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Cardiovascular Therapy and Prevention

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From life history theory to clinical practice: potential markers of fast life strategy

https://doi.org/10.15829/1728-8800-2024-4198

EDN: TKQNOF

Abstract

Currently, there is increasing evidence that early human development mediates the risk of early cardiometabolic diseases and their risk factors in adulthood. This publication considers potential markers of the so-called fast life strategy — a life cycle characterized by a high disease risk, as well as the conditions leading to the formation of such a strategy. In the future, they may allow stratifying groups at high risk of premature death from cardiovascular and metabolic diseases in routine clinical practice and conducting their early prevention.

About the Authors

O. T. Kim
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



O. M. Drapkina
National Medical Research Center for Therapy and Preventive Medicine
Russian Federation

Moscow



References

1. Sokolova LA, Gorlova IA, Omelchenko MYu, et al. Development of the concept of cardiovascular risk factors from the perspective of translational medicine. Translational Medicine. 2023;10(3):173-82. (In Russ.) doi:10.18705/2311-4495-2023-10-3-173-182.

2. Lurbe E, Ingelfinger J. Developmental and Early Life Origins of Cardiometabolic Risk Factors: Novel Findings and Implications. Hypertension. 2021;77(2):308-18. doi:10.1161/HYPERTENSIONAHA.120.14592.

3. Kavanagh PS, Kahl BL. Life History Theory. In: Weekes-Shackelford V, Shackelford T, Weekes-Shackelford V. (eds) Encyclopedia of Evolutionary Psychological Science. Springer, Cham. doi:10.1007/978-3-319-16999-6_1914-1. ISBN: 978-3-319-16999-6.

4. Gutiérrez F, Peri JM, Baillès E, et al. A Double-Track Pathway to Fast Strategy in Humans and Its Personality Correlates. Front Psychol. 2022;13:889730. doi:10.3389/fpsyg.2022.889730.

5. Csathó Á, Birkás B. Early-Life Stressors, Personality Development, and Fast Life Strategies: An Evolutionary Perspective on Malevolent Personality Features. Front Psychol. 2018;9:305. doi:10.3389/fpsyg.2018.00305.

6. Flatt T, Andreas H. Mechanisms of Life History Evolution: The Genetics and Physiology of Life History Traits and TradeOffs. Oxford University Press. 2013. doi:10.1093/acprof:oso/9780199568765.001.0001. ISBN: 9780191774591.

7. Fatihoglu E, Aydin S. Diagnosing Small for Gestational Age during second trimester routine screening: Early sonographic clues. Taiwan J Obstet Gynecol. 2020;59(2):287-292. doi:10.1016/j.tjog.2020.01.019.

8. Shangareeva RKh, Bryukhanova OA, Fatykhova AI, et al. Risk factors for preterm labor. Immediate outcomes in very low and extremely low birth weight babies. Russian Journal of Preventive Medicine. 2019;22(6):70-9. (In Russ.) doi:10.17116//profmed20192206170.

9. Zhelezova ME, Zephirova TP, Kanyukov SS. Fetal growth retardation: modern approaches to the diagnosis and management of pregnancy. Practical medicine. 2019;17(4):8-14. (In Russ.) doi:10.32000/2072-1757-2019-4-8-14.

10. Lawn JE, Ohuma EO, Bradley E, et al. Small babies, big risks: global estimates of prevalence and mortality for vulnerable newborns to accelerate change and improve counting. Lancet. 2023;401(10389):1707-19. doi:10.1016/S0140-6736(23)00522-6.

11. Mericq V, Martinez-Aguayo A, Uauy R, et al. Long-term metabolic risk among children born premature or small for gestational age. Nat Rev Endocrinol. 2017;13(1):50-62. doi:10.1038/nrendo.2016.127.

12. Wells JC, Yao P, Williams JE, et al. Maternal investment, lifehistory strategy of the offspring and adult chronic disease risk in South Asian women in the UK. Evol Med Public Health. 2016;2016(1):133-45. doi:10.1093/emph/eow011.

