Investigating the relationship between drinking water and gastroenteritis in Edmonton: 1993 - 1998

4: Results

4.1 Descriptive results

4.1 a) Water quality parameters

Summary statistics for the finished and raw water quality parameters of primary interest are provided in Table 8. Because of the changes that were implemented at the Rossdale plant on December 10, 1997 (movement of the intake pipe and the introduction of particle counters), results for this plant are further differentiated as prior to and following this event.

In general, raw water parameters indicate better quality of water entering the E.L. Smith plant in comparison to the Rossdale plant, both before and after December 10, 1997 (Table 8). The differences are most pronounced in total and faecal coliforms. Following December 10, 1997, the differences in raw water parameters between the plants are less prominent.

Of primary interest in the time series analysis was the daily finished water turbidity (TB_i). Prior to December 10, 1997, finished water turbidity values (mean and median) were slightly lower in the E.L. Smith plant (Table 8). Following December 10, 1997, summary statistics appeared to be equivalent. Limited data on particle counts in finished water were provided. Mean and median particle counts from the E.L. Smith plant are marginally lower. However, these data must be interpreted with caution, since they were only available in 1998.

Temporal trends for finished water parameters are further described in Figures 3a and 3b. These data have been presented using the loess smoother and a span appropriate to the data to reduce the 'noise' resulting from daily fluctuations in the data. These figures demonstrate that finished water turbidity values for the Rossdale experienced greater fluctuations (within 0.2 NTU) than those originating from the E.L. Smith plant. There is some suggestion, however, that following December 10, 1997, values became more stabilised.

For both plants, seasonal peaks in raw water turbidity during the summer months were

Table 8: Summary statistics for indicators of raw and finished water quality: Jan. 1, 1993 to Dec. 31, 1998

Water Quality Data	Range	Std. Dev.	Median	Mean	95% Confidence Interval (Mean)
Finished water parameters
* Daily mean turbidity (NTU)
E.L. Smith	0.02 to 0.17	0.01	0.03	0.04	(0.039 , 0.040)
Rossdale	0.00 to 0.38	0.03	0.05	0.06	(0.059 , 0.061)
Before December 10, 19971	0.00 to 0.38	0.03	0.05	0.06	(0.059 , 0.062)
After December 10, 19972	0.02 to 0.07	0.01	0.04	0.04	(0.039 , 0.041)
* Daily mean particle counts, 1998 (counts per mL, (>2µm))
E.L. Smith3	1.2 to 62.2	7.1	7.9	9.3	(8.5 , 10.1)
Rossdale4	2.5 to 55.3	7.3	12.5	13.3	(12.5 , 14.1)
Raw water parameters
* Daily mean turbidity (NTU)
E.L. Smith	0 to1,967	98	6.0	31	(26.9 , 35.1)
Rossdale	1.1 to 1,754	101	8.0	34	(29.7 , 38.3)
Before December 10, 19971	1.6 to 1,481	94	9.0	35	(30.7 , 39.3)
After December 10, 19972	1.1 to 1,754	126	5.2	34	(21.5 , 46.5)
* Daily faecal coliform counts5(counts per 100mL)
E.L. Smith	0 to 510	58	5	30	(28.0 , 32.0)
Rossdale	0 to 15,000	951	160	399	(353.9 , 444.1)
Before December 10, 19971	0 to15,000	1,052	200	480	(425.1 , 534.9)
After December 10, 19972	0 to 2,800	188	51	96	(76.4 , 115.6)
* Daily total coliform counts5(counts per 100mL)
E.L. Smith	0 to 3,800	404	40	133	(115.4 , 150.6)
Rossdale	0 to 346,000	15,886	2,100	6,221	(5,491.9 , 6,950.1)
Before December 10, 19971	0 to 346,000	17,571	3,200	7,717	(6,809.5 , 8,624.5)
After December 10, 19972	2 to 21,000	1,674	265	640	(473.4 , 806.6)

apparent, and were likely due to an increase in run-off from rainfall. Faecal coliforms also appeared to favour these temperate months, as their numbers increased during this time.

