Situational Analysis of Equityin Access to Quality Health

Care for Women and Childrenin VietnamPresentation by

Sarah Bales and Jim Knowles

Ha Long Bay, 8 April 2008

Organization of the Presentation• Purpose• Methodology• Main findings• Data gaps• Interventions to reduce inequality in

MCH• Conclusions

Purpose• Assess the extent of existing inequalities

in key MNCH outcomes• Assess changes over time in the

inequalities, where possible• Identify underlying factors most closely

associated with key MNCH outcomes• Assess the contributions of these factors

to the observed inequalities

Purpose (continued)• Focus is on inequalities, rather than national

averages• Focus is on income inequalities rather than

inequalities with respect to other factors (e.g.,gender, region, ethnicity)

• Why is it important to focus on inequalities?θ To sustain continued improvement in national

averagesθ To achieve an equitable distribution of the benefits of

economic development

Methodology

• Conceptual Framework• Measurement of inequality• Sources of inequality• Analysis of provincial-level data

Conceptual framework

Region levelProvince levelDistrict level

Commune levelVillage levelHousehold

Region levelProvince levelDistrict level

Commune levelVillage levelHousehold

Physical proximityQuality

Affordability

Physical proximityQuality

Affordability

AgeSex

EducationIncome

EthnicityReligionLocation

AgeSex

EducationIncome

EthnicityReligionLocation

Family planningAntenatal care

Obstetric delivery careNeonatal carePostnatal careImmunization

Malaria preventionNutritional supplementsInfant feeding practicesUtilization of safe water

and sanitationCurative care

Family planningAntenatal care

Obstetric delivery careNeonatal carePostnatal careImmunization

Malaria preventionNutritional supplementsInfant feeding practicesUtilization of safe water

and sanitationCurative care

MortalityMorbidity

Nutritional statusFertility

MortalityMorbidity

Nutritional statusFertility

Observed underlying factors

Unobserved factors

Health services

Intermediate outcomes

High-level outcomes

Measurement of inequality• Population-weighted quintiles• Concentration curve• Concentration index (CI)• Living standards measures (LSM)The methodology is described in great

detail in:O’Donnell, O, et al. (2008) Analyzing

Health Equity Using Household SurveyData: A Guide to Techniques and TheirImplementation, Washington, D.C.:World Bank

Population-weighted quintiles

Source: 1992/93 Vietnam Living Standards Survey; 2006 VHLSS

Proportion of children under 5 with moderately low weight for age

051015202530354045

Poorest Nearpoor

Middle Nearrich

Richest

Percent

1992/93 2006

Concentration curve

0.2

.4.6

.81

cum

ul. sh

are

of w

omen

rece

iving

ante

nata

l ser

vices

0 .2 .4 .6 .8 1cumul. share of mothers (poorest first)

weighedblood testultrasoundHIVadviceline of equality

Inequality in the components of a complete antenatal care exam, 2006

Source: 2006 MICS III

Cum

. sha

re o

f wom

e n r e

ceivi

n g a

nten

atal

ser

vices

Concentration index• Definition: Twice the area between the

concentration curve and the line of equality (the45° line).

• The larger the absolute value, the greater theinequality

• Convention is to assign negative values to areasabove the line of equality and positivepositive values toareas belowbelow

• Inequalities may favor or disfavor the poor andfavor or disfavor the rich

Living standards measuresDirect measures• Reported household income per capita• Reported household consumption per capita• Reported household wealth per capita• Average ranking of direct measuresIndirect measures• Predicted household income per capita• Predicted household consumption per capita• Predicted household wealth per capita• Wealth index

Living standards measuresProportions of obstetric deliveries in a hospital by quintile

(using alternative LSMs to define quintiles), 1992/93

Source: 1992/93 Vietnam Living Standards Survey

01 02 03 04 05 06 07 08 09 0

1 0 0

Direct

inc

ome

Direct

co

nsum

ption

Direct

wea

lth

Avera

ge

rank

ing

Indire

ct

incom

e

Indire

ct

cons

umpt

ion

Indire

ct

wealth

Wea

lth

index

Pe

rce

nt P o o r

Near poorA v e r a g eNext richestR i c hes t

Analysis of sources of inequality

• Regression analysis• Decomposition of the concentration

index (i.e., decomposition of theobserved inequality)

