24 VOLUME 114 | NUMBER 1 | January 2006 • Environmental Health Perspectives

Research

Swimming in coastal waters is a favored pastime in the United States. In a survey of

> 75,000 households, 42% of respondents

≥ 16 years of age, equivalent to approximately

89 million individuals, reported swimming in

recreational waters annually (National Survey

on Recreation and the Environment

2000–2002). Such waters are often contaminated by human sewage as a result of discharges or overflows [U.S. Environmental

Protection Agency (EPA) 2001]. Swimming in

fecally contaminated recreational waters has

consistently been associated with gastrointestinal (GI) illness (Pruss 1998; Wade et al.

2003). The incidence of illness attributable to

recreational water exposure appears to be

increasing. The Centers for Disease Control

and Prevention (CDC) reported 21 recreational water outbreaks in 2000, more than any

single previous year since systematic surveillance began (Lee et al. 2002). The Natural

Resources Defense Council (Dorfman 2005)

reported that there were more beach closings

and advisories in 2000 than in any previous

year; 85% of these closings and advisories were

due to bacteria levels that exceeded standards. 

Because of the great diversity of pathogenic microorganisms transmitted by contaminated water and the difficulty and cost of

directly measuring all microbial pathogens in

environmental samples, organisms that may

indicate the presence of sewage and fecal

contamination (indicator organisms) are

often used for monitoring and regulation of

recreational and drinking waters. Indicator

organisms are common inhabitants of the

intestinal tract of warm-blooded animals.

They are found in fecal material at high concentrations and are easier to measure in the

environment than are pathogens. Although

indicator organisms do not cause illness

under normal conditions, they represent a

measure of fecal contamination. Human

sewage is a source of fecal contamination and

also is known to contain pathogenic microorganisms (Griffin et al. 2003; Jones 2001;

Madore et al. 1987). Direct and indirect

exposure to sewage has been associated with

illness (Alexander et al. 1992; El-Sharkawi

and Hassan 1982; Fleisher et al. 1996;

Khuder et al. 1998; Mac Kenzie et al. 1994;

Yamamoto et al. 2000).

Current recreational water-quality guidelines are based on studies conducted in the

1970s and 1980s (Cabelli et al. 1975, 1979,

1982; Dufour 1984). The currently recommended bacterial indicators are based on

microbiological methods that involve culturing fecal indicator bacteria, such as

Enterococcus spp. or Escherichia coli, and

counting the colony-forming units. One

shortcoming of these methods is that the bacteria require at least 24 hr to grow visible

colonies, making it impossible for beach

managers to assess the quality of water on the

day of sample collection.

Because microbial water quality can

change rapidly (Boehm et al. 2002), guidelines based on indicator organisms that require

24 hr to develop are likely to result in both

unnecessary beach closings and the exposure

of swimmers to poor-quality water. A recent

study estimated that up to 40% of beach closures are in error (Kim and Grant 2004).

In 2000, Congress passed an amendment to the Clean Water Act, the Beaches

Environmental Assessment and Coastal

Health (BEACH) Act (2000). Among other

provisions, the BEACH Act required the U.S.

EPA to conduct research to provide the support of new criteria for recreational waters.

Methods have been developed to measure

microorganisms more rapidly. A modified version of polymerase chain reaction (PCR),

quantitative TaqMan PCR (QPCR; Applied

Biosystems, Foster City, CA), has been developed to quantify indicator bacteria in recreational waters (Santo Domingo et al. 2003) in

≤ 2 hr. Because these methods provide a faster

assessment of water quality, they have the

potential to significantly reduce illnesses

resulting from exposure to recreational waters

and also to reduce errors in beach closings or

public notifications.

In 2003, we conducted the first in a series

of studies designed to evaluate the ability of

QPCR to predict health effects of recreational-water exposure. Secondary goals were

to evaluate specific study design and analytical

Address correspondence to R.L. Calderon, U.S. EPA

Human Studies Division, MD 58A, Research Triangle

Park, NC 27711 USA. Telephone: (919) 966-0617.

