Abstracts

Introduction

Violence has been recognized for several decades as a problem for criminal justice and defense departments and sectors. It has been a topic of debate in the most diverse United Nations (UN) resolutions since 1986. The international health agenda at the World Health Assembly in 1996 ¹1. World Health Organization. Resolution WHA49.25, approved by the Forty-ninth World Health Assembly. Geneva: World Health Organization; 1996. included it, declaring violence a major public health issue worldwide. The UN urged its member states to immediately address the problem of violence, asking the World Health Organization (WHO) to develop a scientific approach to understanding and preventing violence ²2. World Health Organization. Global status report on violence prevention. Geneva: World Health Organization; 2014..

Of the different types of violence in our society, this study will focus on homicide. Homicide is the most visible result of the violent behavior recorded in official statistics. Estimates show that, in 2017, 464,000 people were murdered on the planet - which is equivalent to a total rate of 6.1 per 100,000 inhabitants in the world ²2. World Health Organization. Global status report on violence prevention. Geneva: World Health Organization; 2014.^,33. Deplorable' killing of Afro-Brazilian man shows need to address racism, discrimination. United Nations News 2020; 24 nov. https://news.un.org/en/story/2020/11/1078432.
https://news.un.org/en/story/2020/11/107... . The Americas continue to be the region with the highest reported number of homicides and Brazil is the country with the highest absolute number on the planet: one out of every seven homicides reported in the world occurs in Brazil ²2. World Health Organization. Global status report on violence prevention. Geneva: World Health Organization; 2014.^,44. United Nations Office on Drugs and Crime. Global study on homicide. Understanding homicide: typologies, demographic factors, mechanisms, and contributors. Vienna: United Nations Office on Drugs and Crime; 2019.^,55. Waiselfisz JJ. Os jovens do Brasil: mapa da violência 2014. Brasília: Editora FLACSO; 2014.. However, Brazil had the 12th highest homicide rate of all countries in 2017 (around 30 homicides per 100,000 inhabitants), according to data from the UN Office on Drugs and Crime ⁴4. United Nations Office on Drugs and Crime. Global study on homicide. Understanding homicide: typologies, demographic factors, mechanisms, and contributors. Vienna: United Nations Office on Drugs and Crime; 2019.. The WHO ⁶6. World Health Organization. Global Health Observatory data repository. Estimates of rate of homicides (per 100 000 population). https://www.who.int/data/gho/data/indicators/indicator-details/GHO/estimates-of-rates-of-homicides-per-100-000-population (accessed on 24/Aug/2022).
https://www.who.int/data/gho/data/indica... also estimated a rate of 61.5 homicides per 100,000 for men and 6.0/100,000 for women. Overall, Brazil had around 65,602 homicides in 2017, a rate around five times higher than the world average ⁷7. Instituto de Pesquisa Econômica Aplicada; Fórum Brasileiro de Segurança Pública. Atlas da violência 2019. Brasília/Rio de Janeiro/São Paulo: Instituto de Pesquisa Econômica Aplicada; 2019..

Both the different typologies of violence (on a broader spectrum) and homicidal violence more specifically cause different consequences for the people and places in which they occur ⁸8. Cerqueira D, Soares RR. The welfare cost of homicides in Brazil: accounting for heterogeneity in the willingness to pay for mortality reductions. Health Econ 2016; 25:259-76.^,99. Reichenheim ME, Souza ER, Moraes CL, Mello Jorge MHP, Silva CMFP, Souza Minayo MC. Violence and injuries in Brazil: the effect, progress made, and challenges ahead. Lancet 2011; 377:1962-75.. Its impacts range from the individual trauma to its victims and their families to impacts on the economy - since a great number of financial resources are allocated to actions to combat violence. Estimates suggest that, in Brazil, the cost of violence reaches 5.9% of its Gross Domestic Product (GDP), which corresponds to BRL 372 billion every year ¹⁰10. Fórum Brasileiro de Segurança Pública. Anuário Brasileiro de Segurança Pública 2017. São Paulo: Fórum Brasileiro de Segurança Pública; 2017..

