Early-life malnutrition affects the central nervous system of the human brain during gestation( Reference Gillette-Guyonnet and Vellas 1 ) and has a long-term negative impact on cognitive functioning in later life( Reference Harding 2 ). A very limited number of longitudinal studies, conducted in Central America and the Caribbean nations including Barbados and Jamaica, showed that nutritional deprivation had severely deteriorated effect on cognitive impairment in adulthood( Reference Galler, Bryce and Waber 3 , Reference Waber, Bryce and Girard 4 ), and this functional loss can be compensated by early interventions( Reference Walker, Chang and Vera-Hernandez 5 ). Due to apparent ethical consideration, however, experimental studies regarding human cognitive impairment in adulthood after exposure to undernutrition in gestation almost do not exist( Reference Lumey, Stein and Susser 6 ).
Famine, as a natural experiment, provides a unique opportunity to test the long-term association of prenatal malnutrition with adult cognitive functioning. In the past four decades, observational investigations on this issue were mainly conducted for the 1944–1945 Dutch famine and did not suggest a long-term effect of prenatal famine on adult cognitive functioning( Reference Lumey, Stein and Susser 6 ). For example, the first study by Stein et al.( Reference Stein, Susser and Saenger 7 ) in 1972, found that prenatal exposure to famine was not related to prevalence rates of mild and severe mental retardation at about 19 years on male military recruits in the Netherlands. Two studies on the Dutch famine, afterwards, confirmed the findings using samples at ages between 56 and 59 years( Reference de Groot, Stein and Jolles 8 , Reference de Rooij, Wouters and Yonker 9 ).
Chinese famine is one of the most severe famines around the world, causing approximately 15–30 million excess deaths during 1959–1961( Reference Chen and Zhou 10 ). Nevertheless, compared with the Dutch famine, studies focusing on the association between the Chinese famine and cognitive functioning are limited partly due to data unavailability( Reference Kim, Fleisher and Sun 11 ). Among the few, most were at the regional level with small size( Reference Wang, An and Yu 12 ). In addition, analyses of the long-term association of prenatal famine exposure with adult cognitive impairment faced a number of methodological challenges, such as the identification of the causal effect of famine( Reference Chen and Zhou 10 ). Previous studies, as a matter of fact, have not fully addressed these issues. One of the estimation methods to identify the causal effect of famine depends on the regional variation of famine across birth cohorts by using difference-in-difference (DID) models( Reference Huang, Phillips and Zhang 13 ).
The National Sample Survey on Disability is a nationally representative data source that included measures of cognitive impairment in China. In this study, we attempted to analyse this population-based data to provide evidence on the long-term impact of prenatal exposure to the Chinese famine on cognitive impairment in adulthood on the basis of the identification strategy of DID. This study will contribute to the identification strategy of the long-term effect of famine on adult cognitive impairment and potential mechanisms for such effect.
The Chinese famine coincided with a nationwide movement, known as ‘Great Leap Forward (GLF)’, which started sweeping across China in 1958. The GLF aimed to bring about rapid industrialisation and overtake the level of Britain and the USA in a short time( Reference Chen and Zhou 10 ). Contrary to expectation, however, the GLF severely disrupted agricultural production( Reference Kim, Deng and Fleisher 14 ). As a result, grain output dropped by 15 % in 1959, and in the next 2 years, continued to drop to roughly 70 % of the 1958 level( Reference Li and Yang 15 ). Meanwhile, the central government sharply increased grain procurement from the rural population. The plunge in grain output, excess procurement and severe weather disaster jointly caused a dramatic decline in energy intake, and the famine ensued in all regions of China( Reference Lin and Yang 16 ). From 1959 to 1961, death rates sharply increased while fertility rates rapidly decreased at the same time( Reference Lin and Yang 16 ). By 1962, both death and birth rates returned to a normal level( Reference Almond, Edlund and Li 17 ).
