Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-22T17:30:00.721Z Has data issue: false hasContentIssue false

Early-life exposure to the Chinese famine and risk of hyperuricaemia in adult females in Qingdao

Published online by Cambridge University Press:  21 July 2021

Yuhan Shao
Affiliation:
Qingdao Municipal Center for Disease Control and Prevention, Qingdao266033, Shandong Province, People’s Republic of China Qingdao Institute of Preventive Medicine, Qingdao266033, Shandong Province, People’s Republic of China
Li Liu
Affiliation:
Qingdao Municipal Center for Disease Control and Prevention, Qingdao266033, Shandong Province, People’s Republic of China Qingdao Institute of Preventive Medicine, Qingdao266033, Shandong Province, People’s Republic of China
Xiaojing Li
Affiliation:
Qingdao Municipal Center for Disease Control and Prevention, Qingdao266033, Shandong Province, People’s Republic of China Qingdao Institute of Preventive Medicine, Qingdao266033, Shandong Province, People’s Republic of China
Jianping Sun
Affiliation:
Division of Primary Health, Qingdao Municipal Health Commission, Qingdao, Shandong Province, 266071, People’s Republic of China
Xiaomei Huang*
Affiliation:
Department of Obstetrics, Laixi People’s Hospital, Qingdao, Shandong Province, 266600, People’s Republic of China
*
*Corresponding author: Xiao-Mei Huang, email [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Two population-based cross-sectional surveys involving randomly selected Chinese adults aged 35–74 years were conducted in Qingdao, China in 2006 and 2009. Nine thousand fifty-five subjects from the two surveys were grouped into four birth groups of fetal/infant exposed (born between 1 January 1959 and 31 December 1962), childhood exposed (born between 1 January 1950 and 31 December 1958), adolescence exposed (born between 1 January 1942 and 31 December 1949) and the unexposed (born before 1941 and after 1963). Multivariate logistic regression models were used to calculate the OR and 95 % CI of hyperuricaemia in different exposed groups. Overall, famine exposure in the fetal/infant period, childhood and adolescence was not associated with adulthood hyperuricaemia (all P > 0·05). In females, childhood exposed group (OR = 1·59, 95 % CI 1·25, 2·02) and adolescence exposed group (OR = 1·74, 95 % CI 1·30, 2·33) both had higher risks to have hyperuricaemia in adult. However, this difference was not found in fetal/infant exposed group. In males, no significant relation was observed in any famine exposed group (all P > 0·05). Exposure to famine in childhood and adolescence is associated with an increased risk of hyperuricaemia for adulthood of females, but not in males. Adequate nutrition during early life appears to be beneficial to prevent hyperuricaemia of adult females.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Nutrition Society

Uric acid is a product of the metabolic breakdown of purine nucleotides, and it is a normal component of urine. However, an abnormally high level of uric acid in the blood can cause hyperuricaemia. Hyperuricaemia affects worldwide people, and its prevalence ranges from 2·6 % to 36 % in different populations(Reference Uaratanawong, Suraamornkul and Angkeaw1). Generally, the prevalence of hyperuricaemia in developed countries is higher than that in developing countries, but it has been increasing annually in recent years in developing countries, such as China(Reference Zhu, Pandya and Choi2). With the rapid economic development and the improvement of residents’ living standards, prevalence of hyperuricaemia in mainland China has reached 13·3 % (19·4 % in men and 7·9 % in women) though it was once considered as a rare disease in this country(Reference Liu, Han and Wu3,Reference Fang4) . It was reported that hyperuricaemia was related to gout, the metabolic syndrome, hypertension, diabetes, chronic kidney disease, CVD, preeclampsia and stroke(Reference Johnson, Kang and Feig5Reference Li, Hou and Zhang9).

To reduce complications of hyperuricaemia, it is necessary to explore the aetiology of hyperuricaemia. Age, sex, race, genes, smoking, drinking, obesity, physical activity and dietary habits were considered to be associated with the development of hyperuricaemia(Reference Han, Zhang and Zhao10Reference Shiraishi and Une15). Besides, studies suggested that malnutrition was associated with developmental disruption in Notch signalling pathway, an important pathway in nephron formation, which could cause a decline of renal nephron numbers. Less renal nephron numbers indicated renal dysfunction and was related to underexcretion of uric acid, thus leading to hyperuricaemia(Reference Luyckx and Brenner16Reference Murphy and Shipman18). Therefore, malnutrition may be another factor contributing to hyperuricaemia.

