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Developing an annual estimate of community excretion of drugs- Preliminary findings from the Northwest region of the U.S. Caleb Banta-Green PhD MPH MSW Research Scientist Alcohol and Drug Abuse Institute University of Washington & Jennifer Field PhD Professor Department of Environmental and Molecular Toxicology Oregon State University EMCDDA January 28, 2011

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Page 1: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Developing an annual

estimate of community excretion of drugs-

Preliminary findings from the Northwest region

of the U.S.

Caleb Banta-Green PhD MPH MSWResearch Scientist

Alcohol and Drug Abuse Institute

University of Washington

&

Jennifer Field PhDProfessor

Department of Environmental and Molecular Toxicology

Oregon State University

EMCDDA January 28, 2011

Page 2: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Outline

• Background- drug abuse epidemiology, place for WWTP testing• Study design• Annual sampling plan• Characteristics of WWTP

– Population estimates and possible variability – Composite sampling approaches of plants, sewer system

• Major data issues-– population measurement– Catchment area– error measurement– data distributions

• Preliminary data– Methadone

• Developing an annual estimate• Next steps

Page 3: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Drug use data sources e.g. MDMA

Data Name Population

Data

Type

# of

Events

Data

Interval Time Lag Place Terminology Major Strengths Major Limitations

Emergency Dept.,

Drug Abuse

Warning Network

E.D. patients #XXX/

X,XXXAnnual 6 months

3 County

Metro Area

Specific Drug Names

i.e. MDMA, GHB,

LSD

Population based

estimates

Hetero. Severity

Annual trend data.

Poly drug- can't assign

cause

Reporting biases

Public school

surveyStudents #

XX/

XXXXBi-annual 12 months City

MDMA,

Hallucinogens i.e..

LSD and other

psychedelics

Anonymous, self-

report survey, large

sample.

Out of school youth missing.

Inconsistent terminology.

Social desirability reporting

bias.

Drug treatment

admissions

Publicly funded

treatment #

X/

X,XXXOngoing 2 months 5 digit zip

Hallucinogens e.g.

LSD, mescaline,

peyote

Indication of

problematic use of

drugs.

Large population.

Annual trend data.

Club drugs rarely primary

drug.

Private pay missing.

Mortality-

Medical Examiner &

Toxicology Lab

All sudden,

unexpected and

unnatural

deaths

#X/

XXXOngoing 4 months 5 digit zip

Precise chemical

names.

Quantitative

chemistry.

Population based,

annual trend data.

Difficult to assign causation

to specific drug in multi-drug

cases.

Difficult to detect exogenous

GHB.

Community based

survey

Multiple sub-

groups# A

XXX/

XXXOne time 3 months Seattle Area

Specific drugs names-

detailed names &

slang terms for 11

club drugs

Patterns of use,

consequences

Convenience sample

One time survey.

Social desirability reporting

bias.

WWTP

Total

population

(on sewer)

#xxx/

xxxxx

variable/

flexiblenone Varies/City

Precise chemical

names.

Population based

Direct measure

Aggregated data

Precision ?

Accuracy ?

Page 4: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

4

Methamphetamine- Labs and dump sites in Puget Sound Counties

0

100

200

300

400

500

600

700

1990 1992 1994 1996 1998 2000 2002 2004 2006

# o

f In

cid

en

ts (

lab

s a

nd

du

mp

sit

es) King (Seattle)

Pierce (Tacoma)

Snohomish (Everett)

Page 5: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

5

Time and Place Displayed Together

Page 6: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

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Quantitative Drug Surveillance System Development

NIH National Institute on Drug Abuse R21 DA024800-01

• Small, exploratory grant

• ~54 samples in 20 Oregon and

Washington Cities in 2009

• Stratified random sample blocked on

season and day of week

• Cities vary in size, climate,

demographics

Page 7: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

7

Aims

1. Develop and validate a sensitive and selective analytical method for quantifying the concentration of

drugs in 24 hr, [flow-normalized] composites of raw

influent entering WWTPs;

2. Develop procedures for obtaining samples from a

diverse set of WWTPs;

3. Determine the geographic and temporal (seasonal,

day of week) variability of drug excretion on a per capita and community basis in order to describe use

patterns and to develop sampling frames with optimal efficiency; and

4. Determine the correlation between measured drug

discharge estimates and other drug use indicator data.

