R E S EARCH Open Access

Rapidly measured indicators of recreational water

quality and swimming-associated illness at

marine beaches: a prospective cohort study

Timothy J Wade1*, Elizabeth Sams1, Kristen P Brenner2, Richard Haugland2, Eunice Chern2, Michael Beach3,

Larry Wymer2

, Clifford C Rankin2, David Love4, Quanlin Li1, Rachel Noble5, Alfred P Dufour2

Abstract

Introduction: In the United States and elsewhere, recreational water quality is monitored for fecal indicator

bacteria to help prevent swimming-associated illnesses. Standard methods to measure these bacteria take at least

24 hours to obtain results. Molecular approaches such as quantitative polymerase chain reaction (qPCR) can

estimate these bacteria faster, in under 3 hours. Previously, we demonstrated that measurements of the fecal

indicator bacteria Enterococcus using qPCR were associated with gastrointestinal (GI) illness among swimmers at

freshwater beaches. In this paper, we report on results from three marine beach sites.

Methods: We interviewed beach-goers and collected water samples at marine beaches affected by treated sewage

discharges in Mississippi in 2005, and Rhode Island and Alabama in 2007. Ten to twelve days later, we obtained

information about gastrointestinal, respiratory, eye, ear and skin symptoms by telephone. We tested water samples

for fecal indicator organisms using qPCR and other methods.

Results: We enrolled 6,350 beach-goers. The occurrence of GI illness among swimmers was associated with a

log10-increase in exposure to qPCR-determined estimates of fecal indicator organisms in the genus Enterococcus

(AOR = 2.6, 95% CI 1.3-5.1) and order Bacteroidales (AOR = 1.9, 95% CI 1.3-2.9). Estimates of organisms related to

Clostridium perfringens and a subgroup of organisms in the genus Bacteroides were also determined by qPCR in

2007, as was F+ coliphage, but relationships between these indicators and illness were not statistically significant.

Conclusions: This study provides the first evidence of a relationship between gastrointestinal illness and estimates

of fecal indicator organisms determined by qPCR at marine beaches.

Background

It is usually impractical to test recreational waters

directly for the many and diverse pathogenic microorganisms associated with human derived sewage. As a

result, recreational waters are often monitored for fecal

indicator bacteria. Fecal indicator bacteria such as Enterococcus spp. or Escherichia coli are ordinarily harmless

microbes that are commonly found in sewage and other

sources of fecal contamination [1]. These fecal indicator

bacteria have been statistically associated with gastrointestinal (GI) illness in recreational waters [2,3]. Standard

methods for measuring water quality involve growing

fecal indicator bacteria in culture which requires at least

24 hours and may result in incorrect assessments of

water quality by beach managers and regulators [4].

Molecular methods, such as quantitative polymerase

chain reaction (qPCR), have the ability to detect fecal

indicator organisms much faster by targeting and measuring specific genetic markers [5]. We previously

demonstrated that the fecal indicator bacteria Enterococcus spp. estimated by qPCR was well-associated with

gastrointestinal illness among swimmers at freshwater

beaches [6,7].

Previous studies found different associations between

fecal indicator bacteria measured by culture and swimming-associated illness in marine and fresh waters [8,9],

* Correspondence: wade.tim@epa.gov

1

United States Environmental Protection Agency, National Health and

Environmental Effects Research Laboratory, Research Triangle Park, North

Carolina, USA

Full list of author information is available at the end of the article

Wade et al. Environmental Health 2010, 9:66

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© 2010 Wade et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons

Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in

any medium, provided the original work is properly cited.
possibly due to differences in the fate and transport of

indicator and pathogenic microorganisms [8,10,11]. In

this report, we extend our research to three marine beaches in the continental United States where we examine

the relationships between swimming-associated illnesses

and fecal indicator bacteria determined by alternative

rapid methods.

Methods

Beach sites and health survey

We conducted studies at three marine beaches affected

by treated sewage discharge from nearby Publicly

Owned Treatment Works (POTW). In 2005, we studied

Edgewater Beach in Biloxi, Mississippi, and in 2007 we

studied Goddard Beach in Goddard Memorial State

Park in West Warwick, Rhode Island and Fairhope

Municipal Beach in Fairhope, Alabama (Figure 1). Each

beach site was located within 7 miles or less of a treated

sewage discharge outfall from facilities that served

populations of at least 15,000. Based on historical

records, each beach site showed variability in water

quality, but were generally in compliance with local and

federal water quality guidelines.

Data collection procedures for the health survey have

been described previously [6,7]. In brief, we conducted

surveys on weekends and holidays between May and

September. Upon arrival beachgoers were provided a

pamphlet describing the study. After reviewing the

pamphlet, interviewers approached the household group

or individual and offered them the opportunity to enroll

in the study. On most days, all beachgoers arriving

between approximately 11 AM and 4 PM were offered

enrollment. Respondents were ineligible if they had

completed the study in the previous 30 days, or if there

was no adult (18 years of age or older) household member present. Households provided verbal consent and

completed an enrollment questionnaire consisting of

demographic information, swimming exposures in the

Figure 1 Marine beach sites.

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previous two weeks, and the presence of underlying

health conditions, such as chronic diarrhea, asthma, or

skin conditions. As they left the beach for the day, participants completed a questionnaire to ascertain the

extent and duration of their contact with water and

other activities during their visit to the beach such as

contact with sand and food consumption. Ten to twelve

days following the beach visit, we telephoned participants and asked about the occurrence of new gastrointestinal, skin, respiratory, eye, or ear symptoms.

The study procedures, questionnaires, protocols and

consent process were reviewed and approved by the

Institutional Review Board of the Centers for Disease

Control and Prevention.

Illness definitions

We considered the following health endpoints consistent

with those we previously reported [6,7].

“Gastrointestinal illness” (GI illness) was defined as

any of the following: (1) diarrhea (three or more loose

stools in a 24-hour period); (2) vomiting; (3) nausea and

stomachache; (4) nausea or stomachache, and interference with regular activities (missed regular activities as a

result of the illness).

“Upper respiratory illness” (URI) was defined as any

2 of the following: sore throat, cough, runny nose, cold,

or fever.

