Please wait a minute...
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2024, Vol. 18 Issue (1) : 192-203    https://doi.org/10.1007/s11684-023-1023-9
Early-life famine exposure, adulthood obesity patterns, and risk of low-energy fracture
Hongyan Qi, Chunyan Hu, Jie Zhang, Lin Lin, Shuangyuan Wang, Hong Lin, Xiaojing Jia, Yuanyue Zhu, Yi Zhang, Xueyan Wu, Mian Li, Min Xu, Yu Xu, Tiange Wang, Zhiyun Zhao, Weiqing Wang, Yufang Bi, Meng Dai(), Yuhong Chen(), Jieli Lu()
Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the People’s Republic of China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
 Download: PDF(957 KB)   HTML
 Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

Malnutrition in early life increases the risk of osteoporosis, but the association of early-life undernutrition combined with adulthood obesity patterns with low-energy fracture remains unknown. This study included 5323 community-dwelling subjects aged ≥40 years from China. Early-life famine exposure was identified based on the participants’ birth dates. General obesity was assessed using the body mass index (BMI), and abdominal obesity was evaluated with the waist-to-hip ratio (WHR). Low-energy fracture was defined as fracture occurring after the age of 40 typically caused by falls from standing height or lower. Compared to the nonexposed group, the group with fetal, childhood, and adolescence famine exposure was associated with an increased risk of fracture in women with odds ratios (ORs) and 95% confidence intervals (CIs) of 3.55 (1.57–8.05), 3.90 (1.57–9.71), and 3.53 (1.05–11.88), respectively, but not in men. Significant interactions were observed between fetal famine exposure and general obesity with fracture among women (P for interaction = 0.0008). Furthermore, compared with the groups with normal BMI and WHR, the group of women who underwent fetal famine exposure and had both general and abdominal obesity had the highest risk of fracture (OR, 95% CI: 3.32, 1.17–9.40). These results indicate that early-life famine exposure interacts with adulthood general obesity and significantly increases the risk of low-energy fracture later in life in women.

Keywords famine      obesity      body mass index      waist-to-hip ratio      low-energy fracture     
Corresponding Author(s): Meng Dai,Yuhong Chen,Jieli Lu   
About author:

Li Liu and Yanqing Liu contributed equally to this work.

Just Accepted Date: 22 September 2023   Online First Date: 31 October 2023    Issue Date: 22 April 2024
 Cite this article:   
Hongyan Qi,Chunyan Hu,Jie Zhang, et al. Early-life famine exposure, adulthood obesity patterns, and risk of low-energy fracture[J]. Front. Med., 2024, 18(1): 192-203.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-023-1023-9
https://academic.hep.com.cn/fmd/EN/Y2024/V18/I1/192
Famine exposure
Nonexposed Fetal Childhood Adolescence
N (%) 730 (13.71) 735 (13.81) 2525 (47.44) 1333 (25.04)
Age (year) 48.91 ± 2.20 53.88 ± 1.25 60.74 ± 2.81 69.40 ± 2.37
Male (%) 258 (35.34) 251 (34.15) 855 (33.86) 530 (39.76)
Height (cm) 160.85 ± 7.41 159.45 ± 8.06 158.34 ± 7.81 157.01 ± 8.27
Weight (kg) 64.13 ± 11.57 63.41 ± 10.79 62.74 ± 10.47 61.97 ± 10.26
BMI (kg/m2) 24.73 ± 3.87 25.09 ± 6.92 25.08 ± 5.78 25.16 ± 4.35
Waist circumference (cm) 82.24 ± 10.62 82.37 ± 9.85 83.09 ± 10.05 84.95 ± 10.11
Hip circumference (cm) 94.19 ± 7.37 93.44 ± 7.50 93.67 ± 7.72 94.36 ± 8.00
WHR 0.87 ± 0.12 0.88 ± 0.12 0.89 ± 0.12 0.90 ± 0.09
Current smoker (%) 96 (13.15) 102 (13.88) 331 (13.11) 164 (12.30)
Current drinker (%) 69 (9.73) 68 (9.56) 225 (9.18) 95 (7.37)
High school and above (%) 165 (22.60) 310 (42.18) 405 (16.04) 221 (16.58)
Moderate and vigorous physical activity (%) 57 (7.81) 49 (6.67) 191 (7.56) 78 (5.85)
Tab.1  Characteristics of the study participants according to famine exposure
Famine exposure
Nonexposed Fetal Childhood Adolescence
Whole cohort
Case/Total 20/730 50/735 237/2525 136/1333
Model 1 1.00 (ref) 2.59 (1.53–4.40) 3.68 (2.31–5.85) 4.03 (2.50–6.51)
Model 2 1.00 (ref) 2.25 (1.25–4.03) 2.17 (1.10–4.30) 1.69 (0.65–4.42)
Model 3 1.00 (ref) 2.27 (1.27–4.08) 2.20 (1.11–4.36) 1.74 (0.67–4.57)
Men
Case/Total 11/258 16/251 60/855 32/530
Model 1 1.00 (ref) 1.53 (0.70–3.36) 1.70 (0.88–3.27) 1.44 (0.72–2.91)
Model 2 1.00 (ref) 1.46 (0.60–3.56) 0.88 (0.28 −2.78) 0.50 (0.09–2.82)
Model 3 1.00 (ref) 1.57 (0.64–3.84) 0.93 (0.29–2.98) 0.58 (0.10–3.34)
Women
Case/Total 9/472 34/484 177/1670 104/803
Model 1 1.00 (ref) 3.89 (1.84–8.19) 6.10 (3.10–12.01) 7.65 (3.83–15.27)
Model 2 1.00 (ref) 3.49 (1.54–7.91) 3.82 (1.54–9.51) 3.45 (1.03–11.58)
Model 3 1.00 (ref) 3.52 (1.56–7.97) 3.86 (1.55–9.62) 3.48 (1.04–11.69)
Model 4 1.00 (ref) 3.55 (1.57–8.05) 3.90 (1.57–9.71) 3.53 (1.05–11.88)
Tab.2  ORs (95% CIs) for low-energy fracture in relation to famine exposure in early life among the 5323 participants
Fig.1  Prevalence of low-energy fracture according to famine exposure and BMI or WHR. (A) Prevalence of fractures among different famine exposure groups stratified by BMI. (B) Prevalence of fractures among different famine exposure groups stratified by WHR.
Age-balanced group† Fetal exposure (1959–1962) Age-balanced group‡ Childhood-exposure (1949–1958)
Whole cohort
Case/Total 89/1699 50/735 202/2710 237/2525
Model 1 1.00 (ref) 1.32 (0.92–1.89) 1.00 (ref) 1.29 (1.06–1.57)
Model 2 1.00 (ref) 1.56 (1.07–2.27) 1.00 (ref) 1.31 (1.07–1.62)
Model 3 1.00 (ref) 1.55 (1.06–2.26) 1.00 (ref) 1.31 (1.06–1.61)
Men 31/589 16/251 58/1007 60/855
Model 1 1.00 (ref) 1.23 (0.66–2.28) 1.00 (ref) 1.24 (0.85–1.79)
Model 2 1.00 (ref) 1.54 (0.81–2.93) 1.00 (ref) 1.16 (0.79–1.70)
Model 3 1.00 (ref) 1.57 (0.82–3.01) 1.00 (ref) 1.11 (0.76–1.64)
Women 58/1110 34/484 144/1703 177/1670
Model 1 1.00 (ref) 1.37 (0.89–2.12) 1.00 (ref) 1.28 (1.02–1.62)
Model 2 1.00 (ref) 1.69 (1.05– 2.71) 1.00 (ref) 1.36 (1.06–1.75)
Model 3 1.00 (ref) 1.66 (1.03–2.67) 1.00 (ref) 1.37 (1.07–1.76)
Model 4 1.00 (ref) 1.66 (1.03–2.66) 1.00 (ref) 1.37 (1.07–1.76)
Tab.3  ORs (95% CIs) for low-energy fracture in relation to famine exposure compared with specific age-balanced controls
Age-balanced group† Fetal exposure (1959–1962) P for interaction Age-balanced group‡ Childhood exposure (1949–1958) P for interaction
BMI at baselinea, kg/m2
Whole cohort*
< 24.0 1.00 (ref) 0.77 (0.40–1.50) 0.0098 1.00 (ref) 1.71 (1.25–2.35) 0.033
24.0–27.9 0.82 (0.49–1.36) 1.75 (0.98–3.11) 1.12 (0.89–1.58) 1.25 (0.88–1.76)
≥ 28.0 1.22 (0.62–2.39) 3.06 (1.58–5.94) 1.30 (0.86–1.97) 1.33 (0.85–2.07)
Men**
