Methods

to

Recruit

Hard-to-Reach

Groups

Comparing

Two

Chain

Referral

Sampling

Methods

of

Recruiting

Injecting

Drug

Users

Across

Nine

Studies

in

Russia

and

Estonia

Evidence

suggests

rapid

diffusion

of

injecting

drug

use

and

associated

outbreaks

of

HIV

among

injecting

drug

users

-LRB-

IDUs

-RRB-

in

the

Russian

Federation

and

Eastern

Europe

There

remains

a

need

for

research

among

non-treatment

and

community-recruited

samples

of

IDUs

to

better

estimate

the

dynamics

of

HIV

transmission

and

to

improve

treatment

and

health

services

access

We

compare

two

sampling

methodologies

respondent-driven

sampling

-LRB-

RDS

-RRB-

and

chain

referral

sampling

using

indigenous

field

workers

-LRB-

IFS

-RRB-

to

investigate

the

relative

effectiveness

of

RDS

to

reach

more

marginal

and

hard-to-reach

groups

and

perhaps

to

include

those

with

the

riskiest

behaviour

around

HIV

transmission

We

evaluate

the

relative

efficiency

of

RDS

to

recruit

a

lower

cost

sample

in

comparison

to

IFS

We

also

provide

a

theoretical

comparison

of

the

two

approaches

We

draw

upon

nine

community-recruited

surveys

of

IDUs

undertaken

in

the

Russian

Federation

and

Estonia

between

and

that

used

either

IFS

or

RDS

Sampling

effects

on

the

demographic

composition

and

injecting

risk

behaviours

of

the

samples

generated

are

compared

using

multivariate

analysis

Our

findings

suggest

that

RDS

does

not

appear

to

recruit

more

marginalised

sections

of

the

IDU

community

nor

those

engaging

in

riskier

injecting

behaviours

in

comparison

with

IFS

RDS

appears

to

have

practical

advantages

over

IFS

in

the

implementation

of

fieldwork

in

terms

of

greater

recruitment

efficiency

and

safety

of

field

workers

but

at

a

greater

cost

Further

research

is

needed

to

assess

how

the

practicalities

of

implementing

RDS

in

the

field

compromises

the

requirements

mandated

by

the

theoretical

guidelines

of

RDS

for

adjusting

the

sample

estimates

to

obtain

estimates

of

the

wider

IDU

population

Introduction

Evidence

suggests

recent

diffusion

of

injecting

drug

use

and

associated

HIV

infection

in

the

Russian

Federation

since

Approximately

of

HIV

case

reports

have

been

associated

with

injecting

drug

use

with

recent

estimates

indicative

of

increased

sexual

HIV

transmission

According

to

UNAIDS

classifications

HIV

in

much

of

the

Russian

Federation

and

former

Soviet

Union

is

a

concentrated

epidemic

with

prevalence

consistently

above

in

a

single

risk

group

-LRB-

i.e.

