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Quality of Life in Developing Countries

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Abstract

The chapter addresses opportunities and challenges presented by the increasing use of population and individual measures of quality of life in developing countries to inform policies and interventions. This shift was made possible by a substantial body of multidisciplinary research into local conceptions of quality of life and greater sophistication in measurement. The chapter argues that research on measurement and meaning needs to be brought together. It shows how working in developing countries can throw the normative assumptions and measurement practices of QoL researchers into sharp relief, for example, the extent to which QoL measures are “appropriate technologies” (i.e., work equally well in resource-poor environments), the challenges of translation, and the ethics of research with people who are poor and powerless. The chapter uses Bangladesh as an example and provides examples of prominent and interesting work in boxes throughout the text. The first section of the chapter summarizes the advantages of QoL research in developing countries for residents, policy makers, and practitioners. It then outlines the main issues around exploring and defining QoL, and the role of qualitative and participatory work in this process. Finally, it reviews previous and ongoing work on using, developing, and adapting measures of subjective QoL in developing countries, including the work of the multidisciplinary Wellbeing in Developing Countries Research Group (WeD) in Bangladesh, Ethiopia, Peru, and Thailand.

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Notes

  1. 1.

    There are notable exceptions to this, for example, the work of Moller et al. in South Africa.

  2. 2.

    See Cummins 2002a; Russell 2003; Davern and Cummins 2005.

  3. 3.

    The estimate takes a cut-off of 0.89 in the Human Development Index (HDR 2005) to exclude OECD members or ‘highly developed’ countries.

  4. 4.

    Bangladesh was 139th in the Human Development Index, has a per capita income of $1,770 PPP and was categorised by Transparency International (2003) as the most corrupt country in the world.

  5. 5.

    See Davis et al. 1999 for the time cost of participatory work. Household surveys, although regarded as a ‘necessary evil’ by researchers, are also notoriously time-consuming.

  6. 6.

    The WeD group’s Resources and Needs Questionnaire included a global happiness question and five questions on domain satisfaction designed to address basic need fulfilment (Guillen-Royo and Velazco 2005).

  7. 7.

    For example, the lowest SWB score ever recorded (1.6 on a 10-point scale) occurred following the overthrow of the government of the Dominican Republic.

  8. 8.

    Inglehardt and Klingemann (2000) observed a decline in the reported SWB of Russians from 70% to 38% between 1981 and 1996 whilst GDP per capita remained roughly the same.

  9. 9.

    The failure to fully acknowledge the importance of these areas could also be explained by resistance from powerful stakeholders as valued aspects of life such as ‘feeling a sense of identity or belonging’ tend not to be affected by medical interventions!

  10. 10.

    See Keedwell and Snaith 1996; Ziebland et al. 1993; Fox-Rushby and Bowden [unpublished].

  11. 11.

    The Dartmouth COOP/WONCA Charts, Nottingham Health Profile, Sickness Impact Profile, SF-36, Quality of Wellbeing Scale, and the WHOQOL, and the health economic measures 15-Dimensional Measure, Health Utilities Index and EuroQol.

  12. 12.

    This was also found by the WeD exploratory QoL research in Bangladesh (Choudhury 2005).

  13. 13.

    For example, German respondents primed for interdependence react in a similar way to Chinese ones, and also perceive the behaviour of others in a similar way.

  14. 14.

    The item on happiness had previously been omitted because (a) it conflated affective and cognitive, as satisfaction was seen as a combination of the two (Okun and Stock 1987), and (b) it was not amenable to objective measurement. It was also difficult to translate because satisfaction and happiness are interchangeable in Chinese.

  15. 15.

    In 2003, Hong Kong’s GDP per capita was US$26,632, and Australia’s was $27,179, and their respective HDI scores were 0.916 and 0.955.

  16. 16.

    See World Database of Happiness Item Bank, http://www1.eur.nl/fsw/happiness/hap_quer/hqi_fp.htm

  17. 17.

    For example, Nigeria has a per capita income of $328, and according to the UNDP, is one of the 25 least developed countries. Nonetheless, the World Values Survey named it the happiest country in the World in 2000, and 70% of Nigerian respondents described themselves as ‘very happy’.

  18. 18.

    Cummins’s review of measures of life satisfaction noted at least 173 different domain names, and suggested the potential number of domains was even larger (1996).

