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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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Temporal evolution of allometric exponent β for homicides (red squares), deaths in traffic accidents (blue circles), and suicides (green diamonds).Time evolution of the power-law exponent β for each behavioral urban indicator in Brazil from 1992 to 2009. We can see that the non-linear behavior for homicides and suicides are robust for this 19 years period, and for the traffic accidents the exponent remain close to 1.0.
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f2: Temporal evolution of allometric exponent β for homicides (red squares), deaths in traffic accidents (blue circles), and suicides (green diamonds).Time evolution of the power-law exponent β for each behavioral urban indicator in Brazil from 1992 to 2009. We can see that the non-linear behavior for homicides and suicides are robust for this 19 years period, and for the traffic accidents the exponent remain close to 1.0.

Mentions: The discrepancies observed in the scaling behaviors of homicides, deaths in traffic accidents and suicides become even more evident if we plot the average number of deaths per capita against city population, as shown in Fig. 1d. Under this framework, the systematic decrease in suicide rate with population indicates that a large supply of potential social contacts and interactions might work as an “antidote” for this tragic event. This result is consistent with the idea that human happiness is more a collective phenomenon than a consequence of individual well-being conditions. In analogy with health, it is then possible to consider a “happiness epidemy” spreading in a social network12. In Fig. 2 we show the dependence on time of the exponent β for a period of 18 years, from 1992 to 2009. We see a robust behavior for β, in such a way that, for different years, we still observe β > 1.0 for homicides, β < 1.0 for suicides, and β slightly above 1.0 for deaths by traffic accidents.


Statistical signs of social influence on suicides.

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

Temporal evolution of allometric exponent β for homicides (red squares), deaths in traffic accidents (blue circles), and suicides (green diamonds).Time evolution of the power-law exponent β for each behavioral urban indicator in Brazil from 1992 to 2009. We can see that the non-linear behavior for homicides and suicides are robust for this 19 years period, and for the traffic accidents the exponent remain close to 1.0.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

f2: Temporal evolution of allometric exponent β for homicides (red squares), deaths in traffic accidents (blue circles), and suicides (green diamonds).Time evolution of the power-law exponent β for each behavioral urban indicator in Brazil from 1992 to 2009. We can see that the non-linear behavior for homicides and suicides are robust for this 19 years period, and for the traffic accidents the exponent remain close to 1.0.
Mentions: The discrepancies observed in the scaling behaviors of homicides, deaths in traffic accidents and suicides become even more evident if we plot the average number of deaths per capita against city population, as shown in Fig. 1d. Under this framework, the systematic decrease in suicide rate with population indicates that a large supply of potential social contacts and interactions might work as an “antidote” for this tragic event. This result is consistent with the idea that human happiness is more a collective phenomenon than a consequence of individual well-being conditions. In analogy with health, it is then possible to consider a “happiness epidemy” spreading in a social network12. In Fig. 2 we show the dependence on time of the exponent β for a period of 18 years, from 1992 to 2009. We see a robust behavior for β, in such a way that, for different years, we still observe β > 1.0 for homicides, β < 1.0 for suicides, and β slightly above 1.0 for deaths by traffic accidents.

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