VHEMBE Birth Cohort.

Introduction

To control mosquito vectors, malaria control programs in 85 predominantly low- and middle-income countries apply insecticides directly to the inside walls of homes, a process known as indoor residual spraying (IRS). Consequently, approximately 106 million people may inadvertently become exposed to IRS insecticides (World Health Organization [WHO] 2016). Fetal exposure to insecticide used for IRS, including the pyrethroid deltamethrin and dichlorodiphenyltrichloroethane (DDT) and its breakdown product dichlorodiphenyldichloroethylene (DDE), have been shown in many animal and in vitro studies to alter immune function (Rehana and Rao 1992; Santoni et al. 1998; Banerjee 1999; Misumi et al. 2005; ATSDR 2002, 2003; Brander et al. 2016) and to specifically increase susceptibility to infection (Nunez et al. 2002; Suwanchaichinda et al. 2005; Rehman et al. 2011). However, epidemiologic investigations of associations between fetal insecticide exposure and childhood infections have yielded conflicting evidence.

In a Spanish cohort, maternal antepartum p,p'-DDE blood concentrations were associated with higher risk of lower respiratory tract infection (LRTI) in the first year of life (Sunyer et al. 2010; Gascon et al. 2012). Similarly, in highly exposed Arctic populations, maternal p,p'-DDE concentrations were associated with elevated risks of gastrointestinal, ear (otitis media), and upper respiratory tract infections (URTI) in 1-y-olds (Dewailly et al. 2000; Dallaire et al. 2004), although dose-response trends were only detected with aggregated infections (Dallaire et al. 2004). Other studies have reported associations with lower risk of infections. For example, a German study reported that child (postnatal) p,p'-DDE concentrations were associated with lower risk of otitis media in 7- to 10-y-olds (Karmaus et al. 2001) and a Mexican study observed an association between higher prenatal p,p'-DDE concentration and lower risk of LRTI in 2-y-old boys (Cupul-Uicab et al. 2014). No studies have reported associations with DDT, possibly because of low detection frequencies (Sunyer et al. 2010). To our knowledge, no human studies have investigated associations between fetal pyrethroid exposure and child infections in settings where IRS is conducted.

Individuals living in IRS areas have been shown to have tissue concentrations of these chemicals orders of magnitude higher than in general populations (Gaspar et al. 2017; Aneck-Hahn et al. 2007; Whitworth et al. 2014). Understanding potential adverse side effects of IRS on childhood infections is critical because respiratory and gastrointestinal infections are leading causes of child morbidity and mortality in these settings. In our study area (Limpopo Province, South Africa), intestinal infections, influenza, and pneumonia together account for 26.2% and 23.6% of all deaths among infants under 1 y and children 1-14 y of age, respectively (Statistics South Africa 2017). Moreover, early adversity factors such as poverty (Appleton et al. 2016; Stein et al. 2016), malnutrition (Banerjee 1999; Bourke et al. 2016; Prescott 2016); and HIV (Ruck et al. 2016; Slogrove et al. 2017) are common among pregnant women in this setting and may increase children's susceptibility to any adverse impact of insecticides. This study aims to investigate whether prenatal exposure to IRS-related chemicals is associated with increased incidence of childhood infection and whether potential effects of IRS insecticides may be exacerbated by these susceptibility factors.

Methods

Study Population and Recruitment

The current study was conducted in the context of the Venda Health Examination of Mothers, Babies, and their Environment (VHEMBE), a prospective birth cohort study investigating the effects of environmental exposures on the health and development of children born in the Vhembe district of Limpopo Province, South Africa, where IRS insecticides, primarily DDT and the pyrethroid deltamethrin, are applied during the malarial season. Between August 2012 and December 2013, women who presented for delivery at Tshilidzini Hospital in the town of Thohoyandou were screened for eligibility. Women were eligible if they were at least 18 y of age, spoke Tshivenda at home, lived within 20 km of the hospital and planned to remain in the area for the next 2 y, were free from malaria during the index pregnancy, had contractions at least 5 min apart, and delivered a live, viable singleton. Informed consent was obtained prior to data collection. The study was approved by the institutional review boards of the University of California, Berkeley; McGill University; the University of Pretoria; the Limpopo Department of Health and Social Development; and Tshilidzini Hospital.

Study staff screened 1,649 mothers, 920 of whom met eligibility criteria. Of the eligible women, 752 (82%) provided informed consent, completed a baseline delivery questionnaire, and provided a peripheral blood sample for DDT/E quantification. Mothers and babies were followed up for a home visit at 1 wk (n = 723, or 96% of initially enrolled; 29 mothers formally withdrew after delivery, had their index child die before 1 wk, or otherwise did not complete the visit), 1 y (n = 700 completed visits, or 93%; 13 children died prior to visit), and 2 y (n = 685 completed visits, or 91%; 7 died prior to visit) after delivery. Eleven children who missed their 1-y visit but were seen at 2 y were excluded because we would be unable to ascertain their infection rate between 1 and 2 y of age. Thus, the final sample size for this study was 674 (90% of initially enrolled) mother-child dyads. Dyads included in this analysis were less likely to be HIV positive, but were otherwise similar to those that were excluded with respect to all other characteristics used for our analyses (see Table S1).

Serum Collection and Analysis

Maternal peripheral blood was collected in red-top vacutainer tubes prior to, or immediately after, delivery. Samples were immediately processed and stored at -80[degrees] C until shipped on dry ice to Emory University's Environmental Health Laboratory (Atlanta, GA) for analyses. Gas chromatography-tandem mass spectrometry (GC-MS/MS) with isotope dilution quantification (Barr et al. 2003) was used to quantify p,p'-DDT, p,p'-DDE, o,p'-DDT, and o,p'-DDE. Limits of detection (LODs) were 0.01 ng/mL (o,p'-DDE, o,p'-DDT, and p,p'-DDT) and 0.03 ng/mL (p,p'-DDE). Corresponding limits of quantification (LOQs) were 0.05 ng/mL and 0.15 ng/mL.v Concentrations of o,p'-DDE were only quantified in 16% (n = 108) of samples and were excluded from analyses. Total serum lipid concentrations were estimated using the Phillips formula (Bergonzi et al. 2009) from total triglyceride and cholesterol concentrations measured by standard enzymatic methods (Roche Chemicals).

Urine Collection and Analysis

Of the 674 women included in this study, 666 (99%) provided a sufficient urine sample for pyrethroid metabolite quantification, of which 413 (62%) provided a urine sample before and 253 (38%) after delivery. Urinary specific gravity was measured shortly after collection using a refractometer (Atago PAL-10S). Samples were immediately processed and stored at -80[degrees]C. Urine aliquots were shipped on dry ice to the Centre de Toxicologie du Quebec (CTQ) of the Institut National de Sante Publique du Quebec (INSPQ) in Quebec City, Canada, for analyses. Gas chromatography-mass spectrometry (Dewailly et al. 2014) was used to quantify the following five pyrethroid metabolites: 4-fluoro-3phenoxybenzoic acid (4-F-3-PBA), cis-3-(2,2-dibromovinyl)-2,2dimethyl-cyclopropane carboxylic acid (cis-DBCA), cis-3-(2, 2,-dicholorvinyl)-2,2-dimethyl-cyclopropane carboxylic acid (cis-DCCA), trans-3-(2,2,-dicholorvinyl)-2,2-dimethyl-cyclopropane carboxylic acid (trans-DCCA), and 3-phenoxybenzoic acid (3-PBA). LODs and LOQs were 0.005, 0.0025, 0.0045, 0.0038, and 0.0047 [micro]g/L and 0.011, 0.0082, 0.015, 0.013, and 0.016 [micro]g/L, respectively. Concentrations of 4-F-3-PBA were only quantified in 7.7% (n = 51) of samples and were excluded from analyses.