Fax: (919) 966-6212. E-mail: Calderon.rebecca@epa.gov

We thank R. Haugland, L. Wymer, J. Hansel,

K. DeLaTorre, K. Patrizi, R. Clickner, and the

NEEAR team; R. Whitman; C. Hoffman; Indiana

Dunes National Park; Cleveland Metroparks; and

the Cuyahoga County Board of Health for their

assistance. 

This study was funded by the U.S. EPA and managed by Westat Corp. (contract 68-D-02-062).

The information in this document has been subjected to review by the National Health and

Environmental Effects Research Laboratory and

approved for publication. Approval does not signify

that the contents reflect the views of the agency.

The authors declare they have no competing

financial interests.

Received 2 May 2005; accepted 1 September 2005.

Rapidly Measured Indicators of Recreational Water Quality Are Predictive

of Swimming-Associated Gastrointestinal Illness

Timothy J. Wade,1 Rebecca L. Calderon,1 Elizabeth Sams,1 Michael Beach,2 Kristen P. Brenner,3 Ann H. Williams,1

and Alfred P. Dufour 3

1National Health and Environmental Effects Research Laboratory, Human Studies Division, U.S. Environmental Protection Agency,

Research Triangle Park, North Carolina, USA; 2Parasitic Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia, USA; 3National Exposure Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, Ohio, USA

Standard methods to measure recreational water quality require at least 24 hr to obtain results,

making it impossible to assess the quality of water within a single day. Methods to measure recreational water quality in ≤ 2 hr have been developed. Application of rapid methods could give considerably more accurate and timely assessments of recreational water quality. We conducted a

prospective study of beachgoers at two Great Lakes beaches to examine the association between

recreational water quality, obtained using rapid methods, and gastrointestinal (GI) illness after

swimming. Beachgoers were asked about swimming and other beach activities and 10–12 days later

were asked about the occurrence of GI symptoms. We tested water samples for Enterococcus and

Bacteroides species using the quantitative polymerase chain reaction (PCR) method. We observed

significant trends between increased GI illness and Enterococcus at the Lake Michigan beach and a

positive trend for Enterococcus at the Lake Erie beach. The association remained significant for

Enterococcus when the two beaches were combined. We observed a positive trend for Bacteroides at

the Lake Erie beach, but no trend was observed at the Lake Michigan beach. Enterococcus samples

collected at 0800 hr were predictive of GI illness that day. The association between Enterococcus

and illness strengthened as time spent swimming in the water increased. This is the first study to

show that water quality measured by rapid methods can predict swimming-associated health effects.

Key words: bathing beaches, cohort studies, diarrhea, gastrointestinal diseases, Great Lakes Region,

recreational water, swimming, water quality. Environ Health Perspect 114:24–28 (2006).

doi:10.1289/ehp.8273 available via http://dx.doi.org/ [Online 1 September 2005]
methods, such as methods for averaging indicator values, assignment of exposure measures

to swimmers, and swimming definitions.

Materials and Methods

We conducted a prospective cohort study of

beachgoers at two beaches in the Great Lakes

region. One beach was located in the Indiana

Dunes National Lakeshore, in Indiana, on

Lake Michigan (beach A), and the second was

located near Cleveland, Ohio, on Lake Erie

(beach B). The study consisted of a health survey of beachgoers and water-quality evaluation.

The beaches were selected specifically

because they were affected by discharges from

waste treatment plants. The sources of fecal

contamination affecting beach A are wastewater treatment plant effluents from at least

four communities that collectively contribute

about 16 million gallons per day to small

streams. The streams are tributaries of Burns

Ditch, which empties into Lake Michigan

approximately 2 miles east of the beach.

