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Statistical signs of social influence on suicides.

Melo HP, Moreira AA, Batista É, Makse HA, Andrade JS - Sci Rep (2014)

Bottom Line: Under the same framework, he considered that crime is bound up with the fundamental conditions of all social life.The social effect on the occurrence of homicides has been previously substantiated, and confirmed here, in terms of a superlinear scaling relation: by doubling the population of a Brazilian city results in an average increment of 135% in the number of homicides, rather than the expected isometric increase of 100%, as found, for example, for the mortality due to car crashes.Differently from homicides (superlinear) and fatal events in car crashes (isometric), we find sublinear scaling behavior between the number of suicides and city population, with allometric power-law exponents, β = 0.84 ± 0.02 and 0.87 ± 0.01, for all cities in Brazil and US counties, respectively.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Física, Universidade Federal do Ceará, 60451-970 Fortaleza, Ceará, Brazil.

ABSTRACT
By treating the suicide as a social fact, Durkheim envisaged that suicide rates should be determined by the connections between people and society. Under the same framework, he considered that crime is bound up with the fundamental conditions of all social life. The social effect on the occurrence of homicides has been previously substantiated, and confirmed here, in terms of a superlinear scaling relation: by doubling the population of a Brazilian city results in an average increment of 135% in the number of homicides, rather than the expected isometric increase of 100%, as found, for example, for the mortality due to car crashes. Here we present statistical signs of the social influence on the suicide occurrence in cities. Differently from homicides (superlinear) and fatal events in car crashes (isometric), we find sublinear scaling behavior between the number of suicides and city population, with allometric power-law exponents, β = 0.84 ± 0.02 and 0.87 ± 0.01, for all cities in Brazil and US counties, respectively. Also for suicides in US, but using the Metropolitan Statistical Areas (MSAs), we obtain β = 0.88 ± 0.01.

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Related in: MedlinePlus

Scaling relations for homicides, traffic accidents, and suicides for the year of 2009 in Brazil.The small circles show the total number of deaths by (a) homicides (red), (b) traffic accidents (blue), and (c) suicides (green) vs the population of each city. Each graph represents only one urban indicator, and the solid gray line indicate the best fit for a power-law relation, using OLS regression, between the average total number of deaths and the city size (population). To reduce the fluctuations we also performed a Nadaraya-Watson kernel regression1718. The dashed lines show the 95% confidence band for the Nadaraya-Watson kernel regression. The ordinary least-squares (OLS)19 fit to the Nadaraya-Watson kernel regression applied to the data on homicides in (a) reveals an allometric exponent β = 1.24 ± 0.01, with a 95% confidence interval estimated by bootstrap. This is compatible with previous results obtained for U.S.2 that also indicate a super-linear scaling relation with population and an exponent β = 1.16. Using the same procedure, we find β = 0.99 ± 0.02 and 0.84 ± 0.02 for the numbers of deaths in traffic accidents (b) and suicides (c), respectively. The values of the Pearson correlation coefficients ρ associated with these scaling relations are shown in each plot. This non-linear behavior observed for homicides and suicides certainly reflects the complexity of human social relations and strongly suggests that the the topology of the social network plays an important role on the rate of these events. (d) The solid lines show the Nadaraya-Watson kernel regression rate of deaths (total number of deaths divided by the population of a city) for each urban indicator, namely, homicides (red), traffic accidents (blue), and suicides (green). The dashed lines represent the 95% confidence bands. While the rate of fatal traffic accidents remains approximately invariant, the rate of homicides systematically increases, and the rate of suicides decreases with population.
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f1: Scaling relations for homicides, traffic accidents, and suicides for the year of 2009 in Brazil.The small circles show the total number of deaths by (a) homicides (red), (b) traffic accidents (blue), and (c) suicides (green) vs the population of each city. Each graph represents only one urban indicator, and the solid gray line indicate the best fit for a power-law relation, using OLS regression, between the average total number of deaths and the city size (population). To reduce the fluctuations we also performed a Nadaraya-Watson kernel regression1718. The dashed lines show the 95% confidence band for the Nadaraya-Watson kernel regression. The ordinary least-squares (OLS)19 fit to the Nadaraya-Watson kernel regression applied to the data on homicides in (a) reveals an allometric exponent β = 1.24 ± 0.01, with a 95% confidence interval estimated by bootstrap. This is compatible with previous results obtained for U.S.2 that also indicate a super-linear scaling relation with population and an exponent β = 1.16. Using the same procedure, we find β = 0.99 ± 0.02 and 0.84 ± 0.02 for the numbers of deaths in traffic accidents (b) and suicides (c), respectively. The values of the Pearson correlation coefficients ρ associated with these scaling relations are shown in each plot. This non-linear behavior observed for homicides and suicides certainly reflects the complexity of human social relations and strongly suggests that the the topology of the social network plays an important role on the rate of these events. (d) The solid lines show the Nadaraya-Watson kernel regression rate of deaths (total number of deaths divided by the population of a city) for each urban indicator, namely, homicides (red), traffic accidents (blue), and suicides (green). The dashed lines represent the 95% confidence bands. While the rate of fatal traffic accidents remains approximately invariant, the rate of homicides systematically increases, and the rate of suicides decreases with population.