Covariate and Outcome Data

Maternal questionnaire data. Study staff administered questionnaires in the local Tshivenda language to mothers prior to hospital discharge to collect information on maternal sociodemographics, nutrition, health, and pregnancy history. The questionnaire was designed in English, translated to Tshivenda, and back-translated to English by native speakers in the translated language. We used maternal age, marital status, parity, food frequencies, and family income recorded in this questionnaire. Family income was classified as above or below the official South African mid-2013 food poverty level (Rand 386 per person per month; W. Ruch, written communication, Jan 2016). Maternal HIV status was ascertained from self-reported diagnosis or use of anti-retroviral drugs based on medical records that were abstracted by registered nurses. Total energy intake in kilojoules (kJ) was estimated by a South African expert nutritionist using FoodFinder 3 software (South Africa Medical Research Council/WAMTechnology CC) from a quantitative food frequency questionnaire designed and validated in a population residing in our study area (MacIntyre et al. 2001). At the 2-y follow-up interview, biological mothers (n = 653) or primary caretakers (n = 21) were asked about the number of persistent fevers lasting [greater than or equal to] 4 d, number of ear infections, and number of severe sore throats the child had since the child's last visit (i.e., at 1 y of age), number of individuals living in the same residence as the child, and whether the mother spent any period during the year living away from the child. Additionally, interviewers were asked to rate the quality of the mother's responses to different questionnaire sections (1 = high quality to 4 = unsatisfactory). To estimate rates of infections (i.e., fever, ear infection, and sore throat rates), the number of days over which the infection events were counted were calculated for each child by taking the difference between the 2-y-and 1-y visit dates (median = 365 d).

Maternal energy intake sufficiency. Mothers were characterized as having insufficient energy intake if total daily energy intake was less than that recommended by the U.S. Institute of Medicine (IOM) for late pregnancy (IOM and NRC 2009). The recommended intake (in kilojoules) was estimated for each mother using the following equation: 4.184 kJ/cal x [452 + 354 - (6.91X age in years) + 1.27 x (9.36 x weight in kg) + 726 x height in meters] (median = 12,055 kJ or 2,880kcal). Two assumptions were made in these calculations: First, because physical activity was not directly measured, women were uniformly categorized as active due to common strenuous activities of daily living in the study area such as walking long distances for transportation and water collection and agricultural activities. Second, postpartum weight was used instead of antepartum weight (because the latter was measured in only 75% of study subjects). The median threshold would be 1,105 kJ lower categorizing women as "low active" (54 women reclassified) or 240 kJ higher based on antepartum weights (56 women with measures reclassified).

Child anthropometrics. Infant weight (to the nearest 2 g using a Tanita BD-815U scale), length (using a Seca 417 infantometer), and head circumference (using a measuring tape) were measured by nurses at delivery. At the 1- and 2-y study visits, study staff measured weight to the nearest 10 g using a digital scale (Tanita HD-351); recumbent length at 1 y of age (Seca 417) or standing height at 2 y of age using a stadiometer (Charder HM200P); and middle-upper arm circumference using a measuring tape. All anthropometric measures were taken in triplicate and averaged and U.S. National Health and Nutrition Examination Survey (NHANES) protocols were followed (National Center for Health Statistics 2011).

Statistical Analyses

For all exposures, we used machine-read values for concentrations between the LOD and LOQ and randomly imputed values below the LOD based on a log-normal probability distribution whose parameters were estimated by maximum likelihood estimation (Lubin et al. 2004). Next, serum DDT/E concentrations were corrected for total lipids (ng/g lipid) and urinary pyrethroid metabolite concentrations were corrected for specific gravity ([micro]g/L) and both were log-transformed to minimize the influence of outliers. To estimate the association between chemical concentrations and count of infection outcomes at 2 y of age, we fitted multivariable, zero-inflated Poisson regression models with the number of days between visits as the offset. The following covariates were identified using a directed acyclic graph (DAG): continuous maternal age and parity; binary marital status, low energy intake, and HIV status at the time of delivery of the index child; binary household poverty; and child sex [see Figure S1; generated via DAGitty (version 2.3; Johannes Textor) Textor et al. 2011]. All analyses were performed using Stata SE (version 12.1; StataCorp).

Zero-inflation model fitting. Because our outcomes of interest, particularly otitis media, may be missed in young children, we assumed a priori that underestimation of events would be likely. Accordingly, we used certain measures from the 2-y follow-up interview related to the likelihood that the primary caretaker of the child may have failed to observe infection events to correct for this underreporting. During the 2-y follow-up interview, the primary caretaker was asked whether they lived with the child for the entire period since the child's last visit, that is, the period for which we were estimating infection rates. Caretakers who did not report living with the child "all of the time" would naturally have a greater chance of missing infection events: 13% of mothers reported this, primarily due to work or study in the city. Caretakers were also asked the number of individuals that regularly reside in the same household as the child. Those with more household members may affect the recall of number infections for the index child. Finally, interviewers were asked to rate the reliability of mother or caregiver' s responses following the completion of the child health section where the number of infections are reported. Reliability was scored 1 for "high quality," 2 for "generally reliable," 3 for "questionable," 4 for "unreliable," and 5 for "not applicable." Scores 3, 4, and 5 were grouped together as poor quality. Poor quality is an indicator that mothers may not have accurate recall of the child' s health, including infection events. These three variables (lived with child, household size, and reliability) were used to model the possibility that infection events were missed (number reported as zero) in regression models described below. To do this, we used the zip command in Stata to incorporate a model for the probability of falsely reported or excess zeroes (i.e., zero-inflation) to the standard Poisson regression. Excess zeroes were modeled by logistic regression with the following variables as independent variables: whether or not the respondent lived with the child throughout the second year; her age and parity; household size at the 2-y follow-up interview; and the interview reliability score. Models were fit in a complete data set generated by randomly imputing missing values (45 of 9,436 possible values = 0.5%) in 40 subjects (5.9%) with any missing values drawing from conditional probability distributions estimated from observed covariate distributions. This was done using multiple imputation by chained equations (White et al. 2011) and the mi set of commands in Stata and keeping the first imputed data set. Estimates using this approach were compared to those resulting from Poisson regression and multiple imputation (10 data sets).

To estimate the degree to which maternal poverty, low energy intake, or HIV status; child sex; or exclusive breastfeeding for <1 month may modify any effect of insecticide exposure on child infections, we included interaction terms between each potential modifier (dichotomous) and mean-centered exposure. Each effect modifier was evaluated in a separate model (i.e., only two-way interactions) and a relative excess risk due to the interaction (RERI) was calculated for each using the equation: RERI = [RR.sub.11] - [RR.sub.10] - [RR.sub.01] + 1 (in which [R.sub.11] = rate ratio for a 1-unit change in chemical concentration in the presence of the modifier; [R.sub.10] = rate ratio for a 1-unit change in chemical concentration in the absence of the modifier; and [R.sub.01] = rate ratio due to the modifier at mean concentration of the chemical; Richardson and Kaufman 2009). Confidence intervals (CIs) and p-values were derived by the delta method (Hosmer and Lemeshow 1992; Assmann et al. 1996) using the nlcom command. All analyses were performed using Stata SE 12.1 (StataCorp; College Station, Texas).

Sensitivity and Exploratory Analyses

Several quantitative sensitivity analyses were conducted to test assumptions made in variable construction and regression model analyses: We compared results obtained using zero-inflated versus standard Poisson regression models qualitatively and by Vuong test for nonnested models (Desmarais and Harden 2013). We additionally adjusted for number of children <5 y of age living in the household at 2 y of age. Because pyrethroids are rapidly metabolized and eliminated, we investigated whether associations differed by pyrethroid collection time (before or after delivery). Finally, we examined the influence of using a lower threshold for daily energy demands (i.e., by classifying women as "low active" rather than "active") on estimated associations.

