Exploring biocultural models of chewing tobacco and paan among reproductive-aged women: Self-medication, protection, or gender inequality?

Am J Hum Biol. 2019 Sep;31(5):e23281. doi: 10.1002/ajhb.23281. Epub 2019 Jun 21.

Abstract

Objectives: Tobacco and areca nut are two of the most widely used psychoactive plant substances worldwide, yet the biocultural factors that account for variation in use patterns are not well understood. Here we attempt to understand the high prevalence of, and variation in, tobacco and areca nut use among reproductive-aged women.

Methods: Research was carried out in Mysore, Karnataka, India. First, we conducted a qualitative investigation where participants engaged in semistructured interviews and focus group discussions to uncover cultural norms of women's tobacco use. Findings informed the second stage of research which quantitatively tested three models of tobacco and areca nut use (N = 74).

Results: The qualitative study found that women were more likely to chew "natural" forms of tobacco and areca nut products (kaddipudi and paan). Quantitative tests of our hypotheses revealed that kaddipudi and combined tobacco use were best explained by the self-medication model, with somatic and environmental stress as strong indicators of use. The presence of cotinine, our biological indicator of tobacco use, was best modeled by gender inequality. We also found that men and women reported approximately equal tobacco use, even though their preferred types of tobacco and areca nut products differed.

Conclusions: Findings did not support the protection hypothesis as it relates to plant toxins. Instead, this study suggests that women might exploit neurotoxins such as nicotine and arecoline to offset the cognitive and energetic costs associated with iron deficiency in stressful environments.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Areca*
  • Female
  • Humans
  • India
  • Nuts*
  • Protective Agents / therapeutic use*
  • Self Medication / statistics & numerical data*
  • Socioeconomic Factors*
  • Tobacco Use / epidemiology*
  • Tobacco, Smokeless / statistics & numerical data*
  • Young Adult

Substances

  • Protective Agents