Beach B is a short distance west of metropolitan Cleveland, Ohio. The beach is potentially

affected by sewage treatment plant discharges

into Lake Erie to the east and west. An outfall

about 7 miles to the west discharges 6.5 million gallons of wastewater per day. Within

5 miles to the east of the beach, two other

wastewater treatment plants discharge about

40 million gallons of treated sewage per day.

The study design, questionnaires, and

materials were reviewed and approved by an

Institutional Review Board for the CDC. All

participants provided verbal informed consent

before enrollment. We complied with all

applicable ethical requirements, in accordance

with all federal regulations for the protection

of human subjects, in conducting this study.

Beachgoer health surveys. The health survey was administered in three parts: enrollment, beach interview, and telephone

interview. Interviewers approached beachgoers

on weekends and holidays during the summer.

Beachgoers who agreed to participate provided

verbal informed consent and returned to complete the beach interview as they left the

beach. An adult (≥ 18 years of age) answered

questions for other household members. The

beach interview included questions about

demographics, swimming and other beach

activities, consumption of raw or undercooked

meat or runny eggs, chronic illnesses, allergies,

acute health symptoms in the past 48 hr, contact with sick persons in the past 48 hr, other

swimming in the past 48 hr, and contact with

animals in the past 48 hr. The telephone interview was conducted 10–12 days after the

beach visit, and an adult ≥ 18 years of age

answered questions for other household members who visited the beach. The telephone

interview consisted of questions about health

symptoms experienced since the beach visit,

and other swimming- or water-related activities, contact with animals, and consumption

of high-risk foods since the beach visit.

Bilingual (English–Spanish) interviewers were

available. Interviews were conducted at

beach A between 1 June 2003 through

3 August 2003 and at beach B between

2 August 2003 and 14 September 2003.

Although respiratory, ear, eye, and skin

rash symptoms were also evaluated, we present

results only for GI illness. GI illness was

defined as any of the following: diarrhea (three

or more loose stools in a 24-hr period), vomiting, nausea and stomachache, and nausea or

stomachache that affect regular activity

(inability to perform regular daily activities).

This definition of GI illness is consistent with

definitions used in recent studies (Colford

et al. 2002; Payment et al. 1991, 1997).

Water sample collection and analysis.

Water samples were collected on each study

day. Three times a day (0800 hr, 1100 hr,

and 1500 hr), two water samples were collected at beach A along each of three transects

perpendicular to the shoreline, one in waisthigh water (1 m deep) and one in shin-high

water (0.3 m deep). A representation of the

sampling locations and additional details of

the sampling protocol have been described

previously (Haugland et al. 2005). Transects

were located ≥ 60 m apart to include the area

used by most beachgoers. Water samples were

collected at beach A on weekends and holidays during the period from 31 May 2003

through 3 August 2003. Samples also were

collected three times a day at nine beach B

locations. Because jetties divided the beach

and prevented free circulation of water, additional samples were collected to characterize

the beach (Haugland et al. 2005). Samples

were kept on ice at 1–4oC during the time

before analysis.

A detailed description of sample preparation and QPCR analysis for Enterococcus spp.

has been described elsewhere (Haugland et al.

2005). Primers and probes for the Bacteroides

analyses were conducted as described by Dick

and Field (2004), and analyses were conducted using conditions described by

Haugland et al. (2005). Additional details

regarding the estimation of cell equivalents

have also been described (Applied Biosystems

1997). In brief, we used QPCR to detect and

quantify Enterococcus and Bacteroides in water

samples based on the collection of these organisms on membrane filters, extraction of their

total DNA, and PCR amplification (i.e., a

process whereby the quantity of DNA is doubled in each cycle of amplification) of a genusspecific DNA sequence using the TaqMan

PCR product detection system. The reactions

were performed in a specially designed state-ofthe-art thermal cycling instrument (SMART

Cycler TD System, Cepheid, Sunnyvale, CA)

that automates the detection and quantitative

measurement of the fluorescent signals produced by probe degradation during each cycle

of amplification. Cell equivalents were estimated by comparing the cycle threshold to

standard samples containing a known quantity

of the target organism cells. If no threshold was

achieved after 45 cycles, the sample was considered below the limit of detection. Because a

separate set of calibrator reactions was conducted for each test sample, the limit of detection (LOD) can vary from sample to sample.

