Understanding child disadvantage from a social determinants perspective

Goldfeld, Sharon; O’Connor, Meredith; Cloney, Dan; Gray, Sarah A. O.; Redmond, Gerry; Badland, Hannah; Williams, Katrina; Mensah, Fiona; Woolfenden, Susan; Kvalsvig, Amanda; Kochanoff, Anita

doi:10.1136/jech-2017-209036

Cited by 51 publications

(47 citation statements)

References 28 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Adjusted models provided statistical evidence of lower composite language, motor and cognitive scores in children whose families participated in the in the Bolsa Família social protection programme. Taken together, these findings reinforce the idea that early disadvantage can drive differential health and developmental outcomes [ 7 ].…”

Section: Discussionsupporting

confidence: 82%

“…In addition to congenital ZIKV infection, socioeconomic position (SEP) may also influence neurodevelopment. Children typically experience poorer health and developmental outcomes with higher levels of disadvantage [ 7 ]. Risk factors for cognitive and socioemotional developmental delays have been shown to include nutrient deficiencies and social and economic deprivation, whilst known protective factors comprise breastfeeding and maternal education [ 8 ].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure

Power

Francis

Clemente

et al. 2020

Viruses

View full text Add to dashboard Cite

Increased rates of Zika virus have been identified in economically deprived areas in Brazil at the population level; yet, the implications of the interaction between socioeconomic position and prenatal Zika virus exposure on adverse neurodevelopmental outcomes remains insufficiently evaluated at the individual level. Using data collected between September 2015 and September 2019 from 163 children with qRT-PCR and/or IgM-confirmed prenatal exposure to Zika virus participating in a prospective cohort study in Rio de Janeiro, Brazil (NCT03255369), this study evaluated the relationships of socioeconomic indicators with microcephaly at birth and Bayley-III neurodevelopmental scores during the early life course. Adjusted logistic regression models indicated increased odds of microcephaly in children born to families with lower household income (OR, 95% CI: 3.85, 1.43 to 10.37) and higher household crowding (OR, 95% CI: 1.83, 1.16 to 2.91), while maternal secondary and higher education appeared to have a protective effect for microcephaly compared to primary education (OR, 95% CI: 0.33, 0.11 to 0.98 and 0.10, 0.03 to 0.36, respectively). Consistent with these findings, adjusted linear regression models indicated lower composite language (−10.78, 95% CI: −19.87 to −1.69), motor (−10.45, 95% CI: −19.22 to −1.69), and cognitive (−17.20, 95% CI: −26.13 to −8.28) scores in children whose families participated in the Bolsa Família social protection programme. As such, the results from this investigation further emphasise the detrimental effects of childhood disadvantage on human health and development by providing novel evidence on the link between individual level socioeconomic indicators and microcephaly and delayed early life neurodevelopment following prenatal Zika virus exposure.

show abstract

Section: Discussionsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure

Power

Francis

Clemente

et al. 2020

Viruses

View full text Add to dashboard Cite

show abstract

“…Perinatal depression provides a lucid example; mothers experiencing perinatal depression can adversely impact on children's emotional and cognitive health because this type of depression “coincides with a period of substantial baby brain development during which infants are entirely dependent on their primary caregivers for physical care, security, and emotional regulation” (p608). Missed opportunities during the formative years of a child's life could contribute to a disadvantaged adulthood, something personally damaging and distressing as well as costly for government and society . This is a context that has given rise to a wide range of approaches including family support services, parenting programmes and one‐to‐one support for expectant and new parents during pregnancy and the first years of a child's life.…”

Section: Introductionmentioning

confidence: 99%

Assessing community readiness for early intervention programmes to promote social and emotional health in children