< 24.0 1.00 (ref) 2.09 (0.70–6.25) 0.4838 1.00 (ref) 1.97 (1.03–3.75) 0.0696
24.0–27.9 1.36 (0.57–3.27) 1.91 (0.67–5.41) 1.30 (0.68–2.50) 1.15 (0.58–2.26)
≥ 28.0 1.01 (0.30–3.43) 1.07 (0.20–5.64) 0.92 (0.38–2.24) 1.15 (0.58–2.26)
Women***
< 24.0 1.00 (ref) 0.52 (0.21–1.28) 0.0008 1.00 (ref) 1.56 (1.08–2.26) 0.2802
24.0–27.9 0.56 (0.28–1.14) 1.80 (0.88–3.68) 0.98 (0.65–1.48) 1.24 (0.83–1.86)
≥ 28.0 1.37 (0.60–3.12) 4.49 (2.13–9.46) 1.36 (0.85–2.19) 1.60 (0.96–2.66)
WHR at baselineb
Whole cohort*
Men < 0.90, women < 0.85 1.00 (ref) 1.17 (0.63–2.15) 0.2845 1.00 (ref) 1.56 (1.11–2.19) 0.9097
Men 0.90–0.94, women 0.85–0.89 0.86 (0.51–1.47) 1.55 (0.85–2.81) 1.17 (0.81–1.70) 1.03 (0.70–1.52)
Men ≥ 0.95, women ≥ 0.90 0.61 (0.33–1.14) 1.19 (0.59–2.38) 1.03 (0.70–1.52) 1.60 (1.11–2.31)
Men**
< 0.90 1.00 (ref) 1.31 (0.43–3.934) 0.9155 1.00 (ref) 1.89 (0.97–3.66) 0.5556
0.90–0.94 1.38 (0.54–3.49) 3.13 (1.09–9.02) 2.83 (1.43–5.57) 1.71 (0.81–3.61)
≥ 0.95 1.41 (0.52–3.83) 1.64 (0.46–5.86) 1.95 (0.90–4.23) 2.90 (1.36–6.18)
Women ***
< 0.85 1.00 (ref) 1.14 (0.54–2.39) 0.1263 1.00 (ref) 1.36 (0.91–2.03) 0.5332
0.85–0.89 0.69 (0.36–1.32) 1.23 (0.59–2.55) 0.75 (0.48–1.19) 0.80 (0.51–1.26)
≥ 0.90 0.36 (0.16–0.82) 1.05 (0.45–2.46) 0.74 (0.47–1.17) 1.23 (0.81–1.87)
Tab.4  Multivariable-adjusted ORs (95% CIs) for the association between adult BMI or WHR and low-energy fracture in accordance with famine exposure in early life compared with specific age-balanced controls
Abdominal obesity i Overweight obesity ii Age-balanced group† Fetal exposure (1959–1962) P for interaction Age-balanced group‡ Childhood exposure (1949–1958) P for interaction
Whole cohort
No No 1.00 (ref) 1.00 (ref) 0.0468 1.00 (ref) 1.00 (ref) 0.0613
Yes 0.77 (0.36–1.64) 1.85 (0.66–5.18) 0.97 (0.56–1.68) 0.68 (0.42–1.11)
Yes No 0.89 (0.45–1.75) 0.56 (0.15–2.15) 0.85 (0.52–1.41) 0.83 (0.55–1.25)
Yes 0.82 (0.48–1.40) 2.26 (1.04–4.90) 1.14 (0.78–1.67) 0.69 (0.49–0.97)
Men
No No 1.00 (ref) 1.00 (ref) 0.9997 1.00 (ref) 1.00 (ref) 0.0321
Yes 1.94 (0.57–6.66) 0.51 (0.05–4.78) 0.87 (0.29–2.61) 0.54 (0.22–1.34)
Yes No 1.92 (0.49–7.55) 2.11 (0.34–13.23) 1.58 (0.56–4.49) 1.16 (0.51–2.64)
Yes 1.76 (0.62–5.03) 1.37 (0.40–4.67) 1.93 (0.93–3.97) 0.64 (0.34–1.22)
Women
No No 1.00 (ref) 1.00 (ref) 0.0136 1.00 (ref) 1.00 (ref) 0.6807
Yes 0.45 (0.15–1.36) 3.08 (0.83–11.43) 1.02 (0.54–1.95) 0.77 (0.47–1.38)
Yes No 0.64 (0.29–1.41) 0.28 (0.03–2.52) 0.64 (0.35–1.14) 0.74 (0.46–1.19)
Yes 0.57 (0.29–1.10) 3.32 (1.17–9.40) 0.82 (0.52–1.30) 0.69 (0.47–1.03)
Tab.5  Multivariable-adjusted ORs (95% CIs) for joint association of general and abdominal obesity with the risk of low-energy fracture in accordance with specific age-balanced controls and famine-exposed groups
1 P Chen, Z Li, Y Hu. Prevalence of osteoporosis in China: a meta-analysis and systematic review. BMC Public Health 2016; 16(1): 1039
https://doi.org/10.1186/s12889-016-3712-7
2 N Li, D Cornelissen, S Silverman, D Pinto, L Si, I Kremer, S Bours, R de Bot, A Boonen, S Evers, J van den Bergh, JY Reginster, M Hiligsmann. An updated systematic review of cost-effectiveness analyses of drugs for osteoporosis. Pharmacoeconomics 2021; 39(2): 181–209
https://doi.org/10.1007/s40273-020-00965-9