• Contribution to inequality depends onelasticity and the concentration indexfor explanatory variables

Decomposition of inequalities for fullantenatal care

0.497Total

-0.012Residual

0.049-12.6222.713Commune fixed effects(combined)

0.4070.3011.352Wealth index

-0.0370.137-0.267Head of household isVietnamese or Chineseethnicity

0.0160.0770.208

Highest education of adultsin household

0.0590.1320.449Mother’s schooling

0.0140.0140.999Mother’s age (years)

ContributionConcentrationindicesElasticitiesVariable

Decomposition of inequalityDecomposition of concentration index for antenatal care and

full package of antenatal care, 2006

Source: 2006 MICS III

-0.10

0.00

0.10

0.20

0.30

0.40

0.50

Age ofmother(years)

Mother'sschooling

Highestschooling

EthnicVietnameseor Chinese

Wealthindex

Communefixed effects

"Residual"

Cont

ribut

ion

Any antenatal care (0.059)Full antenatal (0.497)

Offsetting factor

Analysis of provincial data• Outcome data available from surveys and

Health Statistics Yearbook by province• Living standard measure is mean

household income per capita• Concentration curves, indices and

decompositions• Complements analysis at the household

level

Main findings

High level outcomes• Child mortality• Maternal mortality• Morbidity• Nutritional status• Fertility

Intermediate outcomes• Family planning• Antenatal care• Obstetric delivery care• Immunization• Malaria prevention• Nutritional supplements• Infant feeding practices• Curative care

Important achievements inimproving basic health indicators

2.12.25TFR (births perwoman)

23.431.9Child malnutritionrate (%)

2642U5MR (per 1000 livebirths)

1631IMR (per 1000 livebirths)

7595MMR (per 100 000live births)

20062001

Important achievements inimproving access to health care

61.739.1% of children under 5 completelyvaccinated (according to mother’sreporting)

84.454.7% of women delivering at health facility

87.773.6% of women receiving professionalassistance at delivery

91.259.5% of pregnant women receivingantenatal care

75.666.1Contraceptive prevalence amongmarried women (%)

20061992/93

Important variation in degree ofinequality

• The degree of inequality in both high-leveloutcomes and intermediate outcomesvaries greatly.

• As a reference point for this comparison,the Gini-coefficients (basically theconcentration indices for living standardsvariables) using the 2006 MICSIII are:– Wealth index (0.297)– Estimated consumption (0.394)

Variation in inequality for high-leveloutcomes

Inci

denc

e of

re

spira

tory

in

fect

ion

Fert

ility

Diar

rhea

Stun

ting

Und

erw

eigh

t

% o

f chi

ldre

n w

hose

mot

her h

as

died

-0.60

-0.50

-0.40

-0.30

-0.20

-0.10

0.00C

once

ntra

tion

inde

x

Variation in inequality for selectedintermediate outcomes (1)

Any

ante

nata

l ca

re

Wei

ghed

Bloo

d pr

essu

re

mea

sure

d

Ultra

soun

d

Urin

e te

st

Bloo

d te

st

HIV

advi

ce

Full

ante

nata

l

0.00

0.10

0.20

0.30

0.40

0.50

0.60C

once

ntra

tion

inde

x

Variation in inequality for selectedintermediate outcomes (2)

Full

dose

of a

ll va

ccin

es

BC

G Polio

DPT

Mea

sles

Full

dose

in fi

rst

year

of l

ife

0.00

0.10

0.20

0.30

0.40

0.50

0.60C

once

ntra

tion

inde

x

Changes in inequality over time• There has been significant improvement in

reducing inequalities in some intermediateoutcomes, but little improvement inreducing inequalities in several higher-level outcomes

Reduced inequality over time• Use of contraception• Any antenatal care• Professional assistance at delivery• Facility or hospital delivery

Almost complete reduction ininequality for use of contraception

% of married women using contraception

0%

20%

40%

60%

80%

100%

Poorest Nearpoor

Middle Nearrich

Richest

1992/932006

Important reduction in inequality foruse of any antenatal care

0.2

.4.6

.81

cum

ul. s

hare

of a

ny a

nten

atal

car

e

0 .2 .4 .6 .8 1cumul. share of pregnancies (poorest first)