13. Rotar O, Moguchaia E, Boyarinova M, et al. Seventy years after the siege of Leningrad: does early life famine still affect cardiovascular risk and aging? J Hypertens. 2015;33(9):1772-9. doi:10.1097/HJH.0000000000000640.

14. Moguchaia EV, Rotar OP, Boyarinova MA, et al. Long-term cardiovascular damage in Leningrad Siege survivors. "Arterial’naya Gipertenziya" ("Arterial Hypertension"). 2021;27(2):170-9. (In Russ.) doi:10.18705/1607-419X-2021-27-2-170-179.

15. Belbasis L, Savvidou MD, Kanu C, et al. Birth weight in relation to health and disease in later life: an umbrella review of systematic reviews and meta-analyses. BMC Med. 2016;14(1):147. doi:10.1186/s12916-016-0692-5.

16. Dalle Molle R, Bischoff AR, Portella AK, Silveira PP. The fetal programming of food preferences: current clinical and experimental evidence. J Dev Orig Health Dis. 2016;7(3):222-30. doi:10.1017/S2040174415007187.

17. Quinn EB, Hsiao CJ, Maisha FM, Mulligan CJ. Low birthweight is associated with epigenetic age acceleration in the first 3 years of life. Evol Med Public Health. 2023;11(1):251-61. doi:10.1093/emph/eoad019.

18. Bolund E. The challenge of measuring trade-offs in human life history research. Evol Hum Behav. 2020;41(6):502-12. doi:10.1016/j.evolhumbehav.2020.09.003.

19. Campisi SC, Carbone SE, Zlotkin S. Catch-Up Growth in Full-Term Small for Gestational Age Infants: A Systematic Review. Adv Nutr. 2019;10(1):104-11. doi:10.1093/advances/nmy091.

20. Silva CCV, El Marroun H, Sammallahti S, et al. Patterns of Fetal and Infant Growth and Brain Morphology at Age 10 Years. JAMA Netw Open. 2021;4(12):e2138214. doi:10.1001/jamanetworkopen.2021.38214.

21. Kiosov AF. Questions of evaluation of postnatal growth in preterm children Part 2. Catch-up growth in preterm infants. Current Pediatrics. 2014;13(1):109-12. (In Russ.) doi:10.15690/vsp.v13i1.919.

22. Chen Y, Wang Y, Chen Z, et al. The effects of rapid growth on body mass index and percent body fat: A meta-analysis. Clin Nutr. 2020;39(11):3262-72. doi:10.1016/j.clnu.2020.02.030.

23. Vogelezang S, Santos S, Toemen L, et al. Associations of Fetal and Infant Weight Change With General, Visceral, and Organ Adiposity at School Age. JAMA Netw Open. 2019;2(4):e192843. doi:10.1001/jamanetworkopen.2019.284.3.

24. Chumakova GA, Kuznetsova TYu, Druzhilov MA, et al. Visceral adiposity as a global factor of cardiovascular risk. Russian Journal of Cardiology. 2018;(5):7-14. (In Russ.) doi:10.15829/1560-4071-2018-5-7-14.

25. Hector KL, Nakagawa S. Quantitative analysis of compensatory and catch-up growth in diverse taxa. J Anim Ecol. 2012;81(3): 583-93. doi:10.1111/j.1365-2656.2011.01942.x.

26. Myrie SB, McKnight LL, King JC, et al. Intrauterine growthrestricted Yucatan miniature pigs experience early catchup growth, leading to greater adiposity and impaired lipid metabolism as young adults. Appl Physiol Nutr Metab. 2017;42(12):1322-9. doi:10.1139/apnm-2017-0311.

27. Yuan R, Hascup E, Hascup K, Bartke A. Relationships among Development, Growth, Body Size, Reproduction, Aging, and Longevity — Trade-Offs and Pace-Of-Life. Biochemistry (Mosc). 2023;88(11):1692-703. doi:10.1134/S0006297923110020.