Several studies shed light on the impacts of homicides in Brazil ¹¹11. Nsoesie EO, Lima Neto AS, Jay J, Wang H, Zinszer K, Saha S, et al. Mapping disparities in homicide trends across Brazil: 2000-2014. Int J Epidemiol 2020; 7:47.^,1212. Oliveira ALS, Luna CF, Silva MGP. Homicídios do Brasil na última década: uma revisão integrativa. Ciênc Saúde Colet 2020; 25:1925-33.^,1313. Walselfisz JJ. Mapa da violência 2016: homicídios por armas de fogo no Brasil. https://flacso.org.br/2016/08/25/mapa-da-violencia-2016-homicidios-por-armas-de-fogo-no-brasil/ (accessed on 13/Sep/2021).
https://flacso.org.br/2016/08/25/mapa-da... ^,1414. Costa DH, Njaine K, Schenker M. Repercussions of homicide on victims' families: a literature review. Ciênc Saúde Colet 2017; 22:3087-97.. Recent studies ¹²12. Oliveira ALS, Luna CF, Silva MGP. Homicídios do Brasil na última década: uma revisão integrativa. Ciênc Saúde Colet 2020; 25:1925-33.^,1515. Tavares R, Catalan VDB, Romano PMM, Melo EM. Homicides and social vulnerability. Ciênc Saúde Colet 2016; 21:923-34.^,1616. Wanzinack C, Signorelli MC, Reis C. Homicides and socio-environmental determinants of health in Brazil: a systematic literature review. Cad Saúde Pública 2018; 34:e00012818. show the relation between homicides and social determinants of health (SDH) in Brazil, of which young, black, poor, and low-educated men are its main victims ⁵5. Waiselfisz JJ. Os jovens do Brasil: mapa da violência 2014. Brasília: Editora FLACSO; 2014.^,1717. Araújo EM, Araújo TM, Santana F. Distribuição desigual da mortalidade por causas externas: avaliação de aspectos socioeconômicos. Rev Baiana Saúde Pública 2005; 29:262-72.. However, research needs more studies to understand this complex scenario, particularly considering wider periods of analysis and differences between Brazilian municipalities. The WHO Commission on the Social Determinants of Health has defined SDH as “the conditions in which people are born, grow, live, work and age” and “the fundamental drivers of these conditions” ¹⁸18. WHO Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of dealth. Geneva: World Health Organization; 2008. (p. 1). “Social determinants” include the health-related factors of cities and communities (e.g., decent urban conditions and sanitation) but also socioeconomic (e.g., income and education) and structural ones (e.g., gender, race/ethnicity, and age). All these factors are considered fundamental causes of a wide range of health outcomes ¹⁸18. WHO Commission on Social Determinants of Health. Closing the gap in a generation: health equity through action on the social determinants of dealth. Geneva: World Health Organization; 2008.^,1919. Braveman P, Egerter S, Williams DR. The social determinants of health: coming of age. Annu Rev Public Health 2011; 32:381-98.^,2020. Braveman P, Gottlieb L. The social determinants of health: it's time to consider the causes of the causes. Public Health Rep 2014; 129 Suppl 2:19-31..

More recently, the WHO ²¹21. World Health Organization. Social determinants of health. https://apps.who.int/gb/ebwha/pdf_files/EB148/B148_R2-en.pdf (accessed on 10/May/2022).
https://apps.who.int/gb/ebwha/pdf_files/... reinforced the need to strengthen the monitoring systems which provide disaggregated data to assess inequities in health, their relation to SDH, and the national, regional, and global impacts of policies on the SDH in support of the 2030 Agenda for Sustainable Development ²¹21. World Health Organization. Social determinants of health. https://apps.who.int/gb/ebwha/pdf_files/EB148/B148_R2-en.pdf (accessed on 10/May/2022).
https://apps.who.int/gb/ebwha/pdf_files/... . Based on these assumptions and facing the complexity of Brazil as having amongst the highest homicide rates in the world, the question which guided our study was: is there an association between selected SDH and homicides in Brazil if we analyze all Brazilian municipalities during a longer period (2005 to 2015)?

Studies show that homicides are unevenly distributed across the Brazilian territory ¹⁶16. Wanzinack C, Signorelli MC, Reis C. Homicides and socio-environmental determinants of health in Brazil: a systematic literature review. Cad Saúde Pública 2018; 34:e00012818.^,2222. Bando DH, Lester D. An ecological study on suicide and homicide in Brazil. Ciênc Saúde Colet 2014; 19:1179-89.^,2323. Briceño-León R, Villaveces A, Concha-Eastman A. Understanding the uneven distribution of the incidence of homicide in Latin America. Int J Epidemiol 2008; 37:751-7.. Nevertheless, national ecological studies analyzing the associations between homicide and SDH at the municipal level and during longer periods of analysis are scarce. Therefore, considering these gaps, this study aimed to analyze the relations between homicidal violence, recorded between 2005 and 2015, and SDH selected from all 5,570 Brazilian municipalities. This study focused on analyzing the following SDH: human development, income inequality, municipal population size, and urbanization rate.

Methods

A retrospective exploratory ecological time-series study was conducted ²⁴24. Morgenstern H, Thomas D. Principles of study design in environmental epidemiology. Environ Health Perspect 1993; 101 Suppl 4:23-38.. Average homicide rates from 2005 to 2015 was calculated and compared with socioeconomic indicators for all 5,570 Brazilian municipalities. A longer analysis period (2005-2015) helps us to understand the evolution of homicides in Brazilian municipalities with greater data precision. More recent years are still unavailable in the consulted database.

Only secondary data obtained from open and free access databases were analyzed. Consequently, approval from the Research Ethics Committee could be waivered.

Data source: dependent variable

(a) Homicides: data were obtained from the Brazilian Health Informatics Department (DATASUS) of the Brazilian Unified National Health System (SUS) website of the Brazilian Ministry of Health. Deaths due to aggression were selected (codes X85 to Y09 and Y35 and 36 of the International Classification of Diseases 10^th revision (ICD-10), here referred to as homicides) from the Brazilian Mortality Information System (SIM). Data were collected according to the municipality in which the homicides occurred between 2005 and 2015.

Data source: independent variables (SDH)

(a) Population: data from the 5,570 Brazilian municipalities were considered. This information was collected by the Brazilian Institute of Geography and Statistics (IBGE) in the last Brazilian census, conducted in 2010. Population data were obtained directly from the IBGE Automatic Recovery System (SIDRA) ²⁵25. Sistema IBGE de Recuperação Automática. Censo demográfico 2010. https://sidra.ibge.gov.br/home/ipca15/brasil (accessed on 26/Mar/2021).
https://sidra.ibge.gov.br/home/ipca15/br... .

