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September 27, 2010BMJOpen Access

Sociodemographic patterning of non-communicable disease risk factors in rural India: a cross sectional study

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Population

1983 people aged 20–69 years (31% women) from about 1600 villages across 18 states in rural India

Design

Cross-sectional

Authors

SKSanjay KinraLBLiza BowenTLTanica Lyngdoh

Discussion

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Overview

Distinct SEP patterning of NCD risks in rural India may inform surveillance; leaves open causal mechanisms and longitudinal outcomes.

Key Points

  • To evaluate the distribution and sociodemographic patterning of non-communicable disease risk factors among rural residents across India.
  • Conducted a cross-sectional survey of 1,983 participants aged 20–69 years (31% women; 49% response rate) using convenience sampling across approximately 1,600 villages in 18 Indian states.
  • Assessed behavioral and cardiometabolic risk factors, including tobacco and alcohol use, diet, physical activity, obesity, central adiposity, hypertension, dyslipidaemia, and diabetes.
  • Tobacco use, low fruit and vegetable intake, and underweight were concentrated in lower socioeconomic positions, with male smoking at 37% (95% CI 30% to 44%) in the lowest vs 15% (12% to 17%) in the highest socioeconomic group.
  • Obesity, dyslipidaemia, diabetes in men, and hypertension in women clustered in higher socioeconomic groups, with female obesity reaching 35% (95% CI 30% to 40%) in the highest vs 13% (7% to 19%) in the lowest group.
  • Regional variations showed higher risk factor burdens in south versus north India, including dyslipidaemia in men at 33% (95% CI 29% to 38%) vs 21% (17% to 33%) and female obesity at 24% (19% to 30%) vs 13% (9% to 17%).

Structured PICO

P
Population
1983 people aged 20–69 years (31% women) from about 1600 villages across 18 states in rural India
O
Outcome
Prevalence of tobacco use, alcohol use, low fruit and vegetable intake, low physical activity, obesity, central adiposity, hypertension, dyslipidaemia, diabetes, and underweight

Non-communicable disease risk factors are highly prevalent in rural India and exhibit distinct sociodemographic patterning, highlighting the need for targeted monitoring and control.

Limitations

  • convenience sampling design
  • low response rate

Cite This Study

Kinra et al. (2010) studied this question.

synapsesocial.com/papers/6a01fa68e8ec6bd19dcb136bhttps://doi.org/10.1136/bmj.c4974
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