  19. 19.

    See http://www.welldev.org.uk/research/methods-toobox/ranq-toolbox.htm

  20. 20.

    Qualitative and quantitative data were collected from 68 men and women, primarily distinguished by age and socioeconomic status. The respondents were living in six peri-urban, rural and urban sites, which were chosen for their relative proximity to the capital.

  21. 21.

    Periods when they had a close relationship with their spouse were also sources of happy memories for some men.

  22. 22.

    This domain was labelled ‘Work and productive activity in the measure’ in the PWI’s predecessor, the ComQoL (Cummins 1997).

  23. 23.

    The last three questions were added in 2002.

  24. 24.

    Community connectedness was interpreted as including respect and status, for example, having a ‘good appearance’ (Ethiopia).

  25. 25.

    See also Hagerty et al.’s review of QoL Indexes for public policy (2001).

  26. 26.

    The extent of the correlation between these questions is still debated (e.g. Lyubomirsky 2001). For example, Rojas only found a correlation of 0.49 in his data from Mexico city, which led him to conclude that they were separate concepts, with life satisfaction being ‘closer to the philosophers’ conception of wellbeing as a happy life, which involves a person’s judgement of her life’ (2007).

  27. 27.

    This may be a form of positivity bias where North American survey respondents appear to be more likely to say the things that are going well for them are important.

  28. 28.

    Global positivity bias is a tendency, particularly common in North America, to respond very positively to questions about happiness or satisfaction with life as a whole; see Strack et al. 1990.

  29. 29.

    The first item (‘in most ways my life is close to my ideal’) worked better in richer nations than poor, which the authors suggested could be because ‘ideal selves’ are more important in rich countries and ‘past achievements’ in poor ones.

  30. 30.

    Some HRQoL researchers have described combining different domains in a single score as ‘adding apples and oranges’ (Stewart and Ware 1992), especially when questions about levels of functioning are aggregated with how the person feels about the situation (Muldoon et al. 1998). See also Fayers et al. 1997 on the perils of combining causal and indicator variables, and Cummins et al. 2005 for a general critique.

  31. 31.

    According to Bowden and Fox-Rushby (2003), indigenous South American, South Asian, Arabic and African languages are particularly under-represented.

  32. 32.

    The WHOQOL-Bref omits the spiritual and economic domains, reducing its utility in developing countries.

  33. 33.

    The extent to which it is based on a comprehensive and coherent theory of QoL.

  34. 34.

    For example, Pandey et al. 2004 (Malayalam), Mullin et al. 2000 (three African languages).

  35. 35.

    As with the WHOQOL, the SF-36 social function scale performed poorly, which is especially problematic in Bangladesh as qualitative studies suggest this is the most important area of people’s lives.

  36. 36.

    Translations back into the original language by a native speaker who has not seen the original measure.

  37. 37.

    The GPGI is an extension of the Patient Generated Index (Ruta et al. 1994), which assesses satisfaction with five areas that the respondent identifies as important.

  38. 38.

    Bowden et al. observed that despite the fact that 71% of mortality in Africa and 39% in South East Asia is attributable to communicable disease, only 3.4% of the HRQoL measures in their review covered this area (2003).

  39. 39.

    Fieldworkers from the WeDQoL piloting in Ethiopia noted that respondents could interpret ‘last year’ in at least four ways—as a calendar year (Gregorian or Ethiopian), an agricultural year or 12 months since the question was asked.

  40. 40.

    Local concepts of health incorporate contentment, corporeal capability, cleanliness, cooperation and completeness.

  41. 41.

    The highest number of points—nine—is assigned to areas with the most points for importance and satisfaction, whilst the lowest is assigned to areas with the most points for importance and the least for satisfaction.

  42. 42.

    The construct of ‘general QoL’ excluded work, couple relationship and children, as not all subjects were employed, in relationships or parents.

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Acknowledgements

Particular thanks to Jackeline Velazco and Monica Guillen-Royo, who wrote the review of happiness economics in developing countries. Thanks also to the Lead Researchers on QoL in the WeD Countries: Kaneta Choudhury and Mohammed Tapan in Bangladesh; Bethlehem Tekola and Ashebir Desalegn in Ethiopia; Jorge Yamamoto and Ana Rosa Feijoo in Peru (who created the WeDQoL Peru on which the final WeDQoL measure has been based); and Darunee Jongudomkarn, Malee Sabaiying and Sawittri Limchaiarunruang in Thailand. The support of the UK Economic and Social Research Council (ESRC) is gratefully acknowledged. The work was part of the programme of the ESRC Research Group on Wellbeing in Developing Countries.

