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Diabetes, employment and behavioural risk factors in China: Marginal structural models versus fixed effects models

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  • Seuring, Till
  • Serneels, Pieter
  • Suhrcke, Marc
  • Bachmann, Max

Abstract

We use longitudinal data from the China Health and Nutrition Survey, covering the years 1997–2011, to estimate the effect of a diabetes diagnosis on an economic outcome (employment probabilities) and behavioural risk factors (alcohol consumption, smoking cessation, body mass index (BMI), physical activity and hypertension) for men and women. We apply two complementary statistical techniques—marginal structural models (MSMs) and fixed effects (FE) models—to deal with confounding. Both methods suggest, despite their different underlying assumptions, similar patterns that indicate important differences between men and women. Employment probabilities decline substantially after the diagnosis for women (−12.4 (MSM) and −15.5 (FE) percentage points), but do not change significantly for men. In particular, the MSM estimates indicate an increase in hypertension (13 percentage points) and a decrease in physical activity for women, while men have small and statistically insignificant changes in these outcomes. For BMI, the MSM results indicate statistically significant changes for men (−.76), but not for women, while the FE estimates show similar reductions for men and women (−.80 and −.73 respectively). Men also reduce their alcohol consumption, but do not cease to smoke. For women these risk factors have a prevalence close to zero to begin with, though women seem to still reduce alcohol consumption somewhat. These results suggest important gender differences in the impact of diabetes in China. To narrow these inequities policies supporting women to reduce diabetes related risk factors are likely important.

Suggested Citation

  • Seuring, Till & Serneels, Pieter & Suhrcke, Marc & Bachmann, Max, 2020. "Diabetes, employment and behavioural risk factors in China: Marginal structural models versus fixed effects models," Economics & Human Biology, Elsevier, vol. 39(C).
  • Handle: RePEc:eee:ehbiol:v:39:y:2020:i:c:s1570677x20301957
    DOI: 10.1016/j.ehb.2020.100925
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    Cited by:

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    2. Gaggero, A. & Gil, J. & Jiménez-Rubio, D. & Zucchelli, E., 2021. "Health information and lifestyle behaviours: the impact of a diabetes diagnosis," Health, Econometrics and Data Group (HEDG) Working Papers 21/02, HEDG, c/o Department of Economics, University of York.
    3. Gaggero, Alessio & Gil, Joan & Jiménez-Rubio, Dolores & Zucchelli, Eugenio, 2022. "Does health information affect lifestyle behaviours? The impact of a diabetes diagnosis," Social Science & Medicine, Elsevier, vol. 314(C).
    4. Luciana Juvenal & Paulo Santos Monteiro, 2024. "Risky Gravity," Journal of the European Economic Association, European Economic Association, vol. 22(4), pages 1590-1627.
    5. Mudrazija, Stipica & Butrica, Barbara A., 2023. "How does debt shape health outcomes for older Americans?," Social Science & Medicine, Elsevier, vol. 329(C).

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    More about this item

    Keywords

    China; Diabetes; Employment; Behavioural risk factors; Marginal structural model;
    All these keywords.

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • E24 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Employment; Unemployment; Wages; Intergenerational Income Distribution; Aggregate Human Capital; Aggregate Labor Productivity
    • F61 - International Economics - - Economic Impacts of Globalization - - - Microeconomic Impacts
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity

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