• ¹ Rossdale intake pipe relocated on December 10, 1997, at which time, particle counters were also introduced. Therefore, presented results are based on data up to and including December 10, 1997
• ² Presented results are based on data from December 11, 1997 and beyond
• ³ Data available March 13 - December 31, 1998
• ⁴ Data available January 1 - December 31, 1998
• ⁵ Data available January 1, 1994- December 31, 1998

Figure 3a: Finished Water Quality Descriptive Results (Jan. 1, 1993 to Dec. 31, 1998) Rossdale plant

(i) Daily mean finished water turbidity(NTU) (span 25 days) ⁵

(ii) Daily mean finished water particle counts (span 25 days)

(iii) Distribution of observed daily mean finished water turbidity values

(iv) Distribution of observed daily mean finished water particle counts

Figure 3b: Finished Water Quality Descriptive Results (Jan. 1, 1993 to Dec. 31, 1998) E.L. Smith plant

(i) Daily mean finished water turbidity (NTU) (span 25 days)

(ii) Daily mean finished water particle counts (span 25 days)

(iii) Distribution of observed daily mean finished water turbidity values

(iv) Distribution of observed daily mean finished water particle counts

Figure 4a: Raw Water Quality Descriptive Results (Jan. 1, 1993 to Dec. 31, 1998) Rossdale plant

(i) Daily mean raw water turbidity (span 60 days) ⁶

(ii) Daily raw water faecal coliform counts (span 60 days)

(iii) Density plot of observed daily mean raw water turbidity values

(iv) Density plot of observed daily mean raw water faecal counts

Figure 4b: Raw Water Quality Descriptive Results (Jan. 1, 1993 to Dec. 31, 1998) E.L. Smith plant

(i) Daily mean raw water turbidity (span 60 days)

(ii) Daily raw water faecal coliform counts (span 60 days)

(iii) Density plot of observed daily mean raw water turbidity values

(iv) Density plot of observed daily mean raw water faecal counts

4.1 b) Environmental parameters

Summary statistics are provided for the environmental parameters in Table 9. Temporal trends for daily extreme temperatures and precipitation are provided in Figures 5 and 6, respecti vely. Strong seasonal patterns were apparent for these data, with peaks being observed during the spring and summer season.

Figures 7 and 8 visually describe the relationship between raw water turbidity and environmental factors. In general, increases in temperature and precipitation were accompanied by an increase in raw water turbidity.

Table 9: Summary statistics for environmental parameters (Jan. 1, 1993 to Dec. 31, 1998)

Environmental Parameter	Range	Std. Dev.	Median	Mean	95% Confidence Interval (Mean)
Daily maximum temperature (degrees Celsius)	-30.9 to 34.5	13.2	10.7	8.7	(8.2 , 9.2)
Daily minimum temperature (degrees Celsius)	-37.8 to 18.6	11.8	0.5	-1.3	(-1.8 , -0.8)
Daily precipitation (millimetres)	0 to 63.4	4.1	0	1.3	(1.1 , 1.5)

Figure 5: Maximum and minimum daily temperatures (°C) (Jan. 1, 1993 to Dec. 31, 1998) (span=25 days) (refer to footnote 5)

Figure 6: Daily precipitation (mm) (Jan. 1, 1993 to Dec. 31, 1998) (span=25 days)

Figure 7: Comparing daily maximum temperature and daily mean raw water turbidity

Figure 8: Comparing daily precipitation and daily mean raw water turbidity

4.1 c) Socio-economic data

Average annual household incomes reported in 1995 are shown in Figure 9.