IDUs

-RRB-

but

less

than

in

the

general

population

Concentrated

epidemics

require

targeted

surveillance

of

the

population

group

most

at

risk

in

order

to

track

the

spread

within

that

group

as

well

as

potential

transmission

to

others

Surveillance

among

IDUs

is

problematic

and

there

has

been

much

discussion

on

the

merits

of

different

methods

to

recruit

marginalized

and

hidden

groups

for

these

purposes

We

know

that

surveying

drug

users

in

treatment

settings

misses

an

important

segment

of

the

drug

using

population

Evidence

suggests

that

behaviours

characteristics

and

HIV

prevalence

amongst

IDUs

in

treatment

often

systematically

differ

to

IDUs

not

in

treatment

Many

surveillance

studies

of

IDUs

conducted

in

the

relied

on

non-probability

sampling

such

as

convenience

snowball

sampling

or

chain

referral

sampling

to

recruit

members

of

the

target

group

These

methods

work

on

the

assumption

that

peers

are

better

able

to

recruit

members

of

a

hidden

population

than

researchers

Typically

studies

employed

privileged

access

interviewers

or

indigenous

field

workers

to

recruit

IDUs

from

community

settings

Indigenous

field

workers

are

interviewers

who

are

either

current

or

former

drug

users

or

individuals

who

have

experience

working

with

drug

users

and

have

privileged

access

to

IDU

networks

Over

the

last

years

this

has

become

the

established

sampling

method

for

recruiting

hidden

populations

of

IDUs

and

sex

workers

both

in

the

UK

and

internationally

A

refinement

of

the

chain

referral

methodology

called

respondent-driven

sampling

-LRB-

RDS

-RRB-

has

recently

been

developed

RDS

is

inspired

by

the

insight

of

small

world

theory

that

suggests

that

every

person

is

indirectly

associated

with

every

other

person

through

approximately

six

intermediaries

and

therefore

that

everyone

in

a

defined

population

could

be

potentially

reached

through

several

waves

of

recruitment

in

a

chain-referral

sample

This

implies

that

there

is

a

probability

greater

than

zero

that

everyone

in

that

population

will

be

sampled

The

unique

selling

point

of

RDS

is

that

the

collection

of

data

on

participants

social

networks

allow

for

adjustment

for

non-random

recruitment

RDS

uses

social

network

data

to

make

inferences

about

the

wider

target

population

from

which

the

sample

is

drawn

to

provide

proportional

population

estimates

of

characteristics

and

behaviours

In

this

paper

we

do

not

attempt

to

test

the

statistical

superiority

of

RDS

in

providing

population

estimates

over

other

sampling

strategies

but

instead

focus

on

RDS

as

a

recruitment

strategy

examining

the

unadjusted

RDS

sample

characteristics

This

paper

compares

two

sampling

methodologies

RDS

and

chain

referral

sampling

using

indigenous

field

workers

-LRB-

IFS

-RRB-

in

terms

of

cost

effectiveness

duration

of

fieldwork

and

effects

on

the

demographic

composition

of

the

sample

First

we

offer

a

theoretical

descriptive

comparison

of

the

two

approaches

Theoretical

Comparison

of

the

Sampling

Methods

Indigenous

Field

Worker

Sampling

The

IFS

recruitment

method

uses

a

standard

chain

referral

approach

Indigenous

field

workers

undergo

training

covering

aims

of

the

study

fieldwork

protocols

ethics

informed

consent

interview

skills

and

safety

procedures

Field

workers

-LRB-

FWs

-RRB-

identify

individuals

known

to

them

from

IDU

networks

recruit

and

then

interview

them

in

community

settings

separate

from

the

rest

of

the

research

team

Eligible

participants

are

given

an

incentive

to

take

part

and

also

asked

to

introduce

their

peers

to

the

FW

The

use

of

multiple

site

and

network

recruitment

ensures

a

wide

coverage

of

the

population

providing

as

representative

a

sample

as

possible

There

is

some

evidence

that

the

use

of

FWs

with

direct

access

to

IDU

social

networks

facilitates

recruitment

and

reduces

masking

-LRB-

undersampling

reclusive

respondents

-RRB-

volunteer

bias

-LRB-

oversampling

cooperative

respondents

-RRB-

and

underreporting

of

socially

undesirable

behaviours

Respondent-driven

Sampling

In

RDS

a

fixed

site

or

store

front

is

established

where

all

interviewing

takes

place

providing

the

research

team

with

greater

control

over

the

fieldwork

Unlike

IFS

and

other

chain

referral

samples

RDS

uses

a

dual

incentive

system

a

primary

incentive

for

participating

in

the

study

and

a

secondary

incentive

for

recruiting

others

into

the

study

Sampling

begins

with

a

set

of

initial

subjects

who

serve

as

seeds

for

an

expanding

chain

of

referrals

with

respondents

from

each

link

in

the

chain

or

wave

referring

respondents

who

form

subsequent

waves

Rather

than

being

asked

to

identify

their

peers

to

interviewers

respondents

inform

their

peers

about

the

study

and

allow

them

to

decide

independently

whether

they

want

to

participate

or

not

This

theoretically

reduces

masking

since

recruiters

are

part

of

the

target

group

with

direct

access

to

other

IDUs

and

it

reduces

volunteer

bias

since

recruitees

decide

themselves

whether

to

participate

Information

on

the

relationships

between

recruiters

and

recruited

and

their

estimated

network

size

is

collected

during

the

interview

to

allow

for

the

calculation

of

selection

probabilities

This

information

is

used

to

assess

homophily

the

extent

to

which

recruiters

are

likely

to

recruit

individuals

similar

to

themselves

and

to

weight

the

sample

to

compensate

or

control

for

differences

in

network

size

homophily

and

recruitment

success

Materials

and

Methods

Data

Collection

Between

and

we

undertook

nine

community

surveys

of

IDUs

in

the

Russian

Federation

and

Estonia

-LRB-

Table

-RRB-

Four

studies

used

IFS

to

recruit

IDUs

and

five

used

RDS

All

IDUs

were

recruited

from

community

settings

Seven

of

the

studies

had

an

epidemiological

focus

and

measured

the

prevalence

of

HIV

HCV

and

associated

injecting

and

sexual

risk

behaviours

in

IDUs

Two

of

the

studies

collected

data

on

the

social

and

economic

characteristics

of

IDUs

All

studies

collected

some

standardised

indicators

and

defined

current

IDUs

as

individuals

who

injected

drugs

for

non-medical

purposes

in

the

last

weeks

Table

Research

amongst

hard

to

reach

populations

recruited

via

respondent-driven

sampling

-LRB-

RDS

-RRB-

and

indigenous

field

workers

-LRB-

IFS

-RRB-

in

Estonia

and

the

Russian

Federation

PlacePopulation

sizeDates

of

field

work

-LRB-

days

-RRB-

Average

number

of

interviews

conducted

per

daySample

sizeAim

of

studyRecruitment

-LRB-

-RRB-

prevalence

and

risk

-LRB-

-RRB-

prevalence

and

risk

Russia

-LRB-

-RRB-

prevalence

and

risk

Russia

-LRB-

-RRB-

prevalence

and

risk

Russia

-LRB-

-RRB-

and

economic

Russia

-LRB-

-RRB-

and

economic

-LRB-

-RRB-

prevalence

and

risk

Estonia

-LRB-

-RRB-

prevalence

and

risk

Jarve

-LRB-

-RRB-

prevalence

and

risk

For

each

of

the

IFS

studies

IDUs

were

recruited

using

a

team

of

FWs

at

each

site

Settings

included

street

locations

and

respondents

homes

but

excluded

drug

treatment

centres

and

STI

clinics

Volunteers

and

outreach

workers

at

local

harm

reduction

non-governmental

organizations

-LRB-

NGOs

-RRB-

were

employed

as

FWs

as

well

as

two

researchers

at