Methods
Study participants
We obtained data from the Second National Sample Survey on Disability implemented in thirty-one provinces in 2006. The aim of the survey was to investigate the prevalence, causes and severity of disabilities, as well as the living conditions and health service needs of the disabled. Multistage stratified random cluster sampling, with probability proportional to size, was used in 734 counties (districts), 2980 towns (streets) and 5964 communities (villages) from all provinces, autonomous regions and municipalities. More details of sampling were presented in our previous study( Reference Zheng, Chen and Song 18 ). The survey sample size was 2 526 145, accounting for 1·9/1000 inhabitants of China( Reference He, Chen and Wang 19 ).
In this study, the term ‘prenatal famine’ refers to maternal exposure to famine during the roughly 300 d from the peri-conception to delivery( Reference Susser and Clair 20 ). We restricted our analysis to 1956–1965 birth cohorts, mainly because of avoiding other natural disasters before and after the famine, including the extremely cold weather of 1954–1955 and the Chinese Cultural Revolution of 1966–1976( Reference Huang, Phillips and Zhang 13 ). We defined adults born in 1959–1962 as those with prenatal exposure to famine, while those born in 1956–1958 and 1963–1965 were not prenatally exposed. In total, we selected a subsample of 387 093 adults who were born between 1956 and 1965, at the ages of 41–50 years during the survey time.
Ethics approval
The survey was conducted in thirty-one provinces by the Leading Group of the National Sample Survey on Disability and the National Bureau of Statistics. The survey was approved by the China State Council (no. 20051104) and implemented within the legal framework governed by the Statistical Law of the People’s Republic of China (1996 Amendment). All respondents provided consent to the Chinese government, which covered their participation in the survey and the clinical assessment process.
Measures
Cognitive impairment
The outcome variable was whether or not an individual had cognitive impairment. Individuals with cognitive impairment were ascertained by the combination of questionnaire screening and medical diagnosis by psychiatrists. Cognitive impairment was defined as intelligence quotient (IQ) <70 and the age of onset before 18 years( Reference Wu, Qiu and Wong 21 ). The IQ for adults was evaluated by the Wechsler Adult Intelligence Scale – China Revision, which has been widely utilised in China( Reference Xiong, Ye and Zhang 22 ). Survey interviewers were recruited from local primary care institutions and screened adults using screening questionnaires in households. The interviewers were trained by the provincial expert teams on survey methods and participant screening. The screening questions included: (1) do you or your family members have difficulty in learning; and (2) does anybody in your family have poor life or workability and need help from others? If the screeners found that the subjects had potential cognitive impairment, they were referred to psychiatrists for medical diagnosis of cognitive impairment.
Famine severity
The uniqueness of the Chinese famine not only rests on its long duration and extreme severity but also on its substantial variation in severity across regions( Reference Chen and Zhou 10 ). This regional variation in famine severity, combined with differences in cognitive impairment, provides a critical opportunity to identify the causal effects of famine.
Following previous studies( Reference Chen and Zhou 10 , Reference Meng, Qian and Yared 23 ), we used the excess death rate (EDR) as a proxy of famine severity at the province level. The EDR is calculated as the gap between the average death rate during the famine (1959–1961) and 3 years before the famine (1956–1958). The death data across provinces were obtained from the previous studies( Reference Lin and Yang 16 , Reference Peng 24 ). According to the administrative region division during 1956–1965, Hainan and Chongqing were included in Guangdong and Sichuan province, respectively. We dropped Tibet due to lack of population data during the famine period. As a result, we obtained the EDR values of twenty-eight provinces, ranging from 0·07 to 28·63/1000 persons with a mean of 6·94, representing that the death rate during the famine period was 0·694 % higher than the mean death rate in the 3 years before the famine in these provinces.
In addition, we employed the cohort size shrinkage index (CSSI)( Reference Huang, Guo and Nichols 25 , Reference Huang, Li and Wang 26 ), measured by comparing the size of the famine cohorts relative to the surrounding non-famine cohorts in the population, as an alternative measure of famine severity to check the robustness of regressions. The details of CSSI have been shown elsewhere( Reference Huang, Phillips and Zhang 13 , Reference Huang, Li and Narayan 27 ).
Control variables
Control variables in this study included sex (male v. female) and residency (urban v. rural). We defined residency based on current living address at the individual level.