“Rash” was defined as a rash or itchy skin.

“Eye irritations” were defined as either eye infection

or watery eye.

“Earache” was defined as earache, ear infection, or

runny ears.

Diarrhea was also considered as a stand alone outcome because it is a commonly used definition of gastroenteritis in population-based surveillance [12,13].

Participants ill within 3 days before their beach visit

were excluded from analysis of the health outcome

related to their baseline symptoms.

Water sample collection and analysis

Protocols used for water sample collection have been

described [5]. Briefly, we collected two 1-liter water samples at 8:00 AM, 11:00 AM, and 3:00 PM along 3 transects

perpendicular to the shoreline. At each transect, we collected one sample in waist-high water (1 m deep) and one

in shin-high water (0.3 m deep). Transects were located at

least 60 m apart and encompassed the swimming area.

Following collection, samples were placed in coolers and

maintained on ice at 1 to 4°C. At each water sampling

time we recorded environmental conditions, including air

and water temperature, cloud cover, rainfall, wind speed

and direction, wave height, number of people (on the

beach and in the water), boats, animals (number and type,

on the beach and in the water), tide stage, and debris.

Water samples were tested for total Enterococcus

spp. [5] and total Bacteroidales spp. [14], hereafter

referred to as Enterococcus and Bacteroidales respectively, by qPCR using previously published protocols

[5,14]. In 2007, we added qPCR tests for subgroups of

Bacteroides [15], and Clostridium spp. or “Clostridium

perfringens group” [16], hereafter referred to as “fecal

Bacteroides” and “Clostridium”, respectively. In 2007, we

also included a novel, faster test for F+ (male-specific)

coliphage based on a culture and latex agglutination

assay (CLAT assay), which also distinguishes F+ RNA

coliphage and F+ DNA coliphage [17]. F+ coliphage was

also evaluated using a 24-hour spot test according to

EPA Method 1601 [18]. Samples were also tested for

Enterococcus spp. using EPA Method 1600 [19], a culture-based method. Results for Enterococcus measured

by EPA Method 1600 are reported in colony forming

units (CFU) per 100 ml sample and for F+ coliphage in

most probable number (MPN) per 100 ml. Samples for

EPA Method 1600 and qPCR analysis were filtered

within 6 hours of collection. The filters were held at

-20°C and shipped overnight to EMSL Analytical (Westmount NJ) on dry ice where DNA extraction and qPCR

analyses for Enterococcus, Bacteroidales and fecal Bacteroides were conducted. Frozen DNA extracts were

sent from EMSL Analytical to the US EPA in Cincinnati

where qPCR analysis was conducted for Clostridium.

Primer and probe sequences used for the Enterococcus

[5], Bacteroidales [14] and fecal Bacteroides [15] qPCR

assays were described previously. Primers used for the

amplification of Clostridium were those of the “Clostridium perfringens group” assay targeting about 34 Clostridium species as reported by Rinttilä et. al. [16].

Additional details regarding sample processing, DNA

extraction and reaction conditions for qPCR analyses,

are provided in additional file 1. In brief, following filtration, DNA was extracted, and polymerase chain reaction

(PCR) amplification was carried out using the TaqMan

PCR product detection system. The reactions were performed in a thermal cycling instrument (Smart-Cycler

System, Cepheid, Sunnyvale, CA) except for Clostridium

which was performed on a Model 7900 DNA thermal

cycler (Applied Biosystems, Foster City, CA). Both

instruments automated the detection and quantitative

measurement of the fluorescent signals produced by

TaqMan probe degradation during each cycle of

amplification.

PCR cycle threshold (CT) measurements of the test

sample DNA extracts were compared with those of

similarly prepared extracts from calibrator samples containing a known quantity of the target organism cells.

Ratios of the target sequences in the test and calibrator

samples were converted to estimates of calibrator

cell equivalents (CCE) in the test samples [20]. PCR

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measurements of salmon testes DNA, that was added to

the extraction buffer as a source of reference target

sequences, were used to estimate the relative efficiency

of total DNA recovery from the water sample filters

compared to the calibrator samples and to identify

potential PCR inhibition [21]. Five-fold dilutions of the

water filter and calibration sample extracts were analyzed and water filter extracts giving salmon DNA assay

CT values that were > 3 CT units higher than the mean

values from the calibration extracts were reanalyzed

after additional 5-fold dilutions. If both dilutions failed

the salmon CT criterion, the sample was excluded and

results were replaced with mean of valid samples collected at the same location, depth and time. Salmon

DNA assays were performed in separate reaction tubes.

Quantitation of fecal indicator bacteria by qPCR

Two basic approaches were used to quantify CCE: “delta

delta-CT” (CCEΔΔ ) [5-7,14], and “delta-CT” (CCE) [14].

CCE values were determined using only test sample and

batch-mean calibration sample target organism assay

CT values (CCEΔ) and also after corrections using CT

values from the salmon reference assays (CCEΔΔ

method). See previously published manuscripts [5,14,22]

and additional file 1 for a discussion and description of

these calculations. The CCEΔΔ calculation provides

quantitative adjustment for partial inhibition [5,22], but

there is some evidence that the salmon reference assay

may over correct the CCE quantitation due to a higher

sensitivity to matrix inhibitory effects whereas CCEΔ

may lead to underestimations [14]. Therefore, both calculation methods were used to determine whether

health effects associations were substantially affected by

the calculation approach. Additional details on the CCE

calculations are provided in the additional file 1.

The lower detection limit was defined as the upper 95%

CT bound of the Y-intercept from the pooled standard

curve data that was generated from repeated analyses of

serially diluted genomic DNA extracts from the calibrator

bacterial strains during the study period. Target sequence

concentrations in these genomic DNA extracts were determined as previously described [22]. CT values were

restricted at this upper bound for all CCE calculations.

One-half the calculated CCE was used for non-detects

where there was no detection after 45 cycles. Results are

reported in qPCR CCE per 100 ml of original sample.

Swimming exposure

Our primary definition of swimming was “body immersion”, defined as immersion to the waist or higher. Previously, we observed similar risks of illness for those

who immersed their body and those who immersed

their head [7]. Non-swimmers were those who reported

no water contact.

