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. 2011 Jan;3(1):29–34. doi: 10.5249/jivr.v3i1.71

Further evidence for epidemiological transition hypothesis for elderly suicides

Ajit Shah a,*
PMCID: PMC3134919  PMID: 21483212

Abstract:

Background:

A developmental model of epidemiological transition for elderly suicide rates with four sequential stages has been developed to simultaneously explain cross-national variations in elderly suicide rates, trends over time for elderly suicide rates and age-associated trends in suicides rates reported in the literature. This model was supported by demonstration of a curvilinear (inverted U-shaped curve) relationship between elderly suicide rates and socio-economic status fitting the quadratic equation Y = A + BX - CX2 (where Y is the suicide rate, X is the socio-economic status and A,B, and C are constants) in both sexes. However, this relationship was derived from a cross-sectional study and, therefore, only an association can be inferred. One way to substantiate this further would be to examine the above curvilinear relationship between suicide rates and socio-economic status in a series of younger age-bands because a large part of the epidemiological transition hypothesis was contingent upon the impact of socio-economic status, through a series of mechanisms, on life expectancy. It was hypothesized that the curvilinear (inverted U-shaped curve) relationship between suicide rates and socio-economic status would be absent in younger age-bands and may be present in the younger age-bands closer to the older age-bands (i.e. 45-54 years and 55-64 years).

Methods:

The curvilinear relationship between suicide rates in five age-bands 15-24 years to 55-64 years in both sexes and gross national domestic product (GDP), a measure of socio-economic status, fitting the above quadratic equation was examined with curve estimation regression model using data from the World Health Organization.

Results:

In males in the age-bands 35-44 years, 45-54 years and 55-64 years there was a statistically significant curvilinear (inverted U-shaped curve) relationship with GDP and fitted the quadratic equation Y = A + BX - CX2; this relationship was absent in males in the age-bands 15-24 years and 25-34 years. In females in the age-bands 45-54 years and 55-64 years there was a statistically significant curvilinear with GDP (inverted U-shaped curve) and fitted the quadratic equation Y = A + BX - CX2; this relationship was absent in females in the age-bands 15-24 years, 25-34 years and 35-44 years.

Conclusions:

Although caution should be exercised in accepting the model of the epidemiological transition hypothesis for elderly suicide rates because it had been generated from cross-sectional data using an ecological design, the findings of the current study of suicide rates in younger age-bands provide support for this hypothesis.

Introduction

A developmental model of epidemiological transition for elderly suicide rates with four sequential stages has been developed to simultaneously explain cross-national variations in elderly suicide rates, trends over time for elderly suicide rates and age-associated trends in suicides rates reported in the literature.1,2This model suggests that each country would sequentially progress through the four stages over time with its socio-economic development, although different countries will be at different stages of development within this model. A curvilinear (inverted U-shaped curve) relationship between elderly suicide rates (defined as suicide rates for those aged 65-74 years and 75+ years) and socio-economic status fitting the quadratic equation Y = A + BX - CX2 (where Y is the suicide rate, X is the socio-economic status and A,B, and C are constants) has been demonstrated for both sexes to support this model.2The four stages of the model include: (i) low elderly suicide rate-low socio-economic society stage; (ii) high elderly suicide rate-low socio-economic society stage; (iii) high elderly suicide rate-high socio-economic society stage; and (iv) low elderly suicide rate-high socio-economic society stage. An explanatory model for each stage is provided below.

Low elderly suicide rate-low socio-economic society stage

Cross-national studies have observed that low socio-economic status is associated with low rates of suicide in the general population.3,4Cross-national and within country studies have also observed that higher income inequality is associated with lower suicide rates in the general population6,7and in the elderly.5Healthcare services are likely to be poorly developed in societies with low socio-economic status5,8-12and poorly developed healthcare services may lead to an increase in child mortality rates by being unable to provide primary preventative measures for diseases in childhood (e.g. immunization programs) and treatment for diseases that are directly related to low socio-economic status (e.g. infectious diseases).13Countries with low socio-economic status and higher income inequality have higher child mortality rates.3,5,8Increased child mortality rates is likely to lead to reduced life expectancy.3,5,8Suicide rates generally increase with age14and reduced life expectancy will result in fewer people reaching the age of increased risk for suicide in societies with low socio-economic status. This will result in a reduced number of elderly suicides in countries with low socio-economic status.5,15Additionally, selective survival of those at reduced risk of suicide in old age due to genetic or constitutional factors may further compound this trend13Also, in societies with low socio-economic status, those who do survive into old age may be at reduced risk of suicide because they may be able to better tolerate additional hardship in old age due to life-long exposure to adversity.16-19

