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<article xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" article-type="research-article"><?properties manuscript?><front><journal-meta><journal-id journal-id-type="nlm-journal-id">7512134</journal-id><journal-id journal-id-type="pubmed-jr-id">4268</journal-id><journal-id journal-id-type="nlm-ta">Int Arch Occup Environ Health</journal-id><journal-id journal-id-type="iso-abbrev">Int Arch Occup Environ Health</journal-id><journal-title-group><journal-title>International archives of occupational and environmental health</journal-title></journal-title-group><issn pub-type="ppub">0340-0131</issn><issn pub-type="epub">1432-1246</issn></journal-meta><article-meta><article-id pub-id-type="pmid">29026987</article-id><article-id pub-id-type="pmc">5797496</article-id><article-id pub-id-type="doi">10.1007/s00420-017-1265-4</article-id><article-id pub-id-type="manuscript">NIHMS912813</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title-group><article-title>Acetylcholinesterase activity and time after a peak pesticide use
period among Ecuadorian children</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Suarez-Lopez</surname><given-names>Jose R.</given-names></name><xref ref-type="aff" rid="A1">1</xref><xref rid="FN1" ref-type="author-notes">*</xref><!--<email>jrsuarez@ucsd.edu</email>--></contrib><contrib contrib-type="author"><name><surname>Butcher</surname><given-names>Cheyenne R.</given-names></name><xref ref-type="aff" rid="A1">1</xref><!--<email>cheyennerose123@gmail.com</email>--></contrib><contrib contrib-type="author"><name><surname>Gahagan</surname><given-names>Sheila</given-names></name><xref ref-type="aff" rid="A2">2</xref><!--<email>sgahagan@ucsd.edu</email>--></contrib><contrib contrib-type="author"><name><surname>Checkoway</surname><given-names>Harvey</given-names></name><xref ref-type="aff" rid="A1">1</xref><!--<email>hcheckoway@ucsd.edu</email>--></contrib><contrib contrib-type="author"><name><surname>Alexander</surname><given-names>Bruce H.</given-names></name><xref ref-type="aff" rid="A3">3</xref><!--<email>balex@umn.edu</email>--></contrib><contrib contrib-type="author"><name><surname>Al-Delaimy</surname><given-names>Wael K.</given-names></name><xref ref-type="aff" rid="A1">1</xref><!--<email>wael@ucsd.edu</email>--></contrib></contrib-group><aff id="A1">
<label>1</label>Division of Global Health, Department of Family Medicine and Public
Health, University of California, San Diego. 9500 Gilman Drive #0725, La
Jolla, California 92093-0725, USA</aff><aff id="A2">
<label>2</label>Division of Academic General Pediatrics, Child Development and
Community Health, Department of Pediatrics, University of California, 9500 Gilman
Drive #0832, La Jolla, California 92093-0832, USA</aff><aff id="A3">
<label>3</label>Division of Environmental Health Sciences, University of Minnesota,
Minneapolis, 420 Delaware St. SE, MMC 807, Minneapolis MN 55455</aff><author-notes><corresp id="FN1">Corresponding Author: Jose Ricardo Suarez-Lopez, Department of
Family and Preventive Medicine, University of California-San Diego, 9500 Gilman
Drive #0725, La Jolla, California 92093-0725, USA.
<email>jrsuarez@ucsd.edu</email>, Phone: +1 858 822 0165</corresp></author-notes><pub-date pub-type="nihms-submitted"><day>25</day><month>10</month><year>2017</year></pub-date><pub-date pub-type="epub"><day>13</day><month>10</month><year>2017</year></pub-date><pub-date pub-type="ppub"><month>2</month><year>2018</year></pub-date><pub-date pub-type="pmc-release"><day>01</day><month>2</month><year>2019</year></pub-date><volume>91</volume><issue>2</issue><fpage>175</fpage><lpage>184</lpage><!--elocation-id from pubmed: 10.1007/s00420-017-1265-4--><abstract><sec id="S1"><title>PURPOSE</title><p id="P1">Mother&#x02019;s Day (May) is a holiday with substantial demand for
flowers, associated with heightened flower production and escalated
pesticide use. The effect of spray seasons on pesticide exposures of
children living in agricultural communities but who do not work in
agriculture is poorly understood. In this study, we estimated the
association of time after Mother&#x02019;s Day harvest with
children&#x02019;s acetylcholinesterase (AChE) activity. AChE is a
physiological marker of organophosphate/carbamate pesticide exposures that
may take up to 3 months to normalize after its inhibition.</p></sec><sec id="S2"><title>METHODS</title><p id="P2">We examined 308 children, aged 4&#x02013;9 years, in Ecuadorian
agricultural communities during a low flower-production season but within
63&#x02013;100 days (mean: 81.5 days, SD: 10.9) after Mother&#x02019;s Day
harvest. We quantified AChE activity (mean: 3.14 U/mL, SD: 0.49) from a
single finger-stick sample.</p></sec><sec id="S3"><title>RESULTS</title><p id="P3">We observed positive linear associations between time after the
harvest and AChE among participants living near plantations. The
associations were strongest among participants living within 233m (0.15 U/mL
[95%CI: 0.02, 0.28]), slightly weaker among
participants living within 234&#x02013;532m (0.11 U/mL [0.00,
0.23]), and not associated among participants at greater distances.
Similar findings were observed across categories of areas of flower
plantations within 500 m of homes.</p></sec><sec id="S4"><title>CONCLUSIONS</title><p id="P4">These cross-sectional findings suggest that a peak pesticide use
period can decrease AChE activity of children living near plantations. These
seasonal pesticide exposures could induce short- and long-term developmental
alterations in children. Studies assessing exposures at multiple times in
relation to pesticide spray seasons among children who do not work in
agriculture are needed.</p></sec></abstract><kwd-group><kwd>pesticides</kwd><kwd>organophosphate</kwd><kwd>cholinesterase</kwd><kwd>agriculture</kwd><kwd>children</kwd><kwd>Mother&#x02019;s Day</kwd></kwd-group></article-meta></front><body><sec sec-type="intro" id="S5"><title>Introduction</title><p id="P5">The seasonal nature of agricultural work may bring populations in rural
settings into increased contact with pesticides during peak pesticide-use periods.
Studies among agricultural workers have found that pesticide spray periods are
associated with increased pesticide exposure biomarkers and inhibition of
acetylcholinesterase (AChE) activity (<xref rid="R24" ref-type="bibr">Peiris-John et
al. 2005</xref>; <xref rid="R3" ref-type="bibr">Crane et al. 2013</xref>; <xref rid="R31" ref-type="bibr">Strelitz et al. 2014</xref>; <xref rid="R16" ref-type="bibr">Krenz et al. 2015</xref>; <xref rid="R30" ref-type="bibr">Singleton et al. 2015</xref>; <xref rid="R26" ref-type="bibr">Quandt et al.