DDT/E and pyrethroids have been associated with length of gestation and birth (Eskenazi et al. 2009) and child size (Jusko et al. 2006; Burns et al. 2012; Warner et al. 2013), themselves predictors of infection susceptibility (Duijts et al. 2009). We explored the degree to which birth weight, length, head circumference, or preterm birth may mediate any observed relationships using four-way decomposition analyses, allowing for exposure-mediator interaction (Vanderweele 2014). For the decompositions, the exposure effect was defined as increasing the exposure from the 25th percentile of concentration to the 75th percentile in a referent population of lower infection risk: female offspring born to mothers of average age and parity who are married, HIV-negative, living above the food poverty line, and with adequate daily caloric intake during late pregnancy. We were specifically interested in the pure indirect effect; that is, the potential effect of insecticides that is mediated by alterations in child growth but that is not due to interactions. This was estimated as the proportion of the total excess rate of the infectious outcome associated with increasing chemical concentration (from the 25th to 75th percentile) that was due specifically to changes in birth size or risk of preterm birth due to the chemical. This can be estimated under causal inference assumptions of consistency, no unmeasured exposure-outcome, exposure-mediator, exposure-induced, and mediator-outcome confounding, nonpositivity, and correct model specification (Vanderweele 2014).

Results

Participant Characteristics

All mothers were black South Africans and their mean age at delivery of the index child was 26.4 y. Most women were unmarried (53%), had less than a 12th grade education (56%), were multiparous (57%), and lived below the food poverty line (61%) (Table 1). Two-thirds of women (67%; n = 454) ate less than the IOM-recommended daily number of calories for late pregnancy and 13% were HIV positive. Most children (74%) were exclusively breastfed for at least 1 month and 11% for [greater than or equal to] 6 months. During the second year of life (1-2 y of age), persistent fevers lasting [greater than or equal to] 4 d were common, that is, they were reported in nearly 30% of children. Ear infections were less common (16%) and severe sore throats were rare (6%). No children had been diagnosed with malaria by 1 y of age, and one child by 2 y of age.

Maternal Exposure to DDT/E and Pyrethroids. As previously reported (Gaspar et al. 2017), p,p'-DDT, o,p'-DDT, and p, p'-DDE were detected in almost all serum samples in this population (Table 2). Urinary pyrethroid metabolites cis-DBCA, cis-DCCA, trans-DCCA, and 3-PBA were also detected in all samples (Table 2). Concentrations of DDT/E and pyrethroid metabolites were generally higher than those reported in contemporary U.S. populations: Median p,p'-DDE in VHEMBE was 254.4 ng/g lipid versus 113 ng/g lipid among pregnant women 18-40 y of age in the 1999-2000 National Health and Nutrition Examination Survey (NHANES; Bradman et al. 2007). Few pregnant women in NHANES had o,p'-DDT (20%) or p,p'-DDT (0.2%) above the LOD of 10.6 ng/g lipid (Bradman et al. 2007). The 75th percentile of pyrethroid metabolites ranged from 0.48 to 1.38 in VHEMBE vs. 0.15 to 0.5 in NHANES (Castorina et al. 2010). The distributions of urine pyrethroid metabolite concentrations were similar in samples collected before and after delivery (see Figure S2).

We found that higher concentrations of DDT/E were associated with higher rates of persistent fevers and severe sore throats, particularly p,p'-DDE; associations between DDT/E and otitis media were mixed (Table 3). A 10-fold increase in maternal serum p,p'-DDE concentration was associated with a 21% higher rate of persistent fevers [incidence rate ratio (IRR) = 1.21 (95% CI: 1.01, 1.46)]. DDT/E appeared to be associated with higher rates of severe sore throat [IRR = 1.53 (95% CI: 0.77, 3.03), IRR = 1.58 (95% CI: 0.80, 3.14), and IRR= 1.78 (95% CI: 0.82, 3.84) for o,p'-DDT, p,p0'-DDT, and p,p0'-DDE, respectively]; however, due to the small number of events, estimates were imprecise. Findings were similar in sensitivity analyses with adjustments for number of children (see Table S2), using uncorrected exposure concentrations and adjusting for lipid concentrations (see Table S3), and using multiply imputed Poisson regression (see Table S4). Additionally, classifying women as "low active" rather than "active" for the purposes of estimating daily energy requirements did not alter observed associations between DDT/E and infection outcomes (see Table S5).

There was limited evidence that pyrethroid metabolite concentrations were associated with the studied outcomes (Table 3). When stratified by collection timing, cis-DCCA, trans-DCCA, and 3-PBA concentrations were positively associated with higher rates of persistent fevers only among mothers whose urine was collected prior to delivery (i.e., most proximal to home exposures), whereas the opposite was observed for cis-DBCA (see Table S6). However, evidence for effect modification was generally weak (p = 0.08 to 0.59; see Table S6). For ear infections, higher concentrations were associated with higher rates only among the postdelivery subsample (see Table S6). For severe sore throats, inverse associations were observed in both strata; however, CIs were very wide in the postdelivery stratum. Overall, interpretation of true differences by collection timing was limited by reduced stratified sample sizes (see Table S6). Given the limited evidence of associations between pyrethroid metabolites and outcomes, we focused on DDT/E-persistent fever associations in subsequent analyses.

In interaction models, we observed that DDT/E were positively associated with persistent fevers among children from households below, but not above, the South African food poverty line. Similarly, positive associations were observed among children of mothers with insufficient, but not adequate, caloric intake during late pregnancy. There were no consistent patterns across strata defined by maternal HIV status, exclusive breastfeeding duration, or child sex (Table 4). Using formal tests of additive interactions, the rate ratio associated with increasing serum p,p'-DDE concentrations in mothers who were from poorer households was 43% higher [RERI = 0.43 (95% CI: 0.03, 0.84); Table 4] than expected based on observed associations with p,p'-DDE in those above the food poverty line [[IRR.sub.10] = 0.93 (95% CI: 0.69, 1.25)] and food poverty status alone [[IRR.sub.01] = 1.16 (95% CI: 0.91, 1.48)]. Associations with o,p'-DDT and p,p'-DDT showed similar patterns (Table 4). Finally, exploratory mediation analyses provided little evidence that birth characteristics mediated exposure-outcome relationships (see Table S7).

Discussion

A major motivation for this study was to investigate whether common maternal and familial factors found in IRS settings may increase susceptibility to the health effects of insecticides. Overall, we found that higher maternal serum DDT/E, and particularly p,p'-DDE, concentrations were associated with higher rates of persistent fever in their children during their second year of life. Moreover, we found consistent evidence that associations between chemical concentrations and rate of infectious outcomes were stronger among children of mothers living below the poverty line or having insufficient antepartum energy intake. In fact, among children without those susceptibility factors, the associations were weak or absent. Given the high prevalence of these comorbidities in this population (61% and 68%, respectively) and the fact that these factors were rare in previous studies, further replication of our analysis in other low- and middle-income settings is critical: If these are causal susceptibility factors, findings from prior studies, many of which were conducted in Western countries where the prevalence of such susceptibility factors is lower, may not be applicable to populations in which IRS is currently practiced (i.e., where the prevalence of such factors is higher).