3 Y Zhang, H Qi, C Hu, S Wang, Y Zhu, H Lin, L Lin, J Zhang, T Wang, Z Zhao, M Li, Y Xu, M Xu, Y Bi, W Wang, Y Chen, J Lu, G Ning. Association between early life famine exposure and risk of metabolic syndrome in later life. J Diabetes 2022; 14(10): 685–694
https://doi.org/10.1111/1753-0407.13319
4 SR de Rooij, RC Painter, F Holleman, PM Bossuyt, TJ Roseboom. The metabolic syndrome in adults prenatally exposed to the Dutch famine. Am J Clin Nutr 2007; 86(4): 1219–1224
https://doi.org/10.1093/ajcn/86.4.1219
5 J Lu, M Li, Y Xu, Y Bi, Y Qin, Q Li, T Wang, R Hu, L Shi, Q Su, M Xu, Z Zhao, Y Chen, X Yu, L Yan, R Du, C Hu, G Qin, Q Wan, G Chen, M Dai, D Zhang, Z Gao, G Wang, F Shen, Z Luo, L Chen, Y Huo, Z Ye, X Tang, Y Zhang, C Liu, Y Wang, S Wu, T Yang, H Deng, D Li, S Lai, ZT Bloomgarden, L Chen, J Zhao, Y Mu, G Ning, W; 4C Study Group Wang. Early life famine exposure, ideal cardiovascular health metrics, and risk of incident diabetes: findings from the 4C Study. Diabetes Care 2020; 43(8): 1902–1909
https://doi.org/10.2337/dc19-2325
6 Y Li, Y He, L Qi, VW Jaddoe, EJ Feskens, X Yang, G Ma, FB Hu. Exposure to the Chinese famine in early life and the risk of hyperglycemia and type 2 diabetes in adulthood. Diabetes 2010; 59(10): 2400–2406
https://doi.org/10.2337/db10-0385
7 C Hu, R Du, L Lin, R Zheng, H Qi, Y Zhu, R Wei, X Wu, Y Zhang, M Li, T Wang, Z Zhao, M Xu, Y Xu, Y Bi, G Ning, W Wang, Y Chen, J Lu. The association between early-life famine exposure and adulthood obesity on the risk of dyslipidemia. Nutr Metab Cardiovasc Dis 2022; 32(9): 2177–2186
https://doi.org/10.1016/j.numecd.2022.06.005
8 H Qi, C Hu, S Wang, Y Zhang, R Du, J Zhang, L Lin, T Wang, Z Zhao, M Li, Y Xu, M Xu, Y Bi, W Wang, Y Chen, J Lu. Early life famine exposure, adulthood obesity patterns and the risk of nonalcoholic fatty liver disease. Liver Int 2020; 40(11): 2694–2705
https://doi.org/10.1111/liv.14572
9 LA Hughes, den Brandt PA van, Bruïne AP de, KA Wouters, S Hulsmans, A Spiertz, RA Goldbohm, Goeij AF de, JG Herman, MP Weijenberg, Engeland M van. Early life exposure to famine and colorectal cancer risk: a role for epigenetic mechanisms. PLoS One 2009; 4(11): e7951
https://doi.org/10.1371/journal.pone.0007951
10 C Cooper, K Javaid, S Westlake, N Harvey, E Dennison. Developmental origins of osteoporotic fracture: the role of maternal vitamin D insufficiency. J Nutr 2005; 135(11): 2728S–2734S
https://doi.org/10.1093/jn/135.11.2728S
11 CND Balasuriya, KAI Evensen, MP Mosti, AM Brubakk, GW Jacobsen, MS Indredavik, B Schei, AK Stunes, U Syversen. Peak bone mass and bone microarchitecture in adults born with low birth weight preterm or at term: a cohort study. J Clin Endocrinol Metab 2017; 102(7): 2491–2500
https://doi.org/10.1210/jc.2016-3827
12 TM Mikkola, MB von Bonsdorff, C Osmond, MK Salonen, E Kajantie, JG Eriksson. Association of body size at birth and childhood growth with hip fractures in older age: an exploratory follow-up of the Helsinki Birth Cohort Study. J Bone Miner Res 2017; 32(6): 1194–1200
https://doi.org/10.1002/jbmr.3100
13 LJ Zhao, YJ Liu, PY Liu, J Hamilton, RR Recker, HW Deng. Relationship of obesity with osteoporosis. J Clin Endocrinol Metab 2007; 92(5): 1640–1646
https://doi.org/10.1210/jc.2006-0572
14 TL Radak. Caloric restriction and calcium’s effect on bone metabolism and body composition in overweight and obese premenopausal women. Nutr Rev 2004; 62(12): 468–481