2015</xref>), a physiological biomarker of exposure to cholinesterase inhibitor
pesticides (i.e. organophosphate and carbamate pesticides) (<xref rid="R20" ref-type="bibr">Makhaeva et al. 2009</xref>).</p><p id="P6">Children and other non-agricultural workers living in agricultural
communities may also have an elevated risk of exposure to pesticides during
pesticide spray seasons; however, very few studies to date have assessed this in
children who do not work in agriculture (<xref rid="R3" ref-type="bibr">Crane et al.
2013</xref>; <xref rid="R35" ref-type="bibr">Thompson et al. 2014</xref>; <xref rid="R9" ref-type="bibr">Galea et al. 2015</xref>) and, to our knowledge, only
one study with a limited number of such children has assessed AChE activity as an
outcome (<xref rid="R3" ref-type="bibr">Crane et al. 2013</xref>). In the latter
study elevated urinary markers of organophosphate and cholinesterase depressions
were observed during the pesticide spray season compared to baseline (<xref rid="R3" ref-type="bibr">Crane et al. 2013</xref>). In the former studies, high spray
seasons, compared to low spray seasons, were associated with greater urinary
metabolite concentrations of organophosphates among children living with
agricultural workers (<xref rid="R35" ref-type="bibr">Thompson et al. 2014</xref>),
whereas children not living with agricultural workers but living within agricultural
communities were not found to have differences in urinary pesticide metabolites
concentrations between the low and high pesticide spray seasons (<xref rid="R35" ref-type="bibr">Thompson et al. 2014</xref>; <xref rid="R9" ref-type="bibr">Galea et al. 2015</xref>). The limited number of studies on this topic
highlights the importance of conducting these studies in general populations of
children living in agricultural settings.</p><p id="P7">Some routes of exposure of children who do not work in agriculture include
off-target drift from pesticide application sites and take-home pathways from farm
workers. This has been shown in multiple US studies that have measured pesticide
levels in house dust, urine and skin swabs in relation to residential proximity to
plantations and presence of farmworkers at home (<xref rid="R29" ref-type="bibr">Simcox et al. 1995</xref>; <xref rid="R18" ref-type="bibr">Loewenherz et al.
1997</xref>; <xref rid="R19" ref-type="bibr">Lu et al. 2000</xref>; <xref rid="R22" ref-type="bibr">McCauley et al. 2001</xref>; <xref rid="R4" ref-type="bibr">Curl et al. 2002</xref>; <xref rid="R13" ref-type="bibr">Hogenkamp et al. 2004</xref>; <xref rid="R25" ref-type="bibr">Quandt et al.
2004</xref>; <xref rid="R5" ref-type="bibr">Curwin et al. 2005</xref>; <xref rid="R37" ref-type="bibr">Ward et al. 2006</xref>; <xref rid="R38" ref-type="bibr">Weppner et al. 2006</xref>; <xref rid="R27" ref-type="bibr">Ramaprasad et al. 2009</xref>).</p><p id="P8">Many organophosphate pesticides irreversibly inhibit AChE activity, resulting
in build-up of the neurotransmitter, acetylcholine, active in the autonomic nervous
system, at neuromuscular junctions, and as a neuromodulator in the brain.
Irreversible inhibition of erythrocytic AChE can last for approximately 80 days
(<xref rid="R21" ref-type="bibr">Mason 2000</xref>)<sub>,</sub> until a
sufficient number of erythrocytes have been turned over to return activity to
pre-exposure levels. Exposures to cholinesterase inhibitor pesticides have been
consistently associated with cognitive and neurobehavioral deficits in children in
various studies (<xref rid="R15" ref-type="bibr">Kofman et al. 2006</xref>; <xref rid="R8" ref-type="bibr">Eskenazi et al. 2007</xref>, <xref rid="R7" ref-type="bibr">2014</xref>; <xref rid="R28" ref-type="bibr">Rauh et al.
2011</xref>; <xref rid="R34" ref-type="bibr">Suarez-Lopez et al.
2013</xref>).</p><p id="P9">In the present study, we evaluated AChE activity in relation to time after
the Mother&#x02019;s Day flower harvest among children who participated in the
Secondary Exposure to Pesticides among Children and Adolescents (ESPINA:
Exposici&#x000f3;n Secundaria a Plaguicidas en Ni&#x000f1;os y Adolescentes
[Spanish]) study. Children of this study did not work in agriculture
but lived in agricultural communities in Pedro Moncayo county, Ecuador. We
hypothesized that, as a result of pesticide exposures, AChE activity would be lower
in children examined sooner after Mother&#x02019;s Day compared to children examined
later.</p><p id="P10">Production of roses and other flowers in Pedro Moncayo county increases
substantially between October and May to meet the heightened demand of flowers for
holidays including Christmas (December 25), Valentine&#x02019;s Day (February 14),
Easter (March/April) and Mother&#x02019;s Day (May). After the Mother&#x02019;s Day
harvest, production slows substantially during the summer months. Because there are
strict no-tolerance policies for the importation of crops with pests in many
countries including the US (<xref rid="R36" ref-type="bibr">U.S. Department of
Agriculture 2012</xref>), the use of pesticides in floriculture continues until
soon before the harvest (<xref rid="R23" ref-type="bibr">Narvaez et al. 2002</xref>;
<xref rid="R12" ref-type="bibr">Harari 2004</xref>). The floriculture industry
in Pedro Moncayo County employs 21% of adults (<xref rid="R33" ref-type="bibr">Suarez-Lopez et al. 2012</xref>) and occupies 5.8% (1800
hectares) of the land (<xref rid="R10" ref-type="bibr">Gobierno Municipal del Canton
Pedro Moncayo 2011</xref>). The Ecuadorian floriculture industry uses many
different pesticides, including fungicides, herbicides and various classes of
insecticides, which are sprayed by workers using hand sprayers. The pesticide use
reports of 7 flower plantations in Pedro Moncayo County in 2008, as required for
their yearly permit of operation, included 23 different insecticides, including the
following cholinesterase inhibitor pesticides: carbamates (methiocarb, carbofuran,
aldicarb) and organophosphates (diazinon, dimethoate, acephate, chlorpyrifos). Other
reported pesticides included over 50 different fungicides.</p></sec><sec sec-type="methods" id="S6"><title>Methods</title><p id="P11">In 2008 as part of the ESPINA study, we examined 313 4- to 9-year-old
children and interviewed their parents or guardians. Most children (73%)
were recruited from past participation in a large and representative survey (2004
Survey of Access and Demand of Health Services in Pedro Moncayo County) conducted by
Fundacion Cimas del Ecuador in collaboration with Pedro Moncayo County communities.