This process has been described previously

(Applied Biosystems 1997; Haugland et al.

2005). Water samples were filtered at the local

laboratory (Great Lakes Scientific, Inc.,

Stevensville, MI, and Cuyahoga County

Sanitary Engineering Division, Cleveland,

OH), and filters were shipped on dry ice to the

contract laboratory (EMSL Analytical Inc.

Laboratory, Westmont, NJ) for QPCR analysis. Results for the QPCR analyses are expressed

as QPCR cell equivalents (QPCRCE) per

100-mL volume.

Data analysis. We created two variables to

represent exposure to indicator organisms: an

average of all measures collected by day, and an

average of measures specific to day and reported

swimming location. The base 10 log (log10) of

the geometric mean (the mean of the log10 of

the count) was used for averaging results.

Measures below the LOD were assigned values

using maximum likelihood, assuming a lognormal distribution (El-Shaarawi and Viveros

1997). Quantile–quantile plots confirmed the

approximate log-normal distribution of the

water-quality measures, which are often approximately log-normally distributed (El-Shaarawi

1989; El-Shaarawi and Viveros 1997; Noble

et al. 2003). We defined swimming in three

ways: “any contact” included anyone reporting

contact with water; and “body immersion” and

“head immersion” included swimmers who

reported a minimum of immersing their body

or head, respectively. 

We used logistic regression to model the

effect of swimming and water quality on illness. Models included continuous measures

of water quality as predictor variables and a

0/1 indicator of illness as the outcome. We

used nested interaction terms to allow contrasts among swimmers and between swimmers and nonswimmers. To evaluate the

overall risk associated with swimming, we

excluded the water-quality measures from the

models. We determined odds ratios (ORs) by

taking the exponent of the regression coefficients from the logistic regression models. We

estimated adjusted predicted probabilities

from logistic regression models, holding

covariates constant at their mean.

Variables that were related to GI illness or

swimming in tabulations, or were suspected by

investigators to correlate with GI illness, were

Rapidly measured indicators of water quality and illness

Environmental Health Perspectives • VOLUME 114 | NUMBER 1 | January 2006 25
considered for regression models. As a result,

we evaluated the following variables in initial

models: age; sex; race; allergies; swimming

within 48 hr before the beach visit or between

the beach visit and telephone interview; contact with animals; contact with persons with

GI illness; consumption of raw meat, fish, or

undercooked eggs; presence of chronic GI illness, skin conditions, or asthma; frequency of

beach visits; and use of nose plugs. We

excluded from the analysis beachgoers who

reported any GI symptoms within 48 hr of the

beach visit. 

We selected final regression models using

backward deletion as described by Rothman

and Greenland (1998). Initially, all covariates

were included in the model. Covariates were

then removed in an iterative fashion until

removal of any remaining covariates resulted

in > 5% change in the exposure–illness

relationship.

We used SAS, version 8.0 (SAS Institute,

Cary, NC), S-plus, version 6.1 (Insightful

Corp. 2002), and Stata, version 8.2 (Stata

Corp., College Station, TX) for data analysis.

Results

We interviewed beachgoers at beach A from

1 June 2003 through 3 August 2003 on

weekends and holidays, for a total of 20 days.

We interviewed beachgoers at beach B from

2 August 2003 through 14 September 2003,

for a total of 13 days. At beach B, no interviews were conducted because of bad weather

on 17 August and 1 September. There were

5,796 household interview attempts at both

beaches. The household interviewing response

rate (completed/attempted) through the completion of the telephone interview was 56%.