Figure 9: Distribution of average annual household incomes per postal code in Edmonton, 1995

4.1 d) Health outcome data

To ensure that all individuals could be linked to water quality values up to 40 days prior their date of illness, February 10 ^th 1993 was the first service date considered for analysis, and December 31, 1998 was the last. Detailed profiles of each data source are provided in Figures 10a to 10d. The majority of cases were captured by utilizing the physician-office data from the AHCIPP database. Although long-term care c entr es a lso pr ovid e regular treatment to individuals suffering from persistent mental illness and physical disabilities, the majority of patients (70%) captured in this database were greater than 65 years of age. In contrast, only 10% of selected cases in the emergency room and physician-visit billing data sources were greater than 65 years.

The distribution of cases by the most responsible ICD-9 code is also provided. For comparative purposes, the same ICD-9 codes are presented for each data source, and represent the majority of what was observed in the respective databases.

The seasonal distribution of cases on a bi-weekly basis was also apparent, with a higher incidence of cases observed during the spring and early summer months. More cases were also admitted to the hospital at the beginning rather than during the work week. In contrast, more cases sought emergency room services during the weekend.

Figure 10a: Data Profile (February 10, 1993 to December 31, 1998) : Hospital Admissions (CIHI data source)

(i) Distribution of cases by age group and water service area

Age Group (yrs)	Water Service Area
	Rossdale	E.L. Smith	Mixed Zone
2 to 18	1302 (24.5%)	140 (27.6%)	359 (33.1%)
> 18 to 65	548 (44.4%)	214 (42.2%)	443 (40.9%)
> 65	383 (31.1%)	153 (30.2%)	282 (26.0%)
Total Cases per Water Service Area	1,233 (100%)	507 (100%)	1,084 (100%)

(ii) Number of cases per 14-day interval (seasonal distribution)

(iii) Proportion of cases by most responsible ICD-9 code (iv) Proportion of cases by day of week

(iv) Proportion of cases by day of week

Figure 10b: Data Profile (February 10, 1993 to December 31, 1998) : Emergency room-related visits (EMRG data source)

(i) Distribution of cases by age group and water service area

Age Group (yrs)	Water Service Area
	Rossdale	E.L. Smith	Mixed Zone
2 to 18	2,079 (31.4%)	1,361 (37.2%)	2,952 (38.8%)
> 18 to 65	3,834 (57.8%)	2,000 (54.7%)	4,068 (53.5%)
> 65	718 (10.8%)	295 (8.1%)	580 (7.6%)
Total Cases per Water Service Area	6,631 (100%)	3,656 (100%)	7,600 (100%)

(ii) Number of cases per 14-day interval (seasonal distribution)

(iii) Proportion of cases by most responsible ICD-9 code (iv) Proportion of cases by day of week

(iv) Proportion of cases by day of week

Figure 10c: Data Profile (February 10, 1993 to December 31, 1998) : Physician-office visits (PHYS data source)

(i) Distribution of cases by age group and water service area

Age Group (yrs)	Water Service Area
	Rossdale	E.L. Smith	Mixed Zone
2 to 18	20,659 (33.3%)	11,449 (38.4%)	23,366 (36.5%)
> 18 to 65	36,955 (59.5%)	16,369 (54.9%)	32,105 (54.3%)
> 65	4,446 (7.2%)	2,004 (6.7%)	3,708 (6.3%)
Total Cases per Water Service Area	62,060 (100%)	29,822 (100%)	59,179 (100%)

(ii) Number of cases per 14-day interval (seasonal distribution)

(iii) Proportion of cases by most responsible ICD-9 code (iv) Proportion of cases by day of week

(iv) Proportion of cases by day of week

Figure 10d: Data Profile (February 10, 1993 to December 31, 1998) : Long-term care vists (LTC data source)