The remaining 27% of children were newly recruited participants. The ESPINA
study includes participants from all 5 parishes of Pedro Moncayo county and has
similar socio-economic and racial distributions as the general population of
children there. Detailed participant recruitment information has been described
elsewhere (<xref rid="R33" ref-type="bibr">Suarez-Lopez et al. 2012</xref>). Parents
provided informed consent for themselves and for their children. Participants, at
least 7 years old, provided assent for participation in the study. The present
analyses include information of 308 children who had complete co-variate data for
this study. This study was approved by the Institutional Review Boards of
Fundaci&#x000f3;n Cimas del Ecuador, the University of Minnesota, the University of
California San Diego, Universidad San Francisco de Quito and the Ministry of Public
Health of Ecuador. The main objective of the ESPINA study is to understand the
effects of pesticide exposure on children&#x02019;s growth and neurobehavioral
outcomes.</p><p id="P12">Participants were examined once within 100 days of the Mother&#x02019;s Day
harvest in 2008 (range: 63 &#x02013; 100 days, mean: 84.5 days, SD: 10.8 days. AChE
measurements were conducted on 20 different days with an average of 15 participants
being examined each day. Exams were conducted in 7 schools distributed across the 5
parishes that make-up Pedro Moncayo County: Malchingu&#x000ed;, Tocachi, La
Esperanza, Tabacundo and Tupigachi. Parents or guardians were interviewed at home to
obtain information on socio-economic status, health, demographics and pesticide
exposure histories of members of the household.</p><p id="P13">Children&#x02019;s height was measured using a stadiometer to the nearest mm
following standard procedures. Height-for-age z-scores were calculated using the
World Health Organization normative sample (<xref rid="R39" ref-type="bibr">WHO
Multicentre Growth Reference Study Group 2006</xref>). AChE activity and
hemoglobin concentration were assessed using the EQM Test-mate ChE Cholinesterase
Test System 400 (EQM research, Cincinnati, OH) from a finger-stick blood sample,
following standard procedures (<xref rid="R6" ref-type="bibr">EQM Research
2003</xref>).</p><p id="P14">The distance from each participant&#x02019;s home to the nearest flower
plantation was calculated. Geographical coordinates of participant homes were
collected in 2004, 2006 and 2010 by Fundacion Cimas del Ecuador as part of the
System of Local and Community Information (Sistema de Informaci&#x000f3;n Local y
Comunitario), using portable global positioning receivers. Plantation edges (areal
polygons) were created by measuring the coordinates of each corner of each
plantation&#x02019;s perimeter. The distance of homes to the nearest 1 m segment of
flower plantation edge and areas of flower plantation within a given radius from a
home were calculated using ArcGIS 9.3. (Esri, Redlands, CA). We also calculated the
areas of flower plantations within 500 m buffers around each participant&#x02019;s
home.</p><sec id="S7"><title>Statistical Analysis</title><p id="P15">For greater precision, we calculated the number of days between the
approximate end of the Mother&#x02019;s Day harvest (5/08/2008, 00:00 am) and
the date and time of the beginning of the examination. The associations between
time after the Mother&#x02019;s Day harvest and AChE activity were analyzed
using two multiple linear regression models defined a-priori: model 1 adjusted
for a minimal number of potential confounders including age, sex, and race. In
this cohort we observed that age was positively associated with AChE activity
(<xref rid="R33" ref-type="bibr">Suarez-Lopez et al. 2012</xref>). Model 2
further accounted for chronic nutritional status and additional potential
sources of pesticide exposure: model 1 + height-for-age z-score, income,
distance to the nearest plantation edge and flower worker cohabitation status.
In this cohort, children living with floricultural workers were found to have
lower AChE activity compared to children living with non-agricultural workers
(<xref rid="R33" ref-type="bibr">Suarez-Lopez et al. 2012</xref>). We also
considered residential distance to plantations and flower worker cohabitation to
be potential effect modifiers as described below. All models were further
adjusted for hemoglobin concentration considering that the main outcome was
erythrocytic AChE activity. It is important to account for varying red blood
cell compositions of blood, as these variations can alter the values of
erythrocytic AChE activity (<xref rid="R6" ref-type="bibr">EQM Research
2003</xref>).</p><p id="P16">We assessed effect modification by flower worker cohabitation status,
sex and by 2 constructs of potential drift of pesticides from plantations onto
homes: a) home distance to the nearest flower plantation, and b) areas of flower
plantations within 500 m of participants&#x02019; homes. We tested statistical
significance of interaction terms (X&#x003b2;<sub>predictor</sub> *
X&#x003b2;<sub>effect modifier</sub>) within models 1 and 2. We then
analyzed the associations stratified by categories of the significant effect
modifiers. For instance, we analyzed and plotted the associations stratified by
tertiles of residential distance to the nearest flower plantation, and by a
3-category variable of areas of flower plantations within 500 m of
participants&#x02019; homes divided as follows: a) zero m<sup>2</sup>, b) lower
median split of non-zero values, c) upper median split of non-zero values. We
selected this 3-category variable over tertiles considering the substantial
proportion of participants with values of zero m<sup>2</sup> (38%). The
plots consisted of adjusted means of AChE activity across time since
Mother&#x02019;s Day harvest, and the model 2 linear function (association) of
time since Mother&#x02019;s Day harvest and AChE activity. Analyses were
conducted using SAS Version 9.4 (SAS Institute Inc., Cary, NC)</p><p id="P17">To include most children in multivariable analyses, we imputed missing
information for race, income and residential distance to the nearest flower
plantation. Monthly household income was imputed for 17 children according to 3
variables significantly associated with income: maternal education, type of
housing in 2004 (i.e. house, apartment, room, shack) and building materials in
2004 (i.e. brick, adobe, wood). For children not examined in 2004, income
(n=4) and residential distance to the nearest flower plantation
(n=3) were imputed from a random selection of values generated from a
random normal distribution based on the concurrent ESPINA mean &#x000b1;
standard deviation (SD) values of the corresponding variable. We created a
&#x0201c;missing&#x0201d; race category to account for 14 children with missing
information. Because only 5 children in this study were white and 2 were black,
we incorporated these 7 children in the mestizo (mix of white and indigenous)
category to improve model stability when adjusting for race.</p></sec><sec id="S8"><title>Sensitivity Analysis</title><p id="P18">Because children examined earlier in the exam period were younger than
children examined later (<xref rid="T1" ref-type="table">Table 1</xref>), we
considered the possibility of potential for residual confounding of age after
its adjustment in our statistical models. In our participants, we previously
observed positive associations between age and AChE activity (<xref rid="R33" ref-type="bibr">Suarez-Lopez et al. 2012</xref>). We tested all
exposure-outcome associations among a randomly-selected subset of participants
with an equal distribution of age (in quartiles) across quartiles of time after
Mother&#x02019;s Day harvest as sensitivity analyses, using SAS 9.4
(&#x02018;surveyselect&#x02019; procedure). A total of 64 participants
(21%) were excluded to achieve this &#x0201c;age-balanced
subgroup&#x0201d; (n=244). The random selection of participants was
conducted using SAS 9.4 (&#x02018;surveyselect&#x02019; procedure). A total of
64 participants (21%) were excluded to achieve this