Page 8: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Findings to date

• Analytic datasets for 9 cities to date

• Substances measured:– Illicit- Coke/BZE, Methamphetamine, MDMA

– Opioids- Methadone, hydrocodone, oxycodone

– Other compounds- Caffeine, nicotine, cotinine

• Data issues described using preliminary data

• Annual estimation plan described

Page 9: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

9

Population covered by WWTP

WWTPs provide coverage to 85% of the population of King County, WA based upon place of residence: 1,482,427 of 1,737,034residents

Page 10: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

10

Wastewater

Catchment Areas

for King County Area

•Multiple places•Moderate size

•Roughly align with cities

Catchment

switches

Page 11: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Accounting for population size/Estimating Per Capita Loads

=

personday

ng

population

1x

day

Linfluent flow x total

L

drug ng

• Drug concentration (analytical error varies ~5-10%)

• Total flow available from WWTP (variability 5-10%)

• Assumes constant population (not true)

• Missing error component (discussed later)

Page 12: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Population issues

• Measure

– via biomarkers- e.g. creatinine, caffeine,

nicotine- Validity/reliability not established

• Estimate

– Census- fixed value

– Census- estimated daytime population

Page 13: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Census-estimated daytime

population

• Intent- account for worker migration in and out

• Utility- account somewhat for mid-week vs

weekend population differences

• Imperfect if wwtp catchment area is not the

same as the political boundary for a city

• For our purposes, adjust mid-week estimates by

Half of the population estimate (awake 8 hours,

asleep 8 hours)…

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Estimated Daytime Population (U.S. Census 2000 PHC-T-40)

Can create an estimated mid-week and weekend population with these data

Need updated data and match to actual geographic catchment area

WWTP

Total

resident

population

Estimated

daytime

population

Daytime population

change due to

commuting NotesNumber Percent

a 16,461 19,606 3,145 19.1

b 86,438 113,457 27,019 31.3 Regional capitol

c 18,397 21,006 2,609 14.2

d 83,259 71,447 -11,812 -14.2 2 WWTP, complicated geography

e 50,052 72,101 22,049 44.1 Multiple cities and changes based upon time of year

f 563,374 723,417 160,043 28.4 Catchment area changes seasonally

g 23,003 31,509 8,506 37.0

h 529,121 650,864 121,743 23.0

Page 15: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Impact of variable populationFor this city the increase in daytime population is

31%, assume mid-week and assume half of

waking hours, so multiply mid-week population

estimate by 1.155

.01

.02

.03

.04

.05

01jan2009 01apr2009 01jul2009 01oct2009 01jan2010date_n

Methadone_pop_adj Methadone_pop_fxd

Page 16: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

WWTP & Sampling Characteristics

Population Sampling Drainage system

number source mode frequency separate or volume pumped

[T/V] [min] (av-max) combined sewer [S/C] into STP [%]

20,000 census T/V1

~60 S2

33

46,000 census V 18-43 S 18

72800* sewer plan V 20-60(?) na 95% (somewhere in the catchm.)

98,000 connections V 48-75 C 78% (best guess for all pump st.)

19,000 census T/V 30 (29-35) C 100% (probably infl. WWTP)

575,930 census V na 99.9% (somewhere in the catchm.)

35200* sewer plan V 20-60(?) na 95% (somewhere in the catchm.)

650,000 V 10-15min S(90%) all pump stations 85%

1,350,000 na V 45-60 C many interm. and cont. op. pump st.

Time/Volume

None flow prop.

Page 17: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Sample data methadone

Summary statistics are NOT correct as they do not

incorporate <loq and <ld data

Total Samples <LD <LOQ

Data

problem >LOQ

Average daily

excretion

mg/per capita* SD Min Max Range

% Relative

SD

54 … … 1 53 0.0516 0.0179 0.015 0.107 0.09 34.6

52 … … 1 51 0.0222 0.0095 0.006 0.049 0.04 42.7

55 … 1 2 52 0.1047 0.0333 0.020 0.208 0.19 31.9

53 … … … 53 0.0152 0.0055 0.007 0.028 0.02 36.3

48 … … 1 47 0.0299 0.0106 0.0105 0.0558 0.05 35.3

44 … … 1 43 0.0352 0.0153 0.007 0.085 0.078 43.4

41 … … 2 39 0.0310 0.0137 0.0081 0.0625 0.054 44.2

46 … 1 … 45 0.0250 0.0113 0.0070 0.0550 0.048 45.2

50 … … … 50 0.0183 0.0079 0.0043 0.0485 0.0441 43.5

Page 18: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Sample data methadone cont.

• %RSD similar to other WWTP derived estimates

• Fairly large %RSD,

– some recommend not using survey data w/

%RSD >30%

• However, a valid direct measure with a large RSD is more useful than an invalid indirect measure with a small %RSD

Page 19: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Variability

Without error bounds point estimates cannot be compared within or across places

√ (Analytical error)2 + (Flow error)2 + (Sampling error)2

Easy Easy Hard

Page 20: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

How use these complicated data?

• Substantial

– < level of detection

– < level of quantification

• Cannot ignore

• Should not do simple substitutions

• Must report actual data distributions

• Consider censored data techniques

• Excretion estimates to start with

More than obvious: better methods for interpreting nondetect data.

Helsel DR. Environ Sci Technol. 2005 39:419A-423A.

Page 21: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Number and proportion of single-day drug index loads by urbanicity

ORDERED CATEGORICAL DATA

BZE (Cocaine metabolite) Level by Urbanicity

0%

20%

40%

60%

80%

100%

# of Municipalities

Upper Tertile 17 3 6

Middle Tertile 6 13 6

Low est Tertile 9 6 11

Below quantification 3 3 3

Not Detected 1 1 8

UrbanLarge Rural

City/Tow nSmalll Rural Tow n

Equivalency across RUCA* Trend across RUCA**

Substance df chi-square p-value df chi-square p-value

Benzoylecgonine

(cocaine metabolite)8 26.1 0.001 2 10.97 0.004

Methamphetamine 4 3.51 0.477 2 0.894 0.640

MDMA 8 8.88 0.353 2 6.16 0.046

Page 22: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

MDMA Loads in 2 Cities

NIDA StudyCensored quantitative data

City S City O

Median Load 0.0056 0.0072

% ND 16% 58%

City S 0.001 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.002 0.003 0.004 0.004 0.004 0.004 0.004 0.004 0.005 0.005 0.005 0.006 0.006

0.006 0.006 0.006 0.007 0.007 0.008 0.008 0.008 0.008 0.010 0.010 0.010 0.011 0.014 0.014 0.015 0.015 0.017 0.017 0.020 ND ND ND ND ND ND ND ND

City O 0.004 0.004 0.004 0.005 0.005 0.005 0.006 0.006 0.006 0.006 0.007 0.008 0.008 0.008 0.008 0.009 0.009 0.009 0.011 0.011 0.018 0.023

ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND ND

The greatest information is in the proportion ND

Cannot calculate median if more than half of the data are missing!

Page 23: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Censored data methods

Page 24: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

To do:

Generating Annual Estimates• Explore different population estimate

approaches – E.g. reduce variability of expected constant substances

• Determine weekend v mid-week differences by

drug accounting for population, representative

days?

• Explore the impact of reduced sample sizes on

% RSD for different

– Days of week, periods e.g. mid-week

– WWTP sampling approaches and systems

– City characteristics- demographics, migration, events

– Substances

Page 25: Developing an annual estimate of community excretion of drugs- · Developing an annual estimate of community excretion of drugs-Preliminary findings from the Northwest region of the

Summary

• Collecting reliable and valid data over time will require careful attention to:

– Compositing approach

– Population size- actual, flexible

– Catchment changes

– Always include error component

– Appropriate statistical summaries and tests