(b) Municipal Human Development Index (HDI-M): this is the municipal version of the HDI, which is a measure composed of indicators from three dimensions of human development: longevity (life expectancy), education (average completed years of study), and income. They differ since the HDI-M uses the average income of residents in the municipalities instead of GDP per capita (used when calculating HDI). HDI-M ranges from 0 to 1 and the closer to 1, the greater the human development. The 2010 HDI-M of all Brazilian municipalities were collected from the Atlas of Human Development in Brazil²⁶26. Atlas do Desenvolvimento Humano do Brasil. http://www.atlasbrasil.org.br/ (accessed on 26/Mar/2021).
http://www.atlasbrasil.org.br/... .

(c) Gini index: a measurement of income distribution which refers to social inequalities. It ranges from 0 to 1, in which 0 represents a situation of complete income equality (in which each individual has the same income), whereas the value 1 indicates extreme inequality. Data were collected by municipality, for 2010, from the Atlas of Human Development in Brazil²⁶26. Atlas do Desenvolvimento Humano do Brasil. http://www.atlasbrasil.org.br/ (accessed on 26/Mar/2021).
http://www.atlasbrasil.org.br/... .

(d) Urbanization rate: the percentage of urban population against total population. It was extracted from the IBGE Census for each Brazilian municipality in 2010.

Statistical procedures

Being the number of homicides in city i and year t, O _i,t was considered as our outcome. The expected number of deaths obtained from indirect standardization e _i,t , was considered to contemplate demographic differences between municipalities. Standardization was carried out considering gender, age, and race/color variables since municipalities with more men, youths, and black people would be imbalanced since these characteristics are more associated with homicides.

HDI-M, Gini index, urbanization rates, and population were examined to explain the variations which the demographic structure failed to elucidate. This extra variation r _i,t is labeled as the risk for homicide in municipality i and year t. A value of risk (r _i,t greater than 1) indicates that i municipality observed more homicides in year t than expected by its demography.

To be more specific, a Poisson distribution was assumed for O _o,t . The product between the expected value of deaths and standardized mortality risk is the parameter of this distribution. Thus:

HDI-M, Gini index, resident population, and urbanization rates were evaluated for their effect on relative risk. To accommodate extra variation which these factors fail to explain, a spatiotemporal effect representing a risk relative to municipality i and year t,.s _i,t , was considered.

The model for the relative risk is expressed by the following logarithm:

in which is a necessary intercept parameter for best estimation; parameters β _i j = 1,2,3,4β _j represent the effect of the respective factor and the spatiotemporal effect. The interpretability of parameters β _j refers to the risk related to changing one unit of the associated factor.

Spatiotemporal effect s _i,t modeling was expressed by combining two approaches in the literature. A spatiotemporal autoregressive model ²⁷27. Martínez-Beneito MA, López-Quilez A, Botella-Rocamora P. An autoregressive approach to spatio-temporal disease mapping. Stat Med 2008; 27:2874-89. was considered but with a parameterization for the spatial model ²⁸28. Riebler A, Sørbye SH, Simpson D, Rue H. An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Stat Methods Med Res 2016; 25:1145-65..

Consequently:

in which ρ is a temporal persistence parameter and s _i,t is the term with a spatial correlation structure. If ρ is close to 0, the standardized mortality ratio (SMR) between consecutive years has no correlation and the temporal correlation between consecutive years increases to ρ as ρ approaches 1.

The term s _i,t is considered to have a structured part in space and an unstructured parameterized part ²⁸28. Riebler A, Sørbye SH, Simpson D, Rue H. An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Stat Methods Med Res 2016; 25:1145-65.. In this case:

in which v is an unstructured effect in space with variance 1, i.e., v _i,t ~ N(0,1); and u _i,t , the spatially structured effect with a marginal variance equal to 1. Thus, parameter ϕ measures the proportion of the spatial effect structured in space and is associated with the degree of spatial correlation of homicide rates.

The inference procedure was considered under the Bayesian paradigm. The a priori distribution of parameters σ_s , 𝜙, and ρ considers the shape complexity penalty ²⁹29. Simpson D, Rue H, Riebler A, Martins TG, Sørbye SH. Penalising model component complexity: a principled, practical approach to constructing priors. Stat Sci 2017; 32:1-28.. The corresponding a priori complexity penalty for parameter ρ was also considered. To calculate marginal posterior distributions, the Integrated and Nested Laplace Approximation Algorithm, better known as INLA (https://www.r-inla.org/), was used. Based on the described methodology, these procedures guaranteed the hypothesis test, which aimed to investigate the relations between SDH and homicides in all 5,570 Brazilian municipalities over time. The independent variables included in the final model were the Gini index, HDI-M, urbanization rates and population size, whereas the outcome variable was “homicides”, in a multilevel analysis approach.

Analyses were conducted in R version 4.2.0 (http://www.r-project.org), utilizing the following packages: Matrix (https://cran.r-project.org/web/packages/Matrix/index.html), rgdal (https://cran.r-project.org/web/packages/rgdal/), and INLA (https://www.r-inla.org/). Missing data, unavailable in the consulted databases, such as references to the occurrence of homicides (victim’s gender, race, age, or place of occurrence), were standardized according to the resulting N, guaranteeing the proportionality of the sample.

Spatial analysis

The final generated model had its response variable (SMR) predicted for all Brazilian municipalities and its results were rasterized and expressed in maps per year of evaluation.