&#x0201c;age-balanced subgroup&#x0201d; (n=244).</p></sec></sec><sec sec-type="results" id="S9"><title>Results</title><sec id="S10" sec-type="intro"><title>Participant characteristics</title><p id="P19">The mean age of children at the time of assessment was 6.6 years (SD
= 1.6); 51% were male, 76% mestizo, 22%
indigenous, and 49% lived concurrently with at least one floricultural
worker. The overall mean height-for-age z-score was substantially lower than the
WHO normative sample&#x02019;s: &#x02212;1.25 (SD: 0.98). The mean AChE activity
was 3.14 U/mL (SD: 0.49) and the mean hemoglobin concentration was 12.6 g/L (SD:
1.16).</p><p id="P20">Children examined sooner after the Mother&#x02019;s Day harvest were
younger (p-trend= 0.01), had greater household income (p&#x0003c;0.01), were
more likely to live with a floricultural worker (p=0.01), and had lower
hemoglobin concentrations (p&#x0003c;0.01) than children examined later (<xref rid="T1" ref-type="table">Table 1</xref>). The age-balanced subgroup did
achieve a similar distribution of age across quartiles of time after
Mother&#x02019;s Day (p=0.59), while the distributions of other
covariates remained relatively unchanged compared to the full sample (<xref rid="T2" ref-type="table">Table 2</xref>).</p></sec><sec id="S11"><title>Time after harvest and AChE activity</title><p id="P21">The AChE difference per SD (10.8 days) of time after Mother&#x02019;s
Day harvest (&#x003b2;) was non-significant in either the complete study sample
(&#x003b2; [95% CI]: model 1= 0.02 U/ml
[&#x02212;0.02, 0.06]; R<sup>2</sup>=0.42); model 2
= 0.03 U/mL [&#x02212;0.02, 0.07];
R<sup>2</sup>=0.44) or the age-balanced subgroup (model 1= 0.02
U/ml [&#x02212;0.03, 0.06]; R<sup>2</sup>=0.38); model 2
= 0.02 U/mL [&#x02212;0.02, 0.07];
R<sup>2</sup>=0.39).</p></sec><sec id="S12"><title>Time after harvest and AChE activity: interactions with residential distance
to flower plantation</title><p id="P22">We observed significant effect modification by home distance to the
nearest flower plantation in the association between time after Mother&#x02019;s
Day harvest and AChE activity (model 1: p=0.007,
R<sup>2</sup>=0.45, model 2: p<sub>interaction</sub>=0.002,
R<sup>2</sup>= 0.46). In <xref rid="T3" ref-type="table">Table
3</xref>, we present the estimates for all covariates of model 2 including
the interaction term. In models 1 and 2, AChE activity had positive linear
associations with time after Mother&#x02019;s Day harvest among participants
living within 532 m (tertiles 1 and 2) of a flower plantation (<xref rid="F1" ref-type="fig">Figure 1</xref>). The associations were strongest among
participants living within 233m (tertile 1, &#x003b2; [95%
CI]: model 2= 0.15 U/mL [0.02, 0.28]), slightly
weaker among participants living within 234&#x02013;532m (tertile 2: model
2= 0.11 U/mL [0.00, 0.23]), and were not significantly
related among participants living at distances of 533m and greater (tertile 3,
model 2= &#x02212;0.04 U/mL [&#x02212;0.09, 0.01]).
These associations in the age-balanced subgroup were very similar.</p></sec><sec id="S13"><title>Time after harvest and AChE activity: interactions with areas of flower
plantations within 500 m of homes</title><p id="P23">We did not observe a statistically significant interaction by areas of
flower plantations within 500 m of participant&#x02019;s homes in the
association between time after Mother&#x02019;s Day harvest and AChE activity
(model 2: p<sub>interaction</sub>=0.14; R<sup>2</sup>=0.44).
Given the notable correlation between home distances to plantations and
plantation areas within 500 m of homes (r=0.41) and the theoretical
construct of drift of pesticides from plantations to homes, we stratified the
associations of areas of flower plantations within 500 m of
participant&#x02019;s homes (<xref rid="F2" ref-type="fig">Figure 2</xref>). We
observed that children who lived in homes with the highest areas of flower
plantations within 500 m of their homes (upper median split of non-zero values:
7,319&#x02013;165,279 m<sup>2</sup>) had significant positive associations
between AChE activity and time after the harvest (&#x003b2; [95%
CI] model 2: 0.24 U/mL [0.09, 0.38]). The associations
among children in the lower median split of non-zero values (0.92&#x02013;7,390
m<sup>2</sup>) were also positive and reached statistical significance in
model 1 and were borderline non-significant in model 2. No associations were
observed among children with no flower plantations within 500 m of their homes.
These associations were very similar in the age-balanced subgroup.</p></sec><sec id="S14"><title>Time after harvest and AChE activity: interactions with sex and flower worker
cohabitation</title><p id="P24">We observed no effect modification by sex or by flower worker
cohabitation in the association between time after Mother&#x02019;s Day harvest
and AChE activity.</p></sec></sec><sec sec-type="discussion" id="S15"><title>Discussion</title><p id="P25">Our findings suggest that major episodic use of sprayed pesticides of a
large floriculture industry tied to global demand for cut flowers, may have
measurable impacts on children who live in agricultural communities nearby. These
children come into contact with pesticides predominantly through off-target drift
from plantations and parental occupational take-home pathways. Pesticide drift
associated with closer residential proximity to plantations seemed of importance, as
the associations were only observed among children living within 532 m of a flower
plantation (and especially within 233 m), and were strongest with larger areas of
flower plantations within 500 m of their homes. The results of this study support
the hypothesis that children living in agricultural settings are exposed a greater
amount of cholinesterase inhibitor pesticides during high production periods, which
in turn may affect their physiological and/or developmental processes. Within this
study population, we recently reported that children who were examined sooner after
the Mother&#x02019;s Day flower harvest had lower performance in neurobehavioral
domains including attention/inhibitory control, visuospatial processing and
sensorimotor (<xref rid="R32" ref-type="bibr">Suarez-Lopez et al. 2017</xref>).</p><p id="P26">The observed associations in the present cross-sectional analyses had
important parallels with a detailed 10-month longitudinal study of 95 adolescent
agricultural workers in Egypt, which included measures during high and low exposure
seasons. Participants had multiple measurements of AChE and butyrylcholinesterase
(BChE) activity, and of 3,5,6-trichloro-2-pyridinol (TCPy), a urinary metabolite of
the organophosphate chlorpyrifos during the study period (<xref rid="R3" ref-type="bibr">Crane et al. 2013</xref>). TCPy levels increased during the
pesticide application season and decreased shortly thereafter. Consistent with these
findings, AChE and BChE activity decreased during the pesticide application season,
and increased after the end of the application period. The recovery of AChE and BChE
activity continued through 180 days after the end of the application period. This
association remained for longer than the average time of the normalization of AChE
levels after irreversible inhibition with organophosphate exposures previously
described among agricultural workers (mean 82 days, 95% confidence interval:
72&#x02013;98 days) (<xref rid="R21" ref-type="bibr">Mason 2000</xref>). This may be
explained by small renewing (background) pesticide exposures present in the
environment. In our study, the positive association between time and AChE activity
continued through 100 days after the harvest among participants living within 532 m
of a plantation. A longer examination window in our study may have been needed to
observe a plateau in the association which would mark the end of the apparent AChE
&#x0201c;recovery&#x0201d; (we are not able to assess true recovery with
cross-sectional data).</p><p id="P27">There are few existing studies that have assessed the effects of high
pesticide spray seasons on the exposures of children who do not work in agriculture.