We used the mean of the log10 fecal indicator organism estimates to represent exposure. We created separate exposure indices based on all samples (daily

average), representing an estimate of the overall water

quality, and for morning samples (8:00 AM, 11:00 AM)

to evaluate whether morning water quality measures

were associated with illness. For categorical presentations, indicator groups were established according to

quintiles (for indicator bacteria), presence/absence

(F+coliphage by CLAT) or at the median (F+ coliphage

by SPOT). Non-swimmers were considered unexposed

to waterborne fecal indicator organisms.

Statistical analysis

We used logistic regression models to quantify and

describe the relationship between estimates of fecal indicator organisms and the risk of illness among swimmers.

The predictor of interest was the estimate of fecal indicator organisms. Factor variables representing “beach”

were included in all models to control for differences in

baseline illness. Robust estimates of variance were used

to account for non-independence of observations within

households [23-26]. Covariates which could plausibly

affect the relationship between water quality and illness,

or those which were associated with health outcomes

were considered for inclusion in regression models.

These included age, sex, race, contact with animals,

other swimming in the past 1-week, contact with other

persons with diarrhea, distance traveled to the beach,

frequency of visits to the beach under study, any other

chronic illnesses (GI, skin, asthma), digging in sand, use

of insect repellent and sunscreen, and consumption of

raw or undercooked meat. We accounted for the following environmental measures: precipitation since 3:00

PM the previous day, bather density, dogs, birds and

other animals on the beach, air and water temperature,

wind speed, tide stage, wave height, cloud cover, wind

direction and boat density, which were often highly correlated, by reducing them to summary measures using

principal components analysis. The first two principal

components explained 53% of the variability and were

characterized by air and water temperature (first component), and wave height, windspeed and precipitation

(second component). These two components were

included as covariates in regression models. When one

or more of the environmental measurements were missing, we used best-subset regression to impute the principal components [27].

For each analysis, the set of covariates was reduced

through a change-in-estimate procedure [28], where the

parameter of interest was the regression coefficient for

the fecal indicator organism, with a criterion of a 5%

change in the coefficient. To evaluate differences in the

indicator-illness relationship across beaches and age

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groups, we used likelihood ratio tests to compare full

models with multiplicative interaction terms between

beach or age group and water quality (which allowed

slopes to differ) to restricted models constrained to a

single slope. When data were sufficient, we conducted

separate analysis for those 10 years of age and under,

consistent with our previous report [6]. Stratified analyses for older age groups were not conducted due to

small sample size, and infrequent swimming and reporting of illness.

Adjusted Odds Ratios (AORs) estimated from logistic

regression models were used to represent the degree of

association between fecal indicator estimates and risk of

illness. An AOR of 1 indicates no association or a completely flat slope. AORs with a 95% confidence bound

including 1 were considered not statistically significant.

For graphical presentations, adjusted probabilities of illness were predicted from logistic regression models

holding covariates constant at their mean value.

We used Stata version 10.1 for data analysis [29].

Results

Subject recruitment and respondent characteristics

We conducted interviews on 70 study days at the three

beaches (Table 1). At Edgewater Beach, data collection

was stopped several days early due to the effects of Hurricane Katrina. A total of 9,069 beach-goers were offered

enrollment. Of these, 1,715 (19%) refused to participate

or were ineligible. Of those who agreed to participate,

6,350 (78%) completed the telephone interview and were

eligible for analysis. Selected characteristics of the study

population are shown in Table 1. Seventy-five percent of

children age 5-10 immersed their body compared to

only 26% of those over 55 (data not shown). Swimming

was also associated with male gender, non-white race,

less frequent visits to the beach, the absence of chronic

illnesses and less frequent consumption of raw or

undercooked meat (data not shown).

Water quality

We collected and tested a total of 1,242 water samples

on study days (Table 2). In terms of overall water quality, Fairhope Beach had the highest geometric mean

Enterococcus CFU (21 CFU/100 ml) and Goddard Beach

the lowest (4 CFU/100 ml). Individual samples of

Enterococcus CFU ranged from below detection to 3,000

CFU/100 ml. Overall, 142 samples (11.5%) exceeded 104

CFU/100 ml, the EPA recommended single sample maximum for marine beaches [30]. Individual samples most

frequently exceeded the single sample maximum at Fairhope Beach (99 samples, 23%), followed by Edgewater

Beach (32, 8.5%) and Goddard Beach (11 samples, 3%).

Enterococcus CCE estimated by qPCR were higher than

Enterococcus CFU. For all indicators measured by qPCR,

estimates of CCEΔΔ were higher than CCEΔ. Bacteroidales CCE were highest among the indicators.

Fifty-six percent (100/222) of samples at Fairhope

Beach and 65% (203/425) of samples at Goddard Beach

were positive for F+ coliphage by the 24 hour SPOT

test. Fewer samples were positive for F+ coliphage by

the CLAT assay. At Fairhope Beach, 4% (8/228) and

14% (14/224) of samples indicated the presence of F+

RNA and F+ DNA coliphage, respectively. At Goddard

Beach, 8% (31/425) and 9% (37/423) of samples tested

indicated the presence of F+ RNA and F+ DNA coliphage, respectively.

Illness and water quality

Bacterial indicators of water quality and illness

The number and crude (unadjusted) percentage of

respondents reporting illness among non-swimmers and

swimmers for quintiles of exposure based on daily

averages are shown for all subjects in Table 3 for qPCR

CCEΔΔ and for Enterococcus CFU. For Enterococcus

CCE, Bacteroidales CCE and Enterococcus CFU, the

crude cumulative incidence of both GI illness and diarrhea increased with increasing levels of exposure and

peaked in the highest exposure categories. On days

when the daily geometric mean of Bacteroidales CCEΔΔ

was highest (over 3,530 CCE/100 ml), approximately

12% of swimmers reported GI illness compared to 6%

among non-swimmers and 4% among swimmers on

days when Bacteroidales CCEΔΔ was low (< 542 CCE/

100 ml). Similar patterns were noted for Enterococcus

CFU and CCE.