Mentions: The main goal here is to investigate the scaling behavior with city population of three urban indicators, namely the number of homicides, deaths in traffic accidents and suicides. For this, we analyzed data available for all Brazilian cities as well as suicide for US counties and MSAs, as presented previously on Materials and Methods. For 2009 in Brazil, as shown in Fig. 1, the increase in the number of casualties D with city population P for the three death causes can be properly described in terms of power-laws, D = D0Pβ, where D0 is a costant pre-factor, and the exponent β reflects a global property at play across the urban system. Interestingly, while the number of deaths by traffic accidents display isometric scaling, β ≈ 1, homicides and suicides are both allometric, but obeying superlinear and sublinear scaling with population, respectively. These results suggest that the decision to commit a crime or to suicide, instead of being purely a consequence of individual choices, might have strong correlations with the underlying complex social organization and interactions. This does not seem to be the case of traffic accidents, since the strong evidence for isometric scaling, β = 0.99 ± 0.02, indicates that such events should result from random processes, i.e., no social relations need to be implied among the involved people.


Statistical signs of social influence on suicides.

Melo HP, Moreira AA, Batista É, Makse HA, Andrade JS - Sci Rep (2014)

Scaling relations for homicides, traffic accidents, and suicides for the year of 2009 in Brazil.The small circles show the total number of deaths by (a) homicides (red), (b) traffic accidents (blue), and (c) suicides (green) vs the population of each city. Each graph represents only one urban indicator, and the solid gray line indicate the best fit for a power-law relation, using OLS regression, between the average total number of deaths and the city size (population). To reduce the fluctuations we also performed a Nadaraya-Watson kernel regression1718. The dashed lines show the 95% confidence band for the Nadaraya-Watson kernel regression. The ordinary least-squares (OLS)19 fit to the Nadaraya-Watson kernel regression applied to the data on homicides in (a) reveals an allometric exponent β = 1.24 ± 0.01, with a 95% confidence interval estimated by bootstrap. This is compatible with previous results obtained for U.S.2 that also indicate a super-linear scaling relation with population and an exponent β = 1.16. Using the same procedure, we find β = 0.99 ± 0.02 and 0.84 ± 0.02 for the numbers of deaths in traffic accidents (b) and suicides (c), respectively. The values of the Pearson correlation coefficients ρ associated with these scaling relations are shown in each plot. This non-linear behavior observed for homicides and suicides certainly reflects the complexity of human social relations and strongly suggests that the the topology of the social network plays an important role on the rate of these events. (d) The solid lines show the Nadaraya-Watson kernel regression rate of deaths (total number of deaths divided by the population of a city) for each urban indicator, namely, homicides (red), traffic accidents (blue), and suicides (green). The dashed lines represent the 95% confidence bands. While the rate of fatal traffic accidents remains approximately invariant, the rate of homicides systematically increases, and the rate of suicides decreases with population.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4150102&req=5