https://doi.org/10.1111/j.1753-4887.2004.tb00019.x
15 LJ Zhao, H Jiang, CJ Papasian, D Maulik, B Drees, J Hamilton, HW Deng. Correlation of obesity and osteoporosis: effect of fat mass on the determination of osteoporosis. J Bone Miner Res 2008; 23(1): 17–29
https://doi.org/10.1359/jbmr.070813
16 Z Shi, X Shi, AF Yan. Exposure to Chinese famine during early life increases the risk of fracture during adulthood. Nutrients 2022; 14(5): 1060
https://doi.org/10.3390/nu14051060
17 B Wang, M Li, Z Zhao, S Wang, J Lu, Y Chen, M Xu, W Wang, G Ning, Y Bi, T Wang, Y Xu. Glycemic measures and development and resolution of nonalcoholic fatty liver disease in nondiabetic individuals. J Clin Endocrinol Metab 2020; 105(5): 1416–1426
https://doi.org/10.1210/clinem/dgaa112
18 PH Lee, DJ Macfarlane, TH Lam, SM Stewart. Validity of the International Physical Activity Questionnaire Short Form (IPAQ-SF): a systematic review. Int J Behav Nutr Phys Act 2011; 8: 115
https://doi.org/10.1186/1479-5868-8-115
19 R Du, R Zheng, Y Xu, Y Zhu, X Yu, M Li, X Tang, R Hu, Q Su, T Wang, Z Zhao, M Xu, Y Chen, L Shi, Q Wan, G Chen, M Dai, D Zhang, Z Gao, G Wang, F Shen, Z Luo, Y Qin, L Chen, Y Huo, Q Li, Z Ye, Y Zhang, C Liu, Y Wang, S Wu, T Yang, H Deng, L Chen, J Zhao, Y Mu, D Li, G Qin, W Wang, G Ning, L Yan, Y Bi, J Lu. Early-life famine exposure and risk of cardiovascular diseases in later life: findings from the REACTION Study. J Am Heart Assoc 2020; 9(7): e014175
https://doi.org/10.1161/JAHA.119.014175
20 C Li, EW Tobi, BT Heijmans, LH Lumey. The effect of the Chinese famine on type 2 diabetes mellitus epidemics. Nat Rev Endocrinol 2019; 15(6): 313–314
https://doi.org/10.1038/s41574-019-0195-5
21 S Yang, ND Nguyen, JR Center, JA Eisman, TV Nguyen. Association between abdominal obesity and fracture risk: a prospective study. J Clin Endocrinol Metab 2013; 98(6): 2478–2483
https://doi.org/10.1210/jc.2012-2958
22 CM Nielson, P Srikanth, ES Orwoll. Obesity and fracture in men and women: an epidemiologic perspective. J Bone Miner Res 2012; 27(1): 1–10
https://doi.org/10.1002/jbmr.1486
23 R Meng, J Lv, C Yu, Y Guo, Z Bian, L Yang, Y Chen, H Zhang, X Chen, J Chen, Z Chen, L Qi, L; China Kadoorie Biobank Collaborative Group Li. Prenatal famine exposure, adulthood obesity patterns and risk of type 2 diabetes. Int J Epidemiol 2018; 47(2): 399–408
https://doi.org/10.1093/ije/dyx228
24 E Ito, Y Sato, T Kobayashi, S Nakamura, Y Kaneko, T Soma, T Matsumoto, A Kimura, K Miyamoto, H Matsumoto, M Matsumoto, M Nakamura, K Sato, T Miyamoto. Food restriction reduces cortical bone mass and serum insulin-like growth factor-1 levels and promotes uterine atrophy in mice. Biochem Biophys Res Commun 2021; 534: 165–171
https://doi.org/10.1016/j.bbrc.2020.11.122
25 R Pando, M Masarwi, B Shtaif, A Idelevich, E Monsonego-Ornan, R Shahar, M Phillip, G Gat-Yablonski. Bone quality is affected by food restriction and by nutrition-induced catch-up growth. J Endocrinol 2014; 223(3): 227–239
https://doi.org/10.1530/JOE-14-0486
26 CF Kin, WS Shan, LJ Shun, LP Chung, W Jean. Experience of famine and bone health in post-menopausal women. Int J Epidemiol 2007; 36(5): 1143–1150
https://doi.org/10.1093/ije/dym149