AORs of illness among swimmers with respect to indicator density are shown for all subjects (Table 4). The

risks of both GI illness and diarrhea were significantly

associated with exposure to Enterococcus and Bacteroidales CCEΔ and CCEΔΔ (Figures 2 and 3). A log10

increase in the daily average of Enterococcus and Bacteroidales CCE was associated with an approximate doubling or greater (AORs≈2 or more) in the risk of GI

illness (Table 4). Morning estimates of Bacteroidales

and Enterococcus CCE (8:00 and/or 11:00 AM) were

also significantly associated with both GI illness and

diarrhea. Associations between GI illness and fecal Bacteroidales were generally positive but not statistically

significant. Clostridium CCEΔΔ showed a strong statistically significant association with GI illness (AOR = 1.94,

95% CI 1.16-3.23, Table 4), but the relationship with

Clostridium CCEΔ was weaker (AOR = 1.81, 95% CI

0.96-3.39), Table 4).

Enterococcus CFU were also positively associated with

GI illness, but the associations were not statistically significant. None of the associations with non-enteric illnesses were consistently positive (data for rash, earache

and eye irritations see additional file 2, Table S1).

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Children 10 years of age and under were examined

separately (see additional file 2, Table S2) but there was

no evidence of an increased susceptibility to illness with

exposure to fecal indicator bacteria. Statistical models

which allowed a separate slope for children showed no

improvement over models with a single slope for all

subjects.

Associations between GI illness and qPCR CCE

appeared to strengthen with more intense or prolonged

water exposure, although results were based on few

subjects. For example, among those exposed to water

greater than 90 minutes (N = 751), AORs were 6.4

(95% CI: 1.2-33) and 7.14 (95% CI: 1.4-37) for associations between Enterococcus CCEΔΔ and GI illness and

diarrhea, respectively. Among subjects who swallowed

water (N = 632) the AOR for GI illness with respect to

the daily average Enterococcus CCEΔΔ was 8.9 (95% CI:

2.2-37).

Associations between GI illness and qPCR CCE were

robust to many ways of handling and interpreting the

data. Allowing qPCR CT values to extend to either 40

or 45 for CCE calculations and using different

approaches to impute results for non-detected samples

[31] such as a maximum likelihood, regression on order

statistics, or Kaplan-Meier estimates did not affect the

results or the interpretation (data not shown). Excluding

those with swimming contact in the previous 1-week

reduced the sample size, but also had little affect on the

results (for example: AOR = 2.4, 95% CI 1.04-5.5 and

AOR = 2.3, 95% CI 1.3-3.8 for associations between GI

illness and Enterococcus and Bacteroidales CCEΔΔ,

respectively). Restricting the definition of swimmers to

those who immersed their head also had little effect on

the results as did using averages of water quality

approximately specific to the swimmer’s estimated time

of day and location of swimming exposure (data not

shown).

There was no evidence of systematic differences in the

relationships between GI illness and diarrhea and Enterococcus or Bacteroidales CCE exposure across the three

Table 1 Enrollment and selected respondent characteristics

Edgewater Beach Fairhope Beach Goddard Beach Total

N(%) N(%) N(%) N(%)

Days of Study

Total 21 25 24 70

Interviews

Total 1351 2022 2977 6350

Age

0-4 75(5.7) 241(11.9) 238(8.1) 554(8.8)

5-11 157(11.8) 377(18.7) 347(11.8) 881(14)

12-19 201(15.2) 210(10.4) 242(8.2) 653(10.4)

20-34 453(34.2) 454(22.5) 737(25.1) 1644(26.2)

35 and over 439(33.1) 739(36.6) 1375(46.8) 2553(40.6)

Total 1325(100) 2021(100) 2939(100) 6285(100)

Race

Non-white 551(40.8) 702(34.7) 1090(36.7) 2343(36.9)

White 798(59.2) 1320(65.3) 1882(63.3) 4000(63.1)

Total 1349(100) 2022(100) 2972(100) 6343(100)

Sex

Male 665(49.6) 855(42.3) 1285(43.2) 2805(44.3)

Female 676(50.4) 1167(57.7) 1689(56.8) 3532(55.7)

Total 1341(100) 2022(100) 2974(100) 6337(100)

Immersed body in water

No 605(44.9) 1193(59.2) 1889(63.6) 3687(58.2)

Yes 741(55.1) 823(40.8) 1080(36.4) 2644(41.8)

Total 1346(100) 2016(100) 2969(100) 6331(100)

Immersed head in water

No 915(68.1) 1370(68) 2189(73.8) 4474(70.7)

Yes 429(31.9) 646(32) 779(26.2) 1854(29.3)

Total 1344(100) 2016(100) 2968(100) 6328(100)

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beaches. Likelihood ratio tests comparing a full model

which allowed the slope to vary by beach was no better

than a model that allowed a common slope (for example:

p = 0.51 and 0.90 for GI illness associations with Enterococcus and Bacteroidales CCEΔΔ, respectively).

F+ Coliphage and Illness

The odds of GI illness was higher among swimmers

compared to non-swimmers on days when F+ DNA or

F+ RNA coliphage was detected by the CLAT assay or

F+ coliphage was detected by the SPOT assay (Table 5).

Positive associations between GI illness and F+ RNA

and F+ DNA coliphage measured by the CLAT assay

among swimmers were not statistically significant

(Table 5), although statistical power was limited due to

relatively few positive results. F+ coliphage measured by

the SPOT assay was also not associated with GI illness

among swimmers (Table 5). Other illnesses did not

show a relationship with the presence of coliphage (data

not shown).

Illness below and above current indicator criteria

Eleven of the 70 days studied exceeded the Enterococcus

CFU guideline geometric mean value of 35 CFU per

100. On these days, we observed elevated odds of diarrhea, respiratory illness and earache among swimmers

compared to non-swimmers (Table 6). For all categories

of illness, there were no differences in the odds of illness

among swimmers on days when Enterococcus exceeded

35 CFU/100 ml compared to days when Enterococcus

was below 35 CFU/100 ml (Table 6).

Discussion

This is the first study to demonstrate a relationship

between rapid, molecular measures of fecal indicator

organisms and swimming-associated illness at marine

beaches. As we observed at freshwater beaches, of the

various symptom categories those most consistently

associated with fecal indicator bacteria were symptoms

of GI illness. Although daily averaged samples generally

Table 2 Fecal indicator bacteria estimates at marine beaches

Indicator N1 Min. Max. Geometric Mean Non-detects

Edgewater Beach

Enterococcus CFU 377 0.1 920 7.2 48

Enterococcus CCEΔΔ 378 69 10000 380 0

Enterococcus CCEΔ 378 54 3600 150 0

Bacteroidales CCEΔΔ 378 120 430000 3000 4

Bacteroidales CCEΔ 378 47 300000 1300 4

Fairhope Beach

Enterococcus CFU 431 0.1 3000 21 36

Enterococcus CCEΔΔ 438 19 99000 260 97

Enterococcus CCEΔ 438 26 29000 130 97

Bacteroidales CCEΔΔ 432 8.5 200000 1800 28

Bacteroidales CCEΔ 432 10 140000 980 28

Clostridia CCEΔΔ 438 79 20000 1200 1

Clostridium CCEΔ 438 44 7900 650 1

Fecal Bacteroides CCEΔΔ 408 16 37000 450 85

Fecal Bacteroides CCEΔ 408 9.8 25000 210 85

Goddard Beach

Enterococcus CFU 426 0.1 960 3.6 78

Enterococcus CCEΔΔ 425 14 26000 160 28

Enterococcus CCEΔ 425 13 12000 120 28

Bacteroidales CCEΔΔ 426 18 120000 1100 32

Bacteroidales CCEΔ 426 23 65000 900 32

Clostridia CCEΔΔ 420 9.6 52000 890 0

Clostridium CCEΔ 420 29 17000 500 0

Fecal Bacteroides CCEΔΔ 426 11 140000 530 99

Fecal Bacteroides CCEΔ 426 11 66000 410 99

1: Number of samples.

CCE = qPCR Calibrator Cell Equivalents per 100 ml for the delta CCEΔ and delta-delta CCEΔΔ CT calculations CFU = Colony Forming Units per 100 ml (EPA Method

1600).

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showed the strongest associations with illness, the six

morning samples collected at either 8:00 AM or 11:00

AM also were associated with illness occurrence.

The different CCE calculation approaches had little

effect on the interpretation of the results. The finding

that associations were unaffected by the type of CCE

calculation and that the associations strengthened

among those with increased exposure (swallowing water,

and among those exposure longer than 90 minutes)

reinforced the validity of the results.

Average water quality as measured by Enterococcus

CFU at these three marine beaches was relatively good.

Most other epidemiology studies at marine beaches have

reported higher levels of Enterococcus CFU (although

direct comparisons are difficult due to differences in the

way average indicator densities were reported) [32-34].

Table 3 Illness among non-swimmers and swimmers by quintiles of daily average indicator exposures

GI Diarrhea URI Rash Earache Eye

N % N % N %N %N %N %

Enterococcus CCE ΔΔ

1

Non-swimmer 159 5.86 100 3.69 109 4.07 68 2.49 35 1.26 86 3.07

56.8,125 31 5.21 22 3.70 33 5.60 29 4.82 12 1.96 23 3.75

125,170 30 6.90 20 4.60 17 3.90 15 3.45 6 1.36 8 1.79

170,268 44 8.22 21 3.93 31 5.88 18 3.30 13 2.35 12 2.17

268,396 50 10.35 28 5.81 26 5.42 18 3.68 7 1.41 15 2.99

396,1.42e+03 52 10.26 45 8.88 36 7.45 20 3.97 9 1.78 14 2.73

Bacteroidales CCE ΔΔ

1

Non-swimmer 159 5.86 100 3.69 109 4.07 68 2.49 35 1.26 86 3.07

66.5,542 22 4.32 17 3.34 33 6.57 28 5.35 12 2.27 18 3.41

542,1.43e+03 36 6.53 24 4.36 23 4.23 20 3.59 10 1.77 11 1.93

1.43e+03,1.97e+03 33 7.55 16 3.66 22 5.09 11 2.51 6 1.35 10 2.24

1.97e+03,3.53e+03 55 10.34 37 6.97 38 7.18 17 3.20 12 2.24 14 2.56

3.53e+03,1.28e+04 61 11.60 42 7.98 27 5.31 24 4.56 7 1.32 19 3.54

Enterococcus CFU2

Non-swimmer 159 5.86 100 3.69 109 4.07 68 2.49 35 1.26 86 3.07

0.606,2.32 43 7.39 27 4.64 29 5.06 26 4.48 15 2.51 17 2.82

2.32,4.29 29 6.92 19 4.55 20 4.78 15 3.55 9 2.12 8 1.86

4.29,10.2 35 7.64 23 5.02 23 5.13 22 4.73 5 1.06 15 3.16

10.2,22.9 46 7.36 30 4.80 36 5.85 21 3.32 7 1.10 15 2.33

22.9,230 54 11.46 37 7.86 35 7.59 16 3.36 11 2.32 17 3.56

Fecal Bacteroides CCE ΔΔ

1

Non-swimmer 159 5.86 100 3.69 109 4.07 68 2.49 35 1.26 86 3.07

26.2,69 22 5.63 14 3.58 18 4.68 12 3.01 8 1.98 8 1.99

69,224 25 6.11 16 3.91 31 7.64 20 4.82 6 1.44 15 3.57

224,802 33 9.97 22 6.65 20 6.08 15 4.45 5 1.46 5 1.45

802,2.06e+03 30 8.26 22 6.06 24 6.63 10 2.73 9 2.44 15 4.02

2.06e+03,6.08e+03 28 8.07 18 5.19 13 3.88 11 3.20 8 2.29 11 3.12

Clostridium CCE ΔΔ

1

Non-swimmer 159 5.86 100 3.69 109 4.07 68 2.49 35 1.26 86 3.07

157,503 22 5.47 16 3.98 25 6.27 21 5.11 8 1.92 13 3.10

503,890 24 6.90 17 4.89 15 4.36 14 4.00 2 0.57 13 3.68

890,1.45e+03 29 6.94 18 4.31 23 5.50 14 3.29 14 3.25 12 2.76

1.45e+03,1.79e+03 33 9.73 26 7.67 19 5.81 11 3.27 6 1.76 8 2.34

1.79e+03,3.51e+03 30 8.98 15 4.49 24 7.29 8 2.37 6 1.76 8 2.33

1: Calibrator Cell Equivalents per 100 ml calculated by delta delta-CT (CCEΔΔ)

2: Colony Forming Units per 100 ml

GI: gastrointestinal illness, URI: Upper respiratory illness

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A series of randomized studies in the United Kingdom,

however, observed exposure-response associations at

marine beaches impacted by sewage with low levels of

Enterococcus CFU exposures [35]. Here, we report an

association between Enteroccocus and Bacteroidales CCE

and GI illness despite relatively low levels of culturable

Enterococcus. This is consistent with our previous findings at freshwater beaches and provides further evidence

that fecal indicators estimated by qPCR are a sensitive

marker of poor water quality and subsequent health

effects among swimmers at beach sites impacted by

treated sewage discharge. Compared to the freshwater

beach sites we previously studied [6], average Enterococcus CCE were slightly higher and average Enterococcus

CFU were lower. The relationship between Enterococcus

qPCR CCE and Enterococcus CFU can be influenced by

many factors and may vary from beach to beach [36].

Environmental factors, such as sunlight, may affect the

differential persistence of the qPCR signal and culturable

organisms [37-39].

The estimate of the association between Enterococcus

CCEΔΔ and GI illness among swimmers (AOR = 2.59,

95%CI 1.29-5.11) was stronger than we reported at

freshwater beaches (AOR = 1.26, 95% CI 95% CI 1.05-

1.51) [6]. Although the 95% confidence bounds of the

AORs for marine and freshwater overlap, such an overlap does not necessarily indicate no statistical difference

[40,41]. Our sample size at the marine beaches was

smaller and as a result, the 95% confidence bounds are

wider and the AOR is less precise. Previous studies [8]

also observed a higher illness rate and slope for the

association between culturable Enterococcus and GI illness in marine water which the authors suggested may

have been due to a greater die off of indicators relative

to pathogens in marine waters. We anticipate more

detailed comparisons of these results will be the focus of

future reports which should also consider baseline (nonswimmer) illness. We observed positive relationships

between gastrointestinal symptoms and other fecal indicators, Clostridium, fecal Bacteroides CCE, as well as F+

coliphage, but since associations were not consistently

statistically significant among swimmers we cannot

make conclusions regarding these indicators.

Clostridium perfringens has been suggested for use as

an indicator of fecal contamination in tropical environments [42], but it has not been previously associated

with illness in epidemiological studies [3]. Male-specific

coliphage also showed some evidence of an association

with GI illness at a marine site in Mission Bay, California [32] but this was based on few positive samples.

Levels of F+ RNA coliphage were associated with gastrointestinal illnesses among canoeists in freshwater

rivers [43].

Limitations

This study was conducted at beaches in a temperate climate with nearby treated point source sewage discharges

and results may not be directly applicable to sites

Table 4 Adjusted Odds Ratios for illness risk among

swimmers for a 1 log10 increase in indicator density1

GI Diarrhea URI

AOR 95% CI AOR 95% CI AOR 95% CI

Enterococcus CFU2

8:00 AM 1.20 0.91-1.59 1.33 0.92-1.91 1.04 0.73-1.46

11:00 AM 1.16 0.92-1.45 1.19 0.89-1.6 1.13 0.88-1.46

Daily 1.16 0.84-1.61 1.22 0.81-1.86 1.11 0.75-1.63

Enterococcus CCE Δ

3

8:00 AM 1.94 1-3.8 2.57 1.15-5.73 1.46 0.65-3.29

11:00 AM 2.08 1.18-3.67 2.54 1.29-4.99 1.62 0.86-3.04

Daily 2.67 1.34-5.34 3.57 1.57-8.13 1.83 0.76-4.39

Bacteroidales CCE Δ

3

8:00 AM 1.61 1.21-2.16 1.69 1.11-2.58 1.13 0.84-1.52

11:00 AM 1.43 1.02-1.99 1.40 0.92-2.14 0.93 0.67-1.29

Daily 1.67 1.16-2.39 1.68 1.08-2.61 0.96 0.66-1.38

Fecal Bacteroides CCE Δ

3

8:00 AM 1.30 0.99-1.69 1.34 0.94-1.91 1.12 0.81-1.54

11:00 AM 1.15 0.91-1.45 1.14 0.84-1.54 0.93 0.72-1.2

Daily 1.27 0.98-1.64 1.26 0.9-1.75 0.95 0.69-1.31

Clostridia sp. CCE Δ

3

8:00 AM 1.81 0.96-3.39 1.43 0.67-3.08 1.05 0.56-1.95

11:00 AM 1.32 0.68-2.56 1.46 0.6-3.55 0.93 0.54-1.61

Daily 1.87 0.75-4.67 1.68 0.56-5.05 1.24 0.49-3.16

Enterococcus CCE ΔΔ

3

8:00 AM 1.57 0.83-2.94 2.33 1.06-5.12 1.45 0.69-3.02

11:00 AM 2.11 1.27-3.52 2.97 1.63-5.42 1.57 0.79-3.11

Daily 2.56 1.29-5.11 4.42 1.96-9.94 1.88 0.79-4.5

Bacteroidales CCE ΔΔ

3

8:00 AM 1.71 1.23-2.36 1.87 1.16-3 1.13 0.82-1.55

11:00 AM 1.51 1.05-2.17 1.56 0.97-2.5 0.86 0.6-1.22

Daily 1.91 1.26-2.9 1.96 1.11-3.47 0.88 0.59-1.31

Fecal Bacteroides CCE ΔΔ

3

8:00 AM 1.29 0.96-1.74 1.38 0.92-2.07 1.15 0.83-1.61

11:00 AM 1.14 0.88-1.48 1.14 0.82-1.6 0.93 0.71-1.22

Daily 1.26 0.94-1.68 1.26 0.86-1.86 0.96 0.69-1.33

Clostridia sp. CCE ΔΔ

3

8:00 AM 1.94 1.16-3.23 1.62 0.86-3.07 0.99 0.56-1.74

11:00 AM 1.97 1.03-3.77 2.21 0.96-5.13 0.82 0.46-1.46

Daily 2.76 1.29-5.89 2.45 0.96-6.29 1.05 0.47-2.32

1: Exposure indices assigned for daily average of all samples, average of 8:00

AM samples and average of 11:00 AM samples.

2: log10 colony forming units per 100 ml.

3: log10 qPCR Calibrator Cell Equivalents per 100 ml.

GI: gastrointestinal illness, URI: Upper respiratory illness, AOR: Adjusted Odds

Ratio, 95% CI: 95% Confidence Interval.

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affected by fecal contamination from other types of

sources or sites with different climates. Human viruses

such as norovirus have been identified as likely contributors to excess GI illness among swimmers at beaches

impacted by treated sewage discharges [44]. Some

human pathogens, particularly human enteric viruses,

are unlikely to be associated with non-human sources of

fecal indicator bacteria. Results from some recent studies support this limitation. A recently conducted randomized study in Flordia at a sub-tropical beach

without known sources of sewage showed no association

between fecal indicator bacteria levels and GI illness

(including Enterococcus, and three Bacteroidales markers

measured by qPCR [34]). This study did observe an

association between skin rash and culturable Enterococcus [34,45], which they suggested may have been marking conditions favorable to pathogens which could cause

skin infections [34]. A study at a California marine

beach site also failed to find any robust associations

between fecal indicator organisms and swimmingassociated illness, including Enterococcus and Bacteroidales measured by qPCR [32]. This study, conducted at

a beach that was impacted by widespread and diffuse

sources of fecal contamination but no point source of

contamination [46]. Source tracking studies identified

birds as the predominant source of fecal pollution [47].

The results we report from these temperate marine

beach sites also may not be applicable to a humid tropical environmental where fecal indicator bacteria have

been reported to persist or accummulate in the soil [48].

We used an observational cohort study design which

has been used by numerous others both historically and

recently to evaluate the risks associated with recreational

water exposures (for example [32,33,49-52]). This design

allowed us to establish associations between average

water quality and the subsequent risk of illness among

those exposed. One disadvantage of this approach is

that such measures of average water quality may not

0

.05

.1

.15

.2

.25

Probability of illness

10 100 1000 10000

Bacteroidales Geometric Mean

(daily average, qPCR CCE/100 ml)

Probability of illness

95% Confidence bound

Adjusted estimates from logistic model

0

.05

.1

.15

.2

.25

.3

.35

Probability of illness

10 100 1000

Enterococcus Geometric Mean

(daily average, qPCR CCE/100 ml)

Probability of illness

95% Confidence bound

Adjusted estimates from logistic model

Figure 2 Estimated probability of GI illness among swimmers as a function of daily averages of Enterococcus and Bacteroidales qPCR

CCEΔΔ.

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Page 10 of 14
0

.05

.1

.15

.2

.25

Probability of illness

10 100 1000 10000

Bacteroidales Geometric Mean

(daily average, qPCR CCE/100 ml)

Probability of illness

95% Confidence bound

Adjusted estimates from logistic model

0

.05

.1

.15

.2

.25

.3

.35

Probability of illness

10 100 1000

Enterococcus Geometric Mean

(daily average, qPCR CCE/100 ml)

Probability of illness

95% Confidence bound

Adjusted estimates from logistic model

Figure 3 Estimated probability of Diarrhea among swimmers as a function of daily averages of Enterococcus and Bacteroidales qPCR

CCEΔΔ.

Table 5 GI illness by swimming status and presence of F+ coliphage by 24-hour SPOT Assay and 5-hour CLAT Assay

Number ill % AOR2(95% CI) AOR-trend3(95% CI)

F+ Coliphage Spot Assay1

Non-swimmer 87 4.90 ref

0.1, 0.7 39 6.74 1.52(0.98-2.36)

0.7, 24 64 8.47 1.699(1.12-2.57) 1.15(0.69-1.92)

F+ RNA Coliphage CLAT Assay

Non-swimmer 87 4.90 ref

Absent4 39 6.69 1.18(0.74-1.88)

Present4 64 8.51 1.8(1.22-2.66) 1.55(0.9-2.66)

F+ DNA Coliphage CLAT Assay

Non-swimmer 87 4.90 ref

Absent4 23 6.05 1.11(0.64-1.93)

Present4 80 8.38 1.69(1.16-2.47) 1.61(0.86-3)

1: Daily Geometric Mean, Plaque forming units per 100 ml estimated by Most Probable Number (MPN) Method.

2: Adjusted Odds Ratio comparing exposed swimmers to non-swimming reference group.

3: Adjusted Odds Ratio for a 1-log increase in coliphage on a continuous scale among swimmers.

4: Swimmers exposed on days when coliphage absent or present by the CLAT assay.

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represent an individual swimmer’s true exposure. However, in our study, swimmers were exposed for long

durations (an average of 74 minutes, with 25% exposed

more than 2 hours) and entered the water at multiple

time periods and locations, making attempts to characterize individual exposure difficult and impractical. This

prolonged and discontinuous exposure may explain why

attempts to create time and location specific averages of

water quality measures for each swimmer showed no

advantage over broader characterizations of water quality. An advantage of the study design we used is the

ability to field the study over a wide range of study days

which resulted in varying average water quality conditions and enrollment of a large study population.

Furthermore, our sampling design allowed us to demonstrate that estimates Enterococcus and Bacteroidales

CCE in six morning samples were associated with subsequent GI illness among swimmers exposed on that day.

Some of the health endpoints were non-specific, and

may have been affected by recall bias. Broad endpoints

accounted for the diverse range of symptoms potentially

associated with recreational water exposure but such

broad symptoms may obscure more specific effects of

water quality and swimming exposure. The associations

Enterococcus and Bacteroidales CCE and gastrointestinal

symptoms, however, were robust to different definitions

(e.g., diarrhea). While swimmers may have been more

likely to recall illness than non-swimmers, it is unlikely

Table 6 Illness by exposure to Enterococcus CFU, above and below EPA guidelines

Number ill % AOR1 (95% CI) AOR2 (95% CI)

GI

Non-swimmer 159 5.86 ref

Swimmer-below 35 CFU 171 7.7 ref

Swimmer-above 35 CFU 36 10.75 1.52(0.96-2.4) 1.2(0.75-1.91)

Total 366 6.94

Diarrhea

Non-swimmer 100 3.69 ref

Swimmer-below 35 CFU 108 4.87 ref

Swimmer-above 35 CFU 28 8.36 1.78(1.02-3.09) 1.4(0.8-2.43)

Total 236 4.48

URI

Non-swimmer 109 4.07

Swimmer-below 35 CFU 116 5.3 ref

Swimmer-above 35 CFU 27 8.28 1.78(1.02-3.11) 1.35(0.77-2.38)

Total 252 4.85

Rash

Non-swimmer 68 2.49 ref

Swimmer-below 35 CFU 92 4.11 ref

Swimmer-above 35 CFU 8 2.36 1.12(0.47-2.68) 0.68(0.28-1.63)

Total 168 3.17

Earache

Non-swimmer 35 1.26 ref

Swimmer-below 35 CFU 37 1.63 ref

Swimmer-above 35 CFU 10 2.93 2.37(1.06-5.31) 1.8(0.84-3.83)

Total 82 1.53

Eye irritation

Non-swimmer 86 3.07 ref

Swimmer-below 35 CFU 60 2.62 ref

Swimmer-above 35 CFU 12 3.53 1.09(0.56-2.15) 1.3(0.65-2.59)

Total 158 2.91

1: Adjusted Odds Ratio: Swimmers Above 35 CFU vs. non-swimmers.

2: Adjusted Odds Ratio: Swimmers above 35 CFU vs. swimmers below 35 CFU.

GI: Gastrointestinal illness; URI: Upper Respiratory Illness; 95% CI: 95% Confidence interval.

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such a recall bias would occur among swimmers at varying levels of water quality.

Conclusion

Rapid, molecular measures of water quality were associated with illnesses among swimmers at marine beach

sites located in a temperate climate with nearby treated

sewage discharges. The results provide further evidence

that such indicators are a marker of GI illness risk at

such beach sites.

Additional material

Additional file 1: Supplemental information on qPCR assay and CCE

calculations.

Additional file 2: Additional tables.

List of Abbreviations

QPCR: Quantitative polymerase chain reaction; AOR: Adjusted odds ratio; P:

P-value; CI: Confidence interval; GI: Gastrointestinal; URI: Upper respiratory

illness; POTW: Publicly owned treatment works; CCE: Calibrator cell

equivalents; CCEΔΔ: Calibrator cell equivalents, delta-delta cycle threshold

calculation; CCEΔ: Calibrator cell equivalents, delta cycle threshold calculation;

CT: Cycle Threshold; CFU: Colony forming units; CLAT: Culture and latex

agglutination assay for F+ coliphage; SPOT: 24-hour spot test for F+

coliphage.

Acknowledgements

The authors would like to gratefully acknowledge the following individuals

and agencies for their support and assistance. Ann H. Williams, Lucas Neas,

Pauline Mendola, Mike Ray, (US EPA, Chapel Hill, North Carolina), for their

assistance in administering the study. Westat Inc., including Karen Della

Torre, Kurt Patrizi, Robert Clickner, Sharon Jasim-Hanif and many others.

Gunther Craun, Charles Poole, Abdel El-Shaawari, Marty Kanarek, John

Standridge and John Archer for their helpful comments regarding conduct

of the study, analysis of data and reporting of study results. US EPA field

monitors Joel Hansel, Edward Hudgens, Holly Wirick, Greg Hellyer, Danelle

Lobdell, Beth Leamond, James Scott, Scott Rhoney, Markey Johnson. Bob

Mitchell (Fairhope, Alabama) for providing a site for weather gauge

installation. The EMSL Laboratory in Westmont, NJ, the Severn-Trent

Laboratory in Mobile, Alabama, and the BAL Laboratory in Cranston, RI with

special thanks to Darlene Capuano. The authors dedicate this manuscript to

the memory of Dr. Rebecca Calderon.

This document has been reviewed in accordance with U.S. Environmental

Protection Agency policy and approved for publication. Mention of trade

names or commercial products does not constitute endorsement or

recommendation for use. The findings and conclusions in this report are

those of the authors and do not represent the views of the Centers for

Disease Control and Prevention or the EPA.

Author details

1

United States Environmental Protection Agency, National Health and

Environmental Effects Research Laboratory, Research Triangle Park, North

Carolina, USA. 2

United States Environmental Protection Agency, National

Exposure Research Laboratory, Cincinnati, Ohio, USA. 3

Centers for Disease

Control and Prevention, Division of Foodborne, Waterborne and

Environmental Diseases, Atlanta, Georgia, USA. 4

Johns Hopkins University,

Baltimore, Maryland, USA. 5

University of North Carolina at Chapel Hill, Chapel

Hill, North Carolina, USA.

Authors’ contributions

TW led study planning and implementation, data analysis, result

interpretation and manuscript preparation. ES led survey and environmental

data collection. KB led water sampling design and microbiological analysis.

CR conducted microbiological analyses and coliphage testing. EC and RH

conducted qPCR analysis and interpreted qPCR results. DL provided

expertise on the rapid coliphage CLAT assay. QL conducted and provided

input on statistical analyses. RN provided expertise on the Fecal Bacteroides

assay. MB conceptualized the study, designed questionnaires and developed

study materials. AD conceptualized the study, selected beach sites, and

interpreted the results. All authors contributed to writing the manuscript

and all authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Received: 27 August 2010 Accepted: 31 October 2010

Published: 31 October 2010

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doi:10.1186/1476-069X-9-66

Cite this article as: Wade et al.: Rapidly measured indicators of

recreational water quality and swimming-associated illness at marine

beaches: a prospective cohort study. Environmental Health 2010 9:66.

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