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Table 4 Coping strategies adopted by households in response to health shocks in low and middle income countries

From: Economic impacts of health shocks on households in low and middle income countries: a review of the literature

Study

Country

Data source

Statistical model

Measure of health shocks

Coping strategies

Phung Duc & Waibe, 2009 [77]

Vietnam

Cross-sectional survey data, June-August 2007

Fixed effect regression

Idiosyncratic demographic shocks (death or illness of a household member) since 2002

11%-13%*** higher number of income sources used

Kruk et al. 2009 [30]

40 LMICs

World Health Survey, 2002-2003

Multiple logistic regression

Any health expenditure in last one year

***African households 87% and Southeast Asian households 61% more likely (compare to European households) to borrow or sell assets to finance health expenditure

Gertler et al. 2009 [69]

Indonesia

Indonesian Family Life Survey panel (1993, 1997)

Panel regression

Individual’s limitations in performing ADLs. Index based on a formula using self-reported ability to perform basic and intermediate activities of daily living.

***Smaller effects on consumption for households within 1 km of financial institution compared to within 10 km or more

Islam & Maitra, 2012 [72]

Bangladesh

Panel household survey (1998, 2000, 2005)

Fixed effect regression

Household incurred any big expenditure/income loss due to illness in past one years; Whether the main income earner died in the last one year

**Access to microcredit helps to insure consumption

Powell-Jackson & Hoque, 2012 [73]

Bangladesh

Household survey 2 panels (2007–2008)

Panel regression

Severe maternal complications (dystocia, haemorrhage, hypertensive disorders of pregnancy, septic shock or septicaemia, severe anaemia)

*** US$17 borrow per month, **US$4 asset sale and ***US$4.4 transfer per month compared to normal delivery to fully smooth consumption

Dercon & Krishnan, 2000 [63]

Ethiopia

Ethiopian Rural Household Survey 3 panels (1994–1995)

Generalized method of moments

Male or female household members are too weak to work in last 28 days

Household with more land are able to insure consumption

Asfaw & Braun, 2004 [64]

Ethiopia

Ethiopian Rural Household survey panel (1994, 1995)

Two-stage least square

Self-reported illness of household head within 4 weeks before the survey

Able to protect food consumption using own production and gifts

Park, 2006 [78]

Bangladesh

Matlab Health and Socioeconomic Survey, 1996

Two-stage least squares & Instrumental Variable

Income shocks out of death or illness of household members

**Relationship between neighbours and relatives helps in pooling risks to smooth food consumption

Sparrow et al. 2012 [79]

Indonesia

Socio-economic survey panel (2003, 2004)

Fixed effect regression

Household welfare affected during the last year by an event related to illness

15%*** used borrowing; 9%*** used selling assets;

22%*** used family assistance; 9%*** reduced consumption

Abegunde & Stanciole, 2008 [42]

Russia

Life Standards Measurement Survey (8 rounds: 1997–2004)

Two-part Heckit model

Adults reporting chronic disease

7%*** increase in transfer income (gifts) per increase in household number of chronic diseases

Nguyen et al. 2012 [80]

Vietnam

Survey on 706 households (2008)

Multiple logistic regression

Hospitalization

Odds ratio = 18** (using loans);

Odds ratio = 44* (reducing food consumption)

Raccanello et al. 2007 [81]

Mexico

Survey on 400 pawnshop users, 2005

Probit regression

Health expenditure due to persistence health shocks

(+) households used pawning to finance OOP health expenditure**

Modena and Gilbert, 2011 [82]

Indonesia

Family Life Survey, 1993

Poisson Multinomial Model

Demographic shocks (family deaths or illness)

(+) taking loans***;

(+) selling assets***;

(+) using family assistance***

Debebe et al.[83]

Ethiopia

Household survey, 2011

Probit regression

(self-reported illness, death or disability)

(+) 15%*** borrowed;

(+) 17%*** used savings;

(+) 17%*** sold assets;

Dhanaraj, 2014 [84]

India (Andhra Pradesh)

Young Lives survey panel (2006, 2009)

Multinomial logistic regression

Serious illness or death of father affected household economy negatively since the interviewer’s last visit

(+) 49%*** labour supply; (-) 93% *** consumption;

(+) 53% borrowed or sold assets; (+) 54% received help

Alam & Mahal, 2014 [43]

4 South Asian countries

World Health Survey, 2002-2003

Propensity Score Matching (PSM)

Diagnosed or symptomatic angina

(+) 6-10%** households borrowed or sold assets to finance OOP health expenditure

  1. Statistical significance at the level of 1%***, 5%** and 10%*.