a

local

university

in

each

site

In

all

IFS

studies

two

experienced

supervisors

from

Moscow

and

a

researcher

from

the

UK

provided

technical

expertise

and

management

for

all

studies

Measures

to

ensure

data

quality

and

to

minimise

network

bias

included

limiting

the

number

of

interviews

per

FW

random

spot-checks

in

the

field

and

follow-up

validation

interviews

with

of

participants

Primary

incentives

included

HIV

prevention

materials

-LRB-

including

needles/syringes

-RRB-

chocolates

and

cigarettes

In

each

RDS

study

recruitment

was

undertaken

by

a

team

of

seven

to

eight

FWs

at

each

site

The

interview

team

comprised

trained

research

staff

from

a

local

university

two

FWs

recruited

from

local

harm

reduction

NGOs

two

to

three

trained

research

staff

from

a

local

university

and

two

supervisors

from

Moscow

A

researcher

from

the

UK

was

also

present

at

the

studies

with

the

exception

of

the

two

socio-economic

studies

in

Volgograd

and

Barnaul

Russia

In

each

study

a

pre-fieldwork

focus

group

was

held

with

outreach

workers

from

the

local

harm

reduction

NGOs

to

obtain

information

about

the

drug

scene

and

to

identify

seeds

to

begin

recruitment

Respondents

received

the

same

primary

incentives

for

participating

in

the

RDS

study

as

in

the

IFS

study

and

also

an

additional

secondary

incentive

for

each

respondent

they

recruited

into

the

study

In

all

studies

FWs

recorded

their

observations

on

the

drug

scene

progress

of

the

fieldwork

and

any

difficulties

arising

from

the

research

in

detailed

notes

These

observations

provide

a

useful

additional

comparison

between

the

two

sampling

methods

Duration

and

Cost

of

Fieldwork

We

compared

the

duration

of

fieldwork

for

the

IFS

and

RDS

methods

by

calculating

the

mean

number

of

days

of

fieldwork

for

each

method

and

the

proportion

of

the

sample

recruited

on

each

day

as

the

studies

progressed

Means

were

compared

using

t-tests

Costs

were

estimated

for

five

of

the

seven

surveys

conducted

in

Russia

and

analysis

focused

on

examining

the

cost

effectiveness

of

recruiting

a

given

sample

for

each

of

the

sampling

methodologies

from

a

programmatic

point

of

view

as

opposed

to

examining

societal

or

health

system

costs

The

IFS

studies

in

Moscow

Barnaul

and

Volgograd

were

conducted

in

and

the

RDS

studies

in

Togliatti

Barnaul

and

Volgograd

were

conducted

in

Costs

were

calculated

as

-LRB-

-RRB-

outside

costs

including

salary

accommodation

and

travel

of

field

work

consultants

-LRB-

-RRB-

local

salary

costs

of

FWs

and

researchers

-LRB-

-RRB-

recruitment

costs

including

the

packages

of

goods

valued

at

roubles

and

roubles

respectively

for

primary

and

secondary

incentives

and

-LRB-

-RRB-

other

costs

including

local

transport

telephone

calls

and

logistical

costs

of

training

FWs

For

the

RDS

study

the

cost

of

the

fixed

site

used

for

interviews

is

not

included

as

an

explicit

cost

rather

it

is

subsumed

into

the

local

salary

costs

since

local

staff

contracted

to

undertake

the

work

were

employed

from

syringe

exchange

programmes

Costs

are

presented

assuming

that

there

are

elements

of

fixed

and

variable

costs

at

each

sample

size

and

that

an

extra

respondents

will

require

keeping

the

entire

survey

team

in

the

field

for

one

extra

day

Demographic

and

Injecting

Risk

Behaviours

of

Sample

Demographic

and

injecting

risk

behaviours

of

IDUs

recruited

through

IFS

and

RDS

were

compared

in

the

two

sites

-LRB-

Volgograd

and

Barnaul

-RRB-

where

both

survey

methodologies

were

used

to

ensure

a

cleaner

comparison

between

survey

methods

Demographic

and

injecting

characteristics

were

used

as

the

outcome

variables

with

recruitment

method

included

as

an

independent

variable

In

the

univariate

analysis

chi-squared

tests

were

used

to

compare

outcomes

for

categorical

variables

and

Bartlett

's

test

for

equal

variance

to

compare

continuous

variables

For

the

multivariate

analysis

logistic

regression

models

were

used

to

explore

associations

between

explanatory

variables

and

a

binary

outcome

multinomial

logit

models

were

used

for

categorical

variables

with

multiple

values

and

ordinary

least

squares

for

continuous

variables

The

multivariate

analysis

includes

all

common

independent

variables

and

a

categorical

variable

indicating

survey

method

used

This

allows

outcomes

to

be

compared

controlling

for

all

independent

variables

and

to

identify

impacts

associated

with

only

survey

methodology

All

statistical

analyses

were

conducted

using

Stata

with

significance

set

at

-LRB-

Stata

Corporation

College

Station

Texas

-RRB-

Results

The

Surveys

A

total

of

IDUs

were

recruited

into

nine

surveys

across

four

cities

in

the

Russian

Federation

and

two

cities

in

Estonia

-LRB-

Table

-RRB-

A

total

of

-LRB-

-RRB-

participants

were

recruited

through

IFS

and

-LRB-

-RRB-

through

RDS

Only

IDUs

are

included

in

the

analyses

we

present

here

Duration

of

Field

Work

The

mean

-LRB-

standard

deviation

-RRB-

duration

of

fieldwork

for

IFS

surveys

was

-LRB-

-RRB-

days

and

for

RDS

-LRB-

-RRB-

days

-LRB-

t

p

-RRB-

Figure

depicts

the

number

of

respondents

recruited

by

each

successive

day

of

fieldwork

by

city

and

recruitment

method

The

RDS

studies

appear

to

follow

a

pattern

of

recruitment

that

we

might

expect

the

number

of

respondents

increases

steadily

as

the

number

of

waves

increase

and

then

declines

towards

the

end

of

the

study

as

completion

of

the

target

sample

size

approaches

and

respondents

are

asked

to

refer

fewer

contacts

to

the

study

Kohtla

Jarve

Estonia

appears

to

be

an

exception

to

this

as

recruitment

peaks

more

sharply

then

abruptly

finishes

The

recruitment

for

the

IFS

studies

does

not

appear

to

follow

any

set

pattern

across

the

cities

In

Moscow

the

highest

number

of

respondents

in

any

day

occurs

at

the

start

of

the

study

In

Barnaul

and

to

a

less

extent

Volgograd

the

number

of

participants

recruited

per

day

is

more

even

across

the

duration

of

the

study

Figure

of

recruitment

per

day

amongst

studies

of

injecting

drug

users

in

Russia

and

Estonia

-LRB-

-RRB-

by

city

and

recruitment

method

Sample

Characteristics

Table

summarizes

the

characteristics

of

IDUs

by

recruitment

method

from

the

four

surveys

conducted

in

Volgograd

and

Barnaul

In

both

cities

RDS

participants

were

younger

more

likely

to

be

male

to

have

attended

higher

education

and

to

have

official

residency

permits

for

the

city

RDS

participants

were

more

likely

to

report

injecting

heroin

in

both

sites

and

less

likely

to

report

injecting

vint

or

than

IFS

participants

Frequency

of

injecting

did

not

differ

by

recruitment

method

in

either

city

Regarding

injecting

risk

behaviour

there

was

no

difference

between

recruitment

methods

in

the

proportion

of

IDUs

reporting

injecting

with

a

used

needle/syringe

in

the

last

weeks

in

Volgograd

but

in

Barnaul

a

higher

proportion

of

RDS

respondents

reported

this

behaviour

-LRB-

vs.

p

-RRB-

In

Volgograd

IFS

respondents

were

more

likely

to

report

ever

having

injected

with

a

used

needle/syringe

than

RDS

respondents

-LRB-

vs.

p

-RRB-

The

opposite

was

found

in

Barnaul

-LRB-

vs.

