Journal of Gerontology & Geriatric Medicine Category: Medical Type: Short Commentary

Better Exposure Definitions and Control Selections are Needed for Chinese Famine Studies

Chihua Li1*, Hongkai Lian2 and Ningwei Yin2
1 Department Of Epidemiology, Mailman School Of Public Health, Columbia University, 722 W 168th St, New York, NY 10032, United States
2 Zhengzhou Central Hospital Affiliated To Zhengzhou University, Henan, China

*Corresponding Author(s):
Chihua Li
Department Of Epidemiology, Mailman School Of Public Health, Columbia University, 722 W 168th St, New York, NY 10032, United States

Received Date: Sep 26, 2020
Accepted Date: Oct 12, 2020
Published Date: Oct 19, 2020


Age difference; Control selection; Exposure definition; Study quality


Famines in human history have been widely used as natural experiments to study how early-life environments may influence adult health outcomes, including overweight/obesity, diabetes and schizophrenia [1,2]. In the past decade, there is a growing popularity in using the Chinese famine of 1959-61 to examine related questions. For example, over 20 independent studies on the Chinese famine and diabetes have been conducted [3,4]. They show the importance of linking early-life environment shock to increased risk of diabetes for their prevention and management, and illustrate the possibility of using the famine as a model to examine the causal effect of prenatal under nutrition on human aging. Their findings have been interpreted as evidence that the prenatal famine exposure drives the T2DM epidemic among Chinese population [5-10]. However, such interpretations can be misleading because most Chinese famine studies have major methodologic problems, including poor famine exposure definitions and inappropriate unexposed control selections [2,3,11]. 

A recent systematic review and meta-analysis has reported summary effect estimates of fetal and childhood famine exposure on adulthood cardio metabolic conditions including diabetes [12]. This meta-analysis is mainly based on Chinese famine studies. While it provides some valuable information for the impact of early-life famine exposure on adult health, its findings need to be interpreted with caution because it failed to examine the quality of included studies appropriately. First, most Chinese famine studies defined participants born in famine years as exposed subjects but failed to take their birth place into careful consideration [2]. This can lead to misclassifications of exposed and unexposed subjects, and of highly exposed and less exposed subjects, because the severity and timing of the Chinese famine indeed varied substantially across regions. For example, one study used the provincial crude death rate to demonstrate famine severity gradients across provinces [13]. In 1960, the province of Sichuan was considered as a famine severe area because it had 54 deaths per thousand while the province of Heilongjiang had 13 deaths per thousand. 

Second, summary effect estimates of both fetal and childhood famine exposure are likely to be inflated without using appropriate unexposed controls [12]. Previous studies have shown in detail that there is an important age difference between famine exposed individuals and unexposed controls in Chinese studies, which can explain most effects commonly attributed to the famine [2-4,14,15]. Chinese studies usually estimated the effect of fetal famine exposure by comparing individuals born during the famine (famine births) to individuals born after the famine (post-famine births) [2,4]. The age difference between famine births and post-famine births is generally about 3-4 years [2,4], and the difference can be as large as 10 years in some studies [16,17]. Using younger unexposed controls will always generate apparent ‘famine effects’ in older exposed groups because the incidence of most chronic conditions increases nonlinearly with age [2-4]. The same methodologic problem exists for effect estimates of childhood famine exposure by comparing pre-famine births to post-famine births, in which case the age differences even larger. 

Above major methodologic problems can be resolved in future Chinese famine studies by learning from studies of other famine settings. Many studies of the Ukraine famine of 1932-33 and the Dutch famine of 1944-45 have set good examples of using ecological data to define famine exposure [1,18]. For example, Dutch studies defined the timing of the famine based on records of the government’s daily food rations [19-27]; and Ukraine studies used estimates of population loss to measure the severity in different regions [18,28]. This can also be achieved by integrating historical and demographic records to Chinese famine studies. Besides, Ukraine and Dutch famine studies found no difference in multiple cardiometabolic conditions in adulthood when comparing individuals born before and after famines, including overweight/obesity [24-26], diabetes [22,23,28], and other related health outcomes [19-21,27]. These studies, therefore, combined individuals born before and after famines to form unexposed controls with a comparable mean age as fetal exposed individuals [19-28]. This also implies that childhood famine exposure may not increase the risk of related conditions [29]. The Ukraine and Dutch famines were much shorter than the Chinese famine [1], so the mean age and health outcomes were more comparable between individuals born before and after famines in Ukraine and Dutch studies. It will be interesting to explore how the selection of unexposed controls may influence study results across different famine settings. 

