Local environmental quality positively predicts breastfeeding in the UK's Millennium Cohort Study.

Local environmental quality positively predicts breastfeeding in the UK's Millennium Cohort Study.

Brown, Laura J;Sear, Rebecca;
evolution, medicine, and public health 2017 Vol. 2017 pp. 120-135
196
brown2017localevolution

Abstract

Breastfeeding is an important form of parental investment with clear health benefits. Despite this, rates remain low in the UK; understanding variation can therefore help improve interventions. Life history theory suggests that environmental quality may pattern maternal investment, including breastfeeding. We analyse a nationally representative dataset to test two predictions: (i) higher local environmental quality predicts higher likelihood of breastfeeding initiation and longer duration; (ii) higher socioeconomic status (SES) provides a buffer against the adverse influences of low local environmental quality. We ran factor analysis on a wide range of local-level environmental variables. Two summary measures of local environmental quality were generated by this analysis-one 'objective' (based on an independent assessor's neighbourhood scores) and one 'subjective' (based on respondent's scores). We used mixed-effects regression techniques to test our hypotheses. Higher objective, but not subjective, local environmental quality predicts higher likelihood of starting and maintaining breastfeeding over and above individual SES and area-level measures of environmental quality. Higher individual SES is protective, with women from high-income households having relatively high breastfeeding initiation rates and those with high status jobs being more likely to maintain breastfeeding, even in poor environmental conditions. Environmental quality is often vaguely measured; here we present a thorough investigation of environmental quality at the local level, controlling for individual- and area-level measures. Our findings support a shift in focus away from individual factors and towards altering the landscape of women's decision making contexts when considering behaviours relevant to public health.

Citation

ID: 50796
Ref Key: brown2017localevolution
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
50796
Unique Identifier:
10.1093/emph/eox011
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet