DESK REVIEWS | 01.02.03. Prevalence or burden of injury and violence

DESK REVIEW | 01.02.03. Prevalence or burden of injury and violence

According to a map of violence produced by the Institute for Applied Economic Research (IPEA) and the Brazilian Forum of Public Security (FBSP), the homicide rate in Brazil was 30 times higher than that in Europe in 2016 (62,517 murders). Considering only the last decade, 553,000 Brazilians lost their lives through violent death (153 deaths per day). Such deaths represent almost 10% of all deaths in the country and affect mainly young men: 56.5% of the deaths of Brazilians aged between 15 and 19 are from violent deaths. Young victims represent 53.7% of the total number of deaths in the country (that is, 33,590 deaths), 94.6% of whom are males. The number of violent deaths also reflects great racial inequality: 71.5% of the people murdered are black or mixed race (Institute for Applied Economic Research, 2018).

Despite the alarming numbers at the national level, the disparity between the Federation Units draws attention. There was a reduction of homicide rates in the last decade in states such as São Paulo (-46.7%), Espírito Santo (-37.2%) and Rio de Janeiro (-23.4%), and a growth in others, such as Rio Grande do Norte (256.9%), Acre (93.2%), Rio Grande do Sul (58.8%) and Maranhão (121.0%). By 2016, the homicide rate per 100,000 inhabitants had reached almost 45 in the states of the Northeast and the North. In the Southeast, on the other hand, the value was in the 20’s, slightly below the 25 reached by the Southern states (Institute for Applied Economic Research, 2018).

Most homicides in Brazil are caused by fire guns: from 1980 to 2016, almost one million Brazilians lost their lives because of fire guns. A total of 71.1% of homicides was committed with the use of fire guns (a rate that grew for decades until 2003, the year of the creation of the disarmament statute) (Institute for Applied Economic Research, 2018). Currently the Brazilian new government is starting to allow more sectors of the population to have a fire gun.


Institute for Applied Economic Research. (2018). Atlas da violência.


As per the National Crime Records Bureau’s Accidental Deaths and Suicides report (National Crime Records Bureau [NCRB], 2020a) there were 3,74,397 accidental deaths and 1,53,052 deaths from suicide reported in 2020. The Crime in India report (NCRB, 2020b) states that there were 29,193 cases of violence related deaths (homicide) in 2020.

State wise variations in injuries:

As per GBD 2019 data, the prevalence of injuries of various types varies across the states. In 2019, the lowest prevalence rate was in Meghalaya, which had a prevalence rate of 16,545.72 cases per 100,000 people (15,672.39 – 17,471.5) and the highest was in Tamil Nadu with 29,116.16 prevalent cases per 100,000 people (27,570.69 – 30,738.74) (ICMR, PHFI and IHME, 2019). In terms of burden, the number of deaths and DALYs are described. The least number of deaths was in Meghalaya with 30.62 deaths per 100,000 people (22.93 – 43.12) and the highest number of deaths was in Tamil Nadu with 99.41 deaths per 100,000 people (70.01-121.01) (ICMR, PHFI and IHME, 2019). With respect to DALYs, Meghalaya had the lowest number of DALYs with 2,057.27 per 100,000 people (1664.38 – 2618.95) and Tamil Nadu had the highest number of DALYs with 5,055.08 per 100,000 people (4,054.81 – 5,944.4) (ICMR, PHFI and IHME, 2019).


Indian Council of Medical Research, Public Health Foundation of India, and Institute for Health Metrics and Evaluation (ICMR, PHFI and IHME). (2019). GBD India Compare Data Visualization. Available from:

National Crime Records Bureau. (2020a). Accidental Deaths and Suicides in India.

Due to Indonesia’s location on the Pacific Ring of Fire, the country experiences natural disasters in relatively high frequency. These include tsunamis, earthquakes, and volcanic eruptions (Agustina et al., 2019, p.77; International Organization for Migration, 2018). In 2004, natural disasters including ‘294 floods, 54 landslides, 11 earthquakes, two tsunamis, and five volcanic eruptions’ were accountable of 10.2 per cent of total mortality and the leading cause of injury and disability. In 2018, two earthquakes led to more than 2,000 deaths over 1,000 missing people, more than 4,000 injured people, over 223,000 displaced people as well as the destruction or damage of approximately 50 health centres. The implications of natural disasters on health infrastructure is substantial. More than 4,500 health facilities were damaged between 1990 and 2015 (Agustina et al., 2019, p.80). In addition, Indonesia has experienced several acts of terrorism over the last two decades (Agustina et al., 2019, p.78). Finally, road injuries accounted as the main cause of death among the populated aged 10 to 25 years (Agustina et al., 2019, p.80).