Extensive animal evidence suggests several plausible pathways for developmental immunotoxic effects of DDT/E; however, human studies are scarce. In animal studies, postnatal exposure to DDT/E and pyrethroids has been shown to inhibit macrophage activity, response to bacterial infection (Nunez et al. 2002), and leukocyte proliferation and to increase apoptosis (Misumi et al. 2005). Fetal exposure may specifically impair thymocyte proliferation (Rehana and Rao 1992) and alter Th1/Th2 balance (Santoni et al. 1998). The positive associations between p,p'-DDE and fevers, ear infections, and sore throat in this study corroborate past findings in a population of Inuit children exposed to organochlorines in utero through maternal diet (Dallaire et al. 2004). Dallaire et al. (2004) found IRRs for all infections, otitis media, and upper respiratory infections at 1 y of age of 1.13 (95% CI: 0.95, 1.34), 1.02 (95% CI: 0.76, 1.35), and 1.30 (95% CI: 0.96, 1.78) when comparing highest to lowest quartile (>472 vs. <183 ng/g lipid) of prenatal p,p'

DDE exposure using standard Poisson models. Our findings also corroborate other studies showing positive associations between prenatal DDT/E exposure and child infections. In a Spanish birth cohort, Sunyer et al. (2010) found that each log-unit higher maternal serum DDE concentrations during the first trimester of pregnancy was associated with a 25% higher risk of LRTIs in 14month-old offspring [RR = 1.25 (95% CI: 1.01, 1.55)]. In a similar, but larger, cohort, Gascon et al. (2012) reported a positive association between maternal first- and second-trimester DDE serum concentrations and LRTI risk [RR= 1.11 per log-unit (95% CI: 1.00, 1.22)]. Conversely, in a Mexican population residing in an area in which DDT was historically applied for malaria control, Cupul-Uicab et al. (2014) did not find strong evidence for association between maternal DDE levels at delivery and LRTI risk in 21-month-old boys. However, we did not evaluate associations with LRTI directly, limiting the comparability with our findings.

A few limitations of our study are worth highlighting. Notably, child infections are difficult to properly capture, given that they may result in subtle symptoms and may be omitted by self-report. We attempted to address this challenge by several means, including restricting outcomes to those of greater severity and duration (i.e., high fever for [greater than or equal to] 4 d) and explicitly modeling the potential for missing events. Nonetheless, mismeasurement of the outcome, even in a nondifferential fashion, may have reduced our ability to detect associations. Future studies could consider alternative, objective biomarkers of infection history to validate self-reports. Due to their rapid elimination, urinary pyrethroid metabolite concentrations in samples collected after delivery may reflect exposure in the hospital rather than longer-term (i.e., in-home) exposure. We found cis-DCCA, trans-DCCA, and 3-PBA to be positively associated with persistent fevers only among predelivery samples, that is most proximal to home exposure, whereas the reverse was true for cis-DBCA (see Table S6). However, findings stratified by collection timing were imprecise due to small stratified sample sizes and event counts (see Table S6). This was particularly true for the postpartum stratum (n = 253), which had only 30 subjects with any ear infections and 7 with any sore throat events. Differential weight gain, and therefore effective fetal dose, may play a role in explaining observed associations. Because prepregnancy weight is not customarily measured or recorded in our study population, we had no data on pregnancy weight gain. However, adjusting for antepartum weight did not substantially change our estimates (see Table S8).

In addition to novelty as the first study we are aware of which has investigated associations between DDT/E and pyrethroids and child infection in an IRS setting, several strengths of the study population and approach are worth highlighting. First, the VHEMBE study had very high year-to-year retention, with over 91% of all enrolled subjects participating in the 2-y visit (and 94% of all children still alive at 2 y of age). Moreover, strong data collection and quality control protocols meant that very few values (<1%) of variables included in models were missing among study participants. The study also benefited from state-of-the-art serum DDT/E and urinary pyrethroid metabolite quantification and extensive data collection from questionnaire, medical records, and staff-collected anthropometry. To our knowledge, this study is the first to investigate associations between maternal perinatal pyrethroid metabolites and child infections. With respect to data analyses, results were robust to numerous sensitivity analyses to missing data, loss to follow-up, and variable mismeasurement that were conducted to assess the influence of modeling choices and assumptions on our findings.

The potential long-term effects of in utero exposure to DDT/E in low- and middle-income settings where IRS is practiced, including their interaction with maternal and familial factors, such as socioeconomic status (Appleton et al. 2016; Stein et al. 2016; Cakmak et al. 2016), malnutrition (Banerjee 1999; Prescott 2016), and HIV (Ruck et al. 2016; Slogrove et al. 2017) remain poorly studied despite indications that they may increase susceptibility to environmental chemicals. Such interactions are now recognized to be critically important to understanding child health in low- and middle- income countries (Goldstein et al. 2017; DeBoer et al. 2012) because their distributions and effects will differ from high income countries. This study represents one of the first to investigate the interactions between several relevant maternal exposures, including poverty and low energy intake, on the effect of intrauterine insecticide exposure on child health. Specifically, we found that associations with p,p'-DDT/E are stronger, and possibly only present, in the context of poverty and maternal low energy intake. Moreover, we found little evidence for associations between pyrethroid metabolites and rates of childhood infections. Finally, our findings lend additional support to the importance of structural or social deprivation to environmentally related child disease burdens.

https://doi.org/10.1289/EHP2657.

Acknowledgments

B.E., R.B., S.R., and J.C. received financial support from the National Institutes of Environmental Health Sciences (1R01ES020360-01); J.C. receives support as a Canada Research Chair in Environmental Health Sciences. The author acknowledges the hard work and dedication of the VHEMBE field staff and the invaluable contributions of the VHEMBE study participants, without whom this work would have been impossible.

References

Aneck-Hahn NH, Schulenburg GW, Bornman MS, Farias P, de Jager C. 2007. Impaired semen quality associated with environmental DDT exposure in young men living in a malaria area in the Limpopo Province, South Africa. J Androl 28(3):423-434, PMID: 17192596, https://doi.org/10.2164/jandrol.106.001701.

Appleton AA, Holdsworth EA, Kubzansky LD. 2016. A systematic review of the interplay between social determinants and environmental exposures for early-life outcomes. Curr Environ Health Rep 3(3):287-301, PMID: 27344145, https://doi.org/10. 1007/s40572-016-0099-7.

Assmann SF, Hosmer DW, Lemeshow S, Mundt KA. 1996. Confidence intervals for measures of interaction. Epidemiology 7(3):286-290, PMID: 8728443.

ATSDR (Agency for Toxic Substances and Disease Registry). 2002. Toxicological profile for DDT, DDE, DDD. https://www.atsdr.cdc.gov/toxprofiles/tp.asp?id=81& tid=20 [accessed 1 June 2017].

ATSDR. 2003. Toxicological profile for pyrethrins and pyrethroids. https://www.atsdr.cdc.gov/toxprofiles/TP.asp?id=787&tid=153 [accessed 1 June 2017].

Banerjee BD. 1999. The influence of various factors on immune toxicity assessment of pesticide chemicals. Toxicol Lett 107(1-3):21-31, PMID: 10414778, https://doi.org/10.1016/S0378-4274(99)00028-4.

Barr JR, Maggio VL, Barr DB, Turner WE, Sjodin A, Sandau CD, et al. 2003. New high-resolution mass spectrometric approach for the measurement of polychlorinated biphenyls and organochlorine pesticides in human serum. J Chromatogr B Analyt Technol Biomed Life Sci 794(1):137-148, PMID: 12888206, https://doi.org/10.1016/S1570-0232(03)00451-3.

Bergonzi R, De Palma G, Tomasi C, Ricossa MC, Apostoli P. 2009. Evaluation of different methods to determine total serum lipids for normalization of circulating organochlorine compounds. Int Arch Occup Environ Health 82(10):1241-1247, PMID: 19479274, https://doi.org/10.1007/s00420-009-0426-5.

Bourke CD, Berkley JA, Prendergast AJ. 2016. Immune dysfunction as a cause and consequence of malnutrition. Trends Immunol 37(6):386-398, PMID: 27237815, https://doi.org/10.1016/j.it.2016.04.003.

Bradman AS, Schwartz JM, Fenster L, Barr DB, Holland NT, Eskenazi B. 2007. Factors predicting organochlorine pesticide levels in pregnant Latina women living in a United States agricultural area. J Expo Sci Environ Epidemiol 17(4):388-399, PMID: 17033681, https://doi.org/10.1038/sj.jes.7500525.

Brander SM, Gabler MK, Fowler NL, Connon RE, Schlenk D. 2016. Pyrethroid pesticides as endocrine disruptors: molecular mechanisms in vertebrates with a focus on fishes. Environ Sci Technol 50(17):8977-8992, PMID: 27464030, https://doi.org/ 10.1021/acs.est.6b02253.