Some experiments have been conducted on the link between short-term undernutrition and later hyperuricaemia(Reference Alderman and Davis19Reference Lennox21). The ‘fetal origin of adult disease’ hypothesis has proposed that malnutrition at a very early age might be linked to adult chronic diseases(Reference Barker22). Thus, early-life malnutrition might have long-term effect on adult hyperuricaemia. However, up to now, studies in this topic are few and data on the relation between famine exposure in adolescence and adulthood hyperuricaemia are not available(Reference Zhang and Luan23,Reference Wang, Weng and Wan24) . Thus, in the present study, we used the data from ‘Qingdao Diabetes Prevention Program’ study in China in 2006 and 2009 to further analyse the impact of early-life famine exposure on hyperuricaemia in adulthood.

Methods

Subjects and design

Using stratified, random cluster sampling methods, two population-based cross-sectional surveys were conducted in three urban areas (Shinan, Shibei and Sifang) and three rural areas (Huangdao, Jiaonan and Jimo) in Qingdao city, Shandong province, China in 2006 and 2009. Participants who had lived in Qingdao for at least 5 years were recruited. A total of 5335 and 5110 individuals aged 35–74 years participated in the 2006 and 2009 surveys, with response rates of 87·8 % and 67·1 %, respectively. The sampling, protocols, questionnaires, physical examination and laboratory determination methods in 2006 survey were exactly the same as that in 2009 survey, whereas participants of the two surveys were not duplicate.

Because Chinese famine affected almost the entire country, participants could not be categorised into different groups according to exposure areas or non-exposure areas(Reference Liu, Yu and Zhao25). Using birth date to define famine exposure was the most common method in studies about Chinese famine(Reference Lu, Li and Xu26). Precise data on energetic consumption and definite beginning or ending time of Chinese famine are not available(Reference Zimmet and Shi27). Referred to other published studies(Reference van Abeelen, Elias and Bossuyt28,Reference Wang, Wang and Han29) and Bogin’s life cycle theory(Reference Bogin30), we divided subjects into four groups: fetal/infant exposed (born between 1 January 1959 and 31 December 1962), childhood exposed (born between 1 January 1950 and 31 December 1958), adolescence exposed (born between 1 January 1942 and 31 December 1949) and the unexposed (born before 1941 and after 1963). Subjects exposed to famine in the fetal period were likely to experience famine in the infancy period because Chinese famine lasted from 1959 to 1962. Therefore, subjects born between 1 January 1959 and 31 December 1962 were grouped into fetal/infant exposed group in the current study. To minimise misclassification of the famine exposure periods, participants born immediately before (between 1 January 1941 and 31 December 1941) and after (between 1 January 1963 and 31 December 1963), the famine were excluded (n 1390). Finally, 9055 subjects were included in the current study.

Measurements and variables

Participants’ general demographic information including birth date, sex, marital status, education, individual month income, alcohol consumption, smoking habits, family history of hyperuricaemia and residence place was collected by trained doctors or nurses. Height and weight were measured with the participants wearing only light clothes and without shoes. After at least a 15-min rest, three consecutive blood pressure readings from the upper right arm of seated individuals were recorded at least 30 s apart and the mean of the three readings was used in the data analysis. BMI was calculated as weight in kg divided by height in metre squared (kg/m2).

Blood samples were drawn from the antecubital vein into EDTA tubes containing sodium fluoride and centrifuged at the survey site. The blood specimens were placed in ice-cooled containers and transported immediately to Qingdao Hiser Medical Center in 2006 survey and Qingdao Endocrine & Diabetes Hospital in 2009 survey for biochemical tests. Fasting plasma glucose (FPG), 2-h plasma glucose (2hPG), fasting serum uric acid (UA), triglycerides (TAG), total cholesterol (TC), high density lipoprotein cholesterol (HDL)-cholesterol and low density lipoprotein cholesterol (LDL)-cholesterol were tested in laboratories.

Hyperuricaemia was defined as serum uric acid > 420 μmol/l for men and >360 μmol/l for women according to guidelines(Reference Fang and Alderman31). Family history of hyperuricaemia was defined at least one of the first degree relatives had hyperuricaemia. Overweight was defined as BMI ≥ 24·0 kg/m2, and obesity was defined as BMI ≥ 28·0 kg/m2(Reference Chen32). Hypertension was defined as systolic blood pressure (SBP) ≥ 140 mmHg and(or) diastolic blood pressure (DBP) ≥ 90 mmHg. Diabetes was defined as fasting plasma glucose ≥ 7·0 mmol/l and/or 2-h plasma glucose ≥ 11·1 mmol/l(Reference Alberti and Zimmet33). Subjects with at least one of the following criteria were diagnosed with dyslipidaemia: (1) total cholesterol ≥ 5·72 mmol/l; (2) TAG ≥ 1·70 mmol/l; (3) HDL-cholesterol < 0·91 mmol/l and (4) LDL-cholesterol ≥ 3·64 mmol/l(34). According to the statistical bulletin issued by Qingdao, China in 2005, high individual month income was defined as individual month income ≥ RMB 1000 for city citizens and ≥ RMB 600 for urban citizens (2021 average: 1 USD = 6·48 RMB).

Statistical analysis

Group differences were tested using one-way ANOVA complemented by the LSD test for continuous variables with normal distribution and the Mann–Whitney U test or Kruskal–Wallis test for continuous variables with a skewed distribution. The χ 2 test was used to compare differences between groups for categorical variables. We calculated OR with 95 % CI for risk of hyperuricaemia by multivariable logistic regression model. Analyses were adjusted for age, sex, marital status, residence place (urban/rural), individual month income, family history of hyperuricaemia, regular exercise, current smoking, current drinking, BMI, hypertension, dyslipidaemia and diabetes. Interactions between famine exposure, sex, residence place, education, individual monthly income, family history of hyperuricaemia and overweight/obesity on hyperuricaemia were tested by adding multiplicative factors in the multivariable logistic regression model. A two-tailed P < 0·05 was considered as statistically significant. All statistical analyses were performed using SPSS 20.0 (SPSS).

Results

Of the total 9055 participants, 1501 men and 2257 women were exposed to the Chinese Famine in the current study. As shown in Table 1, 67·30 % men and 59·80 % women lived in rural areas and men were more likely to be a smoker or alcohol user than women. The mean values for age, SBP, DBP, uric acid, TAG and fasting plasma glucose were greater in men than those in women, whereas BMI, total cholesterol, HDL-cholesterol and 2-h plasma glucose values were greater in women than that in men.

Table 1. General characteristics of subjects in men and women

(Numbers and percentages; mean values and standard deviations)

UA, uric acid; TC, total cholesterol; FPG, fasting plasma glucose; 2hPG, 2-h plasma glucose.

* P values in t tests for differences in means or χ 2 tests for differences in proportions between men and women.

Table 2 presents the characteristics of subjects in different Chinese famine-exposed groups. 1012, 2683 and 1602 subjects were exposed to famine during fetal/infant period, childhood and adolescence, respectively. The respective prevalence rates of hyperuricaemia in the unexposed, fetal/infant exposed, childhood exposed and adolescence exposed groups were 14·20 %, 13·10 %, 14·40 % and 16·90 %. Compared with the unexposed group, fetal/infant exposed, childhood exposed and adolescence exposed groups had higher BMI, DBP, total cholesterol, TAG, HDL-cholesterol, fasting plasma glucose and 2-h plasma glucose levels and were more likely to suffer from overweight/obesity, hyperlipidaemia, hypertension and diabetes.

Table 2. Characteristics of subjects according to the Chinese famine exposure

(Numbers and percentages; mean values and standard deviations)

UA, uric acid; TC, total cholesterol.

The four different exposure groups were compared by ANOVA or the χ 2-test, as appropriate. *P < 0·05; **P < 0·01.

Famine-exposed and unexposed groups were compared by ANOVA or the χ 2-test, as appropriate, ***P < 0·05; ****P < 0·01.

Associations of famine exposure in early life with adulthood hyperuricaemia stratified by sex are shown in Table 3. For all subjects, famine exposure in the fetal/infant period, childhood and adolescence was not associated with adulthood hyperuricaemia after adjustment for age, sex, marital status, residence place, individual month income, family history of hyperuricaemia, regular exercise, current smoking, current drinking, BMI, hypertension, dyslipidaemia and diabetes (all P > 0·05). In females, after adjustment for age, marital status, residence place, individual month income, family history of hyperuricaemia, regular exercise, current smoking, current drinking, BMI, hypertension, dyslipidaemia and diabetes, childhood exposed group (OR = 1·59, 95 % CI 1·25, 2·02) and adolescence exposed group (OR = 1·74, 95 % CI 1·30, 2·33) had higher risks to have hyperuricaemia in adult, but no significant relation was found in the fetal/infant exposed group. This association was not significant for all the three exposed groups in males. Additionally, no significant interactions between sex, residence place, education, individual month income, family history of hyperuricaemia, overweight/obesity and famine exposure on hyperuricaemia were observed for both males and females (all P interaction > 0·05).

Table 3. Associations of famine exposure in early life with hyperuricaemia in adulthood according to sex

(Odds ratio and 95 % confidence intervals)

Associations of famine exposure with hyperuricaemia according to individual month income are shown in Table 4. The OR were significantly higher in childhood exposed group (OR = 1·41,95 % CI 1·05, 1·89) and adolescence exposed group (OR = 1·59, 95 % CI 1·14, 2·25) than the unexposed among female subjects with low individual month income after adjustment for age, marital status, residence place, family history of hyperuricaemia, regular exercise, current smoking, current drinking, BMI, hypertension, dyslipidaemia and diabetes, and similar results were also found among subjects with high individual month income (both P < 0·05). However, we did not observe significant association between fetal/infant exposure and later hyperuricaemia in both low and high individual month income groups (both P > 0·05).

Table 4. Association of famine exposure with hyperuricaemia according to individual month income

(Odds ratio and 95 % confidence intervals)

Discussion

Overall, we did not find a link between exposure to famine early in life and the increased risk of hyperuricaemia in adulthood. However, after stratification by sex, we found a significant relationship between childhood and adolescence famine exposure with hyperuricaemia in adult women but this significant difference was not present in fetal/infant exposed group and in men.

To our knowledge, this is the first study to reveal the impact of adolescence famine exposure on hyperuricaemia in adulthood though two studies had reported the relation of fetal famine exposure and childhood famine exposure to later-life hyperuricaemia. One study found that fetal famine exposure was associated with an increased risk of hyperuricaemia in adulthood, but the significant result was not obtained in the early childhood exposed(Reference Zhang and Luan23). Another study reported that in subjects with low economic status, early-life famine exposure was negatively associated with hyperuricaemia, while in subjects with high economic status, the associations were positive(Reference Wang, Weng and Wan24). However, we found that childhood and adolescence famine exposure were positively correlated with hyperuricaemia in adult women both in high and low economic status groups, but there was no relation between fetal/infant famine exposure and hyperuricaemia in adulthood neither in men nor in women. The discrepancy might be due to differences in design, like age differences between control group and exposure groups, the way to define different exposed groups and sampling methods of subjects. Additionally, subjects of Wang’s study were divided into low- or high-income brackets based on the gross domestic product of their enrolment site, while participants were categorised according to their personal income in our study; therefore, the results of our study could reflect real economic status(Reference Wang, Weng and Wan24).

Studies that stratified samples by sex mostly found more pronounced impacts of famine on women than on men. In the current study, we also found significant associations only in women. This sex difference has two possible reasons. First, the son preference might interpret better health outcomes for adult males. In Chinese traditional cultures, sons were preferred and valued much more than daughters, which could cause unequal distribution of food. Under this circumstance, males were sufficiently nourished when exposed to famine, while females were more likely to suffer from food shortage(Reference Coale and Banister35). Second, survivor bias was another possible reason leading to sex disparity. Male mortality was greater than female mortality during famine; thus, the survived males might be healthier than females. Furthermore, because of biological differences between males and females, such as differences in coping with stressful life events or differences in social protection, females are experiencing more stress during life and their health appears to be more influenced by early-life conditions than male health(Reference Koistinen, Koivisto and Karonen36Reference Hamil-Luker and O’Rand39).

The significant associations were only observed in childhood and adolescence exposed groups in females but not in the fetal/infant exposed group. This may be because of different sensitiveness on stress of famine. Individuals exposed to famine during childhood and adolescence are more sensitive to stress conditions than those exposed to famine in fetal/infant period; therefore, they are more likely to suffering from hyperuricaemia in later life(Reference Portrait, Teeuwiszen and Deeg40).

Our findings of higher prevalence of overweight/obesity in the exposed groups and in females seem to imply accelerated growth may be a pathway between early-life malnutrition and later hyperuricaemia. Nevertheless, the relation of famine exposure during childhood and adolescence to hyperuricaemia in adulthood in females remained unchanged after adjustment for BMI and other confounding factors, suggesting that overweight/obesity might not be a mediator for the link(Reference Zhang and Luan23).

The mechanism of hyperuricaemia in adulthood caused by malnutrition in early life is not clear. The ‘fetal origin of adult disease’ hypothesis proposed that stress during the critical growth stages promoted adaptations in body structure and function, such as establishing a thrifty phenotype(Reference Sallout and Walker41). Malnutrition, as a kind of stressor, affects the development of less critical organs (e.g. pancreas, liver, kidney) to protect more critical organs such as the brain. Individuals who experienced malnutrition might have impaired kidney function with a decline of uric acid excretion in later life(Reference Wang, Weng and Wan24). Another probable mechanism might be attributed to early-life programming of the hypothalamic–pituitary–adrenal axis(Reference Reynolds42). Malnutrition actives the hypothalamic–pituitary–adrenal axis, following an increase of glucocorticoids(Reference Breton43,Reference Kongsted, Husted and Thygesen44) . Glucocorticoids could promote p38 mitogen-activated protein kinases phosphorylation in adipose tissue, and then phosphorylated p38 mitogen-activated protein kinases activates the transcriptional activity of CCAAT/enhancer binding protein beta. Activated CCAAT/enhancer binding protein beta combines with xanthine oxidoreductase promoter to promote xanthine oxidoreductase expression, resulting in an increase of xanthine oxidase. Increased xanthine oxidase could catalyse hypoxanthine to xanthine, which in turn generates excess uric acid(Reference Ma45). Furthermore, famine exposure in early life may be related to impaired nephrogenesis(Reference Luyckx and Brenner16,Reference Huang, Guo and Nichols46) . Early-life malnutrition is associated with developmental disruption in Notch signalling pathway, an important pathway in nephron formation, which will cause a decrease of renal nephron numbers(Reference Hughson, Farris and Douglas-Denton17). The alteration of renal structure and function could result in underexcretion of uric acid, thus leading to the development of later-life hyperuricaemia(Reference Murphy and Shipman18,Reference Lennox and O’Connor47) . Animal studies have proved less number of nephrons were linked to renal dysfunction in later life(Reference Stelloh, Allen and Mattson48,Reference Luyckx and Brenner49) .

Strengths and limitations

Our study has several strengths. First, we analysed the relation of adolescence famine exposure to hyperuricaemia that previous studies ignored. Second, we used a stratified and random cluster sampling method to recruit a representative sample from the general population. Third, all interviews were conducted face to face by trained doctors or nurses, and blood samples were sent to the laboratory immediately after being centrifuged on site, which ensured rigorous quality control for the survey. Additionally, we combined individuals born before and after famine as the unexposed subjects in order to eliminate the influence of age on hyperuricaemia. However, some limitations should be noticed. First, the cross-sectional study design could not allow causal relation between early-life famine exposure and adulthood hyperuricaemia risk. Second, as one of the most disastrous catastrophes in human history, the Chinese famine almost affected the entire country(Reference Huang, Guo and Nichols46,Reference Justin Yifu and Yang50) , thus, subjects in the current study had to be divided into different groups according to age at exposure. Last, because definite dates of beginning and ending of Chinese famine are not available, there may be misclassification in our study.

Conclusion

We found that exposure to the Chinese famine in childhood and adolescence was associated with higher risks of hyperuricaemia in adult females. This study indicated that nutrition status of childhood and adolescence has a long-term effect on later life. Females who have experienced undernutrition in childhood and adolescence need to be considered as high-risk members of adulthood hyperuricaemia. Measures should be taken to prevent undernutrition during childhood and adolescence to prevent later hyperuricaemia, especially for females.

Acknowledgements

We thank all the participants and team members who took part in the surveys. We sincerely thank the financial supports from the World Diabetes Foundation. We are grateful to the Qingdao Municipal Health Bureau, Qingdao Endocrine and Diabetes Hospital and Qingdao Centers for Disease Control and Prevention, Qingdao, China for their contribution to the field survey. Dr. Liu also received grants supported by Qingdao Outstanding Health Professional Development Fund, Qingdao Health Science and Technology Plan Project.

This work was supported by grants from the World Diabetes Foundation (WDF05-108&07-308), Qingdao Outstanding Health Professional Development Fund, Qingdao Health Science and Technology Plan Project (2019-WJZD157).

Y. S., L. L. and X. L. contributed to the manuscript composition, quality assessment and records review. Y. S., L. L., X. L. and X. H. designed the paper and analysed the data. Y. S. and X. H. were responsible for the integrity of this work and contributed to final study selection and manuscript review. J. S. coordinated the data acquisition and standardisation. All authors reviewed and approved the final manuscript.

The authors declared no conflicts of interest.

Supplementary material

For supplementary material referred to in this article, please visit https://doi.org/10.1017/S0007114521002749

Footnotes

These authors contributed equally to this work.

References

Uaratanawong, S, Suraamornkul, S, Angkeaw, S, et al. (2011) Prevalence of hyperuricemia in Bangkok population. Clin Rheumatol 30, 887893.CrossRefGoogle ScholarPubMed
Zhu, Y, Pandya, BJ & Choi, HK (2011) Prevalence of gout and hyperuricemia in the US general population: the National Health and Nutrition Examination Survey 2007–2008. Arthritis Rheum 63, 31363141.CrossRefGoogle ScholarPubMed
Liu, R, Han, C, Wu, D, et al. (2015) Prevalence of hyperuricemia and gout in Mainland China from 2000 to 2014: a systematic review and meta-analysis. Biomed Res Int 2015, 762820.CrossRefGoogle ScholarPubMed
Fang, QW (1983) Survey of uric acid among healthy Chinese and its relation to blood lipids. Zhonghua nei ke za zhi 22, 434438.Google ScholarPubMed
Johnson, RJ, Kang, DH, Feig, D, et al. (2003) Is there a pathogenetic role for uric acid in hypertension and cardiovascular and renal disease. Hypertension 41, 11831190.CrossRefGoogle Scholar
Nakanishi, N, Okamoto, M, Yoshida, H, et al. (2003) Serum uric acid and risk for development of hypertension and impaired fasting glucose or Type II diabetes in Japanese male office workers. Eur J Epidemiol 18, 523530.CrossRefGoogle ScholarPubMed
Chang, HY, Tung, CW, Lee, PH, et al. (2010) Hyperuricemia as an independent risk factor of chronic kidney disease in middle-aged and elderly population. Am J Med Sci 339, 509515.CrossRefGoogle ScholarPubMed
Dincer, HE, Dincer, AP & Levinson, DJ (2002) Asymptomatic hyperuricemia: to treat or not to treat. Clevel Clinic J Med 69, 597.CrossRefGoogle ScholarPubMed
Li, M, Hou, W, Zhang, X, et al. (2014) Hyperuricemia and risk of stroke: a systematic review and meta-analysis of prospective studies. Atherosclerosis 232, 265270.CrossRefGoogle ScholarPubMed
Han, QX, Zhang, D, Zhao, YL, et al. (2019) Risk factors for hyperuricemia in Chinese centenarians and near-centenarians. Clin Interv Aging 14, 22392247.CrossRefGoogle ScholarPubMed
Yu, S, Yang, H, Guo, X, et al. (2016) Prevalence of hyperuricemia and its correlates in rural Northeast Chinese population: from lifestyle risk factors to metabolic comorbidities. Clin Rheumatol 35, 12071215.CrossRefGoogle ScholarPubMed
Cui, L, Meng, L, Wang, G, et al. (2017) Prevalence and risk factors of hyperuricemia: results of the Kailuan cohort study. Mod Rheumatol 27, 10661071.CrossRefGoogle ScholarPubMed
Ali, N, Perveen, R, Rahman, S, et al. (2018) Prevalence of hyperuricemia and the relationship between serum uric acid and obesity: a study on Bangladeshi adults. PLoS One 13, e0206850.CrossRefGoogle Scholar
Lee, MF, Liou, TH, Wang, W, et al. (2013) Gender, body mass index, and PPARγ polymorphism are good indicators in hyperuricemia prediction for Han Chinese. Genet Test Mol Biomarkers 17, 4046.CrossRefGoogle ScholarPubMed
Shiraishi, H & Une, H (2009) The effect of the interaction between obesity and drinking on hyperuricemia in Japanese male office workers. J Epidemiol 19, 1216.CrossRefGoogle ScholarPubMed
Luyckx, VA & Brenner, BM (2015) Birth weight, malnutrition and kidney-associated outcomes – a global concern. Nat Rev Nephrol 11, 135149.CrossRefGoogle ScholarPubMed
Hughson, M, Farris, AB, Douglas-Denton, R, et al. (2003) Glomerular number and size in autopsy kidneys: the relationship to birth weight. Kidney Int 63, 21132122.CrossRefGoogle ScholarPubMed
Murphy, R & Shipman, KH (1963) Hyperuricemia during total fasting: renal factors. Arch Intern Med 112, 954959.Google ScholarPubMed
Alderman, MH & Davis, RP (1965) Hyperuricemia in starvation. Proc Soc Exp Biol Med 118, 790792.CrossRefGoogle ScholarPubMed
Ogryzlo, MA (1965) Hyperuricemia induced by high fat diets and starvation. Arthritis Rheuma 8, 799822.CrossRefGoogle ScholarPubMed
Lennox, WG (1924) Increase of uric acid in the blood during prolonged starvation. J Am Med Assoc 82, 602604.CrossRefGoogle Scholar
Barker, DJ (2007) The origins of the developmental origins theory. J Intern Med 261, 412417.CrossRefGoogle ScholarPubMed
Zhang, W & Luan, R (2020) Early-life exposure to the Chinese famine of 1959–61 and risk of Hyperuricemia: results from the China health and retirement longitudinal study. BMC Public Health 20, 15.CrossRefGoogle Scholar
Wang, Y, Weng, P, Wan, H, et al. (2020) Economic status moderates the association between early-life famine exposure and hyperuricemia in adulthood. J Clin Endocrinol Metab 105, e3862e3873.CrossRefGoogle ScholarPubMed
Liu, D, Yu, DM, Zhao, LY, et al. (2019) Exposure to famine during early life and abdominal obesity in adulthood: findings from the great Chinese famine during 1959–1961. Nutrients 11, 903.CrossRefGoogle Scholar
Lu, J, Li, M, Xu, Y, et al. (2020) Early life famine exposure, ideal cardiovascular health metrics, and risk of incident diabetes: findings from the 4C study. Diabetes Care 43, 19021909.CrossRefGoogle ScholarPubMed
Zimmet, P & Shi, Z (2018) Epidemic T2DM, early development and epigenetics: implications of the Chinese Famine. Nat Rev Endocrinol 14, 738746.CrossRefGoogle ScholarPubMed
van Abeelen, AF, Elias, SG, Bossuyt, PM, et al. (2012) Famine exposure in the young and the risk of type 2 diabetes in adulthood. Diabetes 61, 22552260.CrossRefGoogle Scholar
Wang, N, Wang, X, Han, B, et al. (2015) Is exposure to famine in childhood and economic development in adulthood associated with diabetes? J Clin Endocrinol Metab 100, 45144523.CrossRefGoogle ScholarPubMed
Bogin, B (1999) Patterns of Human Growth. Cambridge: Cambridge University Press.Google ScholarPubMed
Fang, J & Alderman, MH (2000) Serum uric acid and cardiovascular mortality the NHANES I epidemiologic follow-up study, 1971–1992. National Health and Nutrition Examination Survey. JAMA 283, 24042410.CrossRefGoogle ScholarPubMed
Chen, C (2006) Guideline for Prevention and Control of Overweight and Obesity in Chinese Adults. Beijing: Peoples Medical Publishing House.Google Scholar
Alberti, KG & Zimmet, PZ (1998) Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabetic Med: J Br Diabetic Assoc 15, 539553.3.0.CO;2-S>CrossRefGoogle ScholarPubMed
Joint Committee for Guideline R (2018) 2016 Chinese guidelines for the management of dyslipidemia in adults. J Geriatr Cardiol 15, 129.Google Scholar
Coale, AJ & Banister, J (1994) Five decades of missing females in China. Demography 31, 459479.CrossRefGoogle ScholarPubMed
Koistinen, HA, Koivisto, VA, Karonen, SL, et al. (1998) Serum leptin and longevity. Aging 10, 449454.Google ScholarPubMed
Henrard, JC (1996) Cultural problems of ageing especially regarding gender and intergenerational equity. Soc Sci Med 43, 667680.CrossRefGoogle ScholarPubMed
Hessler, RM, Jia, S, Madsen, R, et al. (1995) Gender, social networks and survival time: a 20-year study of the rural elderly. Arch Gerontol Geriatr 21, 291306.CrossRefGoogle ScholarPubMed
Hamil-Luker, J & O’Rand, AM (2007) Gender differences in the link between childhood socioeconomic conditions and heart attack risk in adulthood. Demography 44, 137158.CrossRefGoogle ScholarPubMed
Portrait, F, Teeuwiszen, E & Deeg, D (2011) Early life undernutrition and chronic diseases at older ages: the effects of the Dutch famine on cardiovascular diseases and diabetes. Soc Sci Med 73, 711718.CrossRefGoogle ScholarPubMed
Sallout, B & Walker, M (2003) The fetal origin of adult diseases. J Obstet Gynaecol 23, 555560.CrossRefGoogle ScholarPubMed
Reynolds, RM (2013) Glucocorticoid excess and the developmental origins of disease: two decades of testing the hypothesis – 2012 Curt Richter Award Winner. Psychoneuroendocrinology 38, 111.CrossRefGoogle ScholarPubMed
Breton, C (2013) The hypothalamus-adipose axis is a key target of developmental programming by maternal nutritional manipulation. J Endocrinol 216, R19R31.CrossRefGoogle ScholarPubMed
Kongsted, AH, Husted, SV, Thygesen, MP, et al. (2013) Pre- and postnatal nutrition in sheep affects β-cell secretion and hypothalamic control. J Endocrinol 219, 159171.CrossRefGoogle ScholarPubMed
Huang, C, Guo, C, Nichols, C, et al. (2014) Elevated levels of protein in urine in adulthood after exposure to the Chinese famine of 1959–61 during gestation and the early postnatal period. Int J Epidemiol 43, 18061814.CrossRefGoogle Scholar
Lennox, WG & O’Connor, M (1925) A study of the retention of uric acid during fasting. J Biol Chem 66, 521572.CrossRefGoogle Scholar
Stelloh, C, Allen, KP, Mattson, DL, et al. (2012) Prematurity in mice leads to reduction in nephron number, hypertension, and proteinuria. Transl Res: J Lab Clin Med 159, 8089.CrossRefGoogle ScholarPubMed
Luyckx, VA & Brenner, BM (2010) The clinical importance of nephron mass. J Am Soc Nephrol: JASN 21, 898910.CrossRefGoogle ScholarPubMed
Justin Yifu, L & Yang, D (1995) Food Availability, Entitlement and the Chinese Famine of 1959–1961. USA: Duke University, Department of Economics.Google Scholar
Figure 0

Table 1. General characteristics of subjects in men and women(Numbers and percentages; mean values and standard deviations)

Figure 1

Table 2. Characteristics of subjects according to the Chinese famine exposure(Numbers and percentages; mean values and standard deviations)

Figure 2

Table 3. Associations of famine exposure in early life with hyperuricaemia in adulthood according to sex(Odds ratio and 95 % confidence intervals)

Figure 3

Table 4. Association of famine exposure with hyperuricaemia according to individual month income(Odds ratio and 95 % confidence intervals)