respectively

p

-RRB-

In

both

cities

and

with

both

methods

the

main

source

of

new

needles/syringes

was

pharmacies

A

higher

proportion

of

IFS

respondents

reported

using

needle/syringe

exchanges

or

treatment

centres

in

both

cities

and

in

Barnaul

a

higher

proportion

of

RDS

respondents

reported

using

a

source

other

than

needle/syringe

exchange

-LRB-

defined

as

friend

dealer

family

or

on

the

street

-RRB-

as

their

main

source

of

needles/syringes

Table

Comparison

of

characteristics

and

injecting

risk

behaviours

among

injecting

drug

users

in

Volgograd

and

Barnaul

-LRB-

-RRB-

by

recruitment

method

CharacteristicBarnaulVolgogradIFRDSaIFRDSan/total

mean

-LRB-

SD

-RRB-

n/total

mean

-LRB-

SD

-RRB-

valuen/total

mean

-LRB-

SD

-RRB-

n/total

mean

-LRB-

SD

-RRB-

valueTotal

age

-LRB-

years

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

Attended

higher

education

Duration

of

injection

-LRB-

years

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

-LRB-

-RRB-

No

official

residency

Injecting

risk

behaviours

in

the

last

weeksMain

drug

injected

Daily

injection

Injected

with

used

needles/syringes

Main

source

of

new

needles/syringes

Other

Ever

injected

with

used

aThe

RDS

data

are

not

adjusted

for

homophily

and

network

effects

Numbers

do

not

always

add

up

to

total

because

not

all

respondents

answered

each

question

Other

refers

to

friends

family

found

on

the

street

drug

dealers

Multivariate

Analysis

Table

summarizes

the

multivariate

analysis

for

the

categorical

and

continuous

variables

for

Barnaul

and

Volgograd

After

controlling

for

all

independent

variables

our

findings

indicate

that

RDS

recruited

a

population

years

younger

in

both

cities

In

both

cities

RDS

participants

had

been

injecting

slightly

longer

than

IFS

participants

In

Barnaul

RDS

participants

were

less

likely

to

report

obtaining

their

new

needles/syringes

from

pharmacies

-LRB-

-RRB-

but

there

was

no

evidence

to

suggest

a

difference

in

Volgograd

In

Volgograd

RDS

participants

were

less

likely

to

report

using

needle/syringe

exchanges

-LRB-

-RRB-

but

there

was

no

difference

in

Barnaul

RDS

participants

in

Barnaul

were

more

likely

to

report

using

another

source

for

their

new

needles/syringes

-LRB-

Table

-RRB-

Table

Effect

of

recruitment

method

on

demographic

indicators

and

injecting

risk

behaviours

amongst

injecting

drug

users

in

Barnaul

and

Volgograd

-LRB-

-RRB-

OutcomesRDSaType

of

CIStd

CIStd

err.log

AGE

-LRB-

-RRB-

-LRB-

-RRB-

Ordinary

least

squaresYears

of

Negative

binomial

regressionIncrease

in

probability

of

using

pharmacies

-LRB-

-RRB-

-RRB-

Multinomial

logitIncrease

in

probability

of

using

needle/syringes

-LRB-

-RRB-

Multinomial

logitIncrease

in

probability

of

using

another

source

for

n/an/an

aMultinomial

logitaThe

RDS

data

are

not

adjusted

for

homophily

and

network

effects.n

a

not

applicable

In

the

logistic

regression

analysis

-LRB-

Table

-RRB-

RDS

was

more

likely

to

result

in

a

higher

proportion

of

male

IDUs

-LRB-

Barnaul

OR

Volgograd

OR

-RRB-

and

participants

who

had

attended

higher

education

-LRB-

Barnaul

OR

Volgograd

OR

-RRB-

In

Barnaul

RDS

participants

were

more

likely

to

have

official

residency

permits

-LRB-

OR

-RRB-

but

not

in

Volgograd

In

both

cities

RDS

participants

were

more

likely

to

inject

heroin

over

mak

or

vint

than

IFS

participants

-LRB-

Barnaul

OR

and

Volgograd

OR

-RRB-

In

Volgograd

RDS

participants

had

almost

twice

the

odds

of

reporting

daily

injection

-LRB-

OR

-RRB-

than

IFS

participants

and

had

reduced

odds

of

ever

injecting

with

used

needles/syringes

-LRB-

OR

-RRB-

In

Barnaul

RDS

participants

were

more

likely

to

report

injecting

with

used

needles/syringes

in

the

last

weeks

and

ever

-LRB-

OR

and

OR

respectively

-RRB-

Table

Effect

of

recruitment

method

on

demographic

indicators

and

injecting

risk

behaviours

amongst

injecting

drug

users

in

Barnaul

and

Volgograd

-LRB-

-RRB-

OutcomesRDSaType

of

analysisBarnaulVolgogradOdds

CIStd

err.Odds

CIStd

Logistic

regressionAttended

higher

Logistic

regressionOfficial

residency

permit

Logistic

regression

Injected

heroin

as

primary

drug

in

the

last

weeks

versus

Logistic

regressionDaily

Logistic

regression

Injected

with

used

needles/syringes

in

the

last

Logistic

regression

Ever

injected

with

used

Logistic

regression

Sold

sex

in

the

last

Logistic

regressionaThe

RDS

data

are

not

adjusted

homophily

and

network

effects

Costs

The

total

cost

of

conducting

an

IFS

survey

recruiting

respondents

was

estimated

to

be

-LRB-

USD

-RRB-

but

for

the

RDS

survey

-LRB-

Table

-RRB-

This

translates

to

per

respondent

using

RDS

and

using

the

IFS

method

Increasing

the

sample

from

to

reduced

the

average

cost

per

respondent

by

for

the

RDS

method

and

by

for

the

IFS

method

Reducing

the

sample

from

to

respondents

increased

the

cost

per

respondent

by

for

the

RDS

method

and

for

the

IFS

method

These

results

are

presented

in

Table

Table

Analysis

of

costs

of

recruiting

IDUs

and

sex

workers

from

five

surveys

in

Moscow

Volgograd

and

Barnaul

Russian

Federation

-LRB-

-RRB-

by

recruitment

method

and

sample

size

Recruitment

methodIndigenous

field

workersRespondent-driven

samplingSample

costsa

Local

costsb

Recruitment

of

respondentsc

Total

Cost

per

respondent

At

the

time

of

writing

rubles

was

equivalent

to

one

US

Dollar

The

costs

are

adjusted

for

inflation

that

occurred

between

August

and

based

on

price

indices

taken

from

the

Bank

of

Russia.aCosts

are

presented

assuming

that

there

are

elements

of

fixed

and

variable

costs

in

each

sample

size

and

that

an

extra

respondents

will

take

one

extra

day

necessitating

employing

the

entire

fieldwork

team

for

that

extra

day.bIn

order

to

protect

the

confidentiality

of

staff

we

report

only

the

total

amount

of

all

salaries

and

fees

paid

to

project

staff.cThe

costs

for

the

RDS

surveys

are

also

based

on

providing

a

package

of

goods

valued

at

rubles

for

each

survey

participant

and

a

secondary

reward

of

rubles

for

each

participant

recruited

Costs

for

the

IFS

surveys

are

based

on

providing

a

package

of

goods

valued

rubles

for

each

participant

and

no

secondary

reward

Discussion

Our

findings

suggest

that

RDS

does

appear

to

be

a

faster

recruitment

method

and

that

there

are

significant

differences

in

the

demographic

characteristics

of

IDUs

recruited

via

RDS

in

comparison

with

those

recruited

via

IFS

However

evidence

from

the

two

cities

is

conflicting

with

regard

to

whether

RDS

recruits

IDUs

who

engage

in

riskier

injecting

practices

One

of

the

suggested

benefits

of

RDS

is

its

apparent

ability

to

recruit

the

hardest

to

reach

sections

of

hidden

populations

We

found

some

differences

in

measures

of

marginalization

and

risk

behaviours

between

the

two

recruitment

methods

RDS

participants

tend

to

be

slightly

younger

and

are

less

likely

to

use

needle/syringe

exchange

programs

Some

evidence

in

Russia

suggests

that

IDUs

whose

primary

source

of

needles/syringes

is

informal

are

at

more

risk

of

engaging

in

high-risk

behaviours

However

IFS

participants

were

less

likely

to

have

attended

higher

education

and

have

official

residency

permits

to

live

in

the

city

and

more

likely

to

be

female

Lack

of

residency

permit

is

an

indicator

of

marginalization

as

it

will

affect

an

individual

's

ability

to

use

health

services

or

obtain

employment

As

no

consistent

trend

emerges

from

the

analysis

of

the

effect

of

recruitment

method

on

sample

characteristics

then

choice

of

method

might

be

made

on

the

basis

of

methodology

and

cost

Inclusion

Criteria

and

Data

Validity

With

IFS

the

responsibility

for

selecting

the

right

target

group

is

placed

with

the

FWs

and

its

success

depends

on

establishing

a

trusting

relationship

between

the

researchers

and

the

fieldwork

team

With

RDS

issues

of

trust

are

less

important

as

researchers

undertake

the

interviews

themselves

The

problems

of

establishing

whether

respondents

are

genuine

members

of

the

target

group

remain

Although

measures

can

be

put

in

place

which

might

reduce

this

from

happening

such

as

using

indigenous

field

workers

to

screen

participants

or

recording

biometric

measurements

to

avoid

the

same

respondent

being

interviewed

twice

it

is

very

difficult

to

measure

to

what

extent

fabricated

data

may

enter

a

survey

A

disadvantage

of

both

methods

is

that

study

participants

who

are

not

members

of

the

target

group

may

lie

about

their

membership

in

order

to

receive

a

reward

This

was

the

case

in

two

of

the

IFS

sites

where

and

of

questionnaires

were

subsequently

found

to

be

fakes

This

was

discovered

because

strict

validation

processes

had

been

set

up

and

there

was

a

good

relationship

between

the

FW

supervisor

and

indigenous

field

workers

In

the

Togliatti

RDS

study

people

were

refused

entry

into

the

study

as

they

were

suspected

of

not

being

current

injectors

However

these

may

be

considered

a

minimum

estimate

as

one

can

not

rule

out

that

additional

fabrication

might

have

occurred

and

gone

undetected

Having

a

modest

primary

and

secondary

incentive

can

minimize

the

chances

that

participants

who

are

not

members

of

the

target

population

will

be

recruited

Determining

the

best

incentive

size

is

difficult

and

has

many

implications

for

the

study

especially

for

RDS

studies

where

the

secondary

incentive

is

so

crucial

to

recruitment

success

The

networks

recruited

through

RDS

are

largely

artificial

created

as

a

result

of

the

study

and

since

their

composition

is

dependent

on

the

incentive

changes

to

the

amount

of

incentive

offered

would

change

the

composition

of

the

network

This

is

illustrated

with

the

case

of

sex

workers

in

Eastern

Europe

who

have

been

found

to

be

harder

to

recruit

through

RDS

in

part

due

to

the

small

incentive

and

social

network

properties

this

is

discussed

in

more

detail

in

a

paper

in

this

issue

by

Simic

et

al.

