Introduction
Methods
Search strategy
Results
Effect on OOP health spending
Study | Country | Data source | Out-of-pocket health expenditure (%) | Poverty incidence (%) |
---|---|---|---|---|
Xu et al. 2003 [6] | 59 countries | Household surveys 1991-2000 | 0-10.45 (40% of CTP) | - |
Xu et al. 2007 [1] | 89 countries | Household surveys 1990-2003 | 0-10.00 (40% of CTP) | - |
Saksena et al. 2010 [12] | 51 countries | World Health Survey 2003 | 0.62-29.96 (40% of CTP | - |
Wagstaff & van Doorslaer, 2003 [5] | Vietnam | Living Standard Survey 1998 | 5.13 (40% of CTP) | 3.40%† |
14.20 (10% of TE) | 0.50%‡ | |||
Van Minh et al. 2012 [13] | Vietnam | Living Standard Survey 2010 | 4.60 (of TE) | 2.50%† |
3.90 (40% of CTP) | ||||
Garg & Karan, 2009 [14] | India | Consumer Expenditure Survey 1999-00 | 4.80 (of TE) | 3.24%‡ |
10.70 (of nFE) | ||||
Joe & Mishra, 2009 [15] | India | Consumer Expenditure Survey 2004-05 | 6.10 (of TE) | 4.40%‡ |
12.00 (of nFE) | ||||
Bonu et al. 2007 [16] | India | Consumer Expenditure Survey 2004-05 | 13.10 (10% of TE) | 3.50%‡ |
5.10 (40% of nFE) | ||||
Gosh, 2011 [17] | India | Consumer Expenditure Survey 2004-05 | 5.51 (of TE) | 4.40%‡ |
15.37 (10% of TE) | ||||
Arsenijevic et al. 2013 [18] | Serbia | Living Standard Measurement Survey 2007 | 5.00 (10% > up to | 1.10%† |
20% of TE) | ||||
Ico, RD. 2008 [19] | Philippines | Family Income and Expenditure Survey 2003 | 3.50 (10% of TE) | 14.00%† |
3.80 (10% of CTP) | ||||
Cavagnero et al. 2006 [20] | Argentina | National Survey on Household Expenditure & Conditions of Life Survey 1996-97 | 5.50 (40% of CTP) | 1.70%† |
Tomini & Packard, 2011 [21] | Albania | Living Standard Measurement Survey 2008 | 13.30 (of TE) | 3.61%† |
Mendola et al. 2007 [22] | 5 Western Balkan countries | Living Standard Measurement Surveys 2000-2005 | 1.14- 26.32 (10% of TE) | 0.05-2.80%± |
van Doorslaer et al. 2006 [10] | 11 Asian countries | Household surveys 1995- 2002 | 1.37-5.49 (of TE) | 0.10-3.80%|| |
0.30-3.60%± | ||||
Flores et al. 2008 [23] | India | National Sample Survey 1995–96 (Hospitalized cases) | 29.20-34.15 (10% of TE) | 7.24-7.91%‡ |
Su et al. 2006 [24] | Burkina Faso | Nouna Health District Household Survey 2000-01 | 8.66 (40% of nFE) | - |
Gotsadze et al. 2009 [7] | Georgia | Health Care Utilization and Expenditure Survey 2007 | 11.70 (40% of CTP) | - |
O’Donnell et al. 2005 [25] | 6 Asian countries | Household surveys 1996-2002 | 2.98-15.57 (10% of TE) | - |
van Doorslaer et al. 2007 [26] | 14 Asian countries | Household surveys 1995-2002 | 2.01-15.57 (10% of TE) | - |
0.21-7.13 (40% of nFE) |
Adult deaths
HIV
Non-communicable conditions
Effect on household labour supply and income
Study | Country | Data source | Statistical model | Measure of health shocks | Labour supply effect | Income effect |
---|---|---|---|---|---|---|
Gertler & Gruber, 2002 [47] | Indonesia | Indonesian Resource Mobilization Study panel (1991, 1993) | Ordinary Least Square (OLS), Instrumental Variable (IV) | Change in index of limitations in household’s head ability to perform activities of daily living (ADLs). Index based on a formula using self-reported ability to perform basic and intermediate activities of daily living. | (-)7.60% in hours relative to baseline | (-)10% per capita of baseline earnings |
Yamano & Jayne, 2004 [48] | Kenya | Rural household survey panel (19997, 2000) | Difference-in-difference (DID), OLS | Any adult death; Death of male household head | (-)35-40% off-farm income | |
(-)79%*off-farm income | ||||||
Beegle, 2005 [49] | Tanzania | Kagera Health and Development Survey 4 panels (1991-1994 | Fixed effect regression & Probit model | Death of an adult household member (15–50 years) due to AIDS | (-)66-75%** men’s wage employment within 6 months | ……. |
Lindelow & Wagstaff, 2005 [50] | China | China Health and Nutrition Survey panel (1991, 1993, 1997, 2000) | Fixed effect regression | Worsening of self-assessed health (SAH) of household head by one rating on a 4 point scale (excellent, good, fair and poor) = small health shock; difference of 2–3 ratings = ‘large health shock’ | (-)15%* labour market participation | (-)6.20%* total per capita income |
(-)10%* earned per capita income | ||||||
