Longitudinal Analysis of the Longitudinal Analysis of the Relationship between Migration and Relationship between Migration and

Health StatusHealth StatusStudy of Adult Population of IndonesiaStudy of Adult Population of Indonesia

Salut Muhidin, Dominic Brown & Martin Bell

4th International Conference on Population Geographies12 July 2007, Hong Kong

What’s New?What’s New?• Some studies have been done on the link between migration (M) & health (H).

Among others:

UK (Bentham 1988; Boyle et al. 1999 & 2001; Dorling 1998)USA (Findley 1988; Kington et al. 1998)NL (Verheij et al. 1998)Australia (Larson et al. 2005)

• The studies are applied in the context of developed countries. YET, it is still little known in the developing countries. One of its main reason is data limitation.

• The ideal design for testing the M-H relationship requires life histories data, with appropriate information on background characteristics at different points in the life cycle

• Fact: Indonesia has now a longitudinal data which cover information on migration and health. IFLS

• The contribution here: – Investigating the relationship M-H in the context of a developing country– Using the available longitudinal data, i.e. IFLS

Research QuestionResearch Question

• Is there any relationship between migration and health in the context of Indonesia?

Q1 Do migrants differ from non migrants in terms of health and socioeconomic status?

Q2 Does the probability of migration depend upon the health status accounting for socioeconomic variables?

Health Migration

Side 1: MigrationSide 1: Migration

• Determinant of Migration– It is strongly related to particular

personal traits and some important life events: e.g. education, marriage and separation, job related, and retired (elderly). Age regularities in migration (Rogers and Castro, 1980)

• Dimension Migration :– Time: Permanent - temporary

(Intention to stay)– Distance: short - long– Geographic: Internal and

international (urban-rural)

Standard Curve

0

0.005

0.01

0.015

0.02

0.025

0.03

0.035

0.04

0 10 20 30 40 50 60 70 80 90

Age

Mig

rati

on

Ra

te

Side 2: Health Side 2: Health

• Health has multi dimensions– It has been linked to many

factors: physical, mental, and social well-being, genotype and phenotype, gender and place of residence.

• Health measures:– General Health Status (GHS)– Physical ability (ADL)– Chronic illness– Mental Health, or– Health related behaviors, etc.

Data SourceData Source• Indonesia Family Life Survey (IFLS)

– Longitudinal survey • 3 waves: 1993, 1997, and 2000

– Organizer• RAND, University of Indonesia and Gadjah Mada

University

– Coverage• 13 provinces (83% population of Indonesia)• 7,224 HH (Base in 1993) • 6,820 HH (94% were re-interviewed)• 33,081 people (Base in 1993)

Data StructureData StructureIFLS-1 IFLS-3

Stayed or Moved away Health

Status1997

Health Status2000

All respondents

Re-tracked respondents

Health Status1993

IFLS-2

Stayed orMoved away

MigrationHistory

Data StructureData Structure

IFLS 1993N=33,081

Age 15<11,451

Age 15+21,630

Healthinfo

12,985

Migrationinfo

21,630

Health 93Migration 93-97

N = 12,985

IFLS 1997(MH93)

N=12,985

Died (454)No traced

(165)

Traced12,366

Healthinfo

11,495

Migrationinfo

12,366

Health 97Migration 97-00

N = 11,495

Variable: MigrationVariable: Migration

• Definition of Migration

It is based on the status of leaving (staying) or changing their usual residence as recorded at the baseline (previous) survey Current Migration– IFLS2 = Migration 1993-1997– IFLS3 = Migration 1997-2000

• Type of Migration

Short Distant (inter village and district) and Long Distant

Information on migration characteristics (age, destination and reasons) of those who have moved was also collected.

Variable: Health StatusVariable: Health Status• General Health Status (GHS): Self reported

GHS was generated from a question “In general, how is your health at this time?” The answers were: (a) Very healthy, (b) somewhat healthy and (c) somewhat unhealthy or (d) unhealthy.

• Activity of Daily Living (ADL): Reported & observed

ADL was constructed by using nine questions if the respondent could do (was capable of) certain daily activities. The answers were three possibilities: “easily”, “with difficulty”, and “unable to do”. It includes three functions:

(1) mobility (to walk 5 kilometers; to bow, squat, and kneel; to stand up from sitting in a chair or from sitting on the floor),

(2) personal care (i.e. to dress and to go to the bathroom without help);

(3) home occupation (i.e. to carry a heavy load; to sweep; and to draw a pail of water).