Burns JS, Williams PL, Sergeyev O, Korrick SA, Lee MM, Revich B, et al. 2012. Serum concentrations of organochlorine pesticides and growth among Russian boys. Environ Health Perspect 120(2):303-308, PMID: 21984531, https://doi.org/10.1289/ ehp.1103743.

Cakmak S, Hebbern C, Cakmak JD, Vanos J. 2016. The modifying effect of socioeconomic status on the relationship between traffic, air pollution and respiratory health in elementary schoolchildren. J Environ Manage 177:1-8, PMID: 27064731, https://doi.org/10.1016/jjenvman.2016.03.051.

Castorina R, Bradman A, Fenster L, Barr DB, Bravo R, Vedar MG, et al. 2010. Comparison of current-use pesticide and other toxicant urinary metabolite levels among pregnant women in the CHAMACOS cohort and NHANES. Environ Health Perspect 118(6):856-863, PMID: 20129873, https://doi.org/10.1289/ehp.0901568.

Cupul-Uicab LA, Terrazas-Medina EA, Hernandez-Avila M, Longnecker MP. 2014. Prenatal exposure to p,p'-DDE and p,p'-DDT in relation to lower respiratory tract infections in boys from a highly exposed area of Mexico. Environ Res 132:19-23, PMID: 24742723, https://doi.org/10.1016/j envres.2014.03.017.

Dallaire F, Dewailly E, Muckle G, Vezina C, Jacobson SW, Jacobson JL, et al. 2004. Acute infections and environmental exposure to organochlorines in Inuit infants from Nunavik. Environ Health Perspect 112(14):1359-1365, PMID: 15471725, https://doi.org/10.1289/ehp.7255.

DeBoer MD, Lima AAM, Oria RB, Scharf RJ, Moore SR, Luna MA, et al. 2012. Early childhood growth failure and the developmental origins of adult disease: do enteric infections and malnutrition increase risk for the metabolic syndrome? Nutr Rev 70(11):642-653, PMID: 23110643, https://doi.org/10.111Vj.1753-4887. 2012.00543.x.

Desmarais BA, Harden JJ. 2013. Testing for zero inflation in count models: bias correction for the Vuong test. Stata J 13(4):810-835.

Dewailly E, Ayotte P, Bruneau S, Gingras S, Belles-Isles M, Roy R. 2000. Susceptibility to infections and immune status in Inuit infants exposed to organochlorines. Environ Health Perspect 108(3):205-211, PMID: 10706525, https://doi.org/10.1289/ ehp.00108205.

Dewailly E, Forde M, Robertson L, Kaddar N, Laouan Sidi EA, Cote S, et al. 2014. Evaluation of pyrethroid exposures in pregnant women from 10 Caribbean countries. Environ Int 63:201-206, PMID: 24317226, https://doi.org/10.1016/j. envint.2013.11.014.

Duijts L, Bakker-Jonges LE, Labout JA, Jaddoe VW, Hofman A, Steegers EA, et al. 2009. Fetal growth influences lymphocyte subset counts at birth: the Generation R Study. Neonatology 95(2):149-156, PMID: 18776729, https://doi.org/10.1159/000153099.

Eskenazi B, Chevrier J, Rosas LG, Anderson HA, Bornman MS, Bouwman H, et al. 2009. The Pine River statement: human health consequences of DDT use. Environ Health Perspect 117(9):1359-1367, PMID: 19750098, https://doi.org/10.1289/ehp.11748.

Gascon M, Vrijheid M, Martinez D, Ballester F, Basterrechea M, Blarduni E, et al. 2012. Pre-natal exposure to dichlorodiphenyldichloroethylene and infant lower respiratory tract infections and wheeze. Eur Respir J 39(5):1188-1196, PMID: 22075485, https://doi.org/10.1183/09031936.00011711.

Gaspar FW, Chevrier J, Quiros-Alcala L, Lipsitt JM, Barr D, Holland N, et al. 2017. Levels and determinants of DDT and DDE exposure in the VHEMBE cohort. Environ Health Perspect 125(7):077006, PMID: 28696207, https://doi.org/10.1289/EHP353.

Goldstein JA, Norris SA, Aronoff DM. 2017. DOHaD atthe intersection of maternal immune activation and maternal metabolic stress: a scoping review. J Dev Orig Health Dis 8(3): 273-283, PMID: 28196555, https://doi.org/10.1017/ S2040174417000010.

Hosmer DW, Lemeshow S. 1992. Confidence interval estimation of interaction. Epidemiology 3(5):452-456, PMID: 1391139.

IOM (Institute of Medicine), NRC (National Research Council). 2009. Appendix B: Supplementary information on nutritional intake. In: Weight Gain during Pregnancy: Re-examining the Guidelines. Washington, DC:National Academies Press, 316.

Jusko TA, Koepsell TD, Baker RJ, Greenfield TA, Willman EJ, Charles MJ, et al. 2006. Maternal DDT exposures in relation to fetal and 5-year growth. Epidemiology 17(6):692-700, PMID: 17003683, https://doi.org/10.1097/01.ede.0000232226.06807.90.

Karmaus W, Kuehr J, Kruse H. 2001. Infections and atopic disorders in childhood and organochlorine exposure. Arch Environ Health 56(6):485-492, PMID: 11958547, https://doi.org/10.1080/00039890109602896.

Lubin JH, Colt JS, Camann D, Davis S, Cerhan JR, Severson RK, et al. 2004. Epidemiologic evaluation of measurement data in the presence of detection limits. Environ Health Perspect 112(17):1691-1696, PMID: 15579415, https://doi.org/10. 1289/ehp.7199.

MacIntyre UE, Venter CS, Vorster HH. 2001. A culture-sensitive quantitative food frequency questionnaire used in an African population: 1. Development and reproducibility. Public Health Nutr 4(1):53-62, PMID: 11315681, https://doi.org/ 10.1079/PHN200040.

Misumi I, Vella AT, Leong JA, Nakanishi T, Schreck CB. 2005. p,p'-DDE depresses the immune competence of chinook salmon (Oncorhynchus tshawytscha) leukocytes. Fish Shellfish Immunol 19(2):97-114, PMID: 15752649, https://doi.org/ 10.1016/j.fsi.2004.11.005.

National Center for Health Statistics. 2011. National Health and Nutrition Examination Survey 2011-2012 Survey Operations Manuals--Anthropometry (body measures). https://www.n.cdc.gov/nchs/nhanes/continuousnhanes/manuals.aspx?BeginYear= 2011 [accessed 1 June 2017].

Nunez GM, Estrada I, Calderon-Aranda ES. 2002. DDT inhibits the functional activation of murine macrophages and decreases resistance to infection by Mycobacterium microti. Toxicology 174(3):201-210, PMID: 12007859, https://doi.org/10.1016/S0300483X(02)00078-1.

Prescott SL. 2016. Early nutrition as a major determinant of 'immune health': implications for allergy, obesity and other noncommunicable diseases. Nestle Nutr Inst Workshop Ser 85:1-17, PMID: 27088328, https://doi.org/10.1159/000439477.

Rehana T, Rao PR. 1992. Effect of DDT on the immune system in Swiss albino mice during adult and perinatal exposure: humoral responses. Bull Environ Contam Toxicol 48(4):535-540, PMID: 1504498.

Rehman H, Mohan A, Tabassum H, Ahmad F, Rahman S, Parvez S, et al. 2011. Deltamethrin increases Candida albicans infection susceptibility in mice. Scand J Immunol 73(5):459-464, PMID: 21272049, https://doi.org/10.111Vj.13653083.2011.02521.x

Richardson DB, Kaufman JS. 2009. Estimation of the relative excess risk due to interaction and associated confidence bounds. Am J Epidemiol 169(6):756-760, PMID: 19211620, https://doi.org/10.1093/aje/kwn411.

Ruck C, Reikie BA, Marchant A, Kollmann TR, Kakkar F. 2016. Linking susceptibility to infectious diseases to immune system abnormalities among HIV-exposed uninfected infants. Front Immunol 7:310, PMID: 27594857, https://doi.org/10. 3389/fimmu.2016.00310.

Santoni G, Cantalamessa F, Cavagna R, Romagnoli S, Spreghini E, Piccoli M. 1998. Cypermethrin-induced alteration of thymocyte distribution and functions in prenatally-exposed rats. Toxicology 1250):67-78, PMID: 9585102.

Slogrove AL, Esser MM, Cotton MF, Speert DP, Kollmann TR, Singer J, et al. 2017. A prospective cohort study of common childhood infections in South African HIV-exposed uninfected and HIV-unexposed infants. Pediatr Infect Dis J 36(2): e38-e44, PMID: 28081048, https://doi.org/10.1097/INF.0000000000001391.

Statistics South Africa. 2017. P0309.3 Mortality and causes of death in South Africa: findings from death notification, 2015. http://www.statssa.gov.za/?page_id=1854& PPN=P0309.3&SCH=6987 [accessed 1 June 2017].

Stein LJ, Gunier RB, Harley K, Kogut K, Bradman A, Eskenazi B. 2016. Early childhood adversity potentiates the adverse association between prenatal organophosphate pesticide exposure and child IQ: the CHAMACOS cohort. Neurotoxicology 56:180- 187, PMID: 27474229, https://doi.org/10.1016/j.neuro.2016.07.010.

Sunyer J, Garcia-Esteban R, Alvarez M, Guxens M, Goni F, Basterrechea M, et al. 2010. DDE in mothers' blood during pregnancy and lower respiratory tract infections in their infants. Epidemiology 21(5):729-735, PMID: 20616741, https://doi.org/ 10.1097/EDE.0b013e3181e5ea96.

Suwanchaichinda C, Khamkong P, Worasuttayangkurn L, Satayavivad J. 2005. Deltamethrin exposure affects host resistance to Plasmodium infection in mice. Environ Toxicol Pharmacol 20(1):77-82, PMID: 21783571, https://doi.org/ 10.1016/j.etap.2004.10.004.

Textor J, Hardt J, Knuppel S. 2011. DAGitty: a graphical tool for analyzing causal diagrams. Epidemiology 22(5):745, PMID: 21811114, https://doi.org/10.1097/EDE. 0b013e318225c2be.

VanderWeele TJ. 2014. A unification of mediation and interaction: a 4-way decomposition. Epidemiology 25(5):749-761, PMID: 25000145, https://doi.org/10.1097/ EDE.0000000000000121.

Warner M, Aguilar Schall R, Harley KG, Bradman A, Barr D, Eskenazi B. 2013. In utero DDT and DDE exposure and obesity status of 7-year-old Mexican-American children in the CHAMACOS cohort. Environ Health Perspect 121(5):631-636, PMID: 23512307, https://doi.org/10.1289/ehp.1205656.

White IR, Royston P, Wood AM. 2011. Multiple imputation using chained equations: issues and guidance for practice. Stat Med 30(4):377-399, PMID: 21225900, https://doi.org/10.1002/sim.4067.

Whitworth KW, Bornman RM, Archer JI, Kudumu MO, Travlos GS, Wilson RE, et al. 2014. Predictors of plasma DDT and DDE concentrations among women exposed to indoor residual spraying for malaria control in the South African Study of Women and Babies (SOWB). Environ Health Perspect 122(6):545-552, PMID: 24577839, https://doi.org/10.1289/ehp.1307025.

WHO (World Health Organization). 2016. World malaria report 2016. http://www. who.int/malaria/publications/world-malaria-report-2016/report/en/ [accessed 1 June 2017].

Jonathan Huang, [1] Brenda Eskenazi, [2] Riana Bornman, [3] Stephen Rauch, [2] and Jonathan Chevrier [1]

[1] Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada

[2] Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California at Berkeley, Berkeley, California, USA

[3] Centre for Sustainable Malaria Control, School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa

Address correspondence to J. Huang, 1020 Pine Ave. W., Montreal, Quebec, Canada H3A 1A2. Telephone: (514) 398-6989. Email: jon.huang@ mcgill.ca

Supplemental Material is available online (https://doi.org/10.1289/EHP2657).

The authors declare they have no actual or potential competing financial interests.

Received 7 August 2017; Revised 14 May 2018; Accepted 16 May 2018; Published 14 June 2018.

Note to readers with disabilities: EHP strives to ensure that all journal content is accessible to all readers. However, some figures and Supplemental Material published in EHP articles may not conform to 508 standards due to the complexity of the information being presented. If you need assistance accessing journal content, please contact ehponline@niehs.nih.gov. Our staff will work with you to assess and meet your accessibility needs within 3 working days.
Table 1. Characteristics of Venda Health Examination of Mothers,
Babies, and their Environment (VHEMBE) study participants (Vhembe
District, Limpopo, South Africa; n = 674).

Characteristic                            n (%) or mean
                                            [+ or -] SD

Maternal characteristics at delivery
  Age (y)                                26.4 [+ or -] 6.3
Education
  <Grade 12                                  376 (56)
  Grade 12                                   200 (30)
  >Grade 12                                   98 (15)
Parity (number of previous children)
  0                                          288 (43)
  1                                          184 (27)
  2                                          108 (16)
[greater than or equal to] 3                  94 (14)
Marital status
  Married                                    320 (47)
  Unmarried                                  354 (53)
History of high blood pressure
or preeclampsia (a)
  Yes                                         86 (13)
  No                                         588 (87)
Energy intake status (b,c)
  Low/insufficient                           454 (67)
  Sufficient                                 209 (31)
HIV status (b)
  Positive                                    86 (13)
  Negative                                   586 (87)
Family characteristics at birth
  Number of people living                5:2 [+ or -] 2:8
  with index child
Poverty status (b,d)
  Below poverty line                         409 (61)
  Above poverty line                         262 (39)

Child characteristics
Sex
  Female                                     325 (48)
  Male                                       349 (52)
Preterm (<37 wk gestation)
  No                                         589 (87)
  Yes                                         85 (13)
Low birth weight (<3,500 g)
  No                                         623 (92)
  Yes                                         51 (8)
Exclusively breastfed
  <1 month                                   174 (26)
  [greater than or equal to] 1 month,        427 (63)
  but <6 months
  [greater than or equal to] 6 months         73 (11)
Any persistent fever (lasting
[greater than or equal to] 4 d) (b)
  No                                         476 (71)
  Yes                                        197 (29)
Any ear infection (b)
  No                                         563 (84)
  Yes                                        109 (16)
Any severe sore throat (b)
  No                                         631 (94)
  Yes                                         40 (6)

Note: SD, standard deviation.

(a) Any high blood pressure, preeclampsia, or use of blood pressure
medications in current or previous pregnancies, by self-report or
medical records.

(b) Individuals missing values for these variables (count in
parentheses): energy intake (11), HIV status (2), poverty level (3),
persistent fevers (1), ear infections (2), and severe sore throat
(3).

(c) Based on whether the individual's total energy intake falls below
the IOM and NRC (2009) recommendation for women in late pregnancy
based on age, height, weight, and activity level (mean recommended
intake in this population = 12,145 kJ; range=10,163 to 14,711 kJ).

(d) Mid-2013 food poverty threshold = Rand 386 per person per month
(W. Ruch, written communication, Jan 2016).

Table 2. Maternal lipid/corrected concentrations of
dichlorodiphenyltrichloroethane (DDT) and
dichlorodiphenyldichloroethylene (DDE) in serum samples (ng/g lipid)
and specific gravity/corrected concentrations of pyrethroid
metabolites in urine samples ([micro]g/L).