27 L Zong, L Cai, J Liang, W Lin, J Yao, H Huang, K Tang, L Chen, L Li, L Lin, H Chen, M Li, J Lu, Y Bi, W Wang, J Wen, G Chen. Exposure to famine in early life and the risk of osteoporosis in adulthood: a prospective study. Endocr Pract 2019; 25(4): 299–305
https://doi.org/10.4158/EP-2018-0419
28 G Mehta, HI Roach, S Langley-Evans, P Taylor, I Reading, RO Oreffo, A Aihie-Sayer, NM Clarke, C Cooper. Intrauterine exposure to a maternal low protein diet reduces adult bone mass and alters growth plate morphology in rats. Calcif Tissue Int 2002; 71(6): 493–498
https://doi.org/10.1007/s00223-001-2104-9
29 T Winzenberg, G Jones. Vitamin D and bone health in childhood and adolescence. Calcif Tissue Int 2013; 92(2): 140–150
https://doi.org/10.1007/s00223-012-9615-4
30 A Ganpule, CS Yajnik, CH Fall, S Rao, DJ Fisher, A Kanade, C Cooper, S Naik, N Joshi, H Lubree, V Deshpande, C Joglekar. Bone mass in Indian children—relationships to maternal nutritional status and diet during pregnancy: the Pune Maternal Nutrition Study. J Clin Endocrinol Metab 2006; 91(8): 2994–3001
https://doi.org/10.1210/jc.2005-2431
31 T Chevalley, R Rizzoli. Acquisition of peak bone mass. Best Pract Res Clin Endocrinol Metab 2022; 36(2): 101616
https://doi.org/10.1016/j.beem.2022.101616
32 WY Yao, L Li, HR Jiang, YF Yu, WH Xu. Transgenerational associations of parental famine exposure in early life with offspring risk of adult obesity in China. Obesity (Silver Spring) 2023; 31(1): 279–289
https://doi.org/10.1002/oby.23593
33 Y Zhang, Y Ying, L Zhou, J Fu, Y Shen, C Ke. Exposure to Chinese famine in early life modifies the association between hyperglycaemia and cardiovascular disease. Nutr Metab Cardiovasc Dis 2019; 29(11): 1230–1236
https://doi.org/10.1016/j.numecd.2019.07.004
34 EW Tobi, LH Lumey, RP Talens, D Kremer, H Putter, AD Stein, PE Slagboom, BT Heijmans. DNA methylation differences after exposure to prenatal famine are common and timing- and sex-specific. Hum Mol Genet 2009; 18(21): 4046–4053
https://doi.org/10.1093/hmg/ddp353
35 VS Tanwar, S Ghosh, S Sati, S Ghose, L Kaur, KA Kumar, KV Shamsudheen, A Patowary, M Singh, V Jyothi, P Kommineni, S Sivasubbu, V Scaria, M Raghunath, R Mishra, GR Chandak, S Sengupta. Maternal vitamin B12 deficiency in rats alters DNA methylation in metabolically important genes in their offspring. Mol Cell Biochem 2020; 468(1–2): 83–96
https://doi.org/10.1007/s11010-020-03713-x
36 Neel JV. Diabetes mellitus: a “thrifty” genotype rendered detrimental by “progress”? Am J Hum Genet 1962; 14(4): 353–362
pmid: 13937884
37 P Bateson, D Barker, T Clutton-Brock, D Deb, B D’Udine, RA Foley, P Gluckman, K Godfrey, T Kirkwood, MM Lahr, J McNamara, NB Metcalfe, P Monaghan, HG Spencer, SE Sultan. Developmental plasticity and human health. Nature 2004; 430(6998): 419–421
https://doi.org/10.1038/nature02725
38 J Delgado-Calle, AF Fernández, J Sainz, MT Zarrabeitia, C Sañudo, R García-Renedo, MI Pérez-Núñez, C García-Ibarbia, MF Fraga, JA Riancho. Genome-wide profiling of bone reveals differentially methylated regions in osteoporosis and osteoarthritis. Arthritis Rheum 2013; 65(1): 197–205
https://doi.org/10.1002/art.37753