ResultsResultsProportion of MigrationProportion of Migration

Current

Note: GHS (General Health Status) and ADL (Activity of Daily Living)

Migration 1993-1997

0.00

0.05

0.10

0.15

0.20

0.25

Migrated (all) Good GeneralHealthy

Less GeneralHealthy

GoodPhysicalAbility

Less PhisycalAbility

GHS ADL

Migration 1997-2000

0.00

0.05

0.10

0.15

0.20

Migrated (all) Good GeneralHealthy

Less GeneralHealthy

Good PhysicalAbility

Less PhisycalAbility

Current

Figure 1. Probability of Migration in 93-97 based on the Health Status in 1993

0.00

0.10

0.20

0.30

0.40

0.50

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60+

Migrated (all)

Good General Healthy

Less General Healthy

Good Physical Ability

Less Phisycal Ability

Current

Figure 2. Probability of Migration 97-00 based on the Health Status in 1997

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

<15 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60+

Migrated (all)

Good General Healthy

Less General Healthy

Good Physical Ability

Less Phisycal Ability

ModelsModels

• Model 1 SelectivityWhat is the probability of migration with respect to the health status (does migrant has better health?). Migration(93-97) = f (Health 93)

Migration(97-00) = f (Health 97)

• Model 2 State DependencyWhat is the probability of migration with respect to the current and previous health status. Migration(97-00) = f (Health 93, Health 97) Migration(97-00) = f (Health 97) among Healthy Pop.93

• Logit Regression Model: the dependent variable is (1) Migration or (0) No migration

Health Status Short-Move Distant-Move All Move

GHS-93 + (OR=1.013) - (0.995) - (0.986)

ADL-93 + (OR=1.160) + (1.599)*** + (1.294)***

Model 1A: SelectivityModel 1A: SelectivityMigration(93-97) = f (Health 93)Migration(93-97) = f (Health 93)

Health Status Short-Move Distant-Move All Move

GHS-93 - (0.952) - (0.930) - (0.949)

ADL-93 - (0.960) + (1.075) - (0.980)

Without Control Variable

With Control Variables

Yet: significances are washed out by covariates

Health Status All-Move Short-Move Distant-Move

GHS-97 + (OR=1.113)** + (1.195)** + (1. 814)

ADL-97 + (OR=1.421)*** + (1.151)*** + (1.021)***

Model 1B: SelectivityModel 1B: SelectivityMigration(97-00) = f (Health 97)Migration(97-00) = f (Health 97)

Health Status All-Move Short-Move Distant-Move

GHS-97 - (0.996) + (1. 036) - (0.914)

ADL-97 - (0.991) - (0.885) + (1.243)***

Without Control Variable

With Control Variables

Yet: significances are washed out by covariates

Health Status All-Move Short-Move Distant Move

GHS-93 - (OR=0.491)*** - (0.552)*** - (0.440)***

GHS-97 + (OR=1.160)*** + (1.195)*** + (1.082)

ADL-93 - (OR=0.474)*** - (0.537)*** - (0.424)***

ADL-97 + (OR=1.547)*** + (1.319)*** + (2.029)***

Model 2A: DependencyModel 2A: DependencyMigration(97-00) = f (Health 93, Health 97)Migration(97-00) = f (Health 93, Health 97)

Health Status all-Move Short-Move Distant-Move

GHS-97 + (OR=1.152) + (1.206) + (1.001)

ADL-97 + (OR=1.308)*** + (1.109) + (1.743)***

Model 2B: DependencyModel 2B: DependencyMigration(97-00) = f (Health 97) among Healthy 93Migration(97-00) = f (Health 97) among Healthy 93

0.00

1.00

2.00

All-Move Short-Move Distant-Move

GHS97

ADL97

0.0

1.0

2.0

15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60+ Male

All Moves

Short-Move

Distant-Move

Age & Sex

Education

0.0

6.0

12.0

No Education Primary Secondary Tertiary

All Moves

Short-Move

Distant-Move

CovariatesCovariates

Age Groups: 15-19, 20-24….60+

Sex: Male (1) Female (0)

Education: Primary, Secondary, Tertiary

Employment: Working (1)

Expenditure: 21-40%, 41-60%, 61-80%, 81-100%

Marital Status: Union (1)

Birth Place: Urban (1)

Current Residence: Java-Bali (1)

ConclusionConclusion• Longitudinal data (IFLS survey) offers the possibility

– To assess the relationship Health – Migration in Indonesia– To evaluate the selectivity & dependency

• In the context of Indonesia:– The relationship between Health and Migration tends to be

positive– People with good health status (ADL in particular) are more

likely to be positively associated with migration (Mig 97-00 in particular)

– YET, the significances are often washed out by other socio-economic covariates.

• Age Separation: Young & Older• Data: Focus on IFLS2 & IFLS3• Health Measurement

DiscussionDiscussion

• Measurement of Health

• Measurement of MigrationDifferent Result?

• More Questions: – Health Changes: Improved, Deteriorated, Stable

“Does health improve or deteriorate with migration?”

– Changes in socio-economic variables:employment status, marital status, & income

– Relationship Migration Health Status

Thank You…Thank You…