Wagstaff, 2005 [51] | Vietnam | Vietnam Living Standard Survey panel (1993, 1998) | Fixed effect regression | Decline in log of average body mass index (BMI) among household members aged 18 plus between 1993 and 1998 | ……. | (-)59.90%** total per capita income |
(-)102.60%*** earned per capita income | ||||||
Mete & Schultz, 2006 [52] | Taiwan | Surveys of Health and Living Status panel (1989, 1993, 1996) | Ordered probit model | Heart disease among elderly male; | (-)27.30%*** labour-force participation | ……. |
Stroke among elderly male | (-)72.80%*** labour-force participation | |||||
Wagstaff, 2007 [35] | Vietnam | Vietnam Living Standard Survey panel (1993, 1998) | Fixed effect regression | Death of working age member in urban areas in two or so years before the 1998 survey | ……. | (-)26%*** total income |
(-)36.50%*** earned income | ||||||
Bridges & Lawson, 2008 [53] | Uganda | Ugandan national household survey (2002–2003) | Heckman two-part model | Self-reported ill health (female); Self-reported ill health (male) | (-)6.20*** in paid employment | ……. |
(-)3.90*** in paid employment | ||||||
Yamauchi et al. 2008 [54] | South Africa | KwaZulu-Natal Income Dynamics Study panel (1998, 2004) | Conditional fixed effect logit | Prime-age adult (20–44 years) mortality due to AIDS | (+)20%*** labour force participation (adolescents & female adults) | ……. |
Khan, 2010 [37] | Bangladesh (Dinajpur) | SHAHAR household survey 3 panels (2002–2003) | Fixed effect & random effect regression | Death of a household member in past 2 years; Serious illness of a household member that prevented from doing normal activities in past 1 year | (-)8.63 hours worked in the past week | (-)12.00% per capita earned income last month |
(-)2.61 hours worked in the past week | (-)8.65%* per capita earned income last month | |||||
Ghatak & Madheswaran, 2011 [55] | India | National Sample Survey (2004) | Tobit model | Not able to work due to ailment (illness) | ……. | (-)21.60%** annual household income |
Kadiyala et al. 2011 [34] | Ethiopia | Panel Ethiopian Rural Household Survey panel (1994–1997) | DID, Propensity Score Matching (PSM) | Prime age adult (15–54 years) mortality between 1994 and 1997 | (+)dependency ratio = 0.32*** | ……. |
Rocco et al. 2011 [56] | Egypt | Household Health Utilization and Expenditure Survey, 2002 | Fixed effect regression & IV | Self-reported persistent health problem (disability, disease, injury or any other chronic disease) for at least 3 months during last 12 months | (-)26%*** being employed | ……. |
(-)24*** hours per week | ||||||
Omar Mahmoud & Thiele, 2013 [57] | Zambia | Two-wave household panel (2001, 2004) | DID & PSM | Any prime age (12 years+) death between 1996 and 2001, and after 2001 | ……. | (-)4000-78000 (Zambian Kwacha) per adult-equivalent household income |
Bales, 2013 [58] | Vietnam | Household Living Standards Survey panel (2004, 2006) | Fixed effect Poisson regression | Adult (15–60 years) member bedridden due to illness for 14 days or more in 12 months; Onset of disability (with respect to sight, hearing, memory and concentration, walking and climbing stairs, self-care and understanding and making oneself understood) | (-)7.70%** annual workdays | ……. |
(-)11.90%* annual workdays |
Adult deaths
Other health indicators (activities of daily living, self-assessed health, body mass index, any illness)
HIV
Non-communicable diseases
Effect on household non-medical consumption
Study | Country | Data source | Statistical model | Measure of health shocks | Non-medical consumption | Food consumption | Non-food consumption |
---|---|---|---|---|---|---|---|
Dercon & Krishnan, 2000 [63] | Ethiopia | Ethiopian Rural Household Survey 3 panels (1994–1995) | Generalized method of moments | Females among poor Southern households are too weak to work in last 28 days | (-)1.70-2.30%*** body mass index (BMI) per month | ……. | ……. |
Gertler & Gruber, 2002 [47] | Indonesia | Indonesian Resource Mobilization Study panel (1991, 1993) | Ordinary Least Square (OLS), Instrumental Variable (IV) | Change in index of limitations in household’s head ability to perform activities of daily living (ADLs). Index based on a formula using self-reported ability to perform basic and intermediate activities of daily living | (-)19.50% per capita | ……. | ……. |