(i) Distribution of cases by age group and water service area

Age Group (yrs)	Water Service Area
	Rossdale	E.L. Smith	Mixed Zone
2 to 18	22 (6.8%)	10 (8.2%)	20 (8.3%)
> 18 to 65	59 (18.3%)	30 (24.6%)	56 (23.3%)
> 65	241 (74.8%)	82 (67.2%)	164 (68.3%)
Total Cases per Water Service Area	322 (100%)	122 (100%)	240 (100%)

(ii) Number of cases per 14-day interval (seasonal distribution)

(iii) Proportion of cases by most responsible ICD-9 code (iv) Proportion of cases by day of week

(iv) Proportion of cases by day of week

4.2 Statistical Analyses

4.2 a) Multivariate logistic regression

As described in section 3.2, multivariate logistic regression analysis was conducted to determine if the risk of gastroenteritis varied for residents of different water service areas. The final model derived using the generalised linear model (GLM) was :

(refer to Table 5 for a complete description of variable names)

As time was both a component of the seasonal parameter and of the categorical source variable (SOURCE), the impact of water source was assessed by calculating the relative change after December 10, 1997 in the risk of gastroenteritis between Rossdale and E.L. Smith serviced residents. Presented in Table 10 are the results of this comparison, carried out using appropriate contrasts within the final logistic regression model for each health outcome data set. The odds ratios equate to the relative change in risk among service areas after Dec 10 '97. For example, the "risk" in hospitalisation for gastroenteritis among Rossdale serviced residents in comparison to E.L. Smith serviced residents fell by a magnitude of 0.18 times after December 10, 1997 (Table 10).

Table 10: Multivariate Logistic Regression Results: Comparisons Among Service Areas

Comparison	Parameter Estimate	P-value	Odds Ratio
Hospital Admissions (all age groups)
(< Dec '97):Rossdale \ E.L. Smith vs. (≥ Dec '97):Rossdale \ E.L. Smith	0.1669	0.0557	1.18
Emergency Room Visits (all age groups)
(< Dec '97): Rossdale \ E.L. Smith vs. (≥ Dec '97) Rossdale \ E.L. Smith	0.0956	0.0026	1.10
Physician Visits (all age groups)
(< Dec '97): Rossdale \ E.L. Smith vs. (≥ Dec '97):Rossdale \ E.L. Smith	-0.0147	0.5544	0.99
Long-term Care (³ 65 year olds)
(< Dec '97):Rossdale \ E.L. Smith vs. (≥ Dec '97): Rossdale \ E.L. Smith	0.1973	0.3145	1.22

The results of Table 10 suggest a small lowering in risk of gastroenteritis among Rossdale residents (in comparison to E.L. Smith serviced residents) after Dec 10 '97. Statistically significant (P < 0.10) relative "risk" reductions were noted among hospitalisations and emergency room visits.

Based on the model above, the following spatial model was determined using generalised a dditive modeling (GAM):

(refer to Table 5 for a complete description of variable names)

Figure 11: shows the distribution of centroid points associated with all Edmonton postal codes and their assigned water source.

Figure 11: Spatial distribution of postal codes within Edmonton and corresponding water service areas.

Odds ratios corresponding to each longitude and latitude combination for each captured postal code were determined, both before and after December 10, 1997. For illustrative purposes, an odds ratio of 1.2 for each spatial location represents a 20% increase in the likelihood of illness associated with that centroid point, compared to the predicted probability associated with the mean location effect, after adjusting for other parameters in the model. Results for each data source are presented in Figures 12a to 12d. Spatially, there does not appear to be an obvious association between the risk of gastroenteritis and water supply area after controlling for other important risk factors.

