Hostname: page-component-745bb68f8f-cphqk Total loading time: 0 Render date: 2025-02-10T17:57:24.609Z Has data issue: false hasContentIssue false

The behavioural constellation of deprivation: Compelling framework, messy reality

Published online by Cambridge University Press:  29 November 2017

Martin Daly
Affiliation:
Department of Psychology, Neuroscience & Behaviour, McMaster University, Hamilton, ON L8S 4K1, Canada. daly@mcmaster.cawww.martindaly.ca
Dandara Ramos
Affiliation:
Department of Epidemiology, Institute of Social Medicine, State University of Rio de Janeiro, Rio de Janeiro, RJ, 20550-900, Brazil. dandararamos2@gmail.comwww.desin.org
Gretchen Perry
Affiliation:
Department of Social Work, Lakehead University, Orillia, ON L3V 0B9, Canada. gretchenperry@gmail.com

Abstract

Pepper & Nettle's (P&N's) argument is compelling, but apparently contradictory data are easily found. Associations between socioeconomic status (SES) and substance abuse are sometimes positive, the poor are sometimes eager to educate their children, and perceptions of local mortality risk can be so distorted as to constitute an implausible basis for contextually appropriate responding. These anomalies highlight the need for more psychological work.

Type
Open Peer Commentary
Copyright
Copyright © Cambridge University Press 2017 

Natural selection often favours risk taking and future discounting as facultative responses to cues indicating a relatively high risk of unpredictable, uncontrollable catastrophe (Daly & Wilson Reference Daly and Wilson2005; Promislow & Harvey Reference Promislow and Harvey1990). Pepper & Nettle (P&N) make a powerful case that this insight illuminates many aspects of human development and behavioural variability, which we applaud. However, applying their model is not necessarily straightforward.

In support of their proposed “behavioural constellation of deprivation” (BCD), P&N (sect. 2, para. 4) posit “consistent” SES gradients in behaviours affecting health, one of which is that people of lower SES “are more likely to use illicit drugs and to drink excessive amounts of alcohol.” Research in rich countries certainly supports this generalisation, but studies in Latin America contradict it. Researchers in Argentina (Fantin & de Barbenza Reference Fantin and de Barbenza2007), Brazil (Baus et al. Reference Baus, Kupek and Pires2002; Macinko et al. Reference Macinko, Mullachery, Silver, Jimenez and Neto2015; Malta et al. Reference Malta, Mascarenhas, Porto, Barreto and Morais Neto2014; Muza et al. Reference Muza, Bettiol, Muccillo and Barbieri1997; Pratta & Santos Reference Pratta and Santos2007; Ramis et al. Reference Ramis, Mielke, Habeyche, Oliz, Azevedo and Hallal2012; Silva et al. Reference Silva, Malbergier, de Andrade Stempliuk and de Andrade2006; Souza et al. Reference Souza, Areco and Filho2005; Souza & Martins Reference Souza and Martins1998; Tavares et al. Reference Tavares, Béria and Lima2001), Chile (Florenzano et al. Reference Florenzano, Cáceres, Valdés, Calderón, Santander, Cassasus and Aspillaga2010; Peña et al. Reference Peña, Mäkelä, Valdivia, Helakorpi, Markkula, Margozzini and Koskinen2017; Sepúlveda et al. Reference Sepúlveda, Roa and Muñoz2011), and Mexico (Caballero et al. Reference Caballero, de León, San Martín and Villaseñor1999; Hernández & González Reference Hernández and González2013; Herrera-Vázquez et al. Reference Herrera-Vázquez, Wagner, Velasco-Mondragón, Borges and Lazcano-Ponce2004) have repeatedly found SES to be positively associated with alcohol abuse, drug use, and smoking in adolescents and adults.