Among non-agricultural worker adolescents in Egypt (n=38), elevated urinary
markers of organophosphate and depressions of AChE and BChE activity were observed
during the pesticide spray season compared to baseline (<xref rid="R3" ref-type="bibr">Crane et al. 2013</xref>). A study of children living in an
agricultural area in Washington State, USA, observed greater urinary metabolite
concentrations of organophosphates during high-spray compared to low-spray seasons
among children who lived with an agricultural worker. (<xref rid="R35" ref-type="bibr">Thompson et al. 2014</xref>). Both of these studies concur with
our findings. However, in the latter study, these associations were not observed
among children who did not live with agricultural workers. Contrary to our
expectation, in our study, we did not observe differences in the associations
between time after Mother&#x02019;s Day harvest and AChE activity between children
living with a flower plantation worker (n=152) compared to children living
with non-agricultural workers (n=156). This suggests that the rate of
introduction of pesticides into the homes by flower plantation worker (e.g. bringing
pesticide contaminated clothing, tools, etc. into the home) does not increase during
peak exposure periods in amounts to affect AChE activity. Also, discrepant with our
findings, a study of non-agricultural worker adults and children living near
agricultural farms in the United Kingdom did not find differences in urinary
pesticide metabolites between the low and high pesticide spray seasons (<xref rid="R9" ref-type="bibr">Galea et al. 2015</xref>). Differing findings likely
reflect differences in the selection of exposure assessment used (urinary
metabolites vs AChE), and agricultural pesticide use and practices amongst different
crops and countries.</p><p id="P28">Proximity of homes to plantations and greater areas of flower plantations
near participants&#x02019; homes were important pathways of children&#x02019;s
exposure in relation to time after the spray season. Greater proximity of homes to
agricultural crops has been positively associated with greater pesticide exposures
among adults and children not directly involved in agriculture (<xref rid="R14" ref-type="bibr">Keifer et al. 1996</xref>; <xref rid="R37" ref-type="bibr">Ward
et al. 2006</xref>; <xref rid="R2" ref-type="bibr">Coronado et al. 2011</xref>).
Within our study, the associations across strata of areas of flower plantations
within 500 m of participants&#x02019; homes mirrored those across strata of home
distances to the nearest flower plantations. The congruence of the findings across
strata of these related but different constructs of potential drift of pesticides
from plantations strengthens our findings. Area of flower plantations within 500 m
of homes is likely a better predictor of drift than home distances to the nearest
flower plantation because it implicitly accounts for areas of plantations that could
be potentially fumigated with pesticides. The associations between home distances to
flower plantations and areas of flower plantations in relation to AChE activity
within our cohort is a separate topic of analysis.</p><p id="P29">While children in our study did not work in agriculture, our findings are
coherent with various studies of agricultural workers (mostly adult) demonstrating
that pesticide spray periods are associated with increased pesticide exposure
biomarkers, including cholinesterase depression (<xref rid="R24" ref-type="bibr">Peiris-John et al. 2005</xref>; <xref rid="R3" ref-type="bibr">Crane et al.
2013</xref>; <xref rid="R31" ref-type="bibr">Strelitz et al. 2014</xref>; <xref rid="R16" ref-type="bibr">Krenz et al. 2015</xref>; <xref rid="R30" ref-type="bibr">Singleton et al. 2015</xref>; <xref rid="R26" ref-type="bibr">Quandt et al. 2015</xref>).</p><p id="P30">The main limitation of this study is that participants were only examined
once, which precludes us from assessing actual <italic>change</italic> in AChE
activity between pre-pesticide application, application and post-application
periods. Conducting exposure assessments at all three periods is difficult in this
population because the heightened pesticide use periods start at approximately
October/November and remain high until early May. The cross-sectional design of our
study allowed us to estimate the associations of time after the harvest with AChE
activity while avoiding to inflict multiple blood draws to this group of young
children. Additionally, we do not have quantification of pesticide levels from
bio-specimens to determine which specific cholinesterase inhibitors or other
pesticides are entering children&#x02019;s bodies. Yet, the carbamate and
organophosphate pesticides reported to be used by flower plantations in Pedro
Moncayo are reasonably some of the cholinesterase inhibitors we would expect to find
in children of our study. As compared to measurements of pesticides or pesticide
metabolites in body fluids, AChE activity is less sensitive to low-level exposures.
However, it is a low-cost well-established marker of exposure that reflects a
physiological change associated with cholinesterase inhibitor exposures. It is also
a more stable (lower within individual variability) indicator of cholinesterase
inhibitor exposure (<xref rid="R17" ref-type="bibr">Lefkowitz et al. 2007</xref>;
<xref rid="R11" ref-type="bibr">Griffith et al. 2011</xref>; <xref rid="R1" ref-type="bibr">Bradman et al. 2013</xref>) and provides a much wider exposure
window than bio-specimen quantification. Within the ESPINA study, we have found that
children&#x02019;s AChE activity was inversely associated with cohabitation with
floricultural workers, duration of cohabitation and with greater number of pesticide
&#x0201c;take-home&#x0201d; pathways, which provides some evidence of the use of
AChE to assess low-dose pesticide exposures (<xref rid="R33" ref-type="bibr">Suarez-Lopez et al. 2012</xref>).</p><p id="P31">This is one of the largest studies to date to estimate pesticide exposures
in children in relation to a known pesticide exposure period. Our sample size
allowed us to detect effect modification by distances of homes to plantations in
this context for the first time. The high participation rates and fast recruitment
and examination of participants of our study was possible due to the
well-established partnerships and ongoing community-based participatory practices
between our investigators at Fundacion Cimas del Ecuador and communities of Pedro
Moncayo County. Although this study was not designed to specifically assess AChE
change after a known heightened exposure period, our approach allowed us to obtain
AChE values at 20 points in time within 100 days from Mother&#x02019;s Day harvest,
averaging 15 participants per time point. This allowed us to have detailed
approximations of seasonal changes in AChE activity, albeit with cross-sectional
data. The limited number of investigations that have assessed the effects of
pesticide spray seasons on the exposure of non-agricultural worker children living
in agricultural communities raises the need to conduct more investigations assessing
exposures at multiple points in time before and after the spray seasons of various
types of crops.</p><sec id="S16" sec-type="conclusions"><title>Conclusion</title><p id="P32">This study provides additional evidence that heightened pesticide usage
periods can increase pesticide exposures, as reflected by physiological
alterations in AChE activity, among children who do not work in agriculture but
live within approximately 500m of a flower plantation. Our study, though based