1992/932006line of equality

Important improvements in middlequintiles for obstretic care

% of deliveries with professionally assistance

0%

20%

40%

60%

80%

100%

Poorest Nearpoor

Middle Nearrich

Richest

1992/932006

Less improvement in inequality forhigh-level outcomes

• Child malnutrition• Child mortality• Incidence of diarrhea• Fertility

Increased inequality in stunting0

.2.4

.6.8

1

cum

ul. s

hare

of s

tunt

ed c

hild

ren

0 .2 .4 .6 .8 1cumul. share of children (poorest first)

consumptionwealth indexline of equality

0.2

.4.6

.81

cum

ul. s

hare

of s

tunt

ed c

hild

ren

0 .2 .4 .6 .8 1cumul. share of children under 5

wealth indexdirect consumptionline of equality

1992/93 2006

Lowinequality

Higherinequality

No reduction in inequality in childmortality

Child mortality

0102030405060708090

Poorest Nearpoor

Middle Nearrich

RichestDea

ths

per

1000

chi

ldre

n ev

er b

orn

1992/932006

Gap in 1992/93

Gap in 2006

Slow reductions in poorer groups

Number of children ever born

0.00.51.01.52.02.53.03.5

Poorest Nearpoor

Middle Nearrich

Richest

1992/932006

Slower Faster

Factors examined for theircontribution to inequalities

• “Income”• Education of mother, of adults in

household• Ethnicity• Mother’s and father’s nutritional status• Location (communal fixed effects)• Sex• Religion

Main factors affecting inequalityThe main factors contributing to the observed

inequalities in maternal and child healthoutcomes are:

• Inequalities in household “income”• Inequalities related to location (i.e., to the

commune of residence).Other important factors for some outcomes

include:• Inequalities in education• Inequalities in ethnicity

Factors contributing to inequalitiesin child malnutrition, 2006

Ethnic Vietnamese or Chinese

Child's age

Sex

Mother's schooling

Mean adult schooling Commune

fixed effects

Wealth index-0.16-0.14-0.12-0.10-0.08-0.06-0.04-0.020.000.020.04

Cont

ribut

ion

to in

equa

lity

Height for age (-0.181) Weight for age (-0.167)

Factors contributing to inequalitiesin incidence of diarrhea, 2006

Commune fixed effects

Ethnic Vietnamese or Chinese

Wealth index

Child's sex

Mean adult

schooling

Mother's schooling

Child's age

-0.20

-0.15

-0.10

-0.05

0.00

0.05

0.10Co

ntrib

utio

n to

ineq

ualit

y

Concentration index (-0.136)

Factors contributing to inequalitiesin obstetric care, 2006

Ethnic Vietnamese or Chinese

Commune fixed

e f fec ts

Wealth index

Highest adult

schoolingWoman's schoolingWoman's

age 0 . 0 0

0 . 0 2

0 . 0 4

0 . 0 6

0 . 0 8

0 . 1 0

0 . 1 2

0 . 1 4

Con

trib

utio

n to

ine

qual

ity

Professionally assisted delivery (0.096)Facility-based delivery (0.116)Hospital delivery (0.218)

Factors contributing to inequalitiesin child immunization, 2006

Sex

Commune fixed

e f fec ts

Wealth index

Ethnic Vietnamese or Chinese

Mother's schooling

Highest adult

schooling

Days survived

- 0 . 3 0- 0 . 2 5- 0 . 2 0- 0 . 1 5- 0 . 1 0- 0 . 0 50 . 0 00 . 0 50 . 1 00 . 1 50 . 2 0

Cont

ribut

ion

to in

equa

lity

Complete vaccination in first year (0.235)No vaccinations (-0.535)

Contribution of education toinequality

• Women’s/mother’s schooling is not asclosely related to many of the outcomesanalyzed as is the schooling of other adulthousehold members

Parental nutrition• Nutritional status of father and mother are

significantly associated with child’snutritional status (only available in the1992/93 VLSS).