Results

We developed a model for the standardized mortality rate in each Brazilian municipality from 2005 to 2015. We considered HDI-M, Gini index, base-10 logarithm of the resident population, and urbanization rates as fixed effects in a model to explain the evolution of homicide during the period. We calculated four covariates related to SDH for each municipality in 2010, based on demographic census data (Figure 1).

According to Figure 1, Brazil has few municipalities with a very high HDI-M (≥ 0.8), whereas its vast majority had an HDI-M between 0.5 and 0.799 in 2010, showing great variability in terms of human development. Regarding the Gini index, most municipalities have an income inequality index between 0.35 and 0.65. In 2010, no municipality had low inequality, highlighting its persistence among Brazilian cities.

Urbanization rates showed great variability. We found a reasonable number of municipalities with less than 40% of residents in urban areas. Most cities are distributed in similar frequencies along a range between 40% and 100% of urbanization.

As for the resident population in 2010, we considered a base-10 log scale due to its large variation range. Few municipalities had less than 1,000 inhabitants and some, more than one million inhabitants. We found almost 2,000 cities with a population of around 3,000 to 10,000 inhabitants (10^3.5 up to 10⁴) and a little more than 2,000 municipalities with a population between 10,000 to 30,000 inhabitants (10⁴ and 10^4.5). Therefore, most Brazilian cities have less than 30,000 inhabitants.

On the other hand, Table 1 estimates the effect of population size, urbanization rates, the Gini index, and HDI-M on the risk of homicidal violence in Brazilian municipalities. The effect of population size represents the variable most associated with the risk of homicidal violence. Data in Table 1 show that the occurrence of homicides is more associated with populous municipalities (log 10), with an 80.8% (95% credibility interval - 95%CI: 73.0; 88.8) average risk; more urbanized cities, with an 8% (95%CI: 6.7; 9.2) average risk; municipalities with higher Gini index, with 6% (95%CI: 2.6; 9.5) average risk; whereas the relation with HDI-M is inverse. In other words, the risk is greater for municipalities with lower HDI-M, with -17.1% (95%CI: -21.4; -12.6) average risk.

Table 1 also shows the relative effect of each covariable considered in relative risk. The effect of urbanization rates, Gini index, and HDI-M were multiplied by 10 to facilitate the interpretation of the results, thus the estimated effect of an increase of 0.1 (10%) in the urbanization rate, 0.1 in the Gini index, and 0.1 in the HDI-M.

We may consider the relative risk coefficients in Table 1 to assess the effect of these factors. When comparing two municipalities, these coefficients show whether their relative homicide risk rose or fell due to an increase in one unit of the considered factor. Therefore, municipalities with larger populations, higher urbanization rates, or higher Gini index tend to show a higher risk of homicide. On the other direction, municipalities with higher HDI-M tended to show a lower risk of homicide.

Thus, for a municipality with a population 10 times greater than another, its risk of homicide rose around 80%, with a 95%CI of this increase lying between 73% and 88.8%. We can consider this result to show how greater is the risk of homicide in large cities. In addition to having more homicides due to their larger population, the fact that this risk is greater in large cities more pronouncedly concentrates homicides.

As for urbanization rates, we observed that a 10% increase in the proportion of people residing in urban areas is associated with an average increase of 8% in the risk of homicide, with a 95%CI varying from 6.7% to 9.2% in the risk of homicide.

A 0.1 increase in the Gini index is associated with a 6% average increase in the risk of homicide, with a 95% credibility interval ranging from 2.6% to 9.5%. This means that the more socioeconomic inequality increases in a territory, the more the risk of homicide tends to rise. Considering the current Brazilian scenario of 60,000 homicides per year, reducing Gini by 0.1 would represent saving between 1,569 and 5,448 lives annually.

An increase of 0.1 in HDI-M represents an average reduction of 17.1% in the risk of homicide, with a 95%CI ranging from -12.6% to -21.4%. If, on average, the municipal HDI were to raise by 0.1, we would have a considerable reduction in the number of homicides. Considering the annual reported homicides of around 60,000, this decrease would represent saving between 7,560 and 12,834 Brazilian lives. Thus, our analysis suggests that the risk of homicide is greater in more populous cities, with higher urbanization rates, greater income inequality, and lower human development.

Figure 2 displays our SMR maps with the annual spatial distribution of homicides in Brazilian municipalities (2005-2015). It shows a pattern which seems to repeat year after year. The distribution of homicides is quite heterogeneous. Some regions register much more homicides than expected, with an SMR greater than 1. In this group are a range of municipalities in the Eastern portion of Brazil, bordering the Atlantic Ocean from its Northeast to its South. This range encompasses densely populated coastal regions and several state capitals, including the states of Pernambuco, Alagoas, Bahia, Espírito Santo, Rio de Janeiro, and Paraná, among others. In Paraná, this strip seems to move inland toward the West, linking with another long range running through the Brazilian Central-West and North. In this range, homicide rates are much higher than expected close to international borders, particularly with Paraguay (in the states of Paraná and Mato Grosso do Sul), Bolivia (in the states of Mato Grosso and Rondônia), and Venezuela (in the State of Roraima). Another highlight is the so-called “agricultural frontier”, which comprises vast portions of the states of Mato Grosso, Rondônia, and the south of Pará, all areas with recognized land disputes.

