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Longitudinal Analysis of the Relationship between Migration and Health Status

Longitudinal Analysis of the Relationship between Migration and Health Status. Salut Muhidin, Dominic Brown & Martin Bell 4 th International Conference on Population Geographies 12 July 2007, Hong Kong. Study of Adult Population of Indonesia. What’s New?.

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Longitudinal Analysis of the Relationship between Migration and Health Status

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  1. Longitudinal Analysis of the Relationship between Migration and Health Status Salut Muhidin, Dominic Brown & Martin Bell 4th International Conference on Population Geographies 12 July 2007, Hong Kong Study of Adult Population of Indonesia

  2. 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

  3. Research 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

  4. Side 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)

  5. 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.

  6. Data 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)

  7. Migration History Data Structure IFLS-1 IFLS-2 IFLS-3 Stayed or Moved away Stayed or Moved away Health Status 1993 Health Status 1997 Health Status 2000 All respondents Re-tracked respondents

  8. Data Structure Health info 12,985 IFLS 1993 N=33,081 Age 15+ 21,630 Health 93 Migration 93-97 N = 12,985 Age 15< 11,451 Migration info 21,630 IFLS 1997 (MH93) N=12,985 Health info 11,495 Traced 12,366 Health 97 Migration 97-00 N = 11,495 Died (454) No traced (165) Migration info 12,366

  9. Variable: 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.

  10. Variable: 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).

  11. ADL GHS ResultsProportion of Migration Current Note: GHS (General Health Status) and ADL (Activity of Daily Living)

  12. Current

  13. Current

  14. Models • Model 1  Selectivity What 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 Dependency What 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

  15. Model 1A: Selectivity • Migration(93-97) = f (Health 93) Without Control Variable With Control Variables Yet: significances are washed out by covariates

  16. Model 1B: Selectivity • Migration(97-00) = f (Health 97) Without Control Variable With Control Variables Yet: significances are washed out by covariates

  17. Model 2A: Dependency • Migration(97-00) = f (Health 93, Health 97)

  18. Model 2B: Dependency • Migration(97-00) = f (Health 97) among Healthy 93

  19. Covariates 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) Age & Sex Education

  20. Conclusion • 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

  21. Discussion • Measurement of Health • Measurement of Migration • Different 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

  22. Thank You…

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