Islam

Small

Bryant

et al. 2019

Health Expectations

View full text Add to dashboard Cite

Objective Evidence for early intervention and prevention‐based approaches for improving social and emotional health in young children is robust. However, rates of participation in programmes are low. We explored the dynamics which affect levels of community readiness to address the issues of social and emotional health for pregnant women, young children (0‐4 years) and their mothers. Setting A deprived inner‐city housing estate in the north of England. The estate falls within the catchment area of a project that has been awarded long‐term funding to address social and emotional health during pregnancy and early childhood. Methods We interviewed key respondents using the Community Readiness Model. This approach applies a mixed methodology, incorporating readiness scores and qualitative data. A mean community readiness score was calculated enabling the placement of the community in one of nine possible stages of readiness. Interview transcripts were analysed using a qualitative framework approach to generate contextual information to augment the numerical scores. Results An overall score consistent with vague awareness was achieved, indicating a low level of community readiness for social and emotional health interventions. This score suggests that there will be a low likelihood of participation in programmes that address these issues. Conclusion Gauging community readiness offers a way of predicting how willing and prepared a community is to address an issue. Modifying implementation plans so that they first address community readiness may improve participation rates.

show abstract

“…The methods we used to evaluate the MPI-LA were not confined to psychometrics but were also developed by researchers in the fields of agriculture, biology, education, environmental science, medicine, sociology and applied statistics. They have been used extensively across the natural and social sciences, including by poverty researchers in many countries (for example, see Betti, Gagliardi, Lemmi, & Verma, 2015;Cappellari & Jenkins, 2007;Fusco & Dickes, 2008;Goldfeld et al, 2018;Martini & Vanin, 2013;Szeles & Fusco, 2013;Whelan, Layte, Maitre, & Nolan, 2001).…”

Section: The Importance Of the Normative Perspectivementioning

confidence: 99%

Reply to Santos and Colleagues ‘The Importance of Reliability in the Multidimensional Poverty Index for Latin America (MPI-LA)’

Gordon

Nájera

2019

The Journal of Development Studies

View full text Add to dashboard Cite

We thank Santos and her colleagues for their comments and welcome debate about the best ways to improve the measurement of multidimensional poverty in Latin America. While we agree with many of the points that have been raised, there remain some fundamental areas of disagreement. Four main issues have been raised regarding our work, so we will first summarise our position and then address each issue in turn. We fundamentally disagree with the argument that poverty can be measured directly, that latent variable modelling is inadequate, and our conclusions are incorrect. Poverty is a concept (i.e. an idea). The statistical term for a concept is a Latent Variable, i.e. a concept/construct which cannot be measured directly but can be measured/estimated indirectly using indicatorsdata we can collect/ observe on related variables. Thus, concepts like poverty, human rights or mathematical ability can only be measured indirectly by using suitable indicators and adopting a latent variable approach. The MPI-LA uses deprivation indicators which indirectly estimate multidimensional poverty as a latent variable (i.e. the MPI-LA aggregates across its dimensions to produce a single estimate of multidimensional povertyan adjusted headcount number). We are in agreement that the MPI-LA is a measurement instrument, however, all measurement instruments depend on an explicit or implicit measurement model, i.e. to measure length you need both a ruler (a measurement instrument) and a concept and definition about the size of a centimetre (a measurement model). There is, of course, no such thing as error free measurement and all poverty measures will be affected by some amount of random and systematic error (Loken & Gelman, 2017). Santos and Villatoro's (2016) methods were not devised to estimate error. However, over the past one hundred years, across both the natural and social sciences, standard methods have been developed to assess the degree of measurement error and identify acceptable and unacceptable levels of such error (Brennan, 2006). It is important that poverty measures are developed which conform to these fundamental scientific standards and methods. This is true irrespective of the other properties of

show abstract

Understanding child disadvantage from a social determinants perspective

Cited by 51 publications

References 28 publications

Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure

Examining the Association of Socioeconomic Position with Microcephaly and Delayed Childhood Neurodevelopment among Children with Prenatal Zika Virus Exposure

Assessing community readiness for early intervention programmes to promote social and emotional health in children

Reply to Santos and Colleagues ‘The Importance of Reliability in the Multidimensional Poverty Index for Latin America (MPI-LA)’

Contact Info

Product

Resources

About