Gender differences and clustering pattern of behavioural risk factors for chronic non-communicable diseases: Community-based study from a developing country

Ali Khan Khuwaja, Muhammad Masood Kadir

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)

Abstract

Objectives: This study estimates the burden of behavioural risk factors for chronic non-communicable diseases (CNDs) to evaluate the degree of clustering and the differential of these factors by gender in adults. Methods: In a community-based survey, information was obtained about behavioural risk factors for CNDs among 534 adults in Karachi, Pakistan. Chi-square test and odds ratio (OR) with 95% confidence interval (CI) were calculated to evaluate the differences of these factors by gender. Results: Overall, 22.5% of adults had anxiety/depression, 47.8% did not have adequate intake of fruits and vegetables, 60.1% were physically inactive while 49.8% were overweight/obese. More women had anxiety/ depression (OR = 2.1; 95% CI = 1.4g-3.1), were physically inactive (OR=2.1; 95% CI = 1.5-3.1) and overweight/ obese (OR= 6.2; 95% CI = 4.3-9.1). On the contrary, greater number of men were found to have inadequate fruit and vegetable consumption (OR = 1.8; 95% CI = 1.3-2.5). Only 1.1% of study subjects had none of the studied risk factors, 16.9% had one while 82% had ≥2 factors. The clustering of these risk factors was significantly higher in women (p>0.001). Discussion: This study shows that almost all of the adults in the study had behavioural risk factors for CNDs and clustering of these factors is very common and significantly higher in women. The tendency of clustering risk factors in individuals provides opportunities to address factors with integrated approaches to prevent/delay the onset of CNDs.

Original languageEnglish
Pages (from-to)163-170
Number of pages8
JournalChronic Illness
Volume6
Issue number3
DOIs
Publication statusPublished - Sept 2010

Keywords

  • Behavioural risk factors
  • Chronic non-communicable diseases
  • Clustering pattern
  • Developing country
  • Gender difference

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