on cross-sectional information, contrasted the AChE activity of a relatively
large sample of children across a 1-month exposure window, within 100 days after
the Mother&#x02019;s Day harvest. The findings of our study highlights the
potential impact of globalization and trade on exposures to people living near
flower plantations. Mother&#x02019;s Day is a time to acknowledge the importance
of mothers in our societies, and the gift of flowers has become an important
component of these celebrations. The heightened demand of flowers is important
for the floriculture industry; unfortunately, it is also an important source of
heightened pesticide exposures affecting not only its workers, but also children
living near plantations. These heightened seasonal pesticide exposures are of
concern as they can decrease the neurobehavioral performance of children, and
may induce short- and long-term physiological and developmental alterations.</p></sec></sec></body><back><ack id="S17"><p>We thank Dr. Jose Suarez Torres, Dolores Lopez Paredes and Fundaci&#x000f3;n Cimas
del Ecuador for providing the infrastructure, logistical support, access to the
Local and Community Information System and their long history of collaboration with
Pedro Moncayo County communities; all of which were key to the success of this
study. We also thank the Tabacundo Health Center of the Ministry of Public Health of
Ecuador, for their assistance, and especially the people of Pedro Moncayo County and
their local governments for their collaboration and support of this project.</p><p><bold>Funding Sources:</bold> Research reported in this publication was supported by
the National Institute of Occupational Safety and Health (1R36OH009402-01), and the
National Institute of Environmental Health Sciences of the National Institutes of
Health (grants R01ES025792-01, R21ES026084-01). The content is solely the
responsibility of the authors and does not necessarily represent the official views
of the National Institutes of Health, National Institute of Occupational Safety and
Health</p></ack><fn-group><fn id="FN2"><p><italic>Ethical approval:</italic> All procedures performed in studies involving
human participants were in accordance with the ethical standards of the
institutional and/or national research committee and with the 1964 Helsinki
declaration and its later amendments or comparable ethical standards.</p></fn><fn fn-type="COI-statement" id="FN3"><p><italic>Conflict of Interest:</italic> The authors declare that they have no
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Mother&#x02019;s Day harvest, by tertiles of home distance to the nearest flower
plantation<sup>a</sup>.</p><p>The depicted regression lines correspond to model 2 including all participants
stratified by tertiles. Diamonds are adjusted means of AChE activity</p><p><sup>a</sup>Interaction with home distance to the nearest flower plantation:
P<sub>model 2</sub>=0.002</p><p><sup>b</sup>SD: 10.8 days</p><p>Model 1 adjustments: age, sex, race and hemoglobin concentration.</p><p>Model 2 adjustments: age, sex, race, hemoglobin concentration, height-for-age
z-score, income and flower worker cohabitation status.</p></caption><graphic xlink:href="nihms912813f1"/></fig><fig id="F2" orientation="portrait" position="float"><label>Figure 2</label><caption><p>Children&#x02019;s acetylcholinesterase (AChE) activity in relation to
Mother&#x02019;s Day harvest, by categories of areas of flower plantations
within 500m of participants&#x02019; homes<sup>a</sup>.</p><p>The depicted regression lines correspond to model 2 including all participants
stratified by 3 categories. Diamonds are adjusted means of AChE activity.</p><p><sup>a</sup>Interaction with areas of flower plantations within 500m of homes:
P<sub>model 2</sub>=0.14</p><p><sup>b</sup>Median split of non-zero values</p><p><sup>c</sup>SD: 10.8 days</p><p>Model 1 adjustments: age, sex, race and hemoglobin concentration.</p><p>Model 2 adjustments: age, sex, race, hemoglobin concentration, height-for-age
z-score, income and flower worker cohabitation status.</p></caption><graphic xlink:href="nihms912813f2"/></fig><table-wrap id="T1" position="float" orientation="landscape"><label>Table 1</label><caption><p>Participant characteristics by exam date. N=308</p></caption><table frame="void" rules="none"><thead><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th colspan="5" valign="bottom" align="center" rowspan="1">Days after Mother&#x02019;s
Day harvest (quartiles)</th></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th colspan="5" valign="bottom" align="center" rowspan="1">
<hr/></th></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th valign="bottom" align="center" rowspan="1" colspan="1">1<sup>st</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">2<sup>nd</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">3<sup>rd</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">4<sup>th</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">P-trend</th></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1">N</th><th valign="bottom" align="center" rowspan="1" colspan="1">77</th><th valign="bottom" align="center" rowspan="1" colspan="1">77</th><th valign="bottom" align="center" rowspan="1" colspan="1">77</th><th valign="bottom" align="center" rowspan="1" colspan="1">77</th><th valign="bottom" align="center" rowspan="1" colspan="1"/></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1">Range (days)</th><th valign="bottom" align="center" rowspan="1" colspan="1">63.4&#x02013;76.5</th><th valign="bottom" align="center" rowspan="1" colspan="1">76.6&#x02013;84.5</th><th valign="bottom" align="center" rowspan="1" colspan="1">84.6&#x02013;95.4</th><th valign="bottom" align="center" rowspan="1" colspan="1">95.5&#x02013;99.6</th><th valign="bottom" align="center" rowspan="1" colspan="1"/></tr></thead><tbody><tr><td colspan="6" align="left" valign="top" rowspan="1"><bold>Demographic and
socio-economic status</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Age, years</td><td align="center" valign="top" rowspan="1" colspan="1">6.3 (1.5)</td><td align="center" valign="top" rowspan="1" colspan="1">6.5 (1.4)</td><td align="center" valign="top" rowspan="1" colspan="1">6.8 (1.7)</td><td align="center" valign="top" rowspan="1" colspan="1">6.8 (1.7)</td><td align="center" valign="top" rowspan="1" colspan="1">0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Sex, male</td><td align="center" valign="top" rowspan="1" colspan="1">49%</td><td align="center" valign="top" rowspan="1" colspan="1">52%</td><td align="center" valign="top" rowspan="1" colspan="1">55%</td><td align="center" valign="top" rowspan="1" colspan="1">49%</td><td align="center" valign="top" rowspan="1" colspan="1">0.93</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Race, mestizo</td><td align="center" valign="top" rowspan="1" colspan="1">86%</td><td align="center" valign="top" rowspan="1" colspan="1">63%</td><td align="center" valign="top" rowspan="1" colspan="1">59%</td><td align="center" valign="top" rowspan="1" colspan="1">96%</td><td align="center" valign="top" rowspan="1" colspan="1">0.87</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Race, indigenous</td><td align="center" valign="top" rowspan="1" colspan="1">11%</td><td align="center" valign="top" rowspan="1" colspan="1">36%</td><td align="center" valign="top" rowspan="1" colspan="1">37%</td><td align="center" valign="top" rowspan="1" colspan="1">4%</td><td align="center" valign="top" rowspan="1" colspan="1">0.79</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Monthly household income <xref rid="TFN2" ref-type="table-fn">a</xref></td><td align="center" valign="top" rowspan="1" colspan="1">3.1 (0.9)</td><td align="center" valign="top" rowspan="1" colspan="1">3.6 (0.7)</td><td align="center" valign="top" rowspan="1" colspan="1">3.0 (0.6)</td><td align="center" valign="top" rowspan="1" colspan="1">2.7 (0.8)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Home distance to nearest flower
plantation, m</td><td align="center" valign="top" rowspan="1" colspan="1">584.0 (458)</td><td align="center" valign="top" rowspan="1" colspan="1">293.6 (207)</td><td align="center" valign="top" rowspan="1" colspan="1">402.0 (299)</td><td align="center" valign="top" rowspan="1" colspan="1">501.5 (288)</td><td align="center" valign="top" rowspan="1" colspan="1">0.18</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Area of flower plantation within 500m
of residence (m<sup>2</sup>)</td><td align="center" valign="top" rowspan="1" colspan="1">1880 (0, 24650)</td><td align="center" valign="top" rowspan="1" colspan="1">3239(1056, 15190)</td><td align="center" valign="top" rowspan="1" colspan="1">1797(0, 14264)</td><td align="center" valign="top" rowspan="1" colspan="1">0(0, 1470)</td><td align="center" valign="top" rowspan="1" colspan="1">0.22</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Flower worker cohabitation</td><td align="center" valign="top" rowspan="1" colspan="1">53%</td><td align="center" valign="top" rowspan="1" colspan="1">71%</td><td align="center" valign="top" rowspan="1" colspan="1">30%</td><td align="center" valign="top" rowspan="1" colspan="1">43%</td><td align="center" valign="top" rowspan="1" colspan="1">0.01</td></tr><tr><td colspan="6" align="left" valign="top" rowspan="1"><bold>Anthropometry</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Height-for-age z-score, SD</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.06 (0.75)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.45 (1.04)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.38 (0.94)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.07 (1.03)</td><td align="center" valign="top" rowspan="1" colspan="1">0.98</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Hemoglobin, g/L</td><td align="center" valign="top" rowspan="1" colspan="1">12.19 (1.26)</td><td align="center" valign="top" rowspan="1" colspan="1">12.71 (.96)</td><td align="center" valign="top" rowspan="1" colspan="1">12.62 (1.19)</td><td align="center" valign="top" rowspan="1" colspan="1">13.06 (0.04)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr></tbody></table><table-wrap-foot><fn id="TFN1"><p>Table entries are percentage, mean (SD) or median (25<sup>th</sup>,
75<sup>th</sup> percentile)</p></fn><fn id="TFN2"><label>a</label><p>Monthly income categories (USD): 1=0&#x02013;50,
2=51&#x02013;150, 3=151&#x02013;300,
4=301&#x02013;500, 5=501&#x02013;1000,
6=&#x0003e;1000</p></fn></table-wrap-foot></table-wrap><table-wrap id="T2" position="float" orientation="landscape"><label>Table 2</label><caption><p>Participant characteristics by exam date among a random subset of participants
with similar distributions of age across days after Mother&#x02019;s Day
harvest. N=244</p></caption><table frame="void" rules="none"><thead><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th colspan="5" valign="bottom" align="center" rowspan="1">Days after Mother&#x02019;s
Day harvest (quartiles)</th></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th colspan="5" valign="bottom" align="center" rowspan="1">
<hr/></th></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th valign="bottom" align="center" rowspan="1" colspan="1">1<sup>st</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">2<sup>nd</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">3<sup>rd</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">4<sup>th</sup></th><th valign="bottom" align="center" rowspan="1" colspan="1">P-trend</th></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1">N</th><th valign="bottom" align="center" rowspan="1" colspan="1">61</th><th valign="bottom" align="center" rowspan="1" colspan="1">61</th><th valign="bottom" align="center" rowspan="1" colspan="1">61</th><th valign="bottom" align="center" rowspan="1" colspan="1">61</th><th valign="bottom" align="center" rowspan="1" colspan="1"/></tr><tr><th valign="bottom" align="left" rowspan="1" colspan="1">Range (days)</th><th valign="bottom" align="center" rowspan="1" colspan="1">63.4&#x02013;76.5</th><th valign="bottom" align="center" rowspan="1" colspan="1">76.6&#x02013;84.7</th><th valign="bottom" align="center" rowspan="1" colspan="1">84.8&#x02013;95.4</th><th valign="bottom" align="center" rowspan="1" colspan="1">95.5&#x02013;99.6</th><th valign="bottom" align="center" rowspan="1" colspan="1"/></tr></thead><tbody><tr><td colspan="6" align="left" valign="top" rowspan="1"><bold>Demographic and
socio-economic status</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Age, years</td><td align="center" valign="top" rowspan="1" colspan="1">6.5 (1.5)</td><td align="center" valign="top" rowspan="1" colspan="1">6.5 (1.6)</td><td align="center" valign="top" rowspan="1" colspan="1">6.9 (1.7)</td><td align="center" valign="top" rowspan="1" colspan="1">6.4 (1.5)</td><td align="center" valign="top" rowspan="1" colspan="1">0.59</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Sex, male</td><td align="center" valign="top" rowspan="1" colspan="1">43%</td><td align="center" valign="top" rowspan="1" colspan="1">46%</td><td align="center" valign="top" rowspan="1" colspan="1">54%</td><td align="center" valign="top" rowspan="1" colspan="1">43%</td><td align="center" valign="top" rowspan="1" colspan="1">0.96</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Race, mestizo</td><td align="center" valign="top" rowspan="1" colspan="1">85%</td><td align="center" valign="top" rowspan="1" colspan="1">57%</td><td align="center" valign="top" rowspan="1" colspan="1">61%</td><td align="center" valign="top" rowspan="1" colspan="1">95%</td><td align="center" valign="top" rowspan="1" colspan="1">0.93</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Race, indigenous</td><td align="center" valign="top" rowspan="1" colspan="1">13%</td><td align="center" valign="top" rowspan="1" colspan="1">42%</td><td align="center" valign="top" rowspan="1" colspan="1">35%</td><td align="center" valign="top" rowspan="1" colspan="1">5%</td><td align="center" valign="top" rowspan="1" colspan="1">0.97</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Monthly household income <xref rid="TFN4" ref-type="table-fn">a</xref></td><td align="center" valign="top" rowspan="1" colspan="1">3.2 (0.9)</td><td align="center" valign="top" rowspan="1" colspan="1">3.5 (0.6)</td><td align="center" valign="top" rowspan="1" colspan="1">3.0 (0.6)</td><td align="center" valign="top" rowspan="1" colspan="1">2.8 (0.9)</td><td align="center" valign="top" rowspan="1" colspan="1">0.03</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Home distance to nearest flower
plantation, m</td><td align="center" valign="top" rowspan="1" colspan="1">586 (466)</td><td align="center" valign="top" rowspan="1" colspan="1">297 (217)</td><td align="center" valign="top" rowspan="1" colspan="1">405 (327)</td><td align="center" valign="top" rowspan="1" colspan="1">529 (288)</td><td align="center" valign="top" rowspan="1" colspan="1">0.45</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Area of flower plantation within 500m