High elderly suicide rate-low socio-economic society stage

Improvement in the socio-economic status of countries leads to the development of improved healthcare services.3,5,8-12This, in turn, may facilitate reduction in child mortality rates because of improved ability to provide primary preventative measures for diseases in childhood (e.g. immunization programs) and treatment for diseases that are directly related to low socio-economic status (e.g. infectious diseases).13This reduction in child mortality rates will lead to increased life expectancy.3,5,8,15This will result in greater number of individuals reaching the age of increased risk of suicide and an increase in elderly suicide rates because there is evidence of a positive correlation between elderly population size and elderly suicide rates.5This will lead to a gradual transition from low elderly suicide rate-low socio-economic society stage to a high elderly suicide rate-low socio-economic society stage.

High elderly suicide rate-high socio-economic society stage

Further socio-economic development will change societies from being socio-economically less developed to being socio-economically more developed.3,5,8-12This will lead to further improvement in healthcare services. This, in turn, will facilitate further reductions in child mortality rates because of improved ability to provide primary preventative measures for diseases in childhood (e.g. immunization programs) and treatment for diseases that are directly related to low socio-economic status (e.g. infectious diseases).13This further reduction in child mortality rates will further increase the life expectancy.3,5,8,15This will result in increasing number of individuals reaching the age of increased risk of suicide because there is evidence of a positive correlation between elderly population size and elderly suicide rates.5Both reduced child mortality rates and increased life expectancy will also lead to reduction in selective survival of those at reduced risk of suicide in old age due to constitutional or genetic factors. Also, the protective effects of life-long adversity on elderly suicide rates16-19is likely to be absent in countries with higher socio-economic status. Collectively, these changes will increase the number of individuals at increased risk of suicide in old age in socio-economically more developed societies. This will lead to a gradual transition from the high elderly suicide rate-low socio-economic society stage to a high elderly suicide rate-high socio-economic society stage.

Low elderly suicide rate-high socio-economic society stage

Theoretically, in socio-economically well developed societies, due to further reduction in child mortality rates and increase in life expectancy, greater number of people would reach the age of increased of suicide, and consequently lead to higher elderly suicide rates. However, in many socio-economically well developed countries elderly suicide rates are comparatively low20and they have declined over time.5Elderly suicide rates may progressively decline over many years in socio-economically very well developed societies due to improved efforts to control the risk factors for elderly suicides, enhance protective factors for elderly suicides, advances in medical care, prompt resuscitation of those who attempt suicide, better provision of healthcare (including mental health) services and public health initiatives to reduce suicide rates.21-27This will lead to a gradual transition from a high elderly suicide rate-high socio-economic society stage to a low elderly suicide rate-high socio-economic society stage.

The above epidemiological transition hypothesis is based upon socio-economic status of societies and the consequences of socio-economic status, but there may also be many other factors that interact with socio-economic status and also act independently to influence suicide rates. The above epidemiological model is supported by demonstration of a curvilinear (inverted U-shaped curve) relationship between elderly suicide rates (defined as suicide rates for those aged 65-74 years and 75+ years) and socio-economic status fitting the quadratic equation Y = A + BX - CX2 (where Y is the suicide rate, X is the socio-economic status and A,B, and C are constants) in both sexes.2However, this relationship was derived from a cross-sectional study and, therefore, only an association can be inferred.2The causal relationship and the direction of causality cannot be proved from a cross-sectional study.2One way to investigate this further would be to follow individual countries longitudinally over time as they progress through different socio-economic stages. However, such studies would be expensive and time consuming as they would require several decades. Another approach to substantiate the epidemiological transition hypothesis of elderly suicides would be to examine the above curvilinear relationship between suicide rates and socio-economic status in a series of younger age-bands (the five 10-year age-bands 15-24 years to 55-64 years) because a large part of the epidemiological transition hypothesis was contingent upon the impact of socio-economic status, through a series of mechanisms, on life expectancy. If the epidemiological transition hypothesis and its explanatory models are accurate then it is likely that this relationship will be absent in younger age-bands and would be more likely to be present in the older age-bands. It was hypothesized that the curvilinear (inverted U-shaped curve) relationship between suicide rates and socio-economic status would be absent in younger age-bands and may be present in the younger age-bands closer to the older age-bands (i.e. 45-54 years and 55-64 years). It is important to test this hypothesis because it may have implications for identification of potential risk and protective factors in the context of prevention programs.