Data were available for a total of 3,221 households (5,717 individuals), 1,639 households

(2,840 individuals) at the Lake Erie beach

(beach B), and 1,582 households (2,877 individuals) at the Lake Michigan beach

(beach A). After excluding subjects with GI

illness at baseline, data were available for

5,667 individuals.

Water quality. QPCRCE results for the

measurements of indicator organisms on study

days are shown in Table 1. The QPCRCE for

Bacteroides was considerably higher than that

for Enterococcus, although there were more

results below the LOD for Bacteroides. At

beach A, 28% of Bacteroides samples were

below the LOD, and at beach B, 21% of

Bacteroides samples were below the LOD.

Enterococcus QPCRCE at beach A was slightly

higher than at beach B (p = 0.06). There was

no difference in Bacteroides QPCRCE

between beach A and beach B.

Swimming and GI illness. The incidence

of GI illness among swimmers and nonswimmers is shown in Table 2. At beach A, the incidence of GI illness was 10% among swimmers,

compared to 5% among nonswimmers. At

beach B, the incidence among swimmers

ranged from 12% for those with any contact

with water and to 14% for those who

immersed their head, compared to 10% in

nonswimmers. Fewer beachgoers reported

swimming at beach B than at beach A: at

beach A, 75% of respondents reported contact

with water, whereas only about 50% reported

contact with water at beach B. GI illness was

associated with swimming at both beaches. At

beach A, those with any contact with water

were almost twice as likely to have GI illness

compared with nonswimmers [adjusted OR

(AOR) = 1.96; 95% confidence interval (CI),

1.33–2.90]. Those immersing their body and

head were at slightly higher risk (for body

immersion: AOR = 2.26; 95% CI, 1.51–3.39;

for head immersion: AOR = 2.14; 95% CI,

1.41–3.27). The risk of GI illness associated

with swimming was slightly less at beach B (for

head immersion: AOR = 1.50; 95% CI,

1.06–2.13). 

At both beaches, swimmers were younger,

more likely to be male, more likely to eat food

or consume beverages at the beach, and more

likely to report allergies. At beach A, swimmers

were more likely to have consumed raw or

undercooked meat within 48 hr of the beach

visit, more likely to have had contact with

known or unknown animals, and slightly less

likely to report chronic GI illness (1.2% vs.

2.2%). At beach B, nonswimmers were more

likely to have GI symptoms at baseline (3.4%

vs. 1.7%) and more likely to report asthma.

Water quality and GI illness. Table 3

shows the associations between QPCRCE and

the risk of GI illness for each beach and both

beaches combined. In these models, contrasts

were created to show ORs of a unit increase in

exposure among swimmers. At both beaches,

we observed a trend between increasing mean

log10 QPCRCE of Enterococcus and risk of

GI illness. 

We observed a slightly stronger association with GI illness for the overall daily average of Enterococcus QPCRCE than for

averages specific to a beachgoer’s reported

swimming location. At beach A, a log10

increase in the daily average of Enterococcus

QPCRCE was associated with a 1.43 (95%

CI, 1.08–1.90) increase in the odds of GI illness for those immersing their bodies. At

beach B, estimates for trends between GI illness and Enterococcus QPCRCE daily averages were also elevated but slightly lower. 

Bacteroides QPCRCE was positively associated with illness at beach B, but trends were

of borderline statistical significance (p < 0.1).

Again, we found little difference between the

Wade et al.

26 VOLUME 114 | NUMBER 1 | January 2006 • Environmental Health Perspectives

Table 1. Summary statistics for log10 indicator organisms, measured by QPCR.