28. Mól N, Zasada M, Kwinta P. Does type of feeding affect body composition in very low birth weight infants? — A prospective cohort study. Pediatr Neonatol. 2019;60(2):135-40. doi:10.1016/j.pedneo.2018.04.010.

29. Dadaeva VA, Aleksandrov AA, Orlova AS, et al. The role of breastfeeding in the prevention of overweight and obesity in children and adolescents. Russian Journal of Preventive Medicine. 2019;22(5):125-30. (In Russ.) doi:10.17116/profmed201922051125.

30. Wang X, Yan M, Zhang Y, et al. Breastfeeding in infancy and mortality in middle and late adulthood: A prospective cohort study and meta-analysis. J Intern Med. 2023;293(5):624-35. doi:10.1111/joim.13619.

31. Lin D, Chen D, Huang J, et al. Pre-Birth and Early-Life Factors Associated With the Timing of Adiposity Peak and Rebound: A Large Population-Based Longitudinal Study. Front Pediatr. 2021;9:742551. doi:10.3389/fped.2021.742551.

32. Péneau S, Giudici KV, Gusto G, et al. Growth Trajectories of Body Mass Index during Childhood: Associated Factors and Health Outcome at Adulthood. J Pediatr. 2017;186:64-71.e1. doi:10.1016/j.jpeds.2017.02.010.

33. Gritsinskaya VL. Early adiposity rebound as a predictor of adolescent obesity. Vopr. det. dietol. (Pediatric Nutrition). 2017;15(3):20-3. (In Russ). doi:10.20953/17275784-2017-3-20-23.

34. Zhou J, Zhang F, Qin X, et al. Age at adiposity rebound and the relevance for obesity: a systematic review and meta-analysis. Int J Obes (Lond). 2022;46(8):1413-24. doi:10.1038/s41366-02201120-4.

35. Martino F, Bassareo PP, Martino E, et al. Cardiovascular prevention in childhood: a consensus document of the Italian Society of Cardiology Working Group on Congenital Heart Disease and Cardiovascular Prevention in Paediatric Age. J Cardiovasc Med (Hagerstown). 2023;24(8):492-505. doi:10.2459/JCM.0000000000001488.

36. Plachta-Danielzik S, Bosy-Westphal A, Kehden B, et al. Adiposity rebound is misclassified by BMI rebound. Eur J Clin Nutr. 2013;67(9):984-9. doi:10.1038/ejcn.2013.131.

37. Marakaki C, Karapanou O, Gryparis A, et al. Early Adiposity Rebound and Premature Adrenarche. J Pediatr. 2017;186:72-7. doi:10.1016/j.jpeds.2017.03.058.

38. Williams SM, Goulding A. Patterns of growth associated with the timing of adiposity rebound. Obesity (Silver Spring). 2009;17(2):335-41. doi:10.1038/oby.2008.547.

39. Cissé AH, Lioret S, de Lauzon-Guillain B, et al. Association between perinatal factors, genetic susceptibility to obesity and age at adiposity rebound in children of the EDEN mother–child cohort. Int J Obes. 2021;45:1802-10. doi:10.1038/s41366-02100847-w.

40. Baldassarre ME, Di Mauro A, Caroli M, et al. Premature Birth is an Independent Risk Factor for Early Adiposity Rebound: Longitudinal Analysis of BMI Data from Birth to 7 Years. Nutrients. 2020;12(12):3654. doi:10.3390/nu12123654.

41. Camier A, Cissé AH, Lioret S, et al. Infant feeding practices associated with adiposity peak and rebound in the EDEN motherchild cohort. Int J Obes (Lond). 2022;46(4):809-16. doi:10.1038/s41366-021-01059-y.

42. Cerasani J, Consales A, Gangi S, et al. Exclusive human milk feeding and prevalence of early adiposity rebound in ELBW infants: a retrospective cohort study. Eur J Pediatr. 2024; 183(3):1295-303. doi:10.1007/s00431-023-05374-6.