Analytic approach
The famine impact on adult cognitive impairment was estimated by the DID models, which examined the regional variations of famine exposure across birth cohorts. The idea behind this approach is that we can use the birth year to identify whether or not an individual was prenatally exposed during the famine. Meanwhile, we can also rely on the famine severity across regions to identify the variation of famine exposure in the same birth cohorts. The detailed rationale of using this method to infer the causal effect of famine was explained elsewhere( Reference Chen and Zhou 10 ) and was broadly used in Chinese famine studies( Reference Huang, Phillips and Zhang 13 , Reference Meng, Qian and Yared 23 , Reference Huang, Guo and Nichols 25 , Reference Hu, Liu and Fan 28 ). Logit regression models with the DID estimators were fitted as the following:
$$Y_{{ijk}} \,{\equals}\,B_{0} {\plus}\delta {\rm EDR}_{j} {\plus}\varphi _{k} {\rm Cohort}_{k} {\plus}\mathop \sum\limits_{k{\equals}1956}^{1965} \beta _{k} \left( {{\rm EDR}_{r} {\times}{\rm Cohort}_{k} } \right){\plus}VX_{{ijk}} ,$$
where Y
ijk
is the risk of cognitive impairment for individual i, born in province j and year k (k ranges from 1956 to 1965), EDR
j
is the EDR of province j,
$\varphi _{k} $
represents the cohort fixed effect, X
ijk
constitutes a vector of control variables involving sex and residency, and V is the scalar that contains the corresponding coefficients of the covariates. Standard errors are clustered at the province level to deal with potential heteroscedasticity and serial correlation problems(
Reference Bertrand, Duflo and Mullainathan
29
).
The coefficient of the interaction between the EDR and the birth cohort dummies, namely β k , evaluates the impact of the prenatal exposure to famine on the risk of cognitive impairment in the DID models. The estimates of this effect using the interaction term in non-linear DID models were shown elsewhere( Reference Athey and Imbens 30 , Reference Puhani and Sonderhof 31 ). To estimate the average effect across provinces, we multiplied the interaction coefficient by 6·94, the mean of EDR in all provinces.
For all models, we first analysed all samples and subsamples by residency and sex. A P value of <0·05 was considered statistically significant. The software Stata version 13 for Windows (StataCorp) was used for the statistical analysis.
Results
Table 1 shows the characteristics of the sample by birth cohorts. Overall, of the 387 093 adults, 38·24 % lived in the urban area, 49·78 % were female and 0·61 % had cognitive impairment. The proportion of urban population accounting for the total population fluctuated before, during and after famine period, peaking at 42·21 % in 1960. The proportion of females was stable from 1956 to 1965, representing about a half of the total population.
Table 1 Characteristics of sample, by birth cohorts
Table 2 presents the odds ratios for risk of cognitive impairment predicted by famine exposure. In the total sample, adults born in 1959, 1960 and 1961 were 1·11 (95 % CI 1·02, 1·20), 1·20 (95 % CI 1·07, 1·35) and 1·21 (95 % CI 1·02, 1·43) times more likely to have cognitive impairment than those who were born between 1956 and 1958, respectively, after adjusting for sex and residency.
Table 2 Risk of cognitive impairment predicted by famine exposure, based on logit regression with difference-in-difference estimator (n 235 697) (Odds ratios and 95 % confidence intervals)
Ref., referent value.
* Adjusting for sex and urban-rural residence.
† P value is statistically significant at the 0·05 level.
Table 3 shows the odds ratios for risk of cognitive impairment predicted by famine exposure by urban and rural residency. In the rural sample, compared with pre-famine cohorts, adults born in 1960 had a higher rate of cognitive impairment, with an OR of 1·20 (95 % CI 1·03, 1·40). In the urban sample, there was no statistically significant difference in the prevalence of cognitive impairment between famine cohorts and pre-famine cohorts.
Table 3 Risk of cognitive impairment predicted by famine exposure, based on logit regression with difference-in-difference estimator, by urban-rural residency (Odds ratios and 95 % confidence intervals)
Ref., referent values.
* Adjusting for sex.
† P value is statistically significant at the 0·05 level.