of residence (m<sup>2</sup>)</td><td align="center" valign="top" rowspan="1" colspan="1">6089 (0, 50058)</td><td align="center" valign="top" rowspan="1" colspan="1">3239(1012, 15190)</td><td align="center" valign="top" rowspan="1" colspan="1">2562(0, 14443)</td><td align="center" valign="top" rowspan="1" colspan="1">0(0, 1092)</td><td align="center" valign="top" rowspan="1" colspan="1">0.08</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Flower worker cohabitation</td><td align="center" valign="top" rowspan="1" colspan="1">51%</td><td align="center" valign="top" rowspan="1" colspan="1">84%</td><td align="center" valign="top" rowspan="1" colspan="1">26%</td><td align="center" valign="top" rowspan="1" colspan="1">46%</td><td align="center" valign="top" rowspan="1" colspan="1">0.02</td></tr><tr><td colspan="6" align="left" valign="top" rowspan="1"><bold>Anthropometry</bold></td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Height-for-age z-score, SD</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.06 (0.77)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.60 (1.13)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.36 (0.88)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x02212;1.07 (1.02)</td><td align="center" valign="top" rowspan="1" colspan="1">0.70</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">&#x02003;Hemoglobin, g/L</td><td align="center" valign="top" rowspan="1" colspan="1">12.13 (1.19)</td><td align="center" valign="top" rowspan="1" colspan="1">12.79 (1.03)</td><td align="center" valign="top" rowspan="1" colspan="1">12.64 (1.26)</td><td align="center" valign="top" rowspan="1" colspan="1">13.03 (0.91)</td><td align="center" valign="top" rowspan="1" colspan="1">&#x0003c;0.01</td></tr></tbody></table><table-wrap-foot><fn id="TFN3"><p>Table entries are percentage or mean (SD)</p></fn><fn id="TFN4"><label>a</label><p>Monthly income categories (USD): 1=0&#x02013;50,
2=51&#x02013;150, 3=151&#x02013;300,
4=301&#x02013;500, 5=501&#x02013;1000,
6=&#x0003e;1000</p></fn></table-wrap-foot></table-wrap><table-wrap id="T3" position="float" orientation="landscape"><label>Table 3</label><caption><p>Linear regression estimates of model 2 covariates in relation to AChE activity,
including the interaction term between time after the Mother&#x02019;s Day
harvest and distances of homes to the nearest flower plantation.</p></caption><table frame="void" rules="none"><thead><tr><th valign="bottom" align="left" rowspan="1" colspan="1"/><th valign="bottom" align="left" rowspan="1" colspan="1">Estimate (&#x003b2;)</th><th valign="bottom" align="left" rowspan="1" colspan="1">95% CI</th></tr></thead><tbody><tr><td align="left" valign="top" rowspan="1" colspan="1">Time after Mother&#x02019;s Day (per 10.8
days)</td><td align="left" valign="top" rowspan="1" colspan="1">0.156</td><td align="left" valign="top" rowspan="1" colspan="1">(0.066, 0.247)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Residential distance to the nearest flower
plantation (per 100 m)</td><td align="left" valign="top" rowspan="1" colspan="1">0.159</td><td align="left" valign="top" rowspan="1" colspan="1">(0.071, 0.247)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Time after Mother&#x02019;s Day *
Residential distance to nearest flower plantation (interaction
term)</td><td align="left" valign="top" rowspan="1" colspan="1">&#x02212;0.019</td><td align="left" valign="top" rowspan="1" colspan="1">(&#x02212;0.030, &#x02212;0.007)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Male gender</td><td align="left" valign="top" rowspan="1" colspan="1">0.054</td><td align="left" valign="top" rowspan="1" colspan="1">(&#x02212;0.028, 0.137)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Cohabitation with a flower worker (vs
not)</td><td align="left" valign="top" rowspan="1" colspan="1">&#x02212;0.021</td><td align="left" valign="top" rowspan="1" colspan="1">(&#x02212;0.107, 0.064)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Age (per year)</td><td align="left" valign="top" rowspan="1" colspan="1">0.037</td><td align="left" valign="top" rowspan="1" colspan="1">(0.010, 0.065)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Height-for-age z-score (per SD)</td><td align="left" valign="top" rowspan="1" colspan="1">0.028</td><td align="left" valign="top" rowspan="1" colspan="1">(&#x02212;0.017, 0.074)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Income (per category <xref rid="TFN5" ref-type="table-fn">a</xref>)</td><td align="left" valign="top" rowspan="1" colspan="1">0.041</td><td align="left" valign="top" rowspan="1" colspan="1">(&#x02212;0.014, 0.095)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Indigenous race (vs not)</td><td align="left" valign="top" rowspan="1" colspan="1">0.042</td><td align="left" valign="top" rowspan="1" colspan="1">(&#x02212;0.061, 0.145)</td></tr><tr><td align="left" valign="top" rowspan="1" colspan="1">Hemoglobin (per mg/dL)</td><td align="left" valign="top" rowspan="1" colspan="1">0.252</td><td align="left" valign="top" rowspan="1" colspan="1">(0.213, 0.291)</td></tr></tbody></table><table-wrap-foot><fn id="TFN5"><label>a</label><p>Monthly income categories (USD): 1=0&#x02013;50,
2=51&#x02013;150, 3=151&#x02013;300,
4=301&#x02013;500, 5=501&#x02013;1000,
6=&#x0003e;1000</p></fn><fn id="TFN6"><p>Intercept: &#x02212;1.696 (95% CI: &#x02212;2.584,
&#x02212;0.807)</p></fn><fn id="TFN7"><p>Equation: <inline-formula><mml:math id="M1" display="inline" overflow="scroll"><mml:mrow><mml:mtext>AChE</mml:mtext><mml:mo>=</mml:mo><mml:mtext>intercept</mml:mtext><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>time</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>after</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>mother</mml:mtext><mml:mo>'</mml:mo><mml:mi mathvariant="normal">s</mml:mi><mml:mspace width="0.16667em"/><mml:mtext>day</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>residential</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>distance</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>to</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>the</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>nearest</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>flower</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>plantation</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>Time</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>after</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>Mother</mml:mtext><mml:mo>'</mml:mo><mml:mi mathvariant="normal">s</mml:mi><mml:mspace width="0.16667em"/><mml:mtext>Day</mml:mtext><mml:mo>&#x02217;</mml:mo><mml:mtext>residential</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>distance</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>to</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>the</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>nearest</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>flower</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>plantation</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>male</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>flower</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>worker</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>cohabitation</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>age</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>height-for-age</mml:mtext><mml:mspace width="0.16667em"/><mml:mtext>z-score</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>income</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>indigenous</mml:mtext><mml:mo stretchy="false">)</mml:mo><mml:mo>+</mml:mo><mml:mi mathvariant="normal">&#x003b2;</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mtext>hemoglobin</mml:mtext><mml:mo stretchy="false">)</mml:mo></mml:mrow></mml:math></inline-formula>.</p></fn></table-wrap-foot></table-wrap></floats-group></article>