We have also noticed a growing interest in using meta-analysis to summarize effect estimates of famine effect on health outcomes [30-33]. Their findings can be misleading without a careful examination of above problems. Therefore, we recommend to use meta-analysis to identify differences in the type of methods used across studies and magnitudes of biases caused by existing methodological problems [29,34].


The authors declare no competing interests.


  1. Lumey LH, Stein AD, Susser E (2011) Prenatal famine and adult health. Annu Rev Public Health 32: 237-262.
  2. Li C, Lumey LH (2017) Exposure to the Chinese famine of 1959-61 in early life and long-term health conditions: A systematic review and meta-analysis. Int J Epidemiol 46: 1157-1170.
  3. Li C, Lian H, Lumey LH (2019) Prenatal famine exposure and type 2 diabetes epidemics in China: a systematic review and meta-analysis. Lancet 394: 30.
  4. Li C, Tobi EW, Heijmans BT, Lumey LH (2019) The effect of the Chinese Famine on type 2 diabetes mellitus epidemics. Nat Rev Endocrinol 15: 313-314.
  5. Alberti KG, Zimmet PZ (2014) Diabetes: A look to the future. Lancet Diabetes Endocrinol 2: 1-2.
  6. Zimmet PZ, Magliano DJ, Herman WH, Shaw JE (2014) Diabetes: a 21st century challenge. Lancet Diabetes Endocrinol 2: 56-64.
  7. Ma RCW, Lin X, Jia W (2014) Causes of type 2 diabetes in China. Lancet Diabetes Endocrinol 2: 980-991.
  8. Zimmet PZ (2017) Diabetes and its drivers: The largest epidemic in human history? Clin Diabetes Endocrinol 3: 1.
  9. Ma RCW, Tsoi KY, Tam WH, Wong CKC (2017) Developmental origins of type 2 diabetes: A perspective from China. Eur J Clin Nutr 71: 870.
  10. Zimmet P, Shi Z, El-Osta A, Ji L (2018) Epidemic T2DM, early development and epigenetics: implications of the Chinese Famine. Nat Rev Endocrinol 14: 738-746.
  11. Li C, Lumey LH (2017) Studies into severe famine in early life and diabetes in adulthood: The need to control for differences in participant age and location. Diabetologia 60: 1359-1360.
  12. Hidayat K, Du X, Shi BM, Qin LQ (2020) Foetal and childhood exposure to famine and the risks of cardiometabolic conditions in adulthood: A systematic review and meta-analysis of observational studies. Obes Rev 21: 12981.
  13. Lin JY, Yang DT (2000) Food availability, entitlements and the Chinese famine of 1959-61. The Economic Journal 110: 136-158.
  14. Zou Z, Li C, Patton GC (2020) Early-life exposure to the Chinese Famine and subsequent T2DM. Nat Rev Endocrinol 16: 124-125.
  15. Li C, Tobi EW, Heijmans B, Lumey LH (2019) Reply to ‘Early-life exposure to the Chinese Famine and subsequent T2DM’. Nat Rev Endocrinol 16: 125-126.
  16. Wang J, Li Y, Han X, Liu B, Hu H, et al. (2016) Exposure to the Chinese Famine in Childhood Increases Type 2 Diabetes Risk in Adults. J Nutr 146: 2289-2295.
  17. Wang N, Cheng J, Han B, Li Q, Chen Y, et al. (2017) Exposure to severe famine in the prenatal or postnatal period and the development of diabetes in adulthood: An observational study. Diabetologia 60: 262-269.
  18. Lumey LH, Vaiserman A (2013) Early life nutrition, adult health and development: Lessons from changing diets, famines and experimental studies. Nova Science publishers, New York, USA.