Methods

Suicide rates

Data on suicide rates for males and females in the five 10-year age-bands 15-24 to 54-65 years was ascertained from the WHO (http://www.who.int/whosis/database/mort/ table1.cfm). For a small number of countries only the raw figures for the number of suicides were available from the WHO website. Suicide rates for such countries were calculated by dividing the number of reported suicides by the population size in the relevant age-band and sex group available on the same website. Data were ascertained for the latest available year. The median (range) for the latest year of the suicide rate data was 2005 (1970-2007).

Data on socio-economic status and other variables

Data on the per capita Gross national domestic product (GDP), a proxy measure for socio-economic status of countries3,5,21was ascertained from the WHO website (http://www.who.int/countries/afg/en/) for the year 2006.

Data analysis

The relationship between suicide rates in each of five 10-year age-bands for both sexes and GDP was examined with curve estimation regression model in order to test the “a priori” hypothesis of a curvilinear relationship (inverted U-shaped curve) fitting the quadratic equation Y = A + BX - CX2 (where Y is the suicide rate, X is the GDP, and A,B, and C are constants).

Results

Data on both suicide rates and the GDP were available for 102 countries from the WHO website.Table 1illustrates the characteristics of the curve estimation regression models for both sexes in all the five age-bands from 15-24 years to 55-64 years. In males in the age-bands 35-44 years, 45-54 years and 55-64 years there was a statistically significant curvilinear (inverted U-shaped curve) relationship with GDP and fitted the quadratic equation Y = A + BX - CX2; this relationship was absent in males in the age-bands 15-24 years and 25-34 years. In females in the age-bands 45-54 years and 55-64 years there was a statistically significant curvilinear with GDP (inverted U-shaped curve) and fitted the quadratic equation Y = A + BX - CX2; this relationship was absent in females in the age-bands 15-24 years, 25-34 years and 35-44 years.

Table 1:Curve estimation regression models for the relationship between suicide rates and the GDP.

R2 Degrees of Freedom F Value Significance Regression Equation Y = A + BX – CX2
Males:
15-24 years 0.036 102 1.89 NS Y = 7.66+ 0X – 5.18e-9X2
25-34 years 0.029 102 1.51 NS Y = 12.13+ 0.001X – 1.37e-8X2
35-44 years 0.07 102 3.81 P=0.025 Y = 9.97 + 0.001X – 2.07e-8X2
45-54 years 0.083 102 4.61 P=0.012 Y = 8.52 + 0.002X – 2.84e-8X2
55-64 years 0.11 102 6.51 P=0.002 Y = 7.96 + 0.002X – 3.45e-8X2
Females:
15-24 years 0.006 102 0.31 NS Y = 3.90 – 7.75e-6X - 2.84e-10X2
25-34 years 0.055 102 2.98 NS Y = 2.35 + 0X – 1.38e-9X2
35-44 years 0.054 102 2.91 NS Y = 3.35 + 9.16e-5X – 2.38e-10X2
45-54 years 0.22 102 14.49 P<0.0001 Y = 0.73 + 0X – 5.77e-9X2
55-64 years 0.138 102 8.15 P=0.001 Y = 1.55 + 0X – 5.79e-9X2
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Y = Suicide rates / X = GDP / A, B and C are constants / NS=Not significant

Discussion

Some methodological issues need consideration. Cross-national data on suicide rates should be viewed cautiously because: data were not available from all countries;28,29the validity of this data was unclear;29,30the legal criteria for the proof of suicide vary between countries and in different regions within a country;29,31some countries, particularly low-income countries, may have poor death registration facilities;31and, cultural and religious factors and stigma attached to suicide may lead to under-reporting of suicides.29,32Data on socio-economic status should also be viewed with caution because: the validity of this data is unclear; some countries may have poor infrastructure for providing accurate financial data;5and, their influence on social distribution of risk factors may be complex.33These latter concerns are more likely to be observed in low-income countries. However, data were gathered from the WHO data bank and were the latest and best available data set.

A large part of the epidemiological transition hypothesis described in detail in the Introduction was contingent upon the impact of socio-economic status, through a series of mechanisms, on life expectancy. Thus, it was hypothesized that the curvilinear (inverted U-shaped curve) relationship between suicide rates and socio-economic status would be absent in younger age-bands and may be present in the younger age-bands closer to the older age-bands (i.e. 45-54 years and 55-64 years). The presence of a curvilinear relationship between socio-economic status and age-bands 45-54 years and 55-64 years in both sexes and its absence in the age-bands 15-24 years and 25-34 years in both sexes is consistent with the previously developed epidemiological transition hypothesis of elderly suicides. Essentially as age-bands increased in age, the relationship between suicide rates and GDP became curvilinear (inverted U-shaped curve). Although caution should be exercised in accepting the model of the epidemiological transition hypothesis for elderly suicide rates because it had been generated from cross-sectional data using an ecological design, the findings of the current study of suicide rates in younger age-bands provide support for this hypothesis. The findings have important implications for identification of risk and protective factors for elderly suicides in the context of prevention programs as societies evolve through different soci0-economic stages.