Agustina, R., Dartanto, T., Sitompul, R., Susiloretni, K. A., Suparmi, Achadi, E. L., Taher, A., Wirawan, F., Sungkar, S., Sudarmono, P., Shankar, A. H., Thabrany, H., Susiloretni, K. A., Soewondo, P., Ahmad, S. A., Kurniawan, M., Hidayat, B., Pardede, D., Mundiharno, … Khusun, H. (2019). Universal health coverage in Indonesia: concept, progress, and challenges. The Lancet, 393(10166), 75–102.

International Organization for Migration. (2018). Indonesia 2018. Humanitarian Compendium.

In Kenya, the leading causes of injury include assault (42%), road traffic accidents (28%), unspecified soft tissue injury (11%), and less than 10% for cut-wounds and dog-bites, falls and burn and poisoning each (MoH-Kenya et al., 2015). According to the Kenya Health and Demographic survey 2008/9, 39% and 20.6% of women have experienced physical and sexual violence, respectively (Kenya National Bureau of Statistics (KNBS); ORC Macro, 2010). There has been an increase in transport injuries with pedestrians comprising 43% of fatalities (Kenya National Bureau of Statistics (KNBS); ORC Macro, 2010). Other vulnerable road users include motorcyclists and cyclists. More than 75% of deaths on the roads are males and about 50% of the total deaths are children or young adults. The major killer has been consistently identified as speed and lack of use of safety equipment such as helmets, seat-belts and child-restraints (World Health Organization (WHO), 2010).


Kenya National Bureau of Statistics (KNBS); ORC Macro. (2010). Kenya Demographic and Health Survey 2008-09. Health (San Francisco), 1–314.

MoH-Kenya, KNBS, & WHO. (2015). Kenya STEPwise Survey for Non Communicable Diseases Risk Factors 2015 Report. MoH-Kenya.

World Health Organization (WHO). (2010). Road Safety in Ten Countries: Kenya. Nairobi, Kenya.

Accidents and violence

In 2013, there was a reported rate of 13 deaths due to traffic accidents and 18.3 homicide deaths, both per 100 inhabitants. Types of vehicles studied in traffic accidents are bicycles, motorcycles, and motor vehicles. Also included are hit-and-run vehicles, which account for 41% of the load associated with all traffic accidents.

The risk of premature loss of life from intentional and accidental injury is 92% (almost double) higher for people living in the north than those living in the south (Soto-Estrada et al., 2016).

According to data reported by ENSANUT 2012, from a survey among adolescents (10-19 years) and young adults (20-29 years), 4% reported health damages or health issues due to interpersonal violence. This would represent approximately 1,712,485 cases at national level. The prevalence of interpersonal violence is higher among men (5.0%) than women (3.3%) and the most vulnerable age group is that of men aged 20 to 29 years. For women, the household is still the space where one of the highest proportions of violence is suffered, with one in four women (24.5%) reporting violent incidents in their own home (Valdez-Santiago et al., 2013).

Table 8. Prevalence of young people who suffered damage to their health due to interpersonal violence

Age group Men %

(95% CI)

Woman %

(95% CI)

Total %

(95% CI)


(10-19 years)

4.4 (3.8-5.1) 3.4 (2.8-4.0) 3.9 (3.5-4.3)
Young adults (20-29 years) 5.7 (4.4-7.2) 3.1 (2.4-4.2) 4.4 (3.6-5.3)

Source: Own estimates from ENSANUT 2012 data

Disability and Disability-free life expectancy

Indicators of healthy life expectancy are useful to monitor effectively whether the years of life gained with the increase in life expectancy are spent in a good state of health or not. In Mexico there are a few sources of data in older adults: the 10/66 study, the Mexican Health, the Aging Survey (MHAS), and SAGE.

The healthy life expectancy is the estimate expected years of life in good health for persons at a given age. In 2010-2015 life expectancy was 74 years for men, but healthy life expectancy was 65 years, while for women was 78.9 and 69 respectively, which means that there are almost 10 years with disease. This may be related to two factors: the decrease in premature mortality, which has an important effect on improving life expectancy at birth, and the increase in people with disabling sequelae. In other words, there are fewer premature deaths but more disability.

The 10/66 study is a large cohort study, examining health, social, and biological characteristics of older adults living in eight countries (China, Cuba, Dominical Republic, India, Mexico, Peru, Puerto Rico, and Venezuela). In this study, disability was assessed using the more than 15 disability days in the past (assessed through WHODAS 2.0 (WHO, 2010)) month criteria, and dependence was assessed by needing some or much care (Prina et al., 2019). Table 9 reports the prevalence of disability and dependence in the total sample (n=2002), both increased with older age, and women had higher prevalence in the oldest age group.

 Table 9. Prevalence of disability and dependence, stratified by age group and sex.

  Disability Dependence
Age group Male Female Male Female
65-69 8.1 7.1 3.7 5.0
70-74 5.9 5.9 7.7 6.9
75-79 9.8 15.2 8.4 11.2
80-84 14.9 15.9 11.6 14.9
85+ 17.2 20.4 20.0 31.5

Source: (Prina et al., 2019)

Table 10 reports estimated disability-free life expectancy, which gradually declines with increasing age. Women tend to spend a longer period of time with disability and the proportion of remaining life spent disability-free is lower than among men. In the same way, dependence-free life expectancy, which is fundamental to achieve active life expectancy, also declined with increasing age, women had longer periods of dependence.

Table 10. Disability free life expectancy and proportion of remaining life spent in disability and dependence free, by age group and sex

  Disability free life expectancy Dependence-free life expectancy
Age Male % Female % Male % Female %
65 15.4 89.9 16.5 88.1 15.6 91.0 16.4 87.5
70 12.3 89.1 13.1 86.4 12.3 89.0 12.8 84.9
75 9.3 86.6 9.8 83.0 9.4 87.3 9.6 81.2
80 6.8 84.0 7.3 81.8 6.8 84.3 6.8 76.4
85 5.0 83.1 5.4 79.8 4.9 80.3 4.6 68.6

Source: (Prina et al., 2019)

While in the 10/66 study, Mexico reports the highest disability free life expectancy at age 65 (compared with China, Cuba, the Dominican Republic, India, Peru, Puerto Rico, and Venezuela).

In 2018, Payne reported estimations of the rates of transitions between life without disability, life with disability, and death with data from longitudinal surveys of older adult populations in Costa Rica, Mexico, Puerto Rico, and the United States populations, and he reported that the growing older adult populations in Costa Rica, Puerto Rico, and Mexico are not experiencing a substantially higher burden of disability than the disability experienced by people of the same age in the United States (Payne, 2018).

For all these reasons, Mexico must direct its efforts to address the problems associated with the gap that still exists in relation to infectious diseases, the increase in chronic degenerative diseases and those related to injuries and violence, as well as disability and dependence that arise from all of them.


Payne, C. F. (2018). Aging in the Americas: Disability-free Life Expectancy among Adults Aged 65 and Older in the United States, Costa Rica, Mexico, and Puerto Rico. Journals of Gerontology – Series B Psychological Sciences and Social Sciences, 73(2), 337–348.

Prina, A., Wu, Y., Kralj, C., Acosta, D., Acosta, I., Guerra, M., Huang, Y., Amuthavalli, T., Jimenez-Velazquez, I., Liu, Z., Llibre Rodriguez, J., Salas, A., Sosa, A., & Prince, M. (2019). Dependence- and Disability-Free Life Expectancy Across Eight Low- and Middle-Income Countries: A 10/66 Study. Journal of Aging and Health.

Soto-Estrada, G., Moreno-Altamirano, L., Pahua Díaz, D., Soto-Estrada, G., Moreno-Altamirano, L., & Pahua Díaz, D. (2016). Panorama epidemiológico de México, principales causas de morbilidad y mortalidad. Revista de La Facultad de Medicina (México), 59(6), 8–22.

Valdez-Santiago, R., Hidalgo-Solórzano, E., Mojarro-íñiguez, M., Rivera-Rivera, L., & Ramos-Lira, L. (2013). Violencia interpersonal en jóvenes mexicanos y oportunidades de prevención. Salud Publica de Mexico, 55(SUPPL.2), 259–266.

WHO. (2010). WHODAS 2.0 12-item version, interviewer-administered.