A partial reason for this discrepancy is that in poorer countries, the destitute lack the financial means to use and abuse substances, but there may be larger issues regarding how the BCD model can be applied in different contexts. There is meta-analytic evidence of greater variation in the relationship between SES and alcohol problems in low- to middle-income countries than in high-income countries (Grittner et al. Reference Grittner, Kuntsche, Graham and Bloomfield2012), suggesting that what constitutes deprivation may vary, too. In Latin America, adverse colonial legacies, enduring social injustice, and extreme economic and health inequalities (Andrade et al. Reference Andrade, Pellegrini Filho, Solar, Rígoli, de Salazar, Serrate, Ribeiro, Koller, Cruz and Atun2015; Bambas & Casas Reference Bambas and Casas2001) have created situations in which the experience of deprivation is very different from in the rich world, and what constitutes a “contextually appropriate response” may also differ. P&N caution that the “deprivation” in their model refers to “the experience of various hardships” for which SES is only a “proxy,” a caveat that is appropriate psychologically but problematic for measurement and comparisons. Moreover, how SES itself should be measured is controversial (Ensminger et al. Reference Ensminger, Fothergill, Bornstein, Bradley, Bornstein and Bradley2003; Oakes & Rossi Reference Oakes and Rossi2003; Wagstaff &Watanabe Reference Wagstaff and Watanabe2003), necessitating that we evaluate alternative measures before using SES even as a proxy.

In the target article's section 3.2, P&N explain that although responding to extrinsic mortality risk with future discounting is contextually appropriate, doing so can exacerbate one's mortality disadvantage, and such amplification even operates intergenerationally, further disadvantaging the children of the disadvantaged. How is it, then, that many people in the developing world are escaping this vicious cycle? Although the poor may sometimes see little value in educating their children, they often take the opposite view. Why one response rather than the other? Reduced infant mortality and family size, plus female labour-force participation, seem to be key variables, although the causal links are complicated and bidirectional (Gakidou et al. Reference Gakidou, Cowling, Lozano and Murray2010; Goodall & Vorhaus Reference Goodall and Vorhaus2011). Agencies trying to promote the prioritisation of education often target women as the most effective agents of change (Gakidou et al. Reference Gakidou, Cowling, Lozano and Murray2010; Soares et al. Reference Soares, Ribas and Osório2010). Partly, this reflects a recognition that women are relatively likely to spend subsidies on their children and men on themselves, but it may also be the case that women are better prepared than men to adopt the longer view (Campbell Reference Campbell1999; Daly & Wilson Reference Daly and Wilson2005). Changes in child mortality and education (especially for women/girls) seem to be tightly linked, and shifts to longer time horizons can apparently occur quickly where policies support such change.

Evolved psychological mechanisms and processes are adapted to the past and do not necessarily promote fitness in novel environments. Internet pornography is avidly consumed, and motor vehicles evoke less fear than spiders. P&N are well aware of this issue, raising it implicitly in Section 7 and explicitly in Section 8.4, where they note that “[t]he BCD isn't necessarily adaptive and perceptions aren't necessarily accurate.” Nevertheless, some earlier sections of the target article invite misconstrual as claims to the contrary. Indeed, the very phrase “contextually appropriate response” is open to such misconstrual; the claim of “appropriateness” is often warranted only with respect to the direction of responses, not their magnitude. In Section 2.3, for example, P&N quote a young offender who describes his Atlanta neighbourhood as a “war” zone in which “you never know if you gonna live one minute to the next.” P&N continue, “[T]his may seem exaggerated, but . . . ,” implying that it is not – but it is! In 2001, black males in “high-risk urban environments” in the United States had a life expectancy at birth of 66.7 years (Murray et al. Reference Murray, Kulkarni and Ezzati2005), a number only modestly affected by violent deaths and too high to justify, in and of itself, a belief that one has no future. But although the young offender's words exaggerate the dangers in his milieu, his sense of deprivation is fully justified: That 66.7-year life expectancy is lower than that of any other segment of the U.S. population. The crucial deprivation is relative, and it is unsurprising that people should have evolved to care profoundly about relative deprivation, because fitness itself is relative (Daly Reference Daly2016). Statements like the young offender's abound in urban ethnographies, and the extent to which they represent braggadocio, a massive misperception of actual mortality risks, or something else remains unclear. Answering such questions is important, because they bear on the potential efficacy of providing better information.