Adjusting

the

RDS

sample

to

obtain

population

estimates

depends

on

the

ability

to

recruit

a

random

population

within

a

subject

's

social

networks

and

a

positive

probability

of

recruiting

everyone

in

that

network

The

possibility

that

the

network

is

highly

dependant

on

the

incentive

raises

the

question

whether

the

latter

condition

obtains

This

is

particularly

relevant

when

the

definition

of

the

population

of

study

is

fluid

or

artificially

constructed

by

the

research

as

with

IDUs

and

sex

workers

It

should

also

be

noted

that

the

collection

of

information

describing

network

characteristics

which

allows

RDS

analysis

to

produce

population

estimates

requires

the

respondent

to

recall

detailed

information

on

the

composition

of

their

network

including

its

size

and

each

member

's

relationship

with

the

recruiter

This

process

carries

a

large

potential

for

error

Personal

Safety

and

Capacity

Building

There

are

safety

considerations

that

favour

RDS

as

respondents

attend

a

fixed

site

for

an

interview

in

which

a

minimum

number

of

staff

is

always

present

In

the

IFS

method

interviewers

may

find

themselves

travelling

to

an

area

in

which

they

are

unfamiliar

and

unintentionally

put

themselves

in

danger

especially

if

it

becomes

known

that

they

are

carrying

financial

rewards

or

gift

packs

Limitations

Whilst

we

have

tried

to

limit

confounding

in

our

analysis

by

comparing

RDS

and

IFS

studies

conducted

in

the

same

cities

the

studies

were

conducted

in

different

years

and

the

findings

may

be

confounded

by

time

Time

may

be

important

in

relation

to

behaviour

but

is

likely

to

be

less

important

in

relation

to

socio

demographic

characteristics

of

the

target

group

of

the

studies

were

set

up

specifically

with

the

aim

of

comparing

sampling

methodologies

and

this

limited

the

number

of

characteristics

that

could

be

compared

between

study

methodologies

A

study

set

up

specifically

with

the

aim

of

comparing

the

methodologies

might

produce

different

results

and

facilitate

more

detailed

comparison

of

characteristics

Additionally

the

starting

point

for

both

the

IFS

and

RDS

studies

in

all

sites

was

the

local

outreach

team

This

may

have

led

to

more

similarities

in

the

sample

composition

than

would

have

occurred

if

seeds

had

been

selected

through

other

methods

However

according

to

the

principles

of

RDS

the

selection

of

seeds

does

not

ultimately

influence

the

composition

of

the

sample

since

after

several

waves

of

recruitment

the

sample

should

be

independent

of

the

non-randomly

selected

seeds

Conclusion

The

HIV

epidemic

is

driven

by

populations

engaging

in

high-risk

behaviours

mixing

with

those

engaging

in

lower

risk

behaviours

It

is

important

to

identify

the

parameters

of

risk

behaviour

in

order

to

model

these

epidemics

and

to

design

appropriate

interventions

If

we

assume

that

after

adjusting

for

network

sizes

and

homophily

RDS

is

more

successful

at

estimating

risk

behaviours

across

a

more

representative

population

than

IFS

then

it

could

lead

to

more

effective

modelling

and

prediction

of

such

epidemics

however

to

date

there

is

no

evidence

to

suggest

that

this

is

the

case

Our

findings

indicate

that

as

a

recruitment

strategy

RDS

is

no

better

than

IFS

in

identifying

populations

with

highest

risk

behaviours

It

does

have

practical

advantages

in

terms

of

safety

of

the

FW

team

with

faster

recruitment

at

only

additional

costs

In

the

meantime

until

the

statistical

superiority

of

RDS

can

be

proven

a

preferred

approach

may

be

to

adopt

the

best

aspects

of

both

methodologies

depending

on

the

resources

available

A

combination

could

include

the

use

of

coupons

for

recruitment

but

also

training

indigenous

field

workers

to

work

alongside

researchers

to

undertake

interviews

serving

to

increase

their

capacity

in

research

skills

whilst

ensuring

that

the

correct

target

group

is

being

reached

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Public Finance Policy Strategies to Increase Access to Preconception Care Policy and finance barriers reduce access to preconception care and , reportedly , limit professional practice changes that would improve the availability of needed services . Millions of women of childbearing age -LRB- 15 -- 44 -RRB- lack adequate health coverage -LRB- i.e. , uninsured or underinsured -RRB- , and others live in medically underserved areas . Service delivery fragmentation and lack of professional guidelines are additional barriers . This paper reviews barriers and opportunities for financing preconception care , based on a review and analysis of state and federal policies . We describe states ' experiences with and opportunities to improve health coverage , through public programs such as Medicaid , Medicaid waivers , and the State Children 's Health Insurance Program -LRB- SCHIP -RRB- . The potential role of Title V and of community health centers in providing primary and preventive care to women also is discussed . In these and other public health and health coverage programs , opportunities exist to finance preconception care for low-income women . Three major policy directions are discussed . To increase access to preconception care among women of childbearing age , the federal and state governments have opportunities to : -LRB- 1 -RRB- improve health care coverage , -LRB- 2 -RRB- increase the supply of publicly subsidized health clinics , and -LRB- 3 -RRB- direct delivery of preconception screening and interventions in the context of public health programs . Introduction The overarching goal of preconception care is to provide health promotion , screening , and interventions for the more than 62 million women of childbearing age -LSB- 1 -RSB- to reduce risk factors that might affect future pregnancies -LSB- 2 -- 4 -RSB- . As elsewhere in this supplement , preconception care is defined as a set of interventions that aim to identify and modify biomedical , behavioral , and social risks to a woman 's health or pregnancy outcome through prevention and management , emphasizing those factors which must be acted on before conception or early in pregnancy to have maximal impact . It includes care before a first pregnancy or between pregnancies -LRB- commonly known as interconception or internatal care -RRB- -LSB- 5 -RSB- , and care that would typically be delivered in primary care settings -LSB- 4 -RSB- . Health professional leaders and professional organizations ' guidelines have called for improvements in preconception care for more than 20 years -LSB- 4 , 6 -- 9 -RSB- . and several reviews of the literature have assessed the evidence for specific interventions and documented their effectiveness -LSB- 10 , 11 -RSB- . Without changes in financing , however , it appears unlikely that the nation will improve its preconception health and , thereby , improve the health of women , their children , and their families . Since federal and state policies are important drivers of health care financing , this paper provides suggestions on how policymakers can improve financing for preconception care -LSB- 12 -RSB- . Although many observers have suggested that providers would deliver more preconception care if they could bill payers for the service -LSB- 13 -RSB- , a closer look at the situation suggests that