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Prevalence of Health Shocks and the Influencing Factors: Evidence from Rural Bangladesh

Muntaha Rakib
Associate Professor
Department of Economics, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh

Abstract/ Executive Summary:

To explore the factors associated with the prevalence of health shocks faced by low income people in rural Bangladesh is the major focus of the paper. This paper uses the country representative data called Bangladesh Integrated Household Survey (BIHS) which covers the period 2015 conducted by International Food Policy Research Institute (IFPRI). A simple Probit regression was performed to explore factors associated with the incidence of health shocks, particularly illness and skipping work due to illness. Several influencing factors of health shock exposure are identified; such as household characteristics, health care access and supply-side indicators such as accessibility to different facilities. The study finds that households prevalence to health shocks and experiences of illness are positively associated with increase in consumption while less educated and less affluent households are more hardly affected by health shocks. Access to medical facilities apart from access to financial markets is among the other major influencing factors of health shock prevalence. The finding of the paper is expected to provide evidence for policy-makers in designing health protection mechanisms and targeting the affected people.

Keywords: Health shock, Shock prevalence, Influencing actors, Bangladesh

Location: In Bangladesh

Start Date: 00-00-2015

End Date: 00-00-2015

Program Area: Socio-economic and Policy

Non-commodity: Climate change, Income generation

Objectives:

To understand the severity of health shocks and the influencing factors which correlate with the exposure to health shocks.

Methodology:

The investigation of health shock has become a major concern now-a-days. A good number of research works exist on various types of shocks especially on climatic shocks though health shock has been comparatively less travelled. Among the literature on health shocks, some previous works investigated the effects of health shocks on economic indicators either in urban and rural areas (Wagstaff, 2007; Mitra, 2015). Others worked on the determinants of health (Currie 1999; Pitt 1997; Hartwig, 2008). Health shock is the most unpredictable, burdensome but common of all shocks (Krishna, 2010; Adam Wagstaff, 2010). Losses in utility or social welfare can be used as a measure of health shock. The economic costs of illness include both the cost of seeking health care and the loss of income associated with a fall in labour supply and productivity (Genoni 2012). From the previous literature it is found that there are two important economic costs allied with illness – i) the cost of the medical care used to diagnose and treat the illness, and ii) the loss in income associated with reduced labor supply and productivity (Dhanraj 2014). This large cost suggests that the indirect cost of a household member being sick and not being able to work has severe consequences. Consequences of health shocks can be measured through food and non-food consumption, income, asset, medical cost, health itself. All of these indicators increase the economic cost of seeking health care, fall in income or asset, fall in labor supply, and fall in productivity (DeLeire, and Manning, 2004, Dercon and Krishnan, 2000). Thus the economic consequences can be dire and people may be trapped into persistent poverty (Dercon and Hoddinott, 2004; Grant, 2005). Skipping work due to illness reduces wages (Schultz and Tansel, 1997) while severity of health shock also affect the consumption insurance (Gertler and Gruber, 2002; Wagstaff, 2005). Data: The country representative data used in this study called Bangladesh Integrated Household Survey (BIHS) which covers the period 2011 conducted by International Food Policy Research Institute (IFPRI). The data is representative at the following levels: (1) nationally representative of rural Bangladesh; (2) representative of rural areas of each of the administrative divisions of the country (3) representative of the Feed the Future (FTF) Zone of Influence (ZOI) in south-western Bangladesh. A stratified sampling in two stages was used to calculate the total BIHS sample size of 6,500 households in 325 primary sampling units (PSUs) or villages by using the sampling frame developed from the community series of the 2001 population census of Bangladesh. Description of Variables: A simple probit model is estimated to investigate the factors associated with health shock incidence. The dependent variable is health shock which is consisted of i) death and ii) illness in the household level. Death is defined whether the main income earner in the family member or any other family member died in the last 5 years (after the baseline). Illness shock is defined if the household incurred loss of income due to illness or injury of household member or if there is medical expenses due to illness or injury of household member. Therefore, health shock is defined if the household with binary dependent variable that takes a value of 1 if any member of the household was sick for any kind of coping strategy, and 0 otherwise has been used by household when they get affected by two types of health shocks such as, death and illness. This study measured health shocks in household level on the notion that health shocks such as illness are mostly contagious in nature and often affects all members of the households. Besides, the activity and exposure of one household member affects the other member explicitly. Death of a household member on the other hand, affects the whole household especially the death of an earning member.

Source of Information: Res. Agric. Livest. Fish. Vol. 6, No. 3, December 2019: 363-371. ISSN : P-2409-0603, E-2409-9325

Article Link (Online Journal):

Funding Source:

Budget:

Total Budget (Tk.) :

Achievement/Findings:

People who are vulnerable to shocks and factors which influence their vulnerability is important to know for effective policy measures such as targeting of public health insurance schemes. The study complements the existing works by identifying factors correlates to health shock experiences. Health shocks are likely to affect lower income people more while positively correlates to consumption expenditure. Consumption expenditure responds positively to health shock variables suggesting that households cannot smooth their consumption in the face of health shocks. Supply-side factors of health care such as medical care access are associated with health shock and skipping works due to illness. The result suggests that financial protection and supply side factors should be implemented simultaneously for reducing health shock prevalence and thereby, the economic losses associated with the health shocks (Dupas 2011). The paper also highlights that social safety net programs help households manage their health shocks. Access to financial market is associated with higher health shock and illness exposure. Results show that poorer households are hardly hit by health shocks while illness and death take tools by putting them in the vicious circle of loan and ultimately trapped into poverty. It is recommended that an easy access to formal loan with less interest with the aim to mitigate the health shock might be beneficial for the affected people. However the study has limitations as uses cross-sectional data and self-reported health shocks as the dependent variable. Economic consequences due to health shocks might vary across households. Besides, health shocks might affect in individual level as well as might differ by gender. Further research can consider these issues looking more into direct and indirect cost perspectives.

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