Population density, depressive symptoms, and suicidal thoughts

Considering the high prevalence of depression worldwide and the increasing burden of consequent disability,¹ identification of potential sociodemographic characteristics associated with this health concern on a nationwide level should be sought to support targeted public policies. In this sense, an interesting paper was published on April 15, 2019, in the Brazilian Journal of Psychiatry (then ahead of print; now in a regular, paginated issue). Carpena et al.² extended the knowledge about the association between major determinants and depressive symptoms and found no association of gross domestic product per capita, the Gini index, Psychosocial Care Centers per 20,000 population, and Family Health Strategy per 1,000 population with elevated depressive symptoms or suicidal thoughts. On the other hand, the authors found that men, living with a partner, having a higher assets index, higher educational status, living in a rural area, and a lower number of residents per household were associated with a lower likelihood of depressive symptoms and suicidal thoughts.

We consider the findings of Carpena et al.² of great interest for public health, and the aim of this letter is to include an important factor in this discussion: population density. This indicator, obtained by dividing the number of inhabitants by total geographic area, has been associated with mental disorders in developed countries.³,⁴ Thus, we replicated the procedures of Carpena et al.² with estimates of population density by state provided in the latest Brazilian demographic census (2010). Unlike Carpena et al.,² we considered population density as continuous in the models; we also divided population density into tertiles and analyzed the highest population density (tertile 3) vs. tertiles 1 and 2, as well as the lowest population density (tertile 1) vs. tertiles 2 and 3. We also present models by sex and include the following covariates in the analysis: sex (whole sample), race, chronological age, educational status, employment status, intake of sugary foods (7 days/week), habitual physical activity (≥ 150 min/week), TV-watching (≥ 4 h/day), and tobacco smoking. These variables were self-reported through specific questionnaires, which have been previously described.⁵

We observed that higher population density (highest tertile) was associated with a 21% higher likelihood of elevated depressive symptoms among women and a 21% higher likelihood of suicidal thoughts among men, regardless of sociodemographic and lifestyle covariates (Table 1). Corroborating these findings, women in the lowest tertile of population density were 17% and 20% less likely to present elevated depressive symptoms and suicidal thoughts, respectively (Table 1). When analyzed continuously in the models, population density was only associated with higher suicidal thoughts.

Table 1
Association between population density, elevated depressive symptoms, and suicidal thoughts (n=60,202)

	Elevated depressive symptoms	Suicidal thoughts
Continuous
Model 1
Whole sample	1.0006 (0.9999-1.0012)	1.0004 (0.9996-1.0012)
Men	1.0004 (0.9996-1.0012)	1.0010 (1.0003-1.0017)
Women	1.0005 (0.9998-1.0012)	1.0002 (0.9992-1.0011)
Model 2
Whole sample	1.0005 (0.9998-1.0012)	1.0005 (0.9997-1.0014)
Men	1.0004 (0.9996-1.0011)	1.0010 (1.0003-1.0017)
Women	1.0005 (0.9998-1.0012)	1.0003 (0.9994-1.0013)
Highest population density (Highest tertile)
Model 1
Whole sample	1.22 (1.06-1.40)	1.15 (0.96-1.38)
Men	1.16 (0.98-1.37)	1.23 (1.03-1.48)
Women	1.21 (1.04-1.39)	1.10 (0.90-1.35)
Model 2
Whole sample	1.20 (1.04-1.38)	1.15 (0.97-1.38)
Men	1.13 (0.96-1.33)	1.21 (1.02-1.44)
Women	1.21 (1.05-1.40)	1.12 (0.92-1.38)
Lowest population density (Lowest tertile)
Model 1
Whole sample	0.82 (0.72-0.95)	0.83 (0.70-0.98)
Men	0.86 (0.72-1.01)	0.84 (0.69-1.02)
Women	0.83 (0.72-0.95)	0.84 (0.69-1.01)
Model 2
Whole sample	0.84 (0.73-0.96)	0.81 (0.69-0.95)
Men	0.87 (0.74-1.03)	0.85 (0.70-1.02)
Women	0.83 (0.72-0.96)	0.80 (0.67-0.97)

• Data presented as odds ratio (95% confidence interval).
• Model 1: crude model; model 2: adjusted for sex (whole sample), race, chronological age, educational status, employment status, intake of sugary foods, physical activity, TV-watching, and tobacco smoking.

These results add information to the conclusions of Carpena et al.² and extend previous findings from developed countries about the association between population density and mental health³,⁴ to a middle-income context. Although obtained from cross-sectional data, this information supports the notion of a negative effect of urbanization on mental health of the population. An example can be found in previous research from the São Paulo megacity, where an elevated prevalence of mental disorders was observed in people living in this metropolitan area, which has the highest population density of any place in Brazil.⁶ Public health policies targeting depression should focus on regions with higher population densities.

Acknowledgements

This research received no specific funding. AOW is supported by Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP; process 2017/27234-2 and 2018/19183-1).

References

• ¹
  GBD 2017 DALYs and HALE Collaborators. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392:1859-922.
• ²
  Carpena MX, Martins-Silva T, Costa FS, Darley R, Loret de Mola C. Contextual risk factors of depression and suicidal thoughts in Brazilian adults: a multilevel analysis. Braz J Psychiatry. 2019;41:433-6.
• ³
  Sundquist K, Frank G, Sundquist J. Urbanisation and incidence of psychosis and depression. Br J Psychiatry. 2004;184:293-8.
• ⁴
  Sariaslan A, Larsson H, D’Onofrio B, Långström N, Fazel S, Lichtenstein P. Does population density and neighborhood deprivation predict schizophrenia? A nationwide Swedish family-based study of 2.4 million individuals. Schizophr Bull. 2015;41:494-502.
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  Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa Nacional de Saúde 2013 [Internet]. 2014 [cited 2019 Nov 30]. http://biblioteca.ibge.gov.br/visualizacao/livros/liv94074.pdf
  » http://biblioteca.ibge.gov.br/visualizacao/livros/liv94074.pdf
• ⁶
  Andrade LH, Wang YP, Andreoni S, Silveira CM, Alexandrino-Silva C, Siu ER, et al. Mental disorders in megacities: findings from the São Paulo megacity mental health survey, Brazil. PLoS One. 2012;7:e31879.

Publication Dates

• Publication in this collection
  03 Feb 2020
• Date of issue
  Jan-Feb 2020

History

• Received
  7 May 2019
• Accepted
  10 Sept 2019