more complex changes in women 's health care financing may be necessary to support widespread use of preconception care . Affordability of care is a major concern for many women -LSB- 14 -RSB- . Many women lack basic health coverage , particularly non-pregnant , low-income women who do not meet of Medicaid 's low income eligibility levels -LSB- 15 -RSB- . Securing private insurance coverage for additional preventive services may require more and better evidence about the effectiveness of interventions -LSB- 4 -RSB- . Other barriers to financing are more mechanical . Financing is required for an ongoing care process over a period of years and across the lifespan , not a single visit . Billing mechanisms and codes need refinement ; in addition , cost-benefit analyses , and ongoing alignment with newly emerging approaches to care will also be required -LSB- 16 -RSB- . Improving health coverage for women of childbearing age Financial barriers to health care access are widespread in the United States , with many low-income individuals having no or inadequate health coverage . The Kaiser Family Foundation 's , Women 's Health Survey -LSB- 17 -RSB- does not focus on preconception care , but some of its results are relevant to understanding barriers to women 's health care . Among women of childbearing age -LRB- 18 to 44 years -RRB- 30 percent reported that they delayed or went without care because of cost . Moreover , 21 % of women of all non-elderly women -LRB- 18 to 64 years -RRB- in the survey reported that they did not fill a prescription for medication because of cost , including 40 % of uninsured women -LSB- 17 -RSB- . Uninsured women Millions of Americans live without health coverage . Nearly 17 million American women are uninsured -LSB- 17 -RSB- . One-third of low income women -LRB- with income less than 200 percent of the federal poverty level -RRB- , half of women with disabilities , and 18 percent of all non-elderly women were uninsured in 2003 -LSB- 18 -RSB- . Younger women were more likely than older women to be uninsured . Hispanic , Asian , and Black women were more likely than non-Hispanic white women to be uninsured , reflecting their income and employment status patterns -LRB- i.e. , more likely to have incomes below 200 percent of poverty and less likely to be employed in jobs that offer health insurance -RRB- -LSB- 17 -RSB- . Moreover , recent data indicate that women are more likely to lose coverage than men . Between 2002 and 2003 , nearly 900,000 women ages 18 to 64 became uninsured , compared to 600,000 men -LRB- 53 and 47 percent , respectively -RRB- . Such losses are attributed primarily to welfare reform policies and employer-based coverage trends -LSB- 19 -RSB- . Data for 2002 -- 2003 reveal that the percentage of women ages 18 -- 64 who were uninsured varies substantially , ranging from 30 percent in Texas to 8 percent in Minnesota . The proportion of uninsured low-income adult women shows similar variation , ranging from more than 50 percent in Texas to less than 25 percent in Massachusetts , Minnesota , Tennessee , and Wisconsin . Although to some extent these differences reflect Medicaid eligibility policy , the state-to-state variations also reflect employment patterns . For example , Minnesota had the highest percentage of adult women with private coverage and a fairly low proportion of women covered by Medicaid -LRB- 83 percent and 8 percent , respectively -RRB- . In contrast in Tennessee -LRB- under policies in effect at that time -RRB- , 17 percent of adult women were Medicaid beneficiaries and only 70 percent had private coverage -LSB- 20 -RSB- . Women who are young , single , working part-time , or unemployed are most likely to uninsured . These factors are reflected in an age gradient , the percent of uninsured women ranging from 22 percent among 18 to 24 year olds , 21 percent among 25 to 34 year olds , 19 percent among 35 to 44 year olds , and 13 percent among 45 to 54 year olds -LRB- Fig. 1 -RRB- . Moreover , women ages 25 -- 44 accounted for more than half -LRB- 53 percent -RRB- of all uninsured women under age 65 -LSB- 17 -RSB- . Fig. 1Percent of Non-Elderly U.S. Women who are Unisured , By Age , 2004 Medicaid as a source of coverage for women 's health and PCC Medicaid is effective in improving access to health care for low income women . Medicaid coverage affords women access to essential preventive , primary , and reproductive health care services , thereby allowing them to reduce unintended pregnancy , choose the number and spacing of their pregnancies and , when desired , to plan a healthy birth -LSB- 21 -RSB- . Medicaid plays a particularly important role in financing ambulatory care for women of childbearing age -LSB- 22 -RSB- . While Medicaid coverage and enrollment for women declined during the mid-1990s as a result of changes in health and welfare policies , Medicaid demonstration waiver projects are now being used by some states expand to access to health care for women of childbearing age . Under current Federal and State policies , Medicaid is the primary mechanism for extending health coverage for low-income , uninsured women . In 2003 , 12 percent of all women of childbearing age -LRB- 15 -- 44 years -RRB- and 37 percent of poor women in that age group relied on Medicaid for health care coverage . Because nearly two-thirds -LRB- 63 percent -RRB- of the women covered by Medicaid are of childbearing age -LRB- 19 -- 44 years -RRB- , the program 's performance is related to preconception care access and to the outcomes of pregnancy -LSB- 17 -RSB- . Federal and state policies together define eligibility rules for Medicaid . Data from the Centers for Medicare and Medicaid Services -LRB- CMS -RRB- for female beneficiaries in the year 2000 indicate that 26 percent became eligible because they were pregnant and had low income , while 42 percent had welfare/poverty-linked eligibility -LSB- 23 -RSB- . Federal law requires that states extend Medicaid eligibility to pregnant women with income below 133 percent of the federal poverty level -LRB- FPL -RRB- and many states exceed this level . No similar protections exist for non-pregnant women . As of July 2004 , income eligibility thresholds , mainly parents with dependent children , ranged from 19 percent of FPL in Alabama to 275 percent FPL in Connecticut . Other women were enrolled because they are over age 65 and had below poverty income ; this is a national policy that does not vary by state . Many other low income women do not , however , qualify for Medicaid because they do not have children under age 18 , are not over age 65 , or are undocumented . In addition , Medicaid managed care arrangements have had an impact on the source of services for women in their childbearing years -LSB- 24 -RSB- . Some States have used waiver authority to expand Medicaid coverage to low income , uninsured adults -- particularly the parents of children with publicly subsidized coverage . Parents in low-income families may be covered under so-called Section 1931 expansions , which do not require a waiver . More than 40 states and the District of Columbia provide Medicaid coverage to low-income parents through this option . The majority extend short-term coverage to unemployed parents , while other states extend coverage to parents with incomes to 50 , 100 , or 199 percent FPL , without regard to employment status . Washington State is one state that has used this option to large effect , extending eligibility to 200 percent FPL . In nearly half of states , special waivers include a focus on adults and may have positive impact on coverage for low-income women of childbearing age . Three types of waivers are of particular importance here : -LRB- 1 -RRB- comprehensive