Analyte        n    Detected    Quantified    Geometric    Min    10th
                     (%) (a)      (%) (b)     mean (c)            %ile

Serum DDT/E
  o,p'-DDT    674     90.5         44.5         9.18      <LOD    1.5
  p,p'-DDE    674      100         97.3        292.95     3.98    45.3
  p,p'-DDT    674     98.1         90.5         70.04     <LOD    7.7

Urinary pyrethroid
metabolites

  cis-DBCA    666      100         99.5         0.22      0.005   0.05
  cis-DCCA    666      100         99.8         0.31      0.015   0.08
  trans       666      100         99.5         0.36      0.008   0.08
  -DCCA
  3-PBA       665      100          100         0.72      0.022   0.21

Analyte        n    25th    Median   75th    90th       Max
                     %ile            %ile     %ile

Serum DDT/E
  o,p'-DDT    674    3.5     7.5     23.3     74.8    2029.3
  p,p'-DDE    674   92.3    254.4    878.6   2709.8   26301.3
  p,p'-DDT    674   18.6     56.9    261.3   994.8    15027.6

Urinary pyrethroid
metabolites

  cis-DBCA    666   0.10     0.22    0.48     1.12     17.8
  cis-DCCA    666   0.15     0.30    0.60     1.05     103.5
  trans       666   0.16     0.34    0.80     1.63     132.9
  -DCCA
  3-PBA       665   0.38     0.70    1.38     2.40     58.9

Note: %ile, percentile; DBCA,
3-(2,2-dibromovinyl)-2,2-dimethyl-cyclopropane carboxylic acid; DCCA,
3-(2,2-dichlorovinyl)-2,2-dimethyl-cyclopropane carboxylic acid; LOD,
limit of detection; LOQ, limit of quantification; Max, maximum; Min,
minimum; PBA, phenoxybenzoic acid.

(a) LODs: 0.01 ng/mL (o,p'-DDT, and p,p'-DDT); 0.03 ng/mL (p,p'-DDE);
0.0025 [micro]g/L (cis-DBCA); 0.0045 [micro]g/L (cis-DCCA); 0.0038
[micro]g/L (trans-DCCA); and 0.0047 [micro]g/L (3-PBA).

(b) LOQs: 0.05 ng/mL (o,p'-DDT, andp,p'-DDT); 0.15 ng/mL (p,p'-DDE);
0.0082 [micro]g/L (cis-DBCA); 0.015 [micro]g/L (cis-DCCA); 0.013
[micro]g/L (trans-DCCA); and 0.016 [micro]g/L (3-PBA).

(c) Geometric means for DDT/E include values below the LOD imputed at
random based on log-normal probability distributions whose parameters
were determined by maximum likeli- hood estimation.

Table 3. Associations between insecticide biomarker concentrations
and rate of persistent fevers, ear infections, and severe sore
throats in the second year of life.

                  Persistent fevers (lasting
                  [greater than or equal to]     Ear Infections
                          4 days)

Exposure             IRR      (95% CI)          IRR      (95% CI)

DDT/E (n = 674)
  o,p' 0 -DDT        1.10   (0.94, 1.30)        0.83   (0.60, 1.15)
  p,p' 0 -DDE        1.21   (1.01, 1.46)        1.03   (0.75, 1.41)
  p,p' 0 -DDT        1.14   (0.99, 1.32)        1.06   (0.80, 1.40)

Pyrethroid metabolites
(n = 666)
  cis-DBCA           1.07   (0.82, 1.39)        0.70   (0.45, 1.08)
  cis-DCCA           1.09   (0.82, 1.45)        0.84   (0.50, 1.41)
  trans-DCCA         1.11   (0.87, 1.42)        0.84   (0.57, 1.25)
  3-PBA              1.06   (0.80, 1.40)        0.71   (0.42, 1.20)

                  Severe sore throat

Exposure          IRR      (95% CI)

DDT/E (n = 674)
  o,p' 0 -DDT     1.53   (0.77, 3.03)
  p,p' 0 -DDE     1.78   (0.82, 3.84)
  p,p' 0 -DDT     1.58   (0.80,3.14)

Pyrethroid metabolites
(n = 666)
  cis-DBCA        0.63   (0.21, 1.87)
  cis-DCCA        0.80   (0.14, 4.50)
  trans-DCCA      0.86   (0.29, 2.52)
  3-PBA           0.68   (0.19, 2.42)

Note: IRRs are given per 10-fold higher pesticide concentration.
These were estimated by zero-inflated Poisson regression adjusted for
maternal age, marital status, and parity at birth of index child, as
well as low energy intake (daily intake <IOM recommendations for late
pregnancy, -12,000 kJ), income below the mid-2013 South African food
poverty threshold (monthly income <Rand 386 per household member),
HIV status, and child sex. An offset (in days between last child
visit and date of outcome assessment) was used to account for the
difference in observation time between subjects. The inflation (i.e.,
excess zeroes) due to underreporting or lack of observation were
modeled using maternal age, parity, whether the mother regularly
lived with the child at the 2-y visit, number of individuals living
in the same home as the index child at the 2-y visit, and the
interviewer-rated score of the mother's quality of responses to child
health questions. CI, confidence interval; IRR, incidence rate ratio.

Table 4. Effect measure modification of the association between serum
DDT-E and rate of persistent fevers, by maternal poverty, low energy
intake, HIV status, and exclusive breastfeeding duration and child
sex (n = 674).

Effect modifier                                    o,p'-DDT

Contrast                                        IRR      (95% CI)

Household poverty status (a)
  [arrow down] poverty line vs. [arrow up]     1.18    (0.93, 1.51)
    poverty line ([IRR.sub.01])
  [arrow up] insecticide among [arrow up]      1.00    (0.73, 1.35)
    poverty line ([IRR.sub.10])
  [arrow up] insecticide among [arrow down]    1.07    (0.88, 1.30)
    poverty line ([IRR.sub.11]
    vs. [IRR.sub.01])
  [arrow up] insecticide and [arrow down]      1.27    (0.89, 1.65)
    poverty line ([IRR.sub.11])
  RERI (= [IRR.sub.11] - [IRR.sub.10]          0.09    (-0.31, 0.48)
    - [IRR.sub.01] + 1)
Maternal low daily energy intake (b)
  Insufficient vs. sufficient (IRR.sub.01])    0.88    (0.69, 1.12)

  [arrow up] insecticide among sufficient      0.81    (0.59, 1.10)
    ([IRR.sub.10])
  [arrow up] insecticide among insufficient    1.17    (0.96, 1.43)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and insufficient      1.03    (0.73, 1.33)
    ([IRR.sub.11])
  RERI                                         0.34    (0.02, 0.66)
Maternal HIV status
  Negative vs. positive ([IRR.sub.01])         0.63    (0.41, 0.96)

  [arrow up] insecticide among negative        1.05    (0.89, 1.25)
    ([IRR.sub.10])
  [arrow up] insecticide among positive        0.97    (0.53, 1.78)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and positive          0.61    (0.14, 1.09)
    ([IRR.sub.11])
  RERI                                         -0.07   (-0.48, 0.34)
Exclusive breastfeeding
  <1 month vs. [greater than or equal to]      1.10    (0.83, 1.45)
    1 month ([IRR.sub.01])
  [arrow up] insecticide among                 1.19    (0.96, 1.46)
    [greater than or equal to]
    1 month ([IRR.sub.10])
  [arrow up] insecticide among <1 month        0.96    (0.74, 1.18)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and <1 month          1.06    (0.65, 1.46)
    ([IRR.sub.11])
  RERI                                         -0.23   (-0.56, 0.10
Child Sex
  Female vs. male ([IRR.sub.01])               0.93    (0.70, 1.22)

  [arrow up] insecticide among male            1.05    (0.87, 1.27)
    ([IRR.sub.10])
  [arrow up] insecticide among female          1.17    (0.88, 1.46)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and female            1.08    (0.73, 1.43)
    ([IRR.sub.11])
  RERI                                         0.11    (-0.20, 0.41)