Footnotes

Funding:There was no external funding for this work.

Competing interests:None

Ethical Approval:This was not needed as the work did not involve patients and used data available in the public domain.

References

  • 1.Shah A, Bhat R. Development of an Epidemiological transition model to explain cross-national variations in elderly suicide rates, time trends in elderly suicide rates and age-associated trends in suicide rates. Psychiatric Research Journal. 2009;1(3):241–56. [Google Scholar]
  • 2.Shah A. The possible evidence for an epidemiological transition hypothesis for elderly suicides. Int Psychogeriatr. 2010 Mar;20(2):219–226. doi: 10.1017/S104161020999130X. [DOI] [PubMed] [Google Scholar]
  • 3.Zhang J. Suicide in the world: toward a population increase theory of suicide. Death Stud. 1998 Sep;22(6):525–539. doi: 10.1080/074811898201380. [DOI] [PubMed] [Google Scholar]
  • 4.Simpson ME, Conklin GH. Socioeconomic development, suicide and religion: a test of Durkhiem’s theory of religion and suicide. Social Forces. 1989;67:945–964. [Google Scholar]
  • 5.Shah A, Bhat R, MacKenzie S, Koen C. A cross-national study of the relationship between elderly suicide rates and life expectancy and markers of socioeconomic status and health care. Int Psychogeriatr. 2008 Apr;20(2):347–360. doi: 10.1017/S1041610207005352. [DOI] [PubMed] [Google Scholar]
  • 6.Kowalski GS, Faupel CE, Starr PD. Urbanisation and suicides: a study of American Counties. Social Forces. 1987;66:85–101. [Google Scholar]
  • 7.Vijayakumar L, Nagaraj K, Pirkis J, Whiteford H. Suicide in developing countries (1): frequency, distribution, and association with socio-economic indicators. Crisis. 2005;26(3):104–111. doi: 10.1027/0227-5910.26.3.104. [DOI] [PubMed] [Google Scholar]
  • 8.Shah A. The importance of the socioeconomic status of countries for mental disorders in old age: development of an epidemiological transition model. Int Psychogeriatr. 2007 Aug;19(4):785–787. doi: 10.1017/s1041610207005479. [DOI] [PubMed] [Google Scholar]
  • 9.Shah A. The relationship between socioeconomic status and mental health funding, service provision and national policy: a cross-national study. Int Psychiatry. 2009;6:44–46. [PMC free article] [PubMed] [Google Scholar]
  • 10.Jacob KS, Sharan P, Mirza I, Garrido-Cumbrera M, Seedat S, Mari JJ, et al. Global mental health 4. Mental health systems in countries: where are we now? Lancet. 2007;370:1061–1077. doi: 10.1016/S0140-6736(07)61241-0. [DOI] [PubMed] [Google Scholar]
  • 11.Shah A, Bhat R. The relationship between elderly suicide rates and mental health funding, service provision and national policy: a cross-national study. Int Psychogeriatr. 2008 Jun;20(3):605–15. doi: 10.1017/S1041610207006552. [DOI] [PubMed] [Google Scholar]
  • 12.Shah A, Bhat R. Are elderly suicide rates improved by increased provision of mental health service resources? A cross- national study. Int Psychogeriatr. 2008 Dec;20(6):1230–1237. doi: 10.1017/S1041610208007023. [DOI] [PubMed] [Google Scholar]
  • 13.Suh GH, Shah A. A review of the epidemiological transition in dementia – cross-national comparisons of the indices related to Alzheimer’s disease and vascular dementia. Acta Psychiatr Scand. 2001 Jul;104(1):4–11. doi: 10.1034/j.1600-0447.2001.00210.x. [DOI] [PubMed] [Google Scholar]
  • 14.Shah A, De T. Suicide and the elderly. International Journal of Psychiatry in Clinical Practice. 1998;2:3–17. doi: 10.3109/13651509809115108. [DOI] [PubMed] [Google Scholar]
  • 15. Kiemo K.Towards a socio-economic and demographic theory of elderly suicides: a comparison of 49 countries at various stages of development. 2004,www.soc.ou.se/publications/fulltext/diss2003-3.pdf ,Viewed 2 Febraury 2007. [Google Scholar]