A common denominator of these cautions is that the psychology of deprivation and risk preferences is not transparent, a problem compounded by sex differences and by the evolutionary novelty of modern environments. Applying P&N's valuable insights to the practical business of alleviating the social costs and self-destructive effects of the BCD will remain conceptually, as well as politically, challenging.

References

Andrade, L. O. M., Pellegrini Filho, A., Solar, O., Rígoli, F., de Salazar, L. M., Serrate, P. C. F., Ribeiro, K. F., Koller, T. S., Cruz, F. N. B. C. & Atun, R. (2015) Social determinants of health, universal health coverage, and sustainable development: Case studies from Latin American countries. The Lancet 385(9975):1343–51.CrossRefGoogle Scholar
Bambas, A. & Casas, J. A. (2001) Assessing equity in health: Conceptual criteria. In: Equity and health: Views from the Pan American Sanitary Bureau, ed.Pan American Health Organization, pp. 1221. Pan American Health Organization.Google Scholar
Baus, J., Kupek, E. & Pires, M. (2002) Prevalence and risk factors associated with drug use among school students, Brazil [Portuguese]. Revista de Saúde Pública 36(1):4046.Google Scholar
Caballero, R., de León, E. M., San Martín, A. H. & Villaseñor, A. (1999) El consumo de tabaco, alcohol y drogas ilegales, en los adolescentes de diferentes estratos socioeconómicos de Guadalajara. Salud Mental 22(4):18.Google Scholar
Campbell, A. (1999) Staying alive: Evolution, culture, and women's intrasexual aggression. Behavioral & Brain Sciences 22(2):203–14.CrossRefGoogle ScholarPubMed
Daly, M. (2016) Killing the competition: Economic inequality and homicide. Transaction Publishers.Google Scholar
Daly, M. & Wilson, M. (2005) Carpe diem: Adaptation and devaluing the future. Quarterly Review of Biology 80(1):5560.Google Scholar
Ensminger, M. E., Fothergill, K. E., Bornstein, M. H. & Bradley, R. H. (2003) A decade of measuring SES: What it tells us and where to go from here. In: Socioeconomic status, parenting, and child development, ed. Bornstein, M. H. & Bradley, R. H., pp. 1327. Psychology Press.Google Scholar
Fantin, M. B. & de Barbenza, C. M. (2007) Nivel socioeconómico y consumo de sustancias en una muestra de adolescentes escolarizados de San Luis, Argentina. Fundamentos en Humanidades 15:133–45.Google Scholar
Florenzano, R., Cáceres, E., Valdés, M., Calderón, S., Santander, S., Cassasus, M. & Aspillaga, C. (2010) Comparación de frecuencia de conductas de riesgo, problemas juveniles y estilos de crianza, en estudiantes adolescentes de tres ciudades chilenas. Caudernos Médico Sociales 50(2):115–23.Google Scholar
Gakidou, E., Cowling, K., Lozano, R. & Murray, C. J. L. (2010) Increased educational attainment and its effect on child mortality in 175 countries between 1970 and 2009: A systematic analysis. The Lancet 376(9745):1824.Google Scholar
Goodall, J. & Vorhaus, J. (2011) Review of best practice in parental engagement. UK Department of Education Research Report DFE-RR156. Available at: https://www.gov.uk/government/uploads/system/uploads/attachment_data/file/182508/DFE-RR156.pdf.Google Scholar
Grittner, U., Kuntsche, S., Graham, K. & Bloomfield, K. (2012) Social inequalities and gender differences in the experience of alcohol-related problems. Alcohol and Alcoholism 47(5):597605.Google Scholar
Hernández, R. L. & González, M. E. V. (2013) Consumo de alcohol en estudiantes en relación con el consumo familiar y de los amigos. Psicología y Salud 17(1):1723.Google Scholar