waivers broadly designed to cover uninsured adults and make changes to benefits and cost sharing ; -LRB- 2 -RRB- Health Insurance Flexibility and Accountability -LRB- HIFA -RRB- waivers , and -LRB- 3 -RRB- so-called `` family planning '' waivers -LSB- 25 -RSB- . All three types are authorized under Section 1115 of Medicaid and must be budget neutral . Each type of 1115 requires that states apply for and receive approval by the federal Centers for Medicare and Medicaid Services -LRB- CMS -RRB- . Comprehensive and HIFA waivers designed to increase health coverage among low-income adults Nine states offer Medicaid coverage to low-income parents through Section 1115 waivers . All of these nine states extend coverage to families with incomes at or about 100 percent FPL . Again , some states extend coverage only to unemployed parents , whereas others extend coverage to parents with incomes to 50 , 100 , or 199 percent FPL , without regard to employment status . Minnesota 's waiver extends coverage up to 275 percent FPL -LSB- 26 -RSB- . At the beginning of 2006 , 11 states had active HIFA waivers , with the primary goal being to encourage new state approaches that increase the number of low-income individuals with health insurance coverage within current-level Medicaid and SCHIP resources -LSB- 26 -RSB- . Some of these -LRB- e.g. , Maine and Michigan -RRB- extend coverage only to childless adults . More target the expansions to low-income parents with children enrolled in publicly subsidized coverage -LRB- e.g. , Arizona , California , Illinois -RRB- . Still other states sought a waiver for more general expansion of adult coverage . With enactment of the Deficit Reduction Act of 2005 -LRB- DRA -RRB- , states have increased flexibility to extend coverage , structure alternative benefit packages , and adopt premium and cost sharing requirements without a federal waiver . The DRA creates the potential for states to expand coverage to additional low-income adults , and some states -LRB- e.g. , Kentucky , West Virginia -RRB- are considering expansions to parents of children with Medicaid or other publicly subsidized coverage under the State Children 's Health Insurance Program -LRB- SCHIP -RRB- . Such expansions may use limited benefit packages . Family planning and interconception care waivers States have received federal approval for Medicaid waivers programs that offer coverage to low-income women for family planning and reproductive health services . In 2001 , nine state programs served 1.7 million women , and recent studies documented cost savings , reductions of unintended pregnancies , and improved use of family planning services in states with these programs -LSB- 27 -RSB- . By February 2005 , 21 states had created such family planning waivers . In recent years , 21 states have developed special programs to expand family planning services to women who do not otherwise qualify for Medicaid . Some states offer coverage to women who lose coverage after the birth of a baby or starting a job , while others offer family planning coverage based on income status to men and/or women -LSB- 28 -RSB- . Of review of 15 state family planning waivers prepared for the National Association of State Medicaid Directors -LRB- NASMD -RRB- found that core services covered were comprehensive health history and physical examination including appropriate laboratory testing , health education and counseling , approved birth control methods and supplies , and infertility services . Some states provide coverage for services that may be considered preconception care , such as screening for nutrition , folic acid intake , alcohol and tobacco use , genetic conditions , rubella serostatus , domestic violence , and other health risks -LSB- 29 -RSB- . An evaluation prepared for CMS of family planning waiver projects in six states found that they resulted in significant savings to both the Federal and State governments , as well as some evidence for expanded geographic availability of services and measurable reductions in unintended pregnancy -LSB- 30 -RSB- . This is true , despite the fact that the federal government matches state family planning expenditures at 90/10 for each dollar spent . Greater potential savings and prevention , however , could result if States offered coverage for more comprehensive risk screening , health promotion , and interventions leading toward higher levels of preconception wellness . This would require an extension of states waiver authority aimed at coverage of preconception and interconception care . Public financing to improve access to primary care Preconception care is part of a continuum of women 's health services , typically provided in the context of well-woman visits or integral to chronic care management -LSB- 31 -- 33 -RSB- . Most components of preconception care can be embedded in the process of primary and preventive care , rather than an isolated visit -LSB- 34 , 35 -RSB- . Integration of preconception components into primary care can better serve women across the lifespan and at varying levels of risk -LSB- 36 , 37 -RSB- . Primary care integrates a variety of health promotion , prevention , and acute care services to address a majority of personal health care needs and common health problems in a community setting -LSB- 38 -RSB- . It also may include screening for and ongoing management of chronic conditions in a primary care setting . National survey data for 2004 indicate that 75 percent of U.S. women ages 18 to 44 had a health care visit in the past year , and most women of reproductive age obtain preventive health services in any given year -LSB- 17 -RSB- , offering opportunities for clinicians to deliver preconception care . More than half -LRB- 55 percent -RRB- of women had obstetrician/gynecologist visits in the past year . Notably , however , one-third to one-half of women have more than one primary care providers -LRB- generally a family physician or internal medicine physician , and an obstetrician/gynecologist -RRB- -LSB- 14 -RSB- . Some research indicates that having both a reproductive health provider and a primary care provider may increase utilization of clinical preventive services -LSB- 39 -RSB- . Having a usual or routine source of care -LRB- i.e. , a place or provider they usually go when they need health care -RRB- is one indicator of health care access and a predictor of certain health behaviors -LSB- 40 -RSB- . Women who have a usual source of care are more likely to receive preventive care , to receive continuous care , and to have lower health care costs -LSB- 14 -RSB- . As with health coverage , the percentage of women reporting a usual source of care increases with age . Based on detailed survey data from 2002 -- 03 , the proportion of women with a usual source of care was 82 percent for ages 18 -- 24 , 86 percent for ages 25 -- 34 , and 91 percent for ages 35 -- 44 -LSB- 17 -RSB- . Proportions also varied by race and ethnicity , with Hispanic women most likely to report no usual source of care . Non-Hispanic Black women were more likely to use a clinic and Non-Hispanic White women more likely to use a physician office as their routine source of care . These data suggest that publicly subsidized clinics such as community health centers and other federally qualified health centers -LRB- FQHCs -RRB- might be used to increase access to preconception care among low-income and uninsured women . Community health centers -- local , non-profit , community-owned health clinics -- serve more than 15 million people in 3,600 low-income , medically underserved , urban and rural communities . Health centers are an important source of primary care for millions of low-income and uninsured women . Nearly 30 percent of all patients are women of childbearing age , and health centers provided prenatal care to over 330,000 women in 2003 -LSB- 41 -RSB- . Their patients account for one out of every 10 U.S. births -LSB- 42 -RSB- . Research on health centers shows that patients have less infant mortality and low birthweight -LSB- 43 -RSB- , fewer health disparities -LSB- 44 -RSB- , improved care for chronic conditions -LSB- 42 -RSB- , and improved access to primary and preventive care -LSB- 45 -RSB- . A study of four states clinics suggests that FQHCs may be an important source of reproductive health services to reduce unintended pregnancies and teen births -LSB- 46 -RSB- . Among FQHCs , the Health Disparities Collaboratives Initiative is underway to improve the quality of primary care delivered , and over 600 FQHCs have participated -LSB- 47 -RSB- . This quality improvement model is tailored to fit with the staffing and patient patterns of FQHC and is supported by a partnership among community clinics , federal agencies , and national professional organizations . The Health Disparities Collaboratives started with a Chronic Diseases Care Model for quality improvement -LSB- 48 -RSB- , but now are developing a Primary Health Care model and integrating with the Perinatal Care Collaboratives and other efforts -LSB- 49 -RSB- . Health centers receive about one-quarter of their total revenue from direct federal grants . Their single largest source of support is Medicaid , representing more than one-third of total revenues . Patients self-payments , other insurance , and large amounts of non-federal grants and contracts make up most of the remainder of health center funding -LSB- 41 -RSB- . Thus , federal and state fiscal decisions , in Medicaid and other health program appropriations , affect the fiscal well-being of FQHCs . Financing public health programs and projects Existing public health programs serve millions of women each year . Preconception interventions can be incorporated into these existing programs targeted to reach women at highest risk -LSB- 50 -RSB- . Two program examples illustrate the potential , as well as the funding gaps . The federal Family Planning program is authorized under Title X of the Public Health Service Act . Created in 1970 , the Title X program is the only Federal program solely dedicated to family planning and reproductive health with a mandate to provide a broad range of voluntary , affordable , and effective family planning methods and services . The program is particularly designed to provide family planning services to low-income women , many of whom are uninsured and who would have no other source of care . The program provides funds to approximately 4,500 of the estimated 7,000 family planning clinics in the United States and provides reproductive health services to approximately 6.5 million persons each year -LSB- 27 -RSB- . Title X-funded clinics provide family planning education , contraceptives , and pregnancy tests ; however , many do not offer more comprehensive risk screening and reproductive health promotion and reproductive life planning -LSB- 51 -RSB- . If Title X funding had been increased at the rate of inflation from its FY 1980 funding level , it would have been funded at over $ 590 million in FY 2002 -LSB- 52 , 53 -RSB- . Federal funding was set at only $ 288 million for FY 2005 -LSB- 54 -RSB- . Without additional funding , it seems unlikely that Title X clinics will obtain the financial and staff resources to add components of preconception care -LSB- 55 -RSB- . Federal and State public health programs funded by the Title V Maternal and Child Health Services Block Grant have the flexibility to give priority to preconception health and offer support for demonstration projects and evaluations of prevention programs . Authorized under Title V of the 1935 Social Security Act , this program provides block grants to states to improve the health of all women , children , youth and families . Title V funding is an important source of funding for infrastructure building , population-based services , enabling services , and direct health care services . Preconception care is a priority area for some state Title V programs and is being monitored with performance measures in additional states -LSB- 51 -RSB- . Many state Title V agencies have preconception or interconception projects underway or in the design phase , but most of these operate on a small scale or are targeted only to a special population such as teens . Opportunities exist to use Title V block grant and special project funds more broadly to fund related needs assessment , community-based prevention projects , health education , or preconception care for women . Without additional funding , however , it seems unlikely that new priorities will be adopted and new programs implemented by federal or state Title V-funded entities . As part of an overall funding cut for domestic discretionary programs , Congress reduced FY 2006 funding for the Title V program from $ 724 million to $ 700 million -LSB- 56 -RSB- . Although the federally funded Healthy Start projects have interconception health activities , these projects located in communities with high infant mortality have opportunities to offer more systematic pre/interconception screening , health promotion , and interventions . Healthy Start grantees are required to include interconception care activities as part of their overall project . Such activities might include linkage to local providers , tracking postpartum visits , providing case management services , and/or directly provide interconception services -LSB- 57 -RSB- . Because Healthy Start funding is linked to Title V funding overall , resources for more extensive or systematic efforts are limited . Public health programs funded through the Centers for Disease Control and Prevention -LRB- CDC -RRB- , particularly those offering screening and related services for sexually transmitted diseases and HIV/AIDS also could do more to provide preconception risk assessment and health promotion . Such programs targeted to high risk women are not , however , substitutes for access to primary care and health care coverage . Conclusions Public health policy can be correlated to women 's health outcomes -LSB- 58 -RSB- . Three major policy and finance directions are proposed by this review paper . To increase access to care among women of childbearing age , the federal and state governments have opportunities to improve health care coverage , increase the supply of publicly subsidized health clinics , and encourage delivery of preconception screening and interventions in the context of public health programs . First and foremost , state and federal policymakers might increase health coverage for low-income women of childbearing age through Medicaid policy changes and waivers . Although health coverage in and of itself may not change health behaviors and health care utilization -LSB- 59 -RSB- , having access -- financial and geographic -- to a provider can be seen as threshold requirements for improved health care utilization and delivery of preconception care . A second opportunity is to continue to increase support for community health centers and other federally qualified health centers in medically underserved communities . Last , but not least , policymakers might give greater attention to financing for health promotion and prevention programs , particularly programs such as Title X and Title V which focus on services to women of childbearing age -LSB- 60 -- 62 -RSB- .

O B B O O O O O B O B O B O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O B O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O

finance
policy
preconception
medicaid
title v
family planning