Figure 12a: Spatial distribution of disease risks within the city of Edmonton between 1993-1998: CIHI hospitalisation data source, excluding infants (less than 2 year-olds)

(i) Prior to December 10, 1997

(ii) After December 10, 1997

Figure 12b: Spatial distribution of disease risks within the city of Edmonton between 1993-1998: Emergency room visit data source, excluding infants (less than 2 year-olds)

(i) Prior to December 10, 1997

(ii) After December 10, 1997

Figure 12c: Spatial distribution of disease risks within the city of Edmonton between 1993-1998: Physician-office billing data source (randomised subset), excluding infants (less than 2 year-olds)

(ii) Prior to December 10, 1997

(ii) After December 10, 1997

Figure 12d: Spatial distribution of disease risks within the city of Edmonton between 1993-1998: Long-term care data source, excluding infants (less than 2 year-olds)

(i) Prior to December 10, 1997

(ii) After December 10, 1997

4.2 b) Time series analysis

Based on the findings of the descriptive and multivariate logistic regression analyses, time series analysis was conducted only on individuals that resided within the Rossdale water service area. In addition, only water quality data prior to December 10, 1997 were analysed. Individuals supplied with Rossdale water prior to this date were more likely to be at the greatest potential risk of endemic waterborne gastroenteritis.

Using these data, final models for all time series health outcome data sets were derived using binomial and poisson analyses.

Poisson model:

Binomial model:

(refer to Table 7 for a complete description of variable names)

From these final models, no significant finished water turbidity lags were identified using the criteria outlined in section 3.3c. Similarly, none of the other measured water quality and environmental parameters, including raw water quality parameters and precipitation, were significantly associated with endemic gastroenteritis.

Although no relationship with finished water turbidity was identified in this time series analysis, 3-D surface plots were constructed to facilitate a comparison to what was observed in the Vancouver study. Figures 13a to 13d show the estimated relative rates (Poisson model) and odds ratios (Binomial model) in the final model for lagged daily mean finished water turbidity values. Interpretation for relative rates are similar to that described for odds ratios in the previous section. That is, a relative rate of 1.2 represents a 20% increase in the likelihood of gastroenteritis associated with that level of turbidity for that particular lag, compared to the predicted probability associated with the mean turbidity effect for that particular lag, after adjusting for other parameters in the model. Estimates for the binomial model using the physician-visit billing data are based on a randomised subset of the o riginal data (ref er to Sect ion 3.3a), since the software application that was used to analyse these data (S-PLUS 2000, release 2; Mathsoft, Inc.) could not manipulate the original extensive database. Only results from the greater than 65 year -old age group were presented for the long-term care data so urce since model estimates were highly unstable as a result of the limited data available for analysis in the other age groups.

Colour schemes in these figures are identical to those used in the Vancouver study. Results of point -wise comparisons for each lag and turbidity value were differentiated by the level of statistical significance. Red indicates that a point-wise relative rate or odds ratio was significantly greater than 1.0 (i.e. significantly greater than the average turbidity effect) at the 5% level of significance; yellow indicates significance at the 10% level. The turbidity scale was truncated to exclude days with turbidity values that were greater than the 95 ^th percentile and therefore observed less than 5% of the time. Model estimates for these values were extremely unstable due to the limited data available for analysis, and the correspondingly large standard errors did not provide reliable statistical results.

Although sporadic statistical associations were observed in these 3-D plots, the primary statistical criterion used for identifying significant lags was determined using the likelihood ratio test (Fahrmeir and Tutz, 1994). And, as already stated, no significant lags were identified using this criterion. Furthermore, no consistent patterns could be appreciated among the 3-D plots.

Figure 13a: 3-D time series surface plots of disease risk within the Rossdale water service area between Fe bruary 10, 1993 to December 10, 1997: CIHI data source

Figure 13b: 3-D times series surface plots of disease risk within the Rossdale water service area between February 10, 1003 to December 10, 1997: Emergency room billing data source.

Figure 13c: 3-D time series surface plots of disease risk within the Rossdale water service area between February 10, 1993 to December 10, 1997: Physician-office billing data source

Figure 13d: 3-D time series surface plots of disease risk within the Rossdale water service area between February 10, 1993 to December 10, 1997: Long-term care billing data source.

Poisson

Binomial

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