Scholarlink

Introduction <p>Cervical cancer (CC) screening promotes early identification and treatment. Increasing participation in screening is difficult because of socioeconomic and cultural impacts. The objective was to estimate distribution and factors contributing to socioeconomic inequalities in CC screening across wealth index among women aged <i>≥</i> 30 at the national and subnational levels.</p> Methods <p>STATA-v17 was used to analyse the data from the National Family Health Survey-5 in India to estimate the coverage of CC screening among Indian women aged <i>≥</i> 30. Concentration index highlighted socio-economic disparities across states and union territories (UTs) based on wealth. Screening inequalities were recorded, stratified by residence, area, states, and UTs. Spatial map was used to depict the difference (richest-poorest) in coverage of CC screening (%) for states/UTs. Erreygers method was performed for further decomposition.</p> Results <p>The overall coverage (1.96%) of CC screening raised as the wealth quintile increased (0.99 to 2.45%). Both high overall coverage and disparity (richest-poorest) was reported in Chandigarh, Punjab, Manipur, Mizoram, Maharashtra, and Kerala. The Inequalities of CC screening was concentrated among the wealthy: overall concentration index- 0.011 (0.010 to 0.013)). The north (0.009 (0.007 to 0.010)) and north-east (0.009 (0.007 to 0.010)) have the highest inequality. BMI (6.15%), number of living children (7.15%), education (9.17%), residential variance (14.17%), regional (21.37%), and non-exposure to media (49.21%) positively contributing to disparities, whereas regular fruit consumption (-7.25%) and caste variation (-10.99%) were negatively influencing factors.</p> Conclusion <p>India has a low overall screening adoption percentage. The socioeconomic disparities at different levels can be effectively addressed by early and regular screening, especially for the poor.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Decomposition analysis of coverage of cervical cancer screening among Indian women within reproductive age-group: distribution and determinants of socioeconomic inequalities using a nationally representative survey

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年10月7日

查看全文
  • Pritam Halder,
  • Divya Sharma,
  • Ashish Behera,
  • Arun Kumar Aggarwal,
  • Anshul Mamgai,
  • Pulak Syal,
  • Seema Chopra,
  • Tanvi Kiran

摘要

Introduction

Cervical cancer (CC) screening promotes early identification and treatment. Increasing participation in screening is difficult because of socioeconomic and cultural impacts. The objective was to estimate distribution and factors contributing to socioeconomic inequalities in CC screening across wealth index among women aged ≥ 30 at the national and subnational levels.

Methods

STATA-v17 was used to analyse the data from the National Family Health Survey-5 in India to estimate the coverage of CC screening among Indian women aged ≥ 30. Concentration index highlighted socio-economic disparities across states and union territories (UTs) based on wealth. Screening inequalities were recorded, stratified by residence, area, states, and UTs. Spatial map was used to depict the difference (richest-poorest) in coverage of CC screening (%) for states/UTs. Erreygers method was performed for further decomposition.

Results

The overall coverage (1.96%) of CC screening raised as the wealth quintile increased (0.99 to 2.45%). Both high overall coverage and disparity (richest-poorest) was reported in Chandigarh, Punjab, Manipur, Mizoram, Maharashtra, and Kerala. The Inequalities of CC screening was concentrated among the wealthy: overall concentration index- 0.011 (0.010 to 0.013)). The north (0.009 (0.007 to 0.010)) and north-east (0.009 (0.007 to 0.010)) have the highest inequality. BMI (6.15%), number of living children (7.15%), education (9.17%), residential variance (14.17%), regional (21.37%), and non-exposure to media (49.21%) positively contributing to disparities, whereas regular fruit consumption (-7.25%) and caste variation (-10.99%) were negatively influencing factors.

Conclusion

India has a low overall screening adoption percentage. The socioeconomic disparities at different levels can be effectively addressed by early and regular screening, especially for the poor.