43. Goh EK, Kim OY, Yoon SR, et al. Timing of Adiposity Rebound and Determinants of Early Adiposity Rebound in Korean Infants and Children Based on Data from the National Health Insurance Service. Nutrients. 2022;14(5):929. doi:10.3390/nu14050929.

44. Hõrak P, Valge M, Fischer K, et al. Parents of early-maturing girls die younger. Evol Appl. 2019;12(5):1050-61. doi:10.1111/eva.12780.

45. Zhou X, Hu Y, Yang Z, et al. Overweight/Obesity in Childhood and the Risk of Early Puberty: A Systematic Review and MetaAnalysis. Front Pediatr. 2022;10:795596. doi:10.3389/fped.2022.795596.

46. Song Y, Kong Y, Xie X, et al. Association between precocious puberty and obesity risk in children: a systematic review and meta-analysis. Front Pediatr. 2023;11:1226933. doi:10.3389/fped.2023.1226933.

47. Shi L, Jiang Z, Zhang L. Childhood obesity and central precocious puberty. Front Endocrinol (Lausanne). 2022;13:1056871. doi:10.3389/fendo.2022.1056871.

48. Charalampopoulos D, McLoughlin A, Elks CE, Ong KK. Age at menarche and risks of all-cause and cardiovascular death: a systematic review and meta-analysis. Am J Epidemiol. 2014;180(1):29-40. doi:10.1093/aje/kwu113.

49. Chen X, Liu Y, Sun X, et al. Age at menarche and risk of allcause and cardiovascular mortality: a systematic review and dose-response meta-analysis. Menopause. 2018;26(6):670-6. doi:10.1097/GME.0000000000001289.

50. Behboudi-Gandevan S, Moe CF, Skjesol I, et al. The J shaped association of age at menarche and cardiovascular events: systematic review and meta-analysis. Sci Rep. 2024;14(1):2695. doi:10.1038/s41598-024-53011-5.

51. Day FR, Elks CE, Murray A, et al. Puberty timing associated with diabetes, cardiovascular disease and also diverse health outcomes in men and women: the UK Biobank study. Sci Rep. 2015;5:11208. doi:10.1038/srep11208.

52. Eckert-Lind C, Busch AS, Petersen JH, et al. Worldwide Secular Trends in Age at Pubertal Onset Assessed by Breast Development Among Girls: A Systematic Review and Metaanalysis. JAMA Pediatr. 2020;174(4):e195881. doi:10.1001/jamapediatrics.2019.5881.

53. Hemmingsson E, Johansson K, Reynisdottir S. Effects of childhood abuse on adult obesity: a systematic review and metaanalysis. Obes Rev. 2014;15(11):882-93. doi:10.1111/obr.12216.

54. Wiss DA, Brewerton TD. Adverse Childhood Experiences and Adult Obesity: A Systematic Review of Plausible Mechanisms and Meta-Analysis of Cross-Sectional Studies. Physiol Behav. 2020;223:112964. doi:10.1016/j.physbeh.2020.112964.

55. Street ME, Ponzi D, Renati R, et al. Precocious puberty under stressful conditions: new understanding and insights from the lessons learnt from international adoptions and the COVID-19 pandemic. Front Endocrinol (Lausanne). 2023;14:1149417. doi:10.3389/fendo.2023.1149417.

56. Goggi G, Moro M, Chilà A, et al. COVID-19 lockdown and the rate of central precocious puberty. J Endocrinol Invest. 2024;47(2):315-23. doi:10.1007/s40618-023-02146-9.

57. Holmgren A, Martos-Moreno GÁ, Niklasson A, et al. The pubertal growth spurt is diminished in children with severe obesity. Pediatr Res. 2021;90(1):184-90. doi:10.1038/s41390-020-01234-3.

58. Rogozhkina EA Dzhioeva ON, Angarsky RK, et al. Comparative assessment of echocardiographic parameters in persons without diagnosed chronic non-communicable diseases depending on body mass index. The Siberian Journal of Clinical and Experimental Medicine. 2023;38(3):153-62. (In Russ.) doi:10.29001/2073-8552-2023-39-3-153-162.

59. Zhang L, Zhang D, Sun Y. Adverse Childhood Experiences and Early Pubertal Timing Among Girls: A Meta-Analysis. Int J Environ Res Public Health. 2019;16(16):2887. doi:10.3390/ijerph16162887.

60. Colich NL, Rosen ML, Williams ES, et al. Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis. Psychol Bull. 2020;146(9):721-64. doi:10.1037/bul0000270.

61. Binder AM, Corvalan C, Mericq V, et al. Faster ticking rate of the epigenetic clock is associated with faster pubertal development in girls. Epigenetics. 2018;13(1):85-94. doi:10.1080/15592294.2017.1414127.

62. Hollis B, Day FR, Busch AS, et al. Genomic analysis of male puberty timing highlights shared genetic basis with hair colour and lifespan. Nat Commun. 2020;11(1):1536. doi:10.1038/s41467-020-14451-5.

63. Jáni M, Zacková L, Piler P, et al. Birth outcomes, puberty onset, and obesity as long-term predictors of biological aging in young adulthood. Front Nutr. 2023;9:1100237. doi:10.3389/fnut.2022.1100237.

64. Ibitoye M, Sandfort TGM, Bingenheimer JB, Sommer M. The sexual and reproductive health covariates of early menarche among adolescent girls. J Adolesc. 2024;96(4):789-802. doi:10.1002/jad.12298.

65. Zholondziovskaya OE, Putilova NV, Shakirov RT, et al. Pregnancy and childbirth in young women: risk factors and course features. Russian Bulletin of Obstetrician-Gynecologist. 2021;21(5): 84-9. (In Russ.) doi:10.17116/rosakush20212105184.

66. Ray JG, Fu L, Austin PC, et al. Teen Pregnancy and Risk of Premature Mortality. JAMA Netw Open. 2024;7(3):e241833. doi:10.1001/jamanetworkopen.2024.1833.

67. Woo D, Jae S, Park S. U-shaped association between age at first childbirth and mortality: A prospective cohort study. Maturitas. 2022;161:33-9. doi:10.1016/j.maturitas.2022.01.015.

68. Zeng Y, Ni ZM, Liu SY, et al. Parity and All-cause Mortality in Women and Men: A Dose-Response Meta-Analysis of Cohort Studies. Sci Rep. 2016;6:19351. doi:10.1038/srep19351.

69. Shirazi TN, Hastings WJ, Rosinger AY, Ryan CP. Parity predicts biological age acceleration in post-menopausal, but not premenopausal, women. Sci Rep. 2020;10(1):20522. doi:10.1038/s41598-020-77082-2.

70. Bauserman M, Nowak K, Nolen TL, et al. The relationship between birth intervals and adverse maternal and neonatal outcomes in six low and lower-middle income countries. Reprod Health. 2020;17(Suppl 2):157. doi:10.1186/s12978-020-01008-4.

71. Huan L, Deng X, He M, et al. Meta-analysis: Early Age at Natural Menopause and Risk for All-Cause and Cardiovascular Mortality. Biomed Res Int. 2021;2021:6636856. doi:10.1155/2021/6636856.

72. Goldberg M, Tawfik H, Kline J, et al. Body size at birth, early-life growth and the timing of the menopausal transition and natural menopause. Reprod Toxicol. 2020;92:91-7. doi:10.1016/j.reprotox.2019.02.013.

73. Peycheva D, Sullivan A, Hardy R, et al. Risk factors for natural menopause before the age of 45: evidence from two British population-based birth cohort studies. BMC Womens Health. 2022;22(1):438. doi:10.1186/s12905-022-02021-4.

74. Mishra GD, Pandeya N, Dobson AJ, et al. Early menarche, nulliparity and the risk for premature and early natural menopause. Hum Reprod. 2017;32(3):679-86. doi:10.1093/humrep/dew350.

75. Jiang C, Gao T, Wang Y, et al. Birth weight and premature ovarian insufficiency: a systematic review and meta-analysis. J Ovarian Res. 2024;17(1):74. doi:10.1186/s13048-024-01357-9.

76. Langton CR, Whitcomb BW, Purdue-Smithe AC, et al. Association of Parity and Breastfeeding With Risk of Early Natural Menopause. JAMA Netw Open. 2020;3(1):e1919615. doi:10.1001/jamanetworkopen.2019.19615.

77. Kuzawa CW, Chugani HT, Grossman LI, et al. Metabolic costs and evolutionary implications of human brain development. Proc Natl Acad Sci U S A. 2014;111(36):13010-15. doi:10.1073/pnas.1323099111.

78. Aronoff JE, Ragin A, Wu C, et al. Why do humans undergo an adiposity rebound? Exploring links with the energetic costs of brain development in childhood using MRI-based 4D measures of total cerebral blood flow. Int J Obes (Lond). 2022;46(5):1044-50. doi:10.1038/s41366-022-01065-8.

79. Gurholt TP, Kaufmann T, Frei O, et al. Population-based bodybrain mapping links brain morphology with anthropometrics and body composition. Transl Psychiatry. 2021;11(1):295. doi:10.1038/s41398-021-01414-7.

80. Solis-Urra P, Esteban-Cornejo I, Cadenas-Sanchez C, et al. Early life factors, gray matter brain volume and academic performance in overweight/obese children: The ActiveBrains project. Neuroimage. 2019;202:116130. doi:10.1016/j.neuroimage.2019.116130.

81. Núñez C, García-Alix A, Arca G, et al. Breastfeeding duration is associated with larger cortical gray matter volumes in children from the ABCD study. J Child Psychol Psychiatry. 2023;64(7): 1067-79. doi:10.1111/jcpp.13790.

82. Bick J, Nelson CA. Early Adverse Experiences and the Developing Brain. Neuropsychopharmacology. 2016;41(1):177-96. doi:10.1038/npp.2015.252.

83. Chan SY, Ngoh, ZM, Ong, ZY, et al. The influence of early-life adversity on the coupling of structural and functional brain connectivity across childhood. Nat Mental Health. 2024;(2):52-62. doi:10.1038/s44220-023-00162-5.

84. Duffy KA, McLaughlin KA, Green PA. Early life adversity and healthrisk behaviors: proposed psychological and neural mechanisms. Ann N Y Acad Sci. 2018;1428(1):151-69. doi:10.1111/nyas.13928.


Supplementary files

What is already known about the subject?

  • The human life history strategy is shaped by a number of external and internal factors. A pre­dictable and resource-rich environment shapes a slow strategy, characterized by a long period of growth and development, better health, and a lon­ger life expectancy. A harsh and unpredictable envi­ron­ment shapes a fast life strategy with a short pe­riod of growth and development, worse health, and a shorter life expectancy.

What might this study add?

  • A large body of evidence suggests that low birth weight, catch-up growth, early adipocyte rebound, pre­cocious puberty, and early menopause are mar­kers of increased risk of cardiometabolic diseases in adulthood.
  • These markers may indicate a fast life strategy, which prioritizes early reproduction at the expen­se of maximizing growth, development, and main­tenance.
  • Characteristics of a fast life strategy can be used as prognostic markers in clinical practice for stra­tification of risk groups for early onset of cardio­metabolic diseases and implementation of timely preventive measures.

Review

For citations:


Kim O.T., Drapkina O.M. From life history theory to clinical practice: potential markers of fast life strategy. Cardiovascular Therapy and Prevention. 2024;23(12):4198. (In Russ.) https://doi.org/10.15829/1728-8800-2024-4198. EDN: TKQNOF

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ISSN 2619-0125 (Online)