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Background <p>There is scant research examining income-based inequalities in risk factors of non-communicable diseases (NCDs) and inequities of preventive care services across the South Asian population.</p> Methods <p>We conducted a cross-sectional study of 202,682 adults aged 18 or above in four South Asian countries: Bangladesh, India, Pakistan, and Sri Lanka. We combined South Asia Biobank (SAB) surveillance data with environmental mapping exposure and 24-h dietary recall to estimate income-based inequalities using concentration curves and concentration indices (CI) that measure the magnitude and directional inequality effects. We also computed the horizontal inequity index (HII) for need-standardised healthcare utilisation and advice by measuring the extent to which the distribution of health promotion advice matches the distribution of diet-related risk factor variables across the income distribution. We reported concentration index coefficients and standard errors.</p> Results <p>Inequalities in exposure and diet-related risk factors of NCDs were observed. Underweight was concentrated amongst the poor (CI = − 0.16, SE = 0.005, <i>p</i> &lt; 0.001), while overweight and obesity were concentrated amongst the rich (CI = 0.11, SE = 0.003, <i>p</i> &lt; 0.001). Non-recommended intake of fats (CI = 0.04, SE = 0.003, <i>p</i> &lt; 0.001) and carbohydrates were concentrated amongst the rich (CI = 0.05, SE = 0.003, <i>p</i> &lt; 0.001), while non-recommended intake of free sugars (CI = − 0.05, SE = 0.004, <i>p</i> &lt; 0.001) and fruits and vegetables amongst the poor (CI = − 0.07, SE = 0.005, <i>p</i> &lt; 0.001). Exposure to unhealthy outlets was concentrated amongst the rich (CI = 0.02, SE = 0.002, <i>p</i> &lt; 0.001). There were persistent and pro-rich inequities in healthcare utilisation (HII = 0.02, SE = 0.002, <i>p</i> &lt; 0.001) and advice for salt reduction (HII = 0.02, SE = 0.004, <i>p</i> &lt; 0.001), fat reduction (HII = 0.02, SE = 0.004, <i>p</i> &lt; 0.001), healthy weight (HII = 0.03, SE = 0.006, <i>p</i> &lt; 0.001), and fruits and vegetables consumption (HII = 0.04, SE = 0.004, <i>p</i> &lt; 0.001).</p> Conclusions <p>These findings indicate the need to address and mitigate income-based inequalities in diet-related risk factors of NCDs and underscore the need of policies directed at mitigating NCDs risk exposure and achieving improved and equitable access to healthcare.</p>

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Income-based inequalities in risk factors of NCDs and inequities of preventive care services amongst 202,682 adults: a cross-sectional study of South Asia Biobank

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  • 发表日期：

    2025年8月29日

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  • Bernardo Andretti,
  • Petya Atanasova,
  • Zoey Verdun,
  • Nalinda Tharanga Wellappuli,
  • Rajendra Pradeepa,
  • Sudha Vasudevan,
  • Akansha Tyagi,
  • Ali Ahsan,
  • Md. Mokbul Hossain,
  • Abu Ahmed Shamim,
  • Fahmida Akter,
  • Sara Mahmood,
  • Lathika Athauda,
  • Manoja Gamage,
  • Manuja Kaluarachchi,
  • Thomas Burgoine,
  • Soren Brage,
  • Nita G. Forouhi,
  • Ian Goon,
  • Marie Loh,
  • Prasad Katulanda,
  • Anuradhani Kasturiratne,
  • Khadija Irfan Khawaja,
  • Sajjad Ahmad,
  • Malay K. Mridha,
  • Vinitaa Jha,
  • Ranjit Mohan Anjana,
  • John C. Chambers,
  • Gary Frost,
  • Franco Sassi,
  • Marisa Miraldo

摘要

Background

There is scant research examining income-based inequalities in risk factors of non-communicable diseases (NCDs) and inequities of preventive care services across the South Asian population.

Methods

We conducted a cross-sectional study of 202,682 adults aged 18 or above in four South Asian countries: Bangladesh, India, Pakistan, and Sri Lanka. We combined South Asia Biobank (SAB) surveillance data with environmental mapping exposure and 24-h dietary recall to estimate income-based inequalities using concentration curves and concentration indices (CI) that measure the magnitude and directional inequality effects. We also computed the horizontal inequity index (HII) for need-standardised healthcare utilisation and advice by measuring the extent to which the distribution of health promotion advice matches the distribution of diet-related risk factor variables across the income distribution. We reported concentration index coefficients and standard errors.

Results

Inequalities in exposure and diet-related risk factors of NCDs were observed. Underweight was concentrated amongst the poor (CI = − 0.16, SE = 0.005, p < 0.001), while overweight and obesity were concentrated amongst the rich (CI = 0.11, SE = 0.003, p < 0.001). Non-recommended intake of fats (CI = 0.04, SE = 0.003, p < 0.001) and carbohydrates were concentrated amongst the rich (CI = 0.05, SE = 0.003, p < 0.001), while non-recommended intake of free sugars (CI = − 0.05, SE = 0.004, p < 0.001) and fruits and vegetables amongst the poor (CI = − 0.07, SE = 0.005, p < 0.001). Exposure to unhealthy outlets was concentrated amongst the rich (CI = 0.02, SE = 0.002, p < 0.001). There were persistent and pro-rich inequities in healthcare utilisation (HII = 0.02, SE = 0.002, p < 0.001) and advice for salt reduction (HII = 0.02, SE = 0.004, p < 0.001), fat reduction (HII = 0.02, SE = 0.004, p < 0.001), healthy weight (HII = 0.03, SE = 0.006, p < 0.001), and fruits and vegetables consumption (HII = 0.04, SE = 0.004, p < 0.001).

Conclusions

These findings indicate the need to address and mitigate income-based inequalities in diet-related risk factors of NCDs and underscore the need of policies directed at mitigating NCDs risk exposure and achieving improved and equitable access to healthcare.