  19. Carroll D, Ginty AT, Painter RC, Roseboom TJ, was Phillips ACW (2012) Systolic blood pressure reactions to acute stress are associated with future hypertension status in the Dutch Famine Birth Cohort Study. Int J Psychophysiol 85: 270-273.
  20. de Rooij SR, Painter RC, Holleman F, Bossuyt PM, Roseboom TJ (2007) The metabolic syndrome in adults prenatally exposed to the Dutch famine. Am J Clin Nutr 86: 1219-1224.
  21. Lumey LH, Martini LH, Myerson M, Stein AD, Prineas RJ (2009) No relation between coronary artery disease or electrocardiographic markers of disease in middle age and prenatal exposure to the Dutch famine of 1944-5. Heart 98: 1653-1659.
  22. Lumey LH, Stein AD, Kahn HS (2009) Food restriction during gestation and impaired fasting glucose or glucose tolerance and type 2 diabetes mellitus in adulthood: Evidence from the DutchHunger Winter Families Study. J Dev Orig Health Dis: 164.
  23. Ravelli AC, van der Meulen JH, Michels RP, Osmond C, Barker DJ, et al. (1998) Glucose tolerance in adults after prenatal exposure to famine. Lancet 351: 173-177.
  24. Ravelli A, van der Meulen JH, Osmond C, Barker D, Bleker O (1999) Obesity at the age of 50 y in men and women exposed to famine prenatally. Am J Clin Nutr 70: 811-816.
  25. Ravelli G, Stein Z, Susser M (1976) Obesity in young men after famine exposure in utero and early infancy. N Engl J Med 295: 349-353.
  26. Stein A, Kahn HS, Rundle A, Zybert PA (2007) Anthropometric measures in middle age after exposure to famine during gestation: Evidence from the Dutch famine. Am J Clin Nutr 85: 869-876.
  27. Stein AD, Zybert PA, van der Pal-de Bruin K, Lumey LH (2006) Exposure to famine during gestation, size at birth, and blood pressure at age 59 y: evidence from the Dutch Famine. Eur J Epidemiol 21: 759-765.
  28. Lumey LH, Khalangot MD, Vaiserman AM (2015) Association between type 2 diabetes and prenatal exposure to the Ukraine famine of 1932-33: A retrospective cohort study. Lancet Diabetes Endocrinol 3: 787-794.
  29. Li C, Tobi EW, Heijmans BT, Lumey LH (2019) Reply to ‘Chinese famine and the diabetes mellitus epidemic’. Nat Rev Endocrinol 16: 123-124.
  30. Liu H, Chen X, Shi T, Qu G, Zhao T, et al (2020) Association of famine exposure with the risk of type 2 diabetes: A meta-analysis. Clin Nutr 39: 1717-1723.
  31. Liu L, Wang W, Sun J, Pang Z (2016) Association of famine exposure during early life with the risk of type 2 diabetes in adulthood: A meta-analysis. Eur J Nutr 57: 741-749.
  32. Xin X, Yao J, Yang F, Zhang D (2018) Famine exposure during early life and risk of hypertension in adulthood: A meta-analysis. Crit Rev Food Sci Nutr 58: 2306-2313.
  33. Zhou J, Zhang L, Xuan P, Fan Y, Yang L, et al. (2018) The relationship between famine exposure during early life and body mass index in adulthood: A systematic review and meta-analysis. PLoS One 13: 0192212.
  34. Greenland S (1994) Can meta-analysis be salvaged? Am J Epidemiol 140: 783-787.

Citation: Li C, Lian H, Yin N (2020) Better Exposure Definitions and Control Selections are Needed for Chinese Famine Studies. J Gerontol Geriatr Med 6: 074.

Copyright: © 2020  Chihua Li, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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