On the other hand, Figure 2 also shows that many regions had an SMR < 1, registering fewer homicides than expected. In general, this occurred in the states of Acre, Amazonas, Northwestern Pará, Piauí, and in most of the states of Minas Gerais, São Paulo, Maranhão, and Tocantins. Analysis also showed how the distribution of homicides is heterogeneous even within the states. Bahia is one of these examples, with regions with lower (< 1) SMR (in its Western portion, close to its border with Tocantins); whereas other regions had higher (> 1) SMR, such as its East and South coastal sides.

Discussion

Our study shows that homicides are unevenly distributed within the Brazilian territory and attested the association of SDH with homicides, particularly in more populous cities, urbanized areas, and places with greater socioeconomic inequalities. On the other hand, human development is a factor which seems to protect the population, reducing their exposure to this type of violence in cities with greater HDI-M. Understanding and describing these events and their territorial variations is a permanent challenge and an efficient way to contribute to the improvement of public policies and urban planning ¹⁶16. Wanzinack C, Signorelli MC, Reis C. Homicides and socio-environmental determinants of health in Brazil: a systematic literature review. Cad Saúde Pública 2018; 34:e00012818..

International studies have shown the relations between homicides and SDH in countries like the United States, Mexico, Canada, and Australia ³⁰30. Kim D. Social determinants of health in relation to firearm-related homicides in the United States: a nationwide multilevel cross-sectional study. PLoS Med 2019; 16:e1002978.^,3131. Medina Gómez OS, Villegas Lara B. Homicidios en jóvenes y desigualdades sociales en México, 2017. Rev Panam Salud Pública 2019; 43:e94.^,3232. Wilkins NJ, Zhang X, Mack KA, Clapperton AJ, Macpherson A, Sleet D, et al. Societal determinants of violent death: the extent to which social, economic, and structural characteristics explain differences in violence across Australia, Canada, and the United States. SSM Popul Health 2019; 8:100431.^,3333. Lachaud J, Donnelly PD, Henry D, Kornas K, Calzavara A, Bornbaum C, et al. A population-based study of homicide deaths in Ontario, Canada using linked death records. Int J Equity Health 2017; 16:133.. Previously, only a few nationwide studies ³⁴34. Duarte EC, Garcia LP, Freitas LRS, Mansano NH, Monteiro RA, Ramalho WM. Associação ecológica entre características dos municípios e o risco de homicídios em homens adultos de 20-39 anos de idade no Brasil, 1999-2010. Ciênc Saúde Colet 2012; 17:2259-68.^,3535. Soares Filho AM. Vitimização por homicídios segundo características de raça no Brasil. Rev Saúde Pública 2011; 45:745-55.^,3636. Peres MFT, Nivette A. Social disorganization and homicide mortality rate trajectories in Brazil between 1991 and 2010. Soc Sci Med 2017; 190:92-100.^,3737. Nadanovsky P, Celeste RK, Wilson M, Daly M. Homicide and impunity: an ecological analysis at state level in Brazil. Rev Saúde Pública 2009; 2009; 43:733-42.^,3838. Garcia LP, Freitas LRS, Silva GDM, Höfelmann DA. Estimativas corrigidas de feminicídios no Brasil, 2009 a 2011. Rev Panam Salud Pública 2015; 37:251-7. analyzed this issue for all 5,570 Brazilian municipalities over several years but numerous studies focused on specific Brazilian states ³⁹39. Andrade SM, Soares DA, Souza RKT, Matsuo T, Souza HD. Homicídios de homens de quinze a 29 anos e fatores relacionados no estado do Paraná, de 2002 a 2004. Ciênc Saúde Colet 2011; 16:1281-8.^,4040. Cardoso FLMG, Cecchetto FR, Corrêa JS, Souza TO. Homicides in Rio de Janeiro, Brazil: an analysis of lethal violence. Ciênc Saúde Colet 2016; 21:1277-88.^,4141. Lima MLC, Ximenes RAA, Souza ER, Luna CF, Albuquerque MFPM. Análise espacial dos determinantes socioeconômicos dos homicídios no Estado de Pernambuco. Rev Saúde Pública 2005; 39:176-82.^,4242. Mansano NH, Gutierrez MMU, Ramalho W, Duarte EC. Homicídios em homens jovens de 10 a 24 anos e condições sociais em municípios do Paraná e Santa Catarina, Brasil, 2001-2010. Epidemiol Serv Saúde 2013; 22:203-14.^,4343. Souza TO, Pinto LW, Souza ER. Estudo espacial da mortalidade por homicídio, Bahia, 1996-2010. Rev Saúde Pública 2014; 48:468-77.^,4444. Camds S, Cosme M, Souza ER. Determinants of homicides in the state of Bahia, Brazil, in 2009. Rev Bras Epidemiol 2014; 17:135-46. or cities ⁴⁴44. Camds S, Cosme M, Souza ER. Determinants of homicides in the state of Bahia, Brazil, in 2009. Rev Bras Epidemiol 2014; 17:135-46.^,4545. Barata RB, Ribeiro MCSA. Relação entre homicídios e indicadores econômicos em São Paulo, Brasil, 1996. Rev Panam Salud Pública 2000; 7:118-24.^,4646. Santos SM, Barcellos C, Carvalho MS. Ecological analysis of the distribution and socio-spatial context of homicides in Porto Alegre, Brazil. Health Place 2006; 12:38-47.^,4747. Duarte EC, Tauil PL, Duarte E, Sousa MC, Monteiro RA. Mortalidade por acidentes de transporte terrestre e homicídios em homens jovens das capitais das Regiões Norte e Centro-Oeste do Brasil, 1980-2005. Epidemiol Serv Saúde 2008; 17:7-20.. One of these nationwide studies ³⁴34. Duarte EC, Garcia LP, Freitas LRS, Mansano NH, Monteiro RA, Ramalho WM. Associação ecológica entre características dos municípios e o risco de homicídios em homens adultos de 20-39 anos de idade no Brasil, 1999-2010. Ciênc Saúde Colet 2012; 17:2259-68. specifically analyzed the homicides of men aged 20 to 39 years between 1999-2002 and 2007-2010, showing that homicide rates were significantly higher in larger cities, associated with higher fertility rates, lower literacy levels, higher social inequality, and more urbanized municipalities ³⁴34. Duarte EC, Garcia LP, Freitas LRS, Mansano NH, Monteiro RA, Ramalho WM. Associação ecológica entre características dos municípios e o risco de homicídios em homens adultos de 20-39 anos de idade no Brasil, 1999-2010. Ciênc Saúde Colet 2012; 17:2259-68.. On the other hand, studies draw attention to the fact that small and medium municipalities have been showing rapid growth in homicide rates, despite having lower values for this indicator ³⁴34. Duarte EC, Garcia LP, Freitas LRS, Mansano NH, Monteiro RA, Ramalho WM. Associação ecológica entre características dos municípios e o risco de homicídios em homens adultos de 20-39 anos de idade no Brasil, 1999-2010. Ciênc Saúde Colet 2012; 17:2259-68.^,4848. Soares Filho AM, Duarte EC, Merchan-Hamann E. Tendência e distribuição da taxa de mortalidade por homicídios segundo porte populacional dos municípios do Brasil, 2000 e 2015. Ciênc Saúde Colet 2020; 25:1147-56..

