Internal Migration and 'Rural/Urban‘
Households in China:
Implications for Health care
1

Origins of POVILL Research
• Anecdotal evidence from poor villages:
 Elderly + young children
 High prevalence of chronic illness
 Vulnerability
• New Cooperative Medical Scheme (NCMS)
 Government subsidy
 Risk fund for inpatient care
• ‘Catastrophic healthcare expenditure’
 Model: Get sick – Buy care – Get well
 Extreme reductionism (Dennett)
2

The Limits of ‘Catastrophic
Healthcare Expenditure
• High expenditure on healthcare (even relative to
income) not necessarily ‘catastrophic’.
• Adoption of approach by policy makers encouraged a
excessive focus on hospital inpatient expenditures
• Variety of mechanisms through which health shocks
and poverty may interact:
 Acute events requiring costly hospital care
 Chronic illness requiring long-term medication
 Less serious but often recurring acute illnesses
 Long-term, possibly progressive, conditions that completely or
partially disable the sufferer
 Stigmatising illnesses may induce loss of status, isolation, rejection
and persecution.
• Poorest often cannot afford ‘catastrophic health
expenditure’. 3

Illness-Poverty Links
(China National Heath Service Survey 2008)
Other
Man made causes
Unemployment
Disease: treatment cost
Disease: low productivity
Natural conditions/disaster
Lack labour
0 5 10 15 20 25 304

The POVILL project
• Aims:
 Understand the potentially complex impacts of
major illness on household livelihoods for a
substantial number of households
 Select households using a probability sampling
approach to make valid statistical inferences to the
overall study area populations.
• Major illness conceived very broadly: health problems
which had the potential to seriously damage household
livelihood strategies.
• Primary causal pathways to impoverishment seen as:
 Increased expenditures on healthcare
 Limitations on household activities, linked to illness-
induced changes in labour demand and supply. 5

Research Methods
• Existing knowledge mainly derived from questionnaire
surveys that collect information on illness, care seeking
behaviour and expenditure, typically on the basis of a
two-week recall for acute illness episodes and a one
year recall for inpatient treatments.
• Even panel surveys have limited ability to capture the
step-by-step process whereby households cope, or fail
to cope, with consequences of ill-health.
• Alternatives:
 Case studies: fascinating but limited scale
 Monitoring surveys: increased reliability but limited
to relatively simple data and modest sample size
 Demographic surveillance sites: interesting
possibility (if one exists), difficult ethical problems.
6

POVILL Approach
• Rapid and reasonably large-scale household
questionnaire survey using cluster sampling of
households within selected study areas:
 identify households substantially affected by
different categories of serious health problem
 estimate the proportions of such households in the
population.
• Sampled households stratified using survey data.
• Probability sample of households within selected strata
• In-depth studies (1-2 person days) of these household
undertaken by teams of social scientists
7

In-Depth Studies
• Collected both quantitative and qualitative data. Specific
intention to derive reasonably reliable estimates of
incomes, expenditures, health care cost, financial
support received, duration of illness or disability, etc.
• Underlying framework was an ‘illness narrative’ to
document the history of each health problem addressed.
• Four main components:
 Narrative and construction of one year time line
 Identification of ‘events’: start points for changes in
health status, treatment, assistance, assets, other.
 Detailed description of events
 Dating/quantifying events to the extent possible
8

Illustrative One-Year Timeline
2006 2007
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Back Village Condition Township Borrow money County
pain. Health worse. Unable Hospital to buy drugs. Hospital
limits Station to farm. Son
activity returns to help
9

Three Transitions
• Demographic
 Low mortality and low Fertility
•Epidemiological
 Acute infectious disease → chronic NCDs
•Economic
 Planned → ‘Socialist Market’
10

Resident and Migrant
Populations
Total Resident at Absent more
Population least 6 months than 6 months
0-14 15.9 20.2 7.6
15-19 9.2 5.9 15.5
20-39 29.9 12.8 63.4
40-49 12.8 14.4 9.6
50-59 15.3 21.5 3.1
60-69 10.2 15.1 0.7
70+ 6.8 10.1 0.2
11

Resident and Migrant
Populations
Population and living away from home
• Internal migration: 30% of
100
rural population. Male
90
Female
• 90% of men and 70% of M-living away
80
women between the ages of F-living away
20 and 35 reported as living
70
away from home for part of
60
year (90% migrate 6 months
age
or longer).
40
• So the resident population is 30
dominated by those under 15
20
(21%) or over 50 (48%).
10
• 16.6% of rural residents aged
65 and over (UK:16%).
0
Population
600 500 400 300 200 100 100 200 300 400 500 600
12

The countryside is exporting good
health and re-importing ill-health.
• First, young and healthy people are more
likely to migrate than elderly people,
leaving the weak and sick at home.
• Second, more serious and incapacitating
diseases and intensive-care conditions
result in a migrant’s return to the home in
the village to seek family support and to
avoid the high medical and living costs in
cities.

Reason given by migrants for
returning home
illhealth
Too old
take Care of family member
Pregnancy, delivery & upbring
can't find job %
marriage
investment
0 5 10 15 20 25 30
14

Self reported serious illness
over previous year
10 15 20 25 30 35 40 45 50
migration left behind
proportion of population(%)
5
0
15 20 25 30 35 40 45 50
15
age

‘Rural/urban’ Households
Elderly + children
Parent + children
Three generation
Elderly only
Nuclear Extended
family family
14% 23% 11% 12%
Members left-
Reunited in
56% behind
Rural/urban urban area
Traditional
household household
40% 60%
Return to care
for others Migrants
44%
couple
single
Return due
to illness 16

Four main health insurance
schemes in China
• Government staff(free medical service,FMS)
 5% population 100% coverage
• Basic Medical Insurance (BMI)
 Urban employees, 28% coverage 2006
• Urban Basic Medical Insurance (UBMI)
 Other urban residents, aim: 100% coverage by 2010
• New Community Medical Scheme (NCMS)
 Rural residents, 57% population, 87% coverage 2007
17

Heath insurance scheme
coverage for migrants in Beijing
BMIS FMS other
2% 2% 3%
CI
6%
none
NCMS 46%
41%
18

Reimbursement of NCMS
19

Chronic illness healthcare costs
20

Urban/Rural and Decentralisation
Poor county Shanghai
Limited health insurance Well funded health insurance
supply
supply
Very limited govt revenue High government revenue
Less enterprises and jobs More enterprises and jobs
Healthy labor exported health Healthy labor imported
demand
Elderly less-healthy remain Ill-
demand
joined by returning ill migrants health
Younger, healthier population
21

Shanghai compared to
Western provinces
• In Shanghai, the government plus
personal financial contribution to the rural
NCMS was around 450 yuan per person
• Compared with only 50 yuan per person
in most provinces in Western China.
22

Questions
• Can segmented (urban/rural) and highly
decentralised health care and health
insurance systems cope with these new
ways of constructing family units?
• What happens next?
• What are the implications for the Chinese
economy?
• How do we conduct research on these
new ‘households’?
23