Enterococcusa Bacteroidesb

Beach A Beach B Beach A Beach B

No. of days 20 13 20 13

No. of samples 329 350 329 350

QPCRCE/100 mL

Mean 2.04 1.90 3.08 3.02

Median 2.07 2.05 3.34 3.63

SD 0.97 1.03 1.12 1.56

Minimum/maximum –1.53/4.20 –1.75/4.17 0.97/5.37 –0.23/5.57

No. (%) < LOD 9 (2.74) 11 (3.14) 91 (27.66) 74 (21.14)

ap = 0.06 for difference in log QPCRCE (t-test). bp = 0.55 for difference in log QPCRCE (t-test). 

Table 2. GI illness among swimmers and nonswimmers.

No. reporting

GI illness

No. (% of total) (% of exposed) AOR (95% CI)

Beach A

No contact with water 722 (25) 36 (5.0)

Any contact with water 2,154 (75) 208 (9.7) 1.96 (1.33–2.90)*

Body immersion 1,667 (58) 169 (10) 2.26 (1.51–3.39)*

Head immersion 1,210 (42) 117 (9.7) 2.14 (1.41–3.27)*

Total respondents 2,876a

Beach B

No contact with water 1,535 (54) 147 (10)

Any contact with water 1,305 (46) 159 (12) 1.27 (0.97–1.67)**

Body immersion 757 (27) 101 (13) 1.45 (1.06–1.98)*

Head immersion 524 (18) 71 (14) 1.50 (1.06–2.13)*

Total respondents 2,840

Both beaches

No contact with water 183 (8)

Any contact with water 367 (11) 1.45 (1.17–1.80)*

Body immersion 270 (11) 1.63 (1.29–2.07)*

Head immersion 188 (11) 1.61 (1.25–2.07)*

aOne missing value. *p < 0.05. **p < 0.1.
overall daily average and averages based on a

beachgoer’s reported swimming location. No

association was observed between Bacteroides

QPCRCE and GI illness at beach A.

Trends tended to be stronger when we

defined swimming as body or head immersion

than when we defined swimming as any contact with water. Defining swimming as head

immersion at beach B resulted in a weaker

trend than did body immersion or any contact

with water, but at this beach only 18% of

respondents reported immersing their head.

We included an indicator for beach in the

models that combined the results for both

beaches. No trend between GI illness and

Bacteroides QPCRCE was observed when both

beaches are combined because of the lack of an

observed trend at beach A. Trends between illness and daily averages of Enterococcus

QPCRCE were statistically significant (p =

0.005). A log10 increase in Enterococcus

QPCRCE was associated with a 1.37 (95%

CI, 1.10–1.71) increase in the odds of GI illness. A likelihood ratio test comparing the saturated model with the restricted model

indicated that the interaction between beach

and daily averaged water-quality measure was

not statistically significant (p = 0.48). The

beach effect was statistically significant (AOR =

0.64; 95% CI, 0.52–0.73, beach B vs.

beach A), reflecting the lower overall incidence

of GI illness at beach A.

Figure 1 illustrates the predicted probabilities for GI illness as a function of the log10

QPCRCE Enterococcus measures for swimmers immersing their bodies at both beaches

combined.

We examined the 0800 hr samples separately to see if water samples tested in the

morning were predictive of GI illness among

swimmers that day. As shown in Table 3,

Enterococcus QPCRCE measured at 0800 hr

was associated with GI illness that day.

Although the trends are not as strong as the

daily or location-specific averages, Enterococcus

QPCRCE measured at 0800 hr was predictive

of GI illness that day, with a log10 increase

associated with an approximately 1.2 increase

in the odds of GI illness.

The trend between increasing Enterococcus

QPCRCE with illness was stronger among

swimmers who spent more time in the water

(Table 4). A log10 increase in Enterococcus

QPCRCE and GI illness among those spending > 2 hr in the water was associated with a

nearly 3-fold increase in the odds of GI illness

(AOR = 2.89; 95% CI, 1.55–5.40).

Discussion

This is the first study to demonstrate the ability

of rapid indicator methods to predict health

effects. The results showed that Enterococcus

measured by QPCR can predict GI illness after

swimming in fecally contaminated fresh water.