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 | ……. | (-)1.80% last week | (-)33.59%*** last 4 months |
Dercon et al. 2005 [65] | Ethiopia | Ethiopia Rural Household Survey panel (1999, 2004) | Panel regression | Death of head, spouse or another person; Illness of head, spouse or another person | (+)2.10% per capita | ……. | ……. |
(-)8.90%* per capita | |||||||
Wagstaff, 2005 [51] | Vietnam | Vietnam Living Standard Survey panel (1993, 1998) | Fixed effect regression | Negative changes in the log of average BMI among household members aged 18 plus between 19993 and 1998 | ……. | (-)17.30%* per capita | (-)16.90% per capita |
De Weerdt & Dercon, 2006 [66] | Tanzania | Nyakatoke Household Survey 5 panels (February-December, 2000) | IV-regression | Medical expenditure and reduced labour supply due to due to illness | (-)7.30%* per adult | (-)4.80% per adult | (-)7.80% per adult |
Beegle et al. 2008 [67] | Tanzania | Kagera Health and Development Survey panels (1991–2004) | Fixed effect regression, IV | Prime-aged (20–55 years) deaths due to AIDS (during 2000–2004) | (-)29.80%** annual per capita | ……. | ……. |
Galiano & Vera-Hernández, 2008 [68] | Colombia | Familias en Acci on household panel (2002, 2003, 2006) | Fixed effect regression | Any illness of adult male (aged 18–65 years) that does not let him perform ADLs in last 15 days | (+)US$9.65*** monthly | (+)US$4.46 * monthly | (+)US$3.87** monthly |
Gertler et al. 2009 [69] | Indonesia | Indonesian Family Life Survey panel (1993, 1997) | Panel regression | Limitations in husband’s ADLs; Limitations in wife’s ADLs. Index based on a formula using self-reported ability to perform basic and intermediate activities of daily living. | (-)21.90% monthly per capita | ……. | ……. |
(-)17.20%% monthly per capita | |||||||
Khan, 2010 [37] | Bangladesh (Dinajpur) | SHAHAR household survey 3 panels (2002–2003) | Fixed effect regression | Death of any household member in past two years | ……. | (-)15.30%* log per capita in last 3 days | (+)45.50%** log per capita in last month |
Linnemayr, 2010 [70] | South Africa | Household survey 6 panels (2001–2003) | OLS | HIV non-affected household screened in last month; HIV affected households screened in last month | (+)27.70%*** monthly total | (+)25%***monthly total | (+)26.20%*** monthly total |
(+)2% monthly total | (+)2.20% monthly total | (+)2.20% monthly total | |||||
Wagstaff & Lindelow, 2010 [36] | Laos | Multi-shock cross-section survey (2008) | OLS | Death of any household member in last 12 months in the richest quintile | (-)67.90%*** annual per capita | (-)18.80% annual per capita | (-)107.20%*** annual per capita |
Alem & Söderbom, 2012 [71] | Ethiopia | Household survey (2008–2009) | Probit regression | Self-reported illness of a family member; Death of a family member | (+)0.60% per adult equivalent | (-)2.70% per adult equivalent | …… |
(-)11.10% per adult equivalent | (-)13.50% per adult equivalent | ||||||
Islam & Maitra, 2012 [72] | Bangladesh | Panel household survey (1998, 2000, 2005) | Fixed effect regression | Big expenditure/income loss due to illness; death of main family earner | ……. | (+)0.02/100 Taka monthly | (+)1.05 per 1000 Taka yearly |
(+)0.31/100 Taka monthly | (+)1.64 per 1000 Taka yearly | ||||||
Powell-Jackson & Hoque, 2012 [73] | Bangladesh | Household survey 2 panels (2007–2008) | OLS | Severe maternal complications (dystocia, haemorrhage, hypertensive disorders of pregnancy, septic shock or septicaemia, severe anaemia) | (-)5.30% monthly per capita | (-)7.50% monthly per capita | ……. |
Genoni, 2012 [74] | Indonesia | Indonesian Family Life Survey 2 panels (1997, 2000) | Fixed effect regression, IV | Deterioration in ability to walk 5 km; Deterioration in Intermediate ADLs (carrying a heavy load for 20 meters, walking for 5 kilometers, bowing or kneeling, sweeping the floor or yard, and drawing a pail of water from a well) | (+)1.60% monthly per capita | (-)4.20% monthly per capita | ……. |
(+)1.20% monthly per capita | (-)3.60% monthly per capita |
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 |