f1: Scaling relations for homicides, traffic accidents, and suicides for the year of 2009 in Brazil.The small circles show the total number of deaths by (a) homicides (red), (b) traffic accidents (blue), and (c) suicides (green) vs the population of each city. Each graph represents only one urban indicator, and the solid gray line indicate the best fit for a power-law relation, using OLS regression, between the average total number of deaths and the city size (population). To reduce the fluctuations we also performed a Nadaraya-Watson kernel regression1718. The dashed lines show the 95% confidence band for the Nadaraya-Watson kernel regression. The ordinary least-squares (OLS)19 fit to the Nadaraya-Watson kernel regression applied to the data on homicides in (a) reveals an allometric exponent β = 1.24 ± 0.01, with a 95% confidence interval estimated by bootstrap. This is compatible with previous results obtained for U.S.2 that also indicate a super-linear scaling relation with population and an exponent β = 1.16. Using the same procedure, we find β = 0.99 ± 0.02 and 0.84 ± 0.02 for the numbers of deaths in traffic accidents (b) and suicides (c), respectively. The values of the Pearson correlation coefficients ρ associated with these scaling relations are shown in each plot. This non-linear behavior observed for homicides and suicides certainly reflects the complexity of human social relations and strongly suggests that the the topology of the social network plays an important role on the rate of these events. (d) The solid lines show the Nadaraya-Watson kernel regression rate of deaths (total number of deaths divided by the population of a city) for each urban indicator, namely, homicides (red), traffic accidents (blue), and suicides (green). The dashed lines represent the 95% confidence bands. While the rate of fatal traffic accidents remains approximately invariant, the rate of homicides systematically increases, and the rate of suicides decreases with population.
Mentions: The main goal here is to investigate the scaling behavior with city population of three urban indicators, namely the number of homicides, deaths in traffic accidents and suicides. For this, we analyzed data available for all Brazilian cities as well as suicide for US counties and MSAs, as presented previously on Materials and Methods. For 2009 in Brazil, as shown in Fig. 1, the increase in the number of casualties D with city population P for the three death causes can be properly described in terms of power-laws, D = D0Pβ, where D0 is a costant pre-factor, and the exponent β reflects a global property at play across the urban system. Interestingly, while the number of deaths by traffic accidents display isometric scaling, β ≈ 1, homicides and suicides are both allometric, but obeying superlinear and sublinear scaling with population, respectively. These results suggest that the decision to commit a crime or to suicide, instead of being purely a consequence of individual choices, might have strong correlations with the underlying complex social organization and interactions. This does not seem to be the case of traffic accidents, since the strong evidence for isometric scaling, β = 0.99 ± 0.02, indicates that such events should result from random processes, i.e., no social relations need to be implied among the involved people.

Bottom Line: Under the same framework, he considered that crime is bound up with the fundamental conditions of all social life.The social effect on the occurrence of homicides has been previously substantiated, and confirmed here, in terms of a superlinear scaling relation: by doubling the population of a Brazilian city results in an average increment of 135% in the number of homicides, rather than the expected isometric increase of 100%, as found, for example, for the mortality due to car crashes.Differently from homicides (superlinear) and fatal events in car crashes (isometric), we find sublinear scaling behavior between the number of suicides and city population, with allometric power-law exponents, β = 0.84 ± 0.02 and 0.87 ± 0.01, for all cities in Brazil and US counties, respectively.

View Article: PubMed Central - PubMed

Affiliation: Departamento de Física, Universidade Federal do Ceará, 60451-970 Fortaleza, Ceará, Brazil.

ABSTRACT
By treating the suicide as a social fact, Durkheim envisaged that suicide rates should be determined by the connections between people and society. Under the same framework, he considered that crime is bound up with the fundamental conditions of all social life. The social effect on the occurrence of homicides has been previously substantiated, and confirmed here, in terms of a superlinear scaling relation: by doubling the population of a Brazilian city results in an average increment of 135% in the number of homicides, rather than the expected isometric increase of 100%, as found, for example, for the mortality due to car crashes. Here we present statistical signs of the social influence on the suicide occurrence in cities. Differently from homicides (superlinear) and fatal events in car crashes (isometric), we find sublinear scaling behavior between the number of suicides and city population, with allometric power-law exponents, β = 0.84 ± 0.02 and 0.87 ± 0.01, for all cities in Brazil and US counties, respectively. Also for suicides in US, but using the Metropolitan Statistical Areas (MSAs), we obtain β = 0.88 ± 0.01.

Show MeSH
Related in: MedlinePlus