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Appendices

Appendix 1: Determinants of Happiness in Developing Countries: Summary of Empirical Studies

Country

Latin American

South Africa

Rural China

Mexico

Ethiopia

Thailand

Authors

Graham (2005)

Kingdon and Knight (2003)

Knight and Song (2004)

Rojas (2005)

Guillen and Velazco (2005)

Guillen and Velazco (2005)

Dependent variable

Happiness: 4-point scale

Happiness: 5-point scale

Happiness: 6-point scale

Happiness: 7-point scale

Happiness: 3-point scale

Happiness: 3-point scale

Estimation method

Ordered logit

Ordered probit

OLS

OLS

Ordered probit

Ordered probit

Independent variables

Relationship a

Relationship

Relationship

Relationship

Relationship

Relationship

Household head characteristics

Age

(−)

(+)

(−)

(−)

(−)

(−)

Education

(−)b

(+)

(+)

(+)b

(−)

(+)b

Male

(−)b

 

(−)

 

(+)b

(+)b

Married

(+)b

 

(+)

(+)

(+)b

(−)b

Employment status (self-employed)

(−)

   

(+)

(−)

Minority

(−)

     

Income

 

(+)

(+)

(+)

  

Unemployed

(−)

(−)

    

African /coloured/ Indian

 

(−)

    

Household characteristics

Number of children  <  16

 

(+)

    

Urban household

 

(−)

    

Basic needs/assets

Health index

(+)

(+)

(+)

   

Wealth/asset index

(+)

   

(+)

(+)

Asset value

 

(+)

 

(+)

  

Household faced food shortage

    

(−)b

(−)

Perception variables

Household’s wealth in village (rich)

  

(+)

 

(+)

(+)

Household’s wealth in village (above average)

  

(+)

 

(+)

(+)

Number of observations

15,209

8,279

9,112

1,540

920

904

Goodness of fit: pseudo R square

0.062

0.09

0.18

0.085

0.14

0.11

  1. aThe estimated relationship is reported. (+) means a positive or direct relationship between the dependent and independent variables, whilst (−) denotes an indirect or negative relationship
  2. bVariable not statistically significant

Appendix 2: Comparison of Characteristics of QoL/Living Well with the Domains of the Personal Wellbeing Index (PWI)

PWI (Cummins et al. 2003)

Bath workshop

Bangladesh

Ethiopia

Thailand

Peru

Personal relationships

Close affiliation (1)

Marriage (7)

Support from natal family

Family relationships (1)

Being in a couple

 

Children (5)

  

Family

 

Relationships (3)

  

Helping each other

Standard of living

Services—formal/informal (4)

Income (1)

Economic stability/need satisfaction

Income, having money (2)

House

Productive assets (8)

Material goods and environment (2)

Land

Assets, savings, inheritance (3)

Sustenance

House/shelter (9)

 

Oxen

Living conditions (8)

Furniture and appliances

  

Livestock

Housing (9)

Power supply, water

  

Modern agricultural equipment

 

Material sufficiency (overcoming scarcity)

  

Good house

  
  

Improved local infrastructure

  

Personal health

Health (10)

Health (6)

Health

Health, longevity (5)

Rest and recuperation

Achieving in life

Participation/non-participation (6)

Education (4)

Business activities

Job (4)

‘Exploration’ and purchase and market exchange

  

Education (self and children)

Personal qualities

 

Community connectedness

Respect/recognition–disrespect/denial (5)

Status (connections) (9)

Good community relationships

Good appearance (7)

Interpersonal/social interaction

Personal safety

No

No

No

No

No

Future security

Security/insecurity (2)

No

No

No

No

Agency/power/powerlessness (3)

    
  1. N.B. The numbers in brackets refer to its importance, where this was analysed

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Camfield, L. (2012). Quality of Life in Developing Countries. In: Land, K., Michalos, A., Sirgy, M. (eds) Handbook of Social Indicators and Quality of Life Research. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2421-1_19

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