Table 4 illustrates the odds ratios for cognitive impairment of famine cohorts in relative to pre-famine cohorts by sex. In the male population, those who were born in 1959 were more likely than their pre-famine peers to have cognitive impairment, with an OR of 1·18 (95 % CI 1·06, 1·32). In the female population, individuals born in 1960 and 1961 had higher rates of cognitive impairment than those in pre-famine cohorts, with an OR of 1·37 (95 % CI 1·15, 1·63) and 1·32 (95 % CI 1·12, 1·55), respectively.
Table 4 Risk of cognitive impairment predicted by famine exposure, based on logit regression with difference-in-difference estimator, by sex (Odds ratios and 95 % confidence intervals)
Ref., referent values.
* Adjusting for urban-rural residency.
† P value is statistically significant at the 0·05 level.
The robustness analyses suggested that when the post-famine cohorts (born in 1963–1965) were used as the reference group, we could still observe a higher rate of cognitive impairment among adults born in 1961 (online Supplementary Table S1). In addition, when we used the CSSI as an alternative measure of famine severity, we found that the results were similar (online Supplementary Table S2).
Discussion
We investigated whether prenatal exposure to the Chinese famine would predict cognitive impairment in adulthood. We found that prenatal exposure to famine had an enduring deleterious effect on cognitive impairment in adulthood. This effect was evident in both males and females, in rural but not in urban areas.
The effect of famine exposure found in this study indicates that prenatal malnutrition has a long-term negative effect on cognitive impairment in adulthood. This result is in line with previous studies in China. For instance, Chinese studies suggested a long-term association between prenatal famine exposure and adulthood cognitive ability, as defined by memory, calculation or word test( Reference Kim, Fleisher and Sun 11 , Reference Wang, An and Yu 12 , Reference Tan, Zhibo and Zhang 32 ). In addition, two longitudinal investigations suggested that in low-resource countries, prenatal nutritional deprivation has a negative impact on human cognitive function in adulthood( Reference Galler, Bryce and Waber 3 , Reference Waber, Bryce and Girard 4 ). This study further verified the Chinese famine effect on cognitive impairment by examining famine survivors aged 41–50 years from the perspective of a natural experiment. Furthermore, laboratory studies in animals revealed the potential mechanisms on how prenatal exposure to malnutrition impacted on adult cognitive impairment. For example, studies on rats showed that prenatal undernutrition was associated with the alteration of brain development( Reference Bedi 33 ), and then had a negative impact on cognitive function in later life( Reference Duran, Cintra and Galler 34 , Reference Ranade, Rose and Rao 35 ). As well, animal studies showed that dietary deprivation in utero influenced sub-regions of the hippocampus( Reference Ranade, Rose and Rao 35 ), and prenatal malnutrition on protein changed the response of medial prefrontal neurons to stress( Reference Rosene, Lister and Schwagerl 36 ).
The negative impact of Chinese prenatal famine on cognitive impairment observed in this study differs from that of the Dutch famine. An excellent review concluded that there was no long-term association between prenatal exposure to the Dutch famine and cognitive functioning in adulthood( Reference Lumey, Stein and Susser 6 ), on the basis of three studies( Reference Stein, Susser and Saenger 7 – Reference de Rooij, Wouters and Yonker 9 ). We cannot directly compare our study with the Dutch studies because the effect of prenatal malnutrition on adult health is determined by multiple factors( Reference Huang, Phillips and Zhang 13 ). For example, the Dutch and Chinese famines were very different. The Dutch famine emerged in a Western, rich country, and mainly impacted urban residents in selected places for less than half a year( Reference Susser and Clair 20 ). By contrast, the Chinese famine occurred in an eastern, poor country, and primarily affected rural people across the entire country for about 3 years( Reference Lin and Yang 37 ). Clearly, the Chinese famine could have induced more chronic malnutrition among the Chinese population. Furthermore, studies of the two famines vary in the study design and data availability. The Dutch famine contained complete vital statistics and detailed nutrition intake before, during and after famine so that exposure timing and duration can be precisely identified for each individual. However, it is almost impossible to obtain vital statistics, especially at the county level, for the Chinese famine studies( Reference Susser and Clair 20 ); instead, most studies used birth cohort as a proxy of famine exposure and defined mortality or fertility indicators as the intensity of exposure at the province level( Reference Chen and Zhou 10 , Reference Kim, Fleisher and Sun 11 ).