The results also demonstrate that samples collected each morning could allow beach managers to assess the microbiological safety of the

beach before most beachgoers are exposed.

Incorporation of rapid measurements such as

these into a regulatory framework has the

potential to improve beach management decisions and protect swimmers’ health.

Swimmers at the two Great Lake beaches

had a higher incidence of GI illness than did

nonswimmers. Among swimmers at beach A,

risk of illness increased as daily averages of

Enterococcus QPCRCE increased. Among

swimmers at beach B, daily averages of

Enterococcus QPCRCE were also positively

associated with GI illness, although the 95%

CI of the OR included 1.0. This power to

detect a significant effect at beach B may have

been limited because of fewer swimmers at this

beach. Combining beaches produced significant trends with both daily averages and averages of samples collected at 0800 hr only. The

association between Enterococcus QPCRCE

and GI illness strengthened as the time spent

in water increased, possibly reflecting an

increased risk of illness resulting from increased

exposure to fecal contamination among those

spending longer periods in the water.

Using QPCRCE averages specific to a

beachgoer’s reported swimming location did

not improve the relationship between illness

and water quality. This may be because swimmers swam in several locations and did not

restrict their swimming along one transect.

Also, recall or reporting errors in swimming

location would lead to misclassification. As a

result, the daily averages that combined results

at each location, time, and water depth may

have been a better characterization of the exposure of an average swimmer.

Results for Bacteroides QPCRCE were less

promising, and interpretation of the results is

limited because a relatively high proportion of

samples were below the LOD. Although a

borderline trend was noted at beach B, where

fewer samples were below the LOD, no trend

was observed at beach A. Imputing the censored values using one-half the LOD did not

improve the relationship, nor did eliminating

the censored data points. Efforts are being

Rapidly measured indicators of water quality and illness

Environmental Health Perspectives • VOLUME 114 | NUMBER 1 | January 2006 27

Table 3. AORs (95% CIs) for a 1 log10 increase in Enterococcus QPCRCE and GI illness.a

Enterococcus QPCRCE Bacteroides QPCRCE

Average by day and Average Average by day and Average

Exposure Average by day location of swimming 0800-hr sample Average by day location of swimming 0800-hr sample

Beach A

Any contact 1.36* (1.05–1.76) 1.32* (1.04–1.67) — 0.89 (0.75–1.06) 0.87 (0.74–1.02) —

Body immersion 1.43* (1.08–1.90) 1.34* (1.03–1.74) — 0.89 (0.74–1.07) 0.87 (0.73–1.04) —

Head immersion 1.49* (1.07–2.08) 1.41* (1.04–1.90) — 0.84 (0.67–1.05) 0.87 (0.37–1.17) —

Beach B

Any contact 1.25 (0.93–1.67) 1.20 (0.87–1.66) — 1.15 (0.94–1.41) 1.12** (0.97–1.31) —

Body immersion 1.38** (0.94–2.01) 1.27 (0.90–1.81) — 1.24** (0.96–1.60) 1.17** (0.97–1.40) —

Head immersion 1.17 (0.76–1.82) 1.15 (0.77–1.71) — 1.28** (0.95–1.73) 1.20* (0.97–1.49) —

Beaches A and B combined

Any contact 1.30* (1.08–1.57) 1.25* (1.05–1.49) 1.18* (1.03–1.34) 0.99 (0.87–1.13) 1.01 (0.90–1.12) 0.95 (0.86–1.05)

Body immersion 1.37* (1.10–1.71) 1.26 (1.04–1.53) 1.21* (1.04–1.40) 1.00 (0.86–1.16) 1.01 (0.89–1.14) 0.94 (0.84–1.06)

Head immersion 1.35* (1.05–1.75) 1.29* (1.03–1.63) 1.21* (1.02–1.44) 0.99 (0.83–1.17) 1.00 (0.86–1.15) 0.92 (0.80–1.06)

aORs estimated from multivariate logistic regression of GI illness on the log (base 10) indicator measure. *p < 0.05. **p < 0.1. 