Our analysis showed that the larger the population of a municipality, the greater the risk of homicide, reaffirming previous studies conducted in other countries ⁴⁹49. Hutchinson G. Variation of homicidal and suicidal behaviour within Trinidad and Tobago and the associated ecological risk factors. West Indian Med J 2005; 54:319-24.. This data is consistent with a spatial analysis which found that few municipalities account for most Brazilian homicides ³⁶36. Peres MFT, Nivette A. Social disorganization and homicide mortality rate trajectories in Brazil between 1991 and 2010. Soc Sci Med 2017; 190:92-100.. In total, 150 Brazilian cities, which correspond to only 2.7% of the municipalities in the country, account for more than 60% of its homicides ⁵⁰50. Wanzinack C, Signorelli M, Reis C. Homicide mortality in Brazilian States and Municipalities from 2005 to 2015: a socio-spatial analysis. Cad Saúde Colet (Rio J.); in press.. Most have a population of over 290,000 inhabitants. Nonetheless, research must analyze these data with caution, considering that they fail to necessarily mean that smaller cities are free from this form of violence - though this study intended to highlight its predominant pattern.

Another covariable we analyzed was urbanization rates: the risk of homicide proportionally increased with it. This result is consistent with studies conducted in other countries ⁵¹51. Cubbin C, Pickle LW, Fingerhut L. Social context and geographic patterns of homicide among US black and white males. Am J Public Health 2000; 90:579-87.. Comparing covariables, urbanization rates show a smaller impact than population size on homicides but the literature knows that, in practice, both factors are usually associated ⁴²42. Mansano NH, Gutierrez MMU, Ramalho W, Duarte EC. Homicídios em homens jovens de 10 a 24 anos e condições sociais em municípios do Paraná e Santa Catarina, Brasil, 2001-2010. Epidemiol Serv Saúde 2013; 22:203-14.. Urbanization, associated with population increase, may become a decisive factor regarding urban violence, in which lack of resources such as income (including its poor distribution) and disordered growth can add to other challenges of large cities, such as lack of access to health, safety, and public education ¹⁵15. Tavares R, Catalan VDB, Romano PMM, Melo EM. Homicides and social vulnerability. Ciênc Saúde Colet 2016; 21:923-34.^,5252. Gawryszewski VP, Costa LS. Homicídios e desigualdades sociais no Município de São Paulo. Rev Saúde Pública 2005; 39:191-7.. Urban poverty and unhealthy living are directly linked to lack of power among the most vulnerable communities to demand and impose better living conditions ⁵³53. Jiménez De La Jara J, Torres Hidalgo M, Salcedo Hansen R. A cidade na perspectiva dos determinantes da saúde. In: Galvão LAC, Finkelman J, Henao S, editors. Determinantes ambientais e sociais da saúde. Rio de Janeiro: Organização Pan-Americana da Saúde/Editora Fiocruz; 2011. p. 197-214.. Authors have been postulating that it is necessary to remove sources of freedom deprivation, including violence, neglect of public services, poverty, and absence of economic opportunities for societies to achieve a satisfactory human development ⁵⁴54. Sen A. Desenvolvimento como liberdade. São Paulo: Editora Companhia das Letras; 2018..