We only found the long-term impact of prenatal famine exposure on adult cognitive impairment in rural areas. This is likely because famine severity was much greater in rural China( Reference Hu, Liu and Fan 28 ). The similar rural-urban differentials have been observed for other health outcomes like schizophrenia( Reference Xu, Sun and Liu 38 ). The disparity of famine between urban and rural areas may be in part explained by the registration system, namely ‘Hukou’ in China, as well as the system of grain procurement from the rural population at that time( Reference Kim, Fleisher and Sun 11 ). The strict registration system of Hukou was launched in 1951, and furtherly reinforced by the end of the 1950s. Chinese residents, regulated by the Hukou system, were prohibited from free migration, especially from rural to urban areas( Reference Wang 39 ). More importantly, in the famine years, rural families were forced to turn in a larger amount of grain despite a huge shrinkage of food production, and consequently caused more severe starvation in rural China; by contrast, urban residents had the legal rights to receive a certain amount of food from state grain store during the famine, and therefore experienced a relatively smaller impact of the famine( Reference Xu, Sun and Liu 38 ).
This study is subject to several limitations. Like other famine studies in China, we need to be cautious to interpret our findings. The first potential threat to the validity of our finding comes from famine-associated selected mortality. It is well understood that those who were more severely affected by the famine were more likely to have died in the famine. Meanwhile, the famine survivors with more serious conditions were also less likely to have survived to middle age by the survey time( Reference Kim, Fleisher and Sun 11 ). In the absence of mortality data associated with cognitive impairment, we were unable to correct the underlying bias, but this would likely underestimate rather than overestimate famine effect. The second source of potential bias is population migration. This study speculated birth place according to individuals’ current living place at the province level, which may lead to the imprecise identification of family severity across provinces. However, the Hukou (passport) system, initiated in the 1950s, greatly restricted population migration in China, especially from rural to urban areas( Reference Gooch 40 ). In fact, during the period of famine, interprovincial migration only constituted less than 1 % of the total population( Reference Chen and Zhou 10 ). In addition, compared to the Dutch famine with high-quality birth and energetic intake statistics across the life course, we acknowledge that there are some limitations in the measurement of the severity of Chinese famine. But so far, within the scope of the existing data, the EDR and CSSI used in this study are two reasonable measures to assess the intensity of the Chinese famine. Finally, the screening process may cause that cognitive impairment data were more likely to be obtained from respondents who were willing to self-identify or to identify family members as having a potential cognitive impairment. Due to lack of information on whether or not an individual got measured for cognitive impairment, we could not run a covariate balance test to see if there was possible sample selection. Despite these limitations, our study extends the long-term impact of the Chinese famine from cognitive ability to cognitive impairment based on a large-scale, nationally representative survey.
Conclusions
We found that prenatal famine has a long-term deteriorate impact on cognitive impairment in adulthood, and the impact was evident among both females and males in rural areas. Further studies need to explore the difference between the Chinese and Dutch famine and the corresponding mechanism on this issue. Policies or programmes should be developed to intervene in those who were exposed to prenatal malnutrition to address their cognitive impairments.
Acknowledgements
The authors thank the provincial and municipal federations of disabled people for their support in data collection and management.
The work was supported by the Key National Project (973) of Study on the Mechanisms of Interaction between Environment and Genetics of Birth Defects in China (grant no. 2007CB5119001), the Key State funds for social science project (Research on Disability Prevention Measurement in China, grant no. 09&ZD072) and the State Scholarship Fund (grant no. 201606010254).
P. H. initiated the study, analysed data and wrote the original article. L. L. gave critical suggestions on data analysis and revised the paper. J. M. I. S., C. G., Y. C. and G. C. provided advice on revising the paper. X. Z. supervised all aspects of implementation of the paper and contributed to writing the article. All authors critically interpreted the findings and edited the article.
The authors declare that there are no conflicts of interest.
Supplementary material
For supplementary material/s referred to in this article, please visit https://doi.org/10.1017/S0007114518000958
