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Cadernos de Saúde Pública

ISSN 1678-4464

36 nº.2

Rio de Janeiro, Fevereiro 2020


CARTA

Carta às Editoras sobre o artigo de Ferdos & Rahman

Lina Marcela Sandoval-Moreno, Andrés Fandiño-Losada, Sara Gabriela Pacichana-Quinayaz, María Isabel Gutiérrez-Martínez

http://dx.doi.org/10.1590/0102-311X00189719


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Dear Editors,

Ferdos & Rahman published an article on women who are victims of intimate partner violence, based on the 2007 Bangladesh Demographic Health Survey (DHS) 1. Nevertheless, some results are not consistent with the current literature, such as malnutrition as a risk factor for all forms of violence. Interestingly, the authors themselves, acknowledged alternative explanations in their Discussion section: Ferdos & Rahman appropriately stated that the food restriction faced by Bangladeshi women was generated by economic, emotional, and psychological abuse, which may result in insufficient or inappropriate food intake among women and leading to malnutrition (measured as high or low body mass index - BMI). In that context, women deal with the incapacity to make decisions by themselves, such as choosing adequate food amount and types. However, the statistical analyses performed by the authors report findings on an opposite causal pathway: altered BMI is the risk factor for physical and/or sexual violence (see Table 3 in the article 1.

Nevertheless, these results may be biased due to lack of adjustments for unobserved confounders, i.e. other forms of violence. Violence is a latent variable, expressed by different observed behavior types, such as economic, physical, sexual, or psychological violence 2,3,4. Economic violence against women occurs when a male partner controls the family finances, deciding how money is spent or saved, forcing the woman into economic dependence 4,5. Thus, there is a link between economic violence and the availability of resources that women have access to, including food 4,5.

Economic concerns could lead to family conflicts, which may end in physical/sexual violence against women 4,6. This type of relationship was shown by an experiment in Ecuador that assessed three interventions for poor households: cash transfers, transfers of food and food coupons. The results showed that, in addition to reducing the household food insecurity and poverty, the interventions reduced the violent behaviors of male partners 7. Apparently, rising economic incomes in a household reduces violence, by reduction of stress and domestic conflicts regarding poverty difficulties. It is unlikely that the women's BMI have changed in the context of the Ecuadorian study, since no intervention was oriented towards that outcome 7. Other studies have shown that increases in household income lead to decreasing couples' conflicts 8.

Furthermore, other studies (including the Ecuadorian one) have shown that economic interventions for reducing household poverty also significantly increased the quantity and quality of food consumed by the families, improving their nutritional status 7,9,10. Thus, a woman's food availability is determined by her socioeconomic status and her economic independence, which also determine her nutritional status and anthropometrics 7,11,12,13.

The causal relationships explained above are summarized in the directed acyclic graph 14,15, shown in Figure 1. In their analysis, Ferdos & Rahman adjusted for different socioeconomic variables (e.g. educational level and wealth quintile) blocking a backdoor pathway between BMI and physical/sexual violence; i.e. controlling a spurious statistical association due to those confounders 14,15. Nevertheless, the authors did not adjust for other confounders, as shown in Figure 1, leaving another backdoor pathway still open: a causal pathway passing through latent violence, economic violence, and food availability. The last causal pathway may be the real explanation of the statistical association reported by Ferdos & Rahman (see Table 3 in their article 1.

 

Figure 1 Directed acyclic graph (DAG) on the causal relationships between body mass index (BMI) and physical/sexual domestic violence against women.

 

Finally, it is noteworthy that the 2007 Bangladesh DHS 16 did not include specific questions for measuring economic violence against women, which could have been used in analyses adjusted for the whole set of confounders showed in Figure 1. In contrast, the Peruvian and Colombian DHS questionnaires included specific questions on domestic economic violence, such as: Has your money been monitored? Have you been threatened denying the economic support you receive? Have you been banned from working or studying? 17,18. The only way to assess the economic violence against women is to measure it directly with objective questions in order to implement appropriate interventions for supporting the victimized women. Thus, questions on economic violence must be included in the DHS questionnaires of Asian countries.

Acknowledgments

This study was performed as part of the research project Evaluación de una Intervención Cognitivo Conductual para Víctimas de la Violencia Intrafamiliar en Cali y Tuluá, Valle del Cauca, Colombia, funded by the Colombian National Department of Science, Innovation and Technology (COLCIENCIAS; grant n. 756-2016).

References

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4.   Fawole OI. Economic violence to women and girls: is it receiving the necessary attention? Trauma Violence Abuse 2008; 9:167-77.
5.   Messersmith LJ, Halim N, Steven Mzilangwe E, Reich N, Badi L, Holmes NB, et al. Childhood trauma, gender inequitable attitudes, alcohol use and multiple sexual partners: correlates of intimate partner violence in northern Tanzania. J Interpers Violence 2017; [Epub ahead of print].
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9.   Hatløy A, Hallund J, Diarra MM, Oshaug A. Food variety, socioeconomic status and nutritional status in urban and rural areas in Koutiala (Mali). Public Health Nutr 2000; 3:57-65.
10.   Darmon N, Lacroix A, Muller L, Ruffieux B. Food price policies improve diet quality while increasing socioeconomic inequalities in nutrition. Int J Behav Nutr Phys Act 2014; 11:66.
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12.   Alvarez LS, Estrada A, Goez JD, Carreno C, Mancilla LP. Los efectos del estatus socioeconómico y la talla baja sobre el sobrepeso, la obesidad y el riesgo de complicaciones metabólicas en adultos. Colomb Med 2013; 44:146-55.
13.   de Morais Sato P, Dimitrov Ulian M, Fernandez Unsain R, Baeza Scagliusi F. Eating practices among low-income overweight/obese Brazilian mothers: a Bourdieusian approach. Sociol Health Illn 2018; 40:1172-85.
14.   Hernán MA, Hernández-Díaz S, Werler MM, Mitchell AA. Causal knowledge as a prerequisite for confounding evaluation: an application to birth defects epidemiology. Am J Epidemiol 2002; 155:176-84.
15.   Oakes JM, Kaufman JS, editors. Methods in social epidemiology. San Francisco: John Wiley & Sons; 2006.
16.   National Institute of Population Research and Training; Mitra and Associates; Macro International. Bangladesh Demographic and Health Survey 2007. Dhaka: National Institute of Population Research and Training; Mitra and Associates/Calverton: Macro International; 2009.
17.   Ministerio de Salud y Protección Social; Profamilia. Colombia Encuesta Nacional de Demográfia y Salud 2015. Bogotá: Profamilia; 2017.
18.   Instituto Nacional de Estadística e Informática. Encuesta Demográfica y de Salud Familiar - ENDES 2014. Lima: Instituto Nacional de Estadística e Informática; 2015.

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