The most recent nationwide data on homicides in Brazil, made available by the Brazilian Forum on Public Security (FBSP) in 2021 ⁵⁵55. Fórum Brasileiro de Segurança Pública. Anuário Brasileiro de Segurança Pública 2022. São Paulo: Fórum Brasileiro de Segurança Pública; 2022., reaffirms that the victim profile consists mostly of men (91.3%), black individuals (76.2%), and young people (54.3%), with 78% of cases involving firearms. The same report ⁵⁵55. Fórum Brasileiro de Segurança Pública. Anuário Brasileiro de Segurança Pública 2022. São Paulo: Fórum Brasileiro de Segurança Pública; 2022. also showed a 4% increase in homicides compared to the previous year. The literature describes this predominant victim profile ¹⁵15. Tavares R, Catalan VDB, Romano PMM, Melo EM. Homicides and social vulnerability. Ciênc Saúde Colet 2016; 21:923-34.^,3535. Soares Filho AM. Vitimização por homicídios segundo características de raça no Brasil. Rev Saúde Pública 2011; 45:745-55.^,4444. Camds S, Cosme M, Souza ER. Determinants of homicides in the state of Bahia, Brazil, in 2009. Rev Bras Epidemiol 2014; 17:135-46. well and studies have added that worse socioeconomic conditions are also linked to exposure to homicides ²²22. Bando DH, Lester D. An ecological study on suicide and homicide in Brazil. Ciênc Saúde Colet 2014; 19:1179-89.^,3636. Peres MFT, Nivette A. Social disorganization and homicide mortality rate trajectories in Brazil between 1991 and 2010. Soc Sci Med 2017; 190:92-100.^,4242. Mansano NH, Gutierrez MMU, Ramalho W, Duarte EC. Homicídios em homens jovens de 10 a 24 anos e condições sociais em municípios do Paraná e Santa Catarina, Brasil, 2001-2010. Epidemiol Serv Saúde 2013; 22:203-14.^,5656. Macedo AC, Paim JS, Silva LM, Costa MCN. Violência e desigualdade social: mortalidade por homicídios e condições de vida em Salvador, Brasil. Rev Saúde Pública 2001; 35:515-22..

Our model showed that social inequality (Gini index) is associated with homicides, whereas income (a component of the HDI-M) has an inverse relation, meaning that less income increases risks of exposure to homicide. Both national and international studies reinforce these two SDH as risk factors for homicides ²²22. Bando DH, Lester D. An ecological study on suicide and homicide in Brazil. Ciênc Saúde Colet 2014; 19:1179-89.^,3030. Kim D. Social determinants of health in relation to firearm-related homicides in the United States: a nationwide multilevel cross-sectional study. PLoS Med 2019; 16:e1002978.^,5151. Cubbin C, Pickle LW, Fingerhut L. Social context and geographic patterns of homicide among US black and white males. Am J Public Health 2000; 90:579-87.^,5757. Elgar FJ, Aitken N. Income inequality, trust and homicide in 33 countries. Eur J Public Health 2011; 21:241-6.. Prominent Brazilian researchers argue that social inequalities and unequal opportunities contribute to explaining the epidemic of violence more than absolute poverty, combined with issues of urbanization and exaggerated population growth ⁴⁵45. Barata RB, Ribeiro MCSA. Relação entre homicídios e indicadores econômicos em São Paulo, Brasil, 1996. Rev Panam Salud Pública 2000; 7:118-24.^,5858. Souza ER, Minayo MCS. Mortalidade de jovens de 15 a 29 anos por violências e acidentes no Brasil: situação atual, tendências e perspectivas. In: Rede Interagencial de Informações para a Saúde, editors. Demografia e saúde: contribuição para análise de situação e tendências. Brasília: Organização Pan-Americana da Saúde; 2009. p. 113-43. (Série G. Estatística e Informação em Saúde) (Série Informe de Situação e Tendências).. A study ³⁹39. Andrade SM, Soares DA, Souza RKT, Matsuo T, Souza HD. Homicídios de homens de quinze a 29 anos e fatores relacionados no estado do Paraná, de 2002 a 2004. Ciênc Saúde Colet 2011; 16:1281-8. analyzing homicides in municipalities in Paraná found a statistically significant correlation between homicide mortality in men aged 15 to 29 years and the Gini index of municipalities, whereas another study suggests that income below the poverty line showed a significant association with homicide rates ³¹31. Medina Gómez OS, Villegas Lara B. Homicidios en jóvenes y desigualdades sociales en México, 2017. Rev Panam Salud Pública 2019; 43:e94.. Given the above, eradicating poverty and socioeconomic inequalities must be an integral part of any program to fight against violence ⁵³53. Jiménez De La Jara J, Torres Hidalgo M, Salcedo Hansen R. A cidade na perspectiva dos determinantes da saúde. In: Galvão LAC, Finkelman J, Henao S, editors. Determinantes ambientais e sociais da saúde. Rio de Janeiro: Organização Pan-Americana da Saúde/Editora Fiocruz; 2011. p. 197-214..