Effect modifier                                    p,p'-DDE

Contrast                                        IRR       (95% CI)

Household poverty status (a)
  [arrow down] poverty line vs. [arrow up]     1.16     (0.91, 1.48)
    poverty line ([IRR.sub.01])
  [arrow up] insecticide among [arrow up]      0.93     (0.69, 1.25)
    poverty line ([IRR.sub.10])
  [arrow up] insecticide among [arrow down]    1.31     (1.08, 1.59)
    poverty line ([IRR.sub.11]
    vs. [IRR.sub.01])
  [arrow up] insecticide and [arrow down]      1.52     (1.08, 1.96)
    poverty line ([IRR.sub.11])
  RERI (= [IRR.sub.11] - [IRR.sub.10]          0.43     (0.03, 0.84)
    - [IRR.sub.01] + 1)
Maternal low daily energy intake (b)
  Insufficient vs. sufficient (IRR.sub.01])    0.85     (0.67, 1.08)

  [arrow up] insecticide among sufficient      0.96     (0.72, 1.28)
    ([IRR.sub.10])
  [arrow up] insecticide among insufficient    1.30     (1.07, 1.58)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and insufficient      1.11     (0.80, 1.42)
    ([IRR.sub.11])
  RERI                                         0.29     (0.06, 0.65)
Maternal HIV status
  Negative vs. positive ([IRR.sub.01])         0.62     (0.41, 0.96)

  [arrow up] insecticide among negative        1.18     (1.00, 1.39)
    ([IRR.sub.10])
  [arrow up] insecticide among positive        1.21     (0.64, 2.27)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and positive          0.75     (0.22, 1.28)
    ([IRR.sub.11])
  RERI                                         -0.05   (-0.56,  0.46)
Exclusive breastfeeding
  <1 month vs. [greater than or equal to]      1.09     (0.83, 1.44)
    1 month ([IRR.sub.01])
  [arrow up] insecticide among                 1.24     (0.99, 1.55)
    [greater than or equal to]
    1 month ([IRR.sub.10])
  [arrow up] insecticide among <1 month        1.15     (0.82, 1.48)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and <1 month          1.25     (0.75, 1.76)
    ([IRR.sub.11])
  RERI                                         -0.08   (-0.51,  0.36)
Child Sex
  Female vs. male ([IRR.sub.01])               0.93     (0.72, 1.22)

  [arrow up] insecticide among male            1.28     (1.03, 1.59)
    ([IRR.sub.10])
  [arrow up] insecticide among female          1.14     (0.82, 1.47)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and female            1.07     (0.70, 1.44)
    ([IRR.sub.11])
  RERI                                         -0.15   (-0.53,  0.23)

Effect modifier                                   p,p'-DDT

Contrast                                       IRR       (95% CI)

Household poverty status (a)
  [arrow down] poverty line vs. [arrow up]     1.18   (0.92, 1.50)
    poverty line ([IRR.sub.01])
  [arrow up] insecticide among [arrow up]      0.92   (0.73, 1.16)
    poverty line ([IRR.sub.10])
  [arrow up] insecticide among [arrow down]    1.18   (1.00, 1.39)
    poverty line ([IRR.sub.11]
    vs. [IRR.sub.01])
  [arrow up] insecticide and [arrow down]      1.39   (1.00, 1.77)
    poverty line ([IRR.sub.11])
  RERI (= [IRR.sub.11] - [IRR.sub.10]          0.29   (-0.02, 0.60)
    - [IRR.sub.01] + 1)
Maternal low daily energy intake (b)
  Insufficient vs. sufficient (IRR.sub.01])    0.87   (0.69, 1.10)

  [arrow up] insecticide among sufficient      0.89   (0.70, 1.13)
    ([IRR.sub.10])
  [arrow up] insecticide among insufficient    1.18   (1.01, 1.39)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and insufficient      1.03   (0.75, 1.31)
    ([IRR.sub.11])
  RERI                                         0.27   (-0.002, 0.55)
Maternal HIV status
  Negative vs. positive ([IRR.sub.01])         0.63   (0.41, 0.96)

  [arrow up] insecticide among negative        1.08   (0.94, 1.24)
    ([IRR.sub.10])
  [arrow up] insecticide among positive        1.19   (0.70, 2.02)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and positive          0.74   (0.27, 1.21)
    ([IRR.sub.11])
  RERI                                         0.04   (-0.37, 0.46)
Exclusive breastfeeding
  <1 month vs. [greater than or equal to]      1.08   (0.81, 1.43)
    1 month ([IRR.sub.01])
  [arrow up] insecticide among                 1.09   (0.93, 1.28)
    [greater than or equal to]

    1 month ([IRR.sub.10])
  [arrow up] insecticide among <1 month        1.24   (0.88, 1.61)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and <1 month          1.34   (0.83, 1.86)
    ([IRR.sub.11])
  RERI                                         0.18   (-0.22, 0.57)
Child Sex
  Female vs. male ([IRR.sub.01])               0.92   (0.70, 1.22)

  [arrow up] insecticide among male            1.12   (0.94, 1.32)
    ([IRR.sub.10])
  [arrow up] insecticide among female          1.17   (0.91, 1.42)
    ([IRR.sub.11] vs. [IRR.sub.01])
  [arrow up] insecticide and female            1.08   (0.74, 1.42)
    ([IRR.sub.11])
  RERI                                         0.04   (-0.24, 0.32)

Note: IRRs are contrasts between levels of the binary effect modifier
(e.g., below vs. above poverty line; first row under each subheading;
[IRR.sub.01]) or per 10-fold higher pesticide concentration (each
of the other rows; [IRR.sub.10], IRRuvs.01 [IRR.sub.11]). These were
estimated by zero-inflated Poisson regression adjusted for maternal
age, marital status, and parity at birth of index child, as well as
low energy intake (daily intake below the IOM and NRC (2009)
recommendations for late pregnancy,  12,000 kJ), income below the
mid-2013 South African food poverty threshold (monthly income <Rand
386 per household member), HIV status, and child sex. Additionally,
for each effect modifier, including a product term for the respective
modifier (e.g., poverty status) and DDT/E concentration. An
offset (in days between last child visit and date of outcome
assessment) was used to account for the difference in observation
time between subjects. The inflation (i.e., excess zeroes) due to
underreporting or lack of observation were modeled using maternal
age, parity, whether the mother regularly lived with the child at the
2-y visit, number of individuals living in the same home as the index
child at the 2-y visit, and the interviewer-rated score of the
mother's quality of responses to child health questions. CI,
confidence interval; DDE, dichlorodiphenyldichloroethylene; DDT,
dichlorodiphenyltrichloroethane; IRR, incidence rate ratio; RERI,
relative excess risk due to interaction.

(a) Mid-2013 South African food poverty line = Rand386 per household
memberpermonth. (b) IOM and NRC (2009) caloric intake recommendations
for late pregnancy  12,000 kJ.
COPYRIGHT 2018 National Institute of Environmental Health Sciences
No portion of this article can be reproduced without the express written permission from the copyright holder.
Copyright 2018 Gale, Cengage Learning. All rights reserved.

Article Details
Printer friendly Cite/link Email Feedback
Title Annotation:Research; dichlorodiphenyltrichloroethane
Author:Huang, Jonathan; Eskenazi, Brenda; Bornman, Riana; Rauch, Stephen; Chevrier, Jonathan
Publication:Environmental Health Perspectives
Article Type:Report
Date:Jun 1, 2018
Words:9786
Previous Article:Evaluation of the Impact of Ambient Temperatures on Occupational Injuries in Spain.
Next Article:Elucidating Gene-by-Environment Interactions Associated with Differential Susceptibility to Chemical Exposure.
Topics:

Terms of use | Privacy policy | Copyright © 2019 Farlex, Inc. | Feedback | For webmasters