Herrera-Vázquez, M., Wagner, F. A., Velasco-Mondragón, E., Borges, G. & Lazcano-Ponce, E. (2004) Inicio en el consumo de alcohol y tabaco y transición a otras drogas en estudiantes de Morelos, México. Salud Pública de México 46(2):132–40.Google Scholar
Macinko, J., Mullachery, P., Silver, D., Jimenez, G. & Neto, O. L. M. (2015) Patterns of alcohol consumption and related behaviors in Brazil: Evidence from the 2013 National Health Survey (PNS 2013). PLOS ONE 10(7):e0134153.Google Scholar
Malta, D. C., Mascarenhas, M. D. M., Porto, D. L., Barreto, S. M. & Morais Neto, O. L. D. (2014) Exposure to alcohol among adolescent students and associated factors [Portuguese]. Revista de Saúde Pública 48(1):5262.Google Scholar
Murray, C. J., Kulkarni, S. & Ezzati, M. (2005) Eight Americas: New perspectives on US health disparities. American Journal of Preventive Medicine 29(Suppl. 1):410.Google Scholar
Muza, G. M., Bettiol, H., Muccillo, G. & Barbieri, M. A. (1997) The consumption of psychoactive substances by adolescents in schools in an urban area of Southeastern region of Brazil. I-Prevalence by sex, age and kind of substance [Portuguese]. Revista de Saúde Pública 31(1):2129.Google Scholar
Oakes, J. M. & Rossi, P. H. (2003) The measurement of SES in health research: current practice and steps toward a new approach. Social Science & Medicine 56(4):769–84.Google Scholar
Peña, S., Mäkelä, P., Valdivia, G., Helakorpi, S., Markkula, N., Margozzini, P. & Koskinen, S. (2017) Socioeconomic inequalities in alcohol consumption in Chile and Finland. Drug & Alcohol Dependence 173:2430.CrossRefGoogle ScholarPubMed
Pratta, E. M. M. & Santos, M. A. D. (2007) Adolescence and the consumption of psychoactive substances: The impact of the socioeconomic status. Revista Latino-Americana de Enfermagem 15(SPE):806–11.Google Scholar
Promislow, D. E. L. & Harvey, P. H. (1990) Living fast and dying young: A comparative analysis of life history variation among mammals. Journal of Zoology 220(3):417–37.Google Scholar
Ramis, T. R., Mielke, G. I., Habeyche, E. C., Oliz, M. M., Azevedo, M. R. & Hallal, P. C. (2012) Smoking and alcohol consumption among university students: prevalence and associated factors [Portuguese]. Revista Brasileira de Epidemiologia 15(2):376–85.Google Scholar
Sepúlveda, C. M., Roa, S. J. & Muñoz, R. M. (2011) Prevalence of the drug consumption among Chilean university students. Revista Medica de Chile 139(7):856–63.Google Scholar
Silva, L. V. R., Malbergier, A., de Andrade Stempliuk, V. & de Andrade, A. G. (2006) Fatores associados ao consumo de álcool e drogas entre estudantes universitários. Revista de Saúde Pública 40(2):280–88.Google Scholar
Soares, F. V., Ribas, R. P. & Osório, R. G. (2010) Evaluating the impact of Brazil's Bolsa Família: Cash transfer programs in comparative perspective. Latin American Research Review 45(2):173–90.Google Scholar
Souza, D. P. O., Areco, K. N. & Filho, D. X. S. (2005) Álcool e alcoolismo entre adolescentes da rede estadual de ensino de Cuiabá, Mato Grosso. Revista de Saúde Pública 39(4):585–92.Google Scholar
Souza, D. P. O. D. & Martins, D. T. D. O. (1998) O perfil epidemiológico do uso de drogas entre estudantes de primeiro e segundo graus da rede estadual de ensino de Cuiabá, Brasil, 1995. Cadernos Saúde Pública 14(2):391400.Google Scholar
Tavares, B. F., Béria, J. U. & Lima, M. S. D. (2001) Drug use prevalence and school performance among teenagers [Portuguese]. Revista de Saúde Pública 35(2):150–58.Google Scholar
Wagstaff, A. & Watanabe, N. (2003) What difference does the choice of SES make in health inequality measurement? Health Economics 12(10):885–90.Google Scholar