  • 16.Lindesay J. Suicide in the elderly. Int J Geriatr Psychiatry. 1991;6:355–361. [Google Scholar]
  • 17.Seiden RH. Mellowing with age: factors affecting the non-white suicide rate. International Journal of Ageing and Human Development. 1981;13:265–284. doi: 10.2190/CVHU-C41F-KCHV-AVB4. [DOI] [PubMed] [Google Scholar]
  • 18.McIntosh JL. Components of the decline in elderly suicides: suicide in young old and old old by race and sex. Death Education. 1984;8:113–124. [Google Scholar]
  • 19.Shah A, Bhat R. Does adversity earlier in life affect elderly suicide rates? Cross-national study. Int J Psychiatry Clin Prac. 2009;13:273–277. doi: 10.3109/13651500902912702. [DOI] [PubMed] [Google Scholar]
  • 20.Shah A, Bhat R, MacKenzie S, Koen C. Elderly suicide rates: cross-national comparisons and association with sex and elderly age-bands. Med Sci Law. 2007 Jul;47(3):244–252. doi: 10.1258/rsmmsl.47.3.244. [DOI] [PubMed] [Google Scholar]
  • 21.Gunnell D, Middleston N, Whitley E, Dorling D, Frankel S. Why are suicide rates rising in young men but falling in the elderly? – a time-series analysis of trends in England and Wales 1950-1998. Soc Sci Med. 2003 Aug;57(4):595–611. doi: 10.1016/s0277-9536(02)00408-2. [DOI] [PubMed] [Google Scholar]
  • 22.Kua EH, Ko SM, Ng TP. Recent trends in elderly suicide rates in a multi-ethnic Asian city. Int J Geriatr Psychiatry. 2003 Jun;18(6):533–536. doi: 10.1002/gps.868. [DOI] [PubMed] [Google Scholar]
  • 23.Lodhi LM, Shah A. Psychotropic prescriptions and elderly suicide rates. Med Sci Law. 2004 Jul;44(3):236–244. doi: 10.1258/rsmmsl.44.3.236. [DOI] [PubMed] [Google Scholar]
  • 24.Lodhi LM, Shah A. Factors associated with the recent decline in the elderly in suicide rates in England and Wales, 1985-1998. Med Sci Law. 2005 Jan;45(1):31–35. doi: 10.1258/rsmmsl.45.1.31. [DOI] [PubMed] [Google Scholar]
  • 25.Yip PS, Liu KY, Hu J, Song XM. Suicide rates in China during a decade of rapid social changes. Soc Psychiatry Epidemiol. 2005 Oct;40:792–798. doi: 10.1007/s00127-005-0952-8. [DOI] [PubMed] [Google Scholar]
  • 26.Shah A, Coupe J. A comparative study of elderly suicides in England and Wales, Scotland and Northern Ireland: trends over time and age-associated trends. Int Psychogeriatr. 2009 Jun;21(3):581–587. doi: 10.1017/S1041610209008515. [DOI] [PubMed] [Google Scholar]
  • 27.Shah A. Attempted suicide in the elderly in England: age-associated rates, time trends and methods. Int Psychogeriatr. 2009 Oct;21(25):889–895. doi: 10.1017/S1041610209009442. [DOI] [PubMed] [Google Scholar]
  • 28.Moscicki EK. North American perspectives: epidemiology of suicide. Int Psychogeriatr. 1995;7:137–148. [PubMed] [Google Scholar]
  • 29.Wasserman D, Cheng Q, Jiang GX. Global suicide rates among young people aged 15-19. World Psychiatry. 2005 Jun;4(2):114–120. [PMC free article] [PubMed] [Google Scholar]
  • 30.Diekstra RF. Suicide and the attempted suicide: an international perspective. Acta Psychiatr Suppl. 1989;80(354):1–24. doi: 10.1111/j.1600-0447.1989.tb03043.x. [DOI] [PubMed] [Google Scholar]
  • 31. Shah A, Ganesvaran T. Suicide in the elderly. In: Chiu E, Ames D, (Eds): Functional Psychiatric Disorders of the Elderly. Cambridge: Cambridge University Press, 1994: 221-44. [Google Scholar]
  • 32.Abraham VJ, Abraham S, Jacob KS. Suicide in the elderly in Kanyambadi block, Tamil Nadu, South India. Int J Geriatr Psychiatry. 2005 Oct;20(10):953–955. doi: 10.1002/gps.1385. [DOI] [PubMed] [Google Scholar]
  • 33. Lynch J, Smith G, Harpe S, Hillemeier M, Ross N, Kaplan GA, et al. Is income inequality a determinant of population health? Part 1. A systematic review. Milbank Q. 2004; 82(1): 5-99. [DOI] [PMC free article] [PubMed] [Google Scholar]

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