Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-22T04:28:03.511Z Has data issue: false hasContentIssue false
  • English
  • Français

Studies on infant mortality: Part I. Influence of social conditions in county boroughs of england and Wales

Published online by Cambridge University Press:  15 May 2009

Barnet Woolf  and
John Waterhouse
Barnet Woolf
Affiliation:
Zoology Department, University of Birmingham
John Waterhouse
Affiliation:
Zoology Department, University of Birmingham
Rights & Permissions [Opens in a new window]

Extract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

1. The Introduction (pp. 67–73) describes the course of infant mortality in England and Wales over the past century, and critically reviews arguments advanced to prove that variations in the infant mortality rate (i.m.) are caused by genetic differences with respect to viability.

2. The i.m. in county boroughs shows a 2-yearly cycle of variability, affecting places with high mortalities.

3. We have devised and tested various social indices and have selected five which gave the highest joint covariance with infant mortality in county boroughs during the 11 years 1928–38. These indices are:

H, percentage of families living more than 1 person per room.

U, percentage of men unemployed.

P, percentage of occupied males in the Registrar-General's Social Classes IV and V.

F, percentage of women employed on manufacturing processes.

L, latitude.

4. We have computed multiple regression equations involving i.m. and the five indices for each of the 11 years, and two summarizing equations. The regressions plus sampling variance account for about 80% of the total variance in infant mortality. The regression is linear.

5. Latitude does not affect infant mortality in Class I. For this and other reasons we regard the latitude effect as expressing miscellaneous poverty indices omitted from our equations.

6. The regression equations enable us to divide the population into various strata with characteristic average infant mortality rates. These include:

‘Better off’ (all poverty indices = 0) i.m.=23·1

Overcrowded poor i.m. = 108

Unemployed overcrowded poor i.m. = 153

Babies whose mothers work in industry suffer an additional mortality risk of at least 35 per 1000, and possibly more. The figure 23·1 is the i.m. rate that would prevail if our five poverty symptoms could be eliminated.

7. In county boroughs two-thirds of infant deaths would be avoided by the abolition of conditions defined by our indices. Of the preventable deaths, one-third are associated with overcrowding, one-quarter with low-paid occupations, one-fifth with unemployment, and one-eighth with industrial employment of women. In England and Wales, over 250,000 deaths in 11 years, about 63% of the total, can be attributed to adverse social conditions.

We have to thank the Rockefeller Foundation for a personal grant to one of us (J. W.) out of an allocation for research work in Prof. Lancelot Hogben's Department, and the Halley Stewart Trust for a grant for mechanical computing equipment. Our thanks are also due to the various members of the Zoology Department in the University of Birmingham who assisted in computing at various times, and especially to Prof. Hogben for his unfailing interest, advice and support.

Type
Research Article
Information
Journal of Hygiene , Volume 44 , Issue 2 , April 1945 , pp. 67 - 98
Copyright
Copyright © Cambridge University Press 1945

References

REFERENCES

Beveridge, (1942). Report on Social Services. London.Google Scholar
Bowley, (1915). Livelihood and Poverty. London.Google Scholar
Bowley, (1925). Has Poverty Diminished? London.Google Scholar
Brownlee, (1917). J. Roy. Statist. Soc. 80, 222.CrossRefGoogle Scholar
Charles, (1936). Article in Political Arithmetic, edited Hogben (1936).Google Scholar
Elderton, & Pearson, (1915). Biometrika, 10, 488.CrossRefGoogle Scholar
Ezekiel, (1930). Methods of Correlation Analysis. New York.Google Scholar
Fisher, (1930). Genetical Theory of Natural Selection. London.CrossRefGoogle Scholar
Fisher, (1938). Statistical Methods for Research Workers, 7th ed. Edinburgh.Google Scholar
Fisher, (1942). Ann. Eugen., Lond., 10.Google Scholar
Jones, (1934). Social Survey of Merseyside, 1. London.Google Scholar
Kuczynski, (1935). Measurement of Population Growth. London.Google Scholar
Love, (1936). Statistical Methods Applied to Agriculture. Shanghai.Google Scholar
M'Gonigle, & Kirby, (1936). Poverty and Public Health. London.Google Scholar
Ministry of Health (1936). Report of Overcrowding Survey, England and Wales.Google Scholar
Ministry of Health (annually). Local Government Financial Statistics.Google Scholar
Ministry of Labour (1927 to 1939). Local Unemployment Index.Google Scholar
Newsholme, (1910, 1913, 1914). Special Reports on Infant and Child Mortality to Local Government Board.Google Scholar
Orr, (1935). Food, Health and Income. London.Google Scholar
Pearson, (1912). Proc. Roy. Soc. B, 85, 469.Google Scholar
Pearson, & Elderton, (1922). Biometrika, 14, 281.CrossRefGoogle Scholar
Peters, & Van, Voorhis (1940). Statistical Procedures and their Mathematical Basis. New York.CrossRefGoogle Scholar
Registrar-General. All references give date to which report refers, not date of publication. Abbreviations: A.R. Annual Review; D.S. Decennial Supplement, Part 2 (Occupational Mortality); Text, Text Volume of Annual Statistical Review.Google Scholar
Rowntree, (1937). Human Needs of Labour. London.Google Scholar
Shewhart, (1931). Economic Control of Quality of Manufactured Product. New York.Google Scholar
Shewhart, (1939). Statistical Method from the Viewpoint of Quality Control. Washington.Google Scholar
Simon, (1941). Engineers' Manual of Statistical Methods. New York.Google Scholar
Simpson, & Roe, (1939). Quantitative Zoology. New York.Google Scholar
Snow, (1911). Intensity of Natural Selection in Man. London.Google Scholar
Stevenson, (1921). J. Roy. Statist. Soc. 84, 90.CrossRefGoogle Scholar
Yule, & Kendall, (1940). Introduction to Theory of Statistics. London.Google Scholar