A child’s sex is not significantlyrelated to any of the outcomes

analyzed in 2006

01020304050607080

Stun

ted

Unde

rwei

ght

Diar

rhea

Coug

h an

dfe

ver

Ill p

ast 4

wee

ks

Full

imm

uniza

tion

Full

imm

uniza

tion

first

yea

rEx

clus

ive

brea

stfe

edin

g6

mon

ths

Vita

min

A

Perc

ent

MaleFemale

Analysis of commune fixed effects• In some cases, commune effects explain a large proportion of

the concentration index.• Important commune level factors include:

– Mean education of adults in households in the commune(for most outcomes)

– Regions (Southeast and Mekong Delta better thanaverage, Northwest, Central Highlands worse thanaverage)

– Proportion ethnic Vietnamese or Chinese in commune– Road goes to center of commune (family planning,

antenatal care, obstetric care)– Proportion Catholic in the commune (fertility, use of family

planning)

EthnicityAnalysis of province-level data, commune

fixed effects and household level data allindicate that ethnicity is an important factorin inequality for many outcomes (IMR,fertility, malaria morbidity, antenatal care,births attended by health worker, childimmunizations).

Fertility and IMR, 2005

Factors contributing to inequality in fertility in provincial analysis

Income

Urbanization

Infant mortality

Residual

Population density

Schooling

Ethnicity

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04

Cont

ribu

tion

Inequalities in governmenthealth spending, 2005

0.2

.4.6

.81

cum

ul. s

hare

of g

ovt

heal

th e

xpen

ditu

re

0 .2 .4 .6 .8 1cumul. share of population (poorest first)

total health expenditurenational program expendituretreatment & prevention expenditureother expenditureline of equality

Pro-poor nationalprogramspending

Pro-rich curative carespending

Indicators of access to curative caredisfavoring the middle income provinces, 2005

0.2

.4.6

.81

cum

ul. s

hare

of p

opul

atio

n w

ith a

cces

s to

car

e

0 .2 .4 .6 .8 1cumul. share of population (poorest first)

medical doctorsinpatient bedsHI coverageline of equality

Pro-poor

Pro-rich

Data gapsThere are still several important data gaps in

the area of maternal-child health in VietNam that need to be addressed to supporteffective monitoring of inequalities inmaternal and child health

Missing data• Maternal nutritional status (to understand

the intergenerational associations withchild malnutrition)

• Complete birth history data is missing forrecent years

• Information on number of antenatal exams

Need for revising surveyinstruments

New or newly available interventions requireconstant revision of survey instruments.For example:– Zinc supplements and use of zinc to treat

diarrhea,– Vitamin K injections at birth,– Use of folic acid and/or iron during pregnancy,– Use of deworming medicines,– Post-natal exams,– Delivery by C-section.

New data collection methodologies

New developments and reductions in cost ofdata collection methods also requireconsideration:

• anemia testing,• HIV testing (with consent),• information about delivery complications,• oral autopsy about child deaths, etc.(Good example is the Cambodian DHS)

Inadequacy of current HISDifficulties in using HIS data for health

equity analysis, either because of:• Under-reporting of pregnancies/births• Only partial coverage (Doesn’t include

private services).• Missing indicators of quality aspects

Interventions to reduce inequality inMaternal and Child health (1)

• Extensive public health infrastructure in alllocalities throughout the country

• Numerous pilot projects (mainly NGO) toreduce mortality among newborns focused atthe grassroots level

• Population and family planning programfocusing efforts and budget in areas withremaining high fertility

Interventions to reduce inequality inMaternal and Child health (2)

• National health target programs focusingefforts and budget on disadvantaged areas

• Military-civilian medical cooperation forborder areas, disaster areas

• School health programs• Targeted health financing for the poor, for

children under age 6

Conclusions (1)• Most government health programs have

been very effective in Viet Nam inimproving average health status amongmothers and children

• For most intermediate outcomes, theyhave been effective in reducinginequalities

• For higher-level outcomes reduction ininequality has been less successful

Conclusions (2)• Income and commune-level factors

explain much of the inequality• Education and ethnicity also contribute

importantly to inequality for someoutcomes

• At the commune level, general educationallevel, region, ethnicity, road access andeven religion explain some of theinequalities

Conclusions (3)• Important data gaps inhibit monitoring of

inequality in some aspects of maternal and childhealth

• Government and non-governmentalinterventions need to increasingly focus effortsand budget on disadvantaged areas or groupswhere outcomes are worse.

• There is a need for interventions on bothdemand and supply side.