39 N Slopen, A Non, DR Williams, AL Roberts, MA Albert. Childhood adversity, adult neighborhood context, and cumulative biological risk for chronic diseases in adulthood. Psychosom Med 2014; 76(7): 481–489
https://doi.org/10.1097/PSY.0000000000000081
40 GE Miller, E Chen, AK Fok, H Walker, A Lim, EF Nicholls, S Cole, MS Kobor. Low early-life social class leaves a biological residue manifested by decreased glucocorticoid and increased proinflammatory signaling. Proc Natl Acad Sci USA 2009; 106(34): 14716–14721
https://doi.org/10.1073/pnas.0902971106
41 M Das, O Cronin, DM Keohane, EM Cormac, H Nugent, M Nugent, C Molloy, PW O’Toole, F Shanahan, MG Molloy, IB Jeffery. Gut microbiota alterations associated with reduced bone mineral density in older adults. Rheumatology (Oxford) 2019; 58(12): 2295–2304
https://doi.org/10.1093/rheumatology/kez302
42 C Caffarelli, C Alessi, R Nuti, S Gonnelli. Divergent effects of obesity on fragility fractures. Clin Interv Aging 2014; 9: 1629–1636
43 Laet C De, JA Kanis, A Odén, H Johanson, O Johnell, P Delmas, JA Eisman, H Kroger, S Fujiwara, P Garnero, EV McCloskey, D Mellstrom, LJ 3rd Melton, PJ Meunier, HA Pols, J Reeve, A Silman, A Tenenhouse. Body mass index as a predictor of fracture risk: a meta-analysis. Osteoporos Int 2005; 16(11): 1330–1338
https://doi.org/10.1007/s00198-005-1863-y
44 HE Meyer, WC Willett, AJ Flint, D Feskanich. Abdominal obesity and hip fracture: results from the Nurses’ Health Study and the Health Professionals Follow-up Study. Osteoporos Int 2016; 27(6): 2127–2136
https://doi.org/10.1007/s00198-016-3508-8
45 M Kauppi, S Stenholm, O Impivaara, J Mäki, M Heliövaara, A Jula. Fall-related risk factors and heel quantitative ultrasound in the assessment of hip fracture risk: a 10-year follow-up of a nationally representative adult population sample. Osteoporos Int 2014; 25(6): 1685–1695
https://doi.org/10.1007/s00198-014-2674-9
46 V Benetou, P Orfanos, IS Benetos, V Pala, A Evangelista, G Frasca, MC Giurdanella, PH Peeters, IT van der Schouw, S Rohrmann, J Linseisen, H Boeing, C Weikert, U Pettersson, B Van Guelpen, HB Bueno de Mesquita, J Altzibar, P Boffetta, A Trichopoulou. Anthropometry, physical activity and hip fractures in the elderly. Injury 2011; 42(2): 188–193
https://doi.org/10.1016/j.injury.2010.08.022
47 V Zarulli, JA Barthold Jones, A Oksuzyan, R Lindahl-Jacobsen, K Christensen, JW Vaupel. Women live longer than men even during severe famines and epidemics. Proc Natl Acad Sci USA 2018; 115(4): E832–E840
https://doi.org/10.1073/pnas.1701535115
48 R Mu, X Zhang. Why does the great Chinese famine affect the male and female survivors differently? Mortality selection versus son preference. Econ Hum Biol 2011; 9(1): 92–105
https://doi.org/10.1016/j.ehb.2010.07.003
49 Y Wang, H Wan, C Chen, Y Chen, F Xia, B Han, Q Li, N Wang, Y Lu. Association between famine exposure in early life with insulin resistance and beta cell dysfunction in adulthood. Nutr Diabetes 2020; 10(1): 18
https://doi.org/10.1038/s41387-020-0121-x
[1] FMD-23042-OF-LJL_suppl_1 Download
[1] Fang Wang, Yuxing Liu, Yi Dong, Meifang Zhao, Hao Huang, Jieyuan Jin, Liangliang Fan, Rong Xiang. Haploinsufficiency of Lipin3 leads to hypertriglyceridemia and obesity by disrupting the expression and nucleocytoplasmic localization of Lipin1[J]. Front. Med., 2024, 18(1): 180-191.
[2] Yalin Liu, Xianghang Luo. New practice in semaglutide on type-2 diabetes and obesity: clinical evidence and expectation[J]. Front. Med., 2022, 16(1): 17-24.
[3] Lingli Cai, Jun Yin, Xiaojing Ma, Yifei Mo, Cheng Li, Wei Lu, Yuqian Bao, Jian Zhou, Weiping Jia. Low-carbohydrate diets lead to greater weight loss and better glucose homeostasis than exercise: a randomized clinical trial[J]. Front. Med., 2021, 15(3): 460-471.
[4] So Jung Yang, Hun-Sung Kim, Kun-Ho Yoon. Analyzing the distinguishing factors that affect childhood obesity in South Korea[J]. Front. Med., 2018, 12(6): 707-716.
[5] Tiange Wang, Min Xu, Yufang Bi, Guang Ning. Interplay between diet and genetic susceptibility in obesity and related traits[J]. Front. Med., 2018, 12(6): 601-607.
[6] Ruiting Han, Junli Ma, Houkai Li. Mechanistic and therapeutic advances in non-alcoholic fatty liver disease by targeting the gut microbiota[J]. Front. Med., 2018, 12(6): 645-657.
[7] Eun Young Lee, Kun-Ho Yoon. Epidemic obesity in children and adolescents: risk factors and prevention[J]. Front. Med., 2018, 12(6): 658-666.
[8] Meng Dong, Jun Lin, Wonchung Lim, Wanzhu Jin, Hyuek Jong Lee. Role of brown adipose tissue in metabolic syndrome, aging, and cancer cachexia[J]. Front. Med., 2018, 12(2): 130-138.
[9] Tianhua Xu, Zitong Sheng, Li Yao. Obesity-related glomerulopathy: pathogenesis, pathologic, clinical characteristics and treatment[J]. Front. Med., 2017, 11(3): 340-348.
[10] Rahim Ullah, Yan Su, Yi Shen, Chunlu Li, Xiaoqin Xu, Jianwei Zhang, Ke Huang, Naveed Rauf, Yang He, Jingjing Cheng, Huaping Qin, Yu-Dong Zhou, Junfen Fu. Postnatal feeding with high-fat diet induces obesity and precocious puberty in C57BL/6J mouse pups: a novel model of obesity and puberty[J]. Front. Med., 2017, 11(2): 266-276.
[11] Lixia Gan,Wei Xiang,Bin Xie,Liqing Yu. Molecular mechanisms of fatty liver in obesity[J]. Front. Med., 2015, 9(3): 275-287.
[12] Tao Wang,Weiping Jia,Cheng Hu. Advancement in genetic variants conferring obesity susceptibility from genome-wide association studies[J]. Front. Med., 2015, 9(2): 146-161.
[13] Jianping Ye. Beneficial metabolic activities of inflammatory cytokine interleukin 15 in obesity and type 2 diabetes[J]. Front. Med., 2015, 9(2): 139-145.
[14] Shuwen Qian,Haiyan Huang,Qiqun Tang. Brown and beige fat: the metabolic function, induction, and therapeutic potential[J]. Front. Med., 2015, 9(2): 162-172.
[15] Jichun Yang, Jihong Kang, Youfei Guan. The mechanisms linking adiposopathy to type 2 diabetes[J]. Front Med, 2013, 7(4): 433-444.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed