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The logic in ecological: I. The logic of analysis

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  • Susser, M.

Abstract

This paper addresses ecological studies in public health research in terms of the logic of their analysis. It makes several distinctions between studies based on ecological and individual units. First, it identifies the variables common to both types of study and those particular to ecological studies. Second, it shows how ecological and individual units combine in two classes: unmixed (purely ecological, purely individual) and mixed. Third, it details how the relationships among and between individual and grouped units (expressed in terms of regression coefficients between independent and dependent variables) yield four coefficients: for all individual members; for all groups; for all individuals within each group; and for all individuals within groups (a weighted average). Equipped with an understanding of the dimensions involved at ecological and individual levels and of the relationships between them, researchers are in a position to exploit the public health potential of the ecological approach.

Suggested Citation

  • Susser, M., 1994. "The logic in ecological: I. The logic of analysis," American Journal of Public Health, American Public Health Association, vol. 84(5), pages 825-829.
    • Handle: RePEc:aph:ajpbhl:1994:84:5:825-829_4
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    Cited by:

    1. S V Subramanian & Emre Özaltin & Jocelyn E Finlay, 2011. "Height of Nations: A Socioeconomic Analysis of Cohort Differences and Patterns among Women in 54 Low- to Middle-Income Countries," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-13, April.
    2. Saroj Kumar & Abhishek Kumar & Rakesh Kumar & William Joe, 2021. "Social Demographics and Health Achievements An Ecological Analysis of Institutional Delivery and Immunization Coverage in India," IEG Working Papers 427, Institute of Economic Growth.
    3. Minuk Kang & Youngjik Lee, 2022. "The Gap in Community Sports: Utilization of Sports Facilities in South Korea," IJERPH, MDPI, vol. 19(8), pages 1-11, April.
    4. S V Subramanian & Craig Duncan & Kelvyn Jones, 2001. "Multilevel Perspectives on Modeling Census Data," Environment and Planning A, , vol. 33(3), pages 399-417, March.
    5. McSweeney Brendan & Brown Donna & Iliopoulou Stravroula, 2016. "Claiming too much, delivering too little: testing some of Hofstede’s generalisations," The Irish Journal of Management, Sciendo, vol. 35(1), pages 34-57, April.
    6. Semaan, Salaam & Sternberg, Maya & Zaidi, Akbar & Aral, Sevgi O., 2007. "Social capital and rates of gonorrhea and syphilis in the United States: Spatial regression analyses of state-level associations," Social Science & Medicine, Elsevier, vol. 64(11), pages 2324-2341, June.
    7. Shubhangi Agrawal & Sambit Bhattacharyya & Chirantan Chatterjee & Somdeep Chatterjee, 2024. "Income shock and Women’s Health Spending:Evidence from India," Working Paper Series 1324, Department of Economics, University of Sussex Business School.
    8. Amitabh Chandra & Jonathan Skinner, 2003. "Geography and Racial Health Disparities," NBER Working Papers 9513, National Bureau of Economic Research, Inc.
    9. Lilia Rodríguez-Tapia & Jorge A. Morales-Novelo, 2017. "Bacterial Pollution in River Waters and Gastrointestinal Diseases," IJERPH, MDPI, vol. 14(5), pages 1-11, May.
    10. Natalia Vincens & Martin Stafström, 2015. "Income Inequality, Economic Growth and Stroke Mortality in Brazil: Longitudinal and Regional Analysis 2002-2009," PLOS ONE, Public Library of Science, vol. 10(9), pages 1-12, September.
    11. Yu-Chi Tung & Guann-Ming Chang & Hsien-Yen Chang & Tsung-Hsien Yu, 2017. "Relationship between Early Physician Follow-Up and 30-Day Readmission after Acute Myocardial Infarction and Heart Failure," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-20, January.

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