Figure 1. Predicted probabilities of GI illness as

a function of Enterococcus QPCRCE, predicted

from the logistic regression model, adjusted for

age and beach.

0.18

0.16

0.14

0.12

0.10

0.08

0.06

10 100 1,000

Daily geometric mean of

Enterococcus QPCRCE

Predicted probability of

GI illness

Predicted probability

95% CI

Table 4. AORs (95% CIs) for a 1 log10 increase in

the daily average of Enterococcus QPCRCE and GI

illness among swimmers by time spent in water,

beaches A and B combined.a

Time spent AOR per 1 log10

in water (min) No. increase (95% CI)

≥ 15 2,477 1.45 (1.14–1.85)*

≥ 30 1,572 1.48 (1.12–1.96)*

≥ 60 735 1.84 (1.25–2.72)*

≥ 120 289 2.89 (1.55–5.40)*

aBody immersed in water. *p < 0.05. 
Wade et al.

28 VOLUME 114 | NUMBER 1 | January 2006 • Environmental Health Perspectives

made to improve the sensitivity of the

Bacteroides assay with the hope of improving its

reliability as a predictor of illness. One of the

advantages of the QPCR method is the ability

to archive samples, and if improvements are

made to the assay, they will be retested.

The two beaches differed with respect to

swimming, demographic characteristics, and

baseline illness. At beach B, more respondents

were > 35 years of age (59% vs. 39%) and

white (90% vs. 73%) than at beach A. A

higher proportion of nonswimmers at beach B

reported illness than at beach A (10% vs. 5%).

Differences in the study populations may have

been responsible for the higher overall risk in

illness among swimmers compared with nonswimmers at beach A.

We observed no striking difference in the

trend between illness and water quality for the

different types of swimming definitions. With

the exception of Enterococcus at the Lake Erie

beach (beach B), trends tended to be stronger

when swimming was defined as body immersion and head immersion compared with any

contact with water. This is consistent with the

hypothesis that more active types of swimming would result in greater exposure to

fecally contaminated water.

Because trends were evaluated among

swimmers, it is unlikely that the observed associations could be attributed to unmeasured

confounding factors. It is unlikely that swimmers associated themselves with different water

quality with respect to characteristics that

could affect GI illness. Adjusting for covariates

tended to strengthen the trend and association

between illness and water quality.

Although we selected beaches affected by

human fecal contamination, we do not know

whether fecal contamination from other bathers

was an important contributor to the overall

level of fecal contamination. Although there

was no significant difference in Enterococcus

QPCRCE by collection time, the average

QPCRCE increased slightly throughout the

day, suggesting that swimmers may have contributed some fecal contamination.

Because QPCR relies on DNA to quantify

organisms, viable organisms are not necessary

for measurement. As a result, indicators measured by QPCR may differ in their sensitivity to

some environmental conditions. For example,

we did not see a reduction in QPCRCE over

the course of the day, an effect that has been

observed for culture-based indicator organisms

resulting from die-off caused by ultraviolet

radiation (Whitman et al. 2004). There is a

need for additional studies to better understand how indicators measured by QPCR are

affected by physical and environmental factors

in recreational waters.

Because this is the first and only study to

evaluate the ability of rapid water-quality indicators to predict GI illness, additional studies

will be required to evaluate the generalizability

of these findings. Additional studies and

analyses will help determine whether these

preliminary findings are consistent and robust

enough from a regulatory perspective to recommend a rapid indicator for recreational

water quality, and to evaluate the conditions

under which such indicators can successfully

be applied. Ultimately, the use of faster indicators of recreational water quality will result in

the ability to make decisions about recreational water quality on the day of sample collection. This, in turn, could lower GI illnesses

in communities, especially in those dependent

on beach-related tourism.

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