Socioeconomic inequalities are among the most common assumptions related to violent crimes ⁵⁷57. Elgar FJ, Aitken N. Income inequality, trust and homicide in 33 countries. Eur J Public Health 2011; 21:241-6.. Along with low income, the poorest suffer from multiple deprivations, which can also be risk factors for violence and homicide ¹⁶16. Wanzinack C, Signorelli MC, Reis C. Homicides and socio-environmental determinants of health in Brazil: a systematic literature review. Cad Saúde Pública 2018; 34:e00012818.^,5454. Sen A. Desenvolvimento como liberdade. São Paulo: Editora Companhia das Letras; 2018.. Under certain conditions, individuals or groups would be vulnerable to violence due to the few or non-existent resources available for their protection ¹⁵15. Tavares R, Catalan VDB, Romano PMM, Melo EM. Homicides and social vulnerability. Ciênc Saúde Colet 2016; 21:923-34.. Brazil still shows some aggravating factors which make it more susceptible to murderous violence, with emphasis on organized crime, recognized by criminal organizations as the First Command of the Capital (PCC) from São Paulo and the Red Command from Rio de Janeiro ⁴4. United Nations Office on Drugs and Crime. Global study on homicide. Understanding homicide: typologies, demographic factors, mechanisms, and contributors. Vienna: United Nations Office on Drugs and Crime; 2019.. Discrimination and the structural racism permeating the Brazilian society and exposing black youth to crime due to lack of opportunities and decent conditions is another factor which must be acknowledged ⁷7. Instituto de Pesquisa Econômica Aplicada; Fórum Brasileiro de Segurança Pública. Atlas da violência 2019. Brasília/Rio de Janeiro/São Paulo: Instituto de Pesquisa Econômica Aplicada; 2019.. The number of black Brazilian homicide victims is disproportionately higher than other groups ³3. Deplorable' killing of Afro-Brazilian man shows need to address racism, discrimination. United Nations News 2020; 24 nov. https://news.un.org/en/story/2020/11/1078432.
https://news.un.org/en/story/2020/11/107... .

Living in unstable and/or stigmatized communities with precarious or no access to public services and under the effect of social inequalities can influence such greater vulnerability to early and violent causes of death ⁴²42. Mansano NH, Gutierrez MMU, Ramalho W, Duarte EC. Homicídios em homens jovens de 10 a 24 anos e condições sociais em municípios do Paraná e Santa Catarina, Brasil, 2001-2010. Epidemiol Serv Saúde 2013; 22:203-14.. This problem is not limited to the outskirts of large cities. Our spatial analysis show that homicides are spreading into rural areas, including the Pantanal and Amazonia, two fragile ecosystems marked by substantial agricultural advances, land disputes, and dispossession of indigenous lands, and both are part of routes for international drug trafficking ⁵⁵55. Fórum Brasileiro de Segurança Pública. Anuário Brasileiro de Segurança Pública 2022. São Paulo: Fórum Brasileiro de Segurança Pública; 2022.^,5959. Wanzinack C, Signorelli MC, Shimakura S, Pereira PPG, Polidoro M, Oliveira LB, et al. Indigenous homicide in Brazil: geospatial mapping and secondary data analysis (2010 to 2014). Ciênc Saúde Colet 2019; 24:2637-48..

Research must reflect on homicide patterns to develop preventive and intervention measures, identify vulnerabilities, and promote strategic actions ⁶⁰60. Sousa GS, Magalhães FB, Gama IS, Lima MVN, Almeida RLF, Vieira LJES, et al. Social determinants and their interference in homicide rates in a city in northeastern Brazil. Rev Bras Epidemiol 2014; 17 Suppl 2:194-203.^,6161. Caiaffa WT, Almeida MCM, Oliveira CDL, Friche AAL, Matos SG, Dias MAS, et al. The urban environment from the health perspective: the case of Belo Horizonte, Minas Gerais, Brazil. Cad Saúde Pública 2005; 21:958-67.. Based on the analyzed indicators, investment in SDH related to education, health, and income (components of the HDI-M calculation), as well as measures to combat inequality (to improve the Gini index), can reduce homicides. Macrostructural measures, such as conditional cash transfer programs (Bolsa Família), have been shown as key strategies to prevent homicides and hospitalization from violence in Brazil by reducing poverty and/or socioeconomic inequalities ⁶²62. Machado DB, Rodrigues LC, Rasella D, Lima Barreto M, Araya R. Conditional cash transfer programme: impact on homicide rates and hospitalisations from violence in Brazil. PLoS One 2018; 13:e0208925.. Other strategies aimed at reducing rural exodus and guaranteeing decent conditions so the population remains in the countryside can prevent population growth in large cities and excessive urbanization, thus mitigating the two analyzed factors which most contribute to the risk of homicide.

This study has limitations, including research with secondary data; its failure to explore in-depth regional specificities; and its limited time-series cut. Also, our interpretation of the coefficients of fixed effect terms of the model, such as changes in the risk log for a unit of variation of the index, e.g., Gini, would mean moving from the extreme of equality to the extreme of inequality. However, we emphasize that this study and interpretation are the result of a model, and like any statistical model, it starts by simplifying a given phenomenon. We must be aware that, under real conditions, countless other aspects can influence a given phenomenon.

Another limitation is that we obtained most of our independent variables from the Census conducted in 2010 (the last census conducted in Brazil), whereas we considered homicides in later periods. It was a methodological option to use census data instead of estimates. However, these limitations fail to significantly affect the validity of our results as the studied independent variables show relative stability over time. Despite the limitations of this study, we should mention its potentialities. As a source of power, we emphasize that this study subsidizes criteria to guide public policies, including financial investments to regions with a higher risk of homicide, groups that are more vulnerable, or to improve the analyzed SDH (population, urbanization, human development, and socioeconomic inequality). Reducing violence is a complex task but it is essential for countries to achieve the Sustainable Development Goals.

Acknowledgments

The authors would like to thank Dr. Elias Teixeira Krainski and Dr. Ana Tereza Bittencourt Guimarães for their support with statistical analysis. They would also like to thank Bachelor of Arts Glória Letícia Wenceslau Barão Marques, and MComm. Vitor Adriano Liebel for their support in translating and reviewing the English translation. This study was partially financed by the Brazilian Graduate Studies Coordinating Board (CAPES, finance code 001), which granted the first author a scholarship for his Ph.D. The funding institution played no role in this study.

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