Public policy and the socioeconomic mortality differential in infancy

Abstract

Abstract. This paper discusses some of the findings and policy implications of a recently completed study of socioeconomic differences in infant mortality in eight metropolitan areas of Ohio at three points in time. The study revealed that, in spite of a considerable decline in the overall rate of infant mortality since 1960, the inverse socioeconomic differential remains as wide as ever. This clearly suggests that, although maternal and child health has improved overall, the lower economic groups in our society still do not have equal access either to health care or to other amenities essential to the maintenance of good health. Moreover, consideration of recent and current policy proposals with respect to welfare programs in general, and maternal and child health care programs in particular, leads to the conclusion that this situation is not likely to change in the near future. Finally, some policy recommendations for enhancing the health status of low-income families are offered.

Racial Differences in the Relationship Between Infant Mortality and Socioeconomic Status

“…The substantial declines in infant mortality across all class and race categories since the 1960s attest to the positive effect of both the general rise in the overall standard of living of the population and the sometimes dramatic advances made in infant care technology (e.g. progress in neonatology and the establishment of neonatal intensive care units in all major metropolitan hospitals); they also reflect the efforts of the Federal Government to extend maternal and child health education and service programmes to the more socially vulnerable groups in the population (Stockwell et al, 1987;Moss & Carver, 1998). At the same time, the persistence of long established economic and racial differentials attests to the failure of health facilities and services to penetrate equally throughout all segments of society (Yankauer, 1990).…”

“…There has also been a growing awareness among health practitioners of the need to develop policies and programmes that would reduce the effects of poverty, and improve the quality of life experienced by low-income groups (Stockwell et al, 1987;Gortmaker & Wise, 1997;Hummer et al, 1999). Good prenatal care and better health education are of limited value where there is insufficient money to purchase recommended foods, or where housing conditions are such that infants experience an abnormally high risk of infection.…”

Estimating the Underlying Infant Mortality Rates for Small Populations, Even Those Reporting Zero Infant Deaths: a Case Study of 66 Local Health Areas in British Columbia

“…It is a measure not only used as a direct indicator of the risk of infant death, but also indirectly as an indicator of overall population health, the availability and quality of health care services, and socioeconomic status differentials (Hummer 2005;Kinge and Kornstad 2014;Kitagawa and Hauser 1973;Link and Phelan 1995;Ram et al 2016;Stockwell et al 2005;Stockwell et al 1987). 1 Because statistical data are often used to guide health policy decisions, it is not surprising that the IMR is used in this regard (Chen et al 2016;Infant Mortality Review Committee 2016;Kleinman 1996;Misra et al 2004;Stockwell et al 1987). Moreover, as observed by VanEenwyk and Macdonald (2012), questions concerning health outcomes and related health behaviors and environmental factors often are studied within small subgroups of a population because many activities to improve health affect relatively small populations.…”

Estimating the Underlying Infant Mortality Rates for Small Populations, Including those Reporting Zero Infant Deaths: A Case Study of Counties in California

“…It is an indicator that can measure the risk of infant death and the availability/quality of health care services, poverty levels, and socio-economic status differentials (Hummer, 2005;Kitagawa and Hauser, 1973;Link and Phelan, 1995;Stockwell, Goza and Balisteri, 2005;Stockwell et al, 1987). 1 Because statistical data are often used to guide health policy decisions, it is not surprising that the IMR also is used in this regard (Chen, Oster, and Williams, 2016;Kleinman, 1996;Misra et al, 2004;Stockwell et al, 1987). Moreover, as observed by VanEenwyk and Macdonald (2012), questions concerning health outcomes and related health behaviors and environmental factors often are studied within small subgroups of a population because many activities to improve health affect relatively small populations.…”