基于出生队列研究2岁内婴幼儿认知发育轨迹与青少年多维度健康结局的关联

Association between cognitive development trajectories within the first two years of life and multidimensional health outcomes in adolescence: evidence from a birth cohort study

摘要

目的 探究陕西农村地区婴幼儿期认知发育水平及认知发育轨迹与青春早期多维度健康结局之间的关联,为制定促进青少年全面健康成长的生命早期干预措施和政策提供科学依据。方法 研究对象来自在陕西农村地区开展的一项出生队列研究,采用贝利婴幼儿量表第二版评价婴幼儿期3、6、12、18、24月龄的智力发育,并采用亚组轨迹模型分析婴幼儿期的智力发育轨迹。采用2种方法评价青少年多维健康结局:一是基于身体质量指数(BMI)、血压、肺活量、智力、行为问题构建的健康综合得分；二是利用潜在剖面分析确定的3种健康模式,分别命名为代谢问题高风险组、行为问题高风险组、健康问题低风险组。在调整多个混杂因素或协变量后,采用广义估计方程、多元Logistic回归模型分别分析婴幼儿期各关键年龄点认知发育水平及整个婴幼儿期的认知发育轨迹与青春早期健康综合得分、健康模式之间的关联大小。结果 共纳入602例10～14岁青少年,其中男孩占比61.1%；青少年健康综合得分均值为(34.68±4.60)分。在控制相关协变量后,发现在12、18、24月龄时认知得分越高的婴幼儿在青春早期健康综合得分也越高(12月龄: β=0.16,95% CI:0.01～0.30；18月龄: β=0.33,95% CI:0.08～0.58；24月龄:β=0.25,95% CI:0.07～0.43)。针对认知发育轨迹的分析发现,与婴幼儿期智力发育始终处于平均水平的个体相比,认知发育始终高于平均水平的婴幼儿在青春期发生行为问题的风险降低49%(OR=0.51,95% CI:0.27～0.99)。结论 婴幼儿时期的认知发育水平越高,青春早期的综合健康水平也越高,且发生行为问题的风险也越低。关注和促进生命早期的认知发育,有利于青少年综合健康水平的发展,对实现全生命周期健康和降低成人慢性病疾病负担具有重要的公共卫生意义。

Abstract

Objective To examine the association between cognitive development levels and developmental trajectories within the first two years of life and multidimensional health outcomes in early adolescence in rural areas of Shaanxi Province, China. The findings are intended to provide scientific evidence for the formulation of early childhood intervention policies targeting at the promotion of adolescent comprehensive health. Methods The study population was drawn from a birth cohort established in rural Shaanxi. Infant cognitive development was assessed at 3, 6, 12, 18, and 24 months of age using the Bayley Scales of Infant Development, Second Edition. Group-based trajectory modeling was employed to identify distinct cognitive development trajectories. Adolescent multidimensional health outcomes were evaluated using two approaches: (1) A composite health score had been established based on physical indicators (height, weight, BMI), blood pressure, cognitive performance, sleep, and behavioral problems; and (2) latent profile analysis was used to classify adolescents into three types of health profiles: high metabolic risk, high behavioral risk, and low overall health risk. After adjusting for multiple covariates, generalized estimating equations and multivariable Logistic regression models were used to examine the association between cognitive development and cognitive trajectories during the first two years of life with adolescent health scores and profile membership. Results A total of 602 adolescents aged 10-14 years were included, with boys accounting for 61.1%. The average composite health score was 34.68 (SD=4.60). After controlling for relevant covariates, higher cognitive scores at 12, 18, and 24 months were significantly associated with higher composite health scores in early adolescence (12 months: β=0.16, 95% CI: 0.01-0.30; 18 months: β=0.33, 95% CI: 0.08-0.58; 24 months: β=0.25, 95% CI: 0.07-0.43). Regarding the cognitive development trajectories, compared with children whose cognitive development remained at an average level during infancy, those with cognitive development consistently above average had a lower risk of behavioral problems in adolescence (OR=0.51, 95% CI: 0.27-0.99). Conclusion Higher cognitive development levels in infancy are associated with better overall health and a lower risk of behavioral problems in early adolescence. These findings highlight the importance of promoting cognitive development during the first two years of life, which may contribute to improved adolescent health outcomes and consequently have significant public health implications for lifelong health and the prevention of chronic diseases in adulthood.

关键词

出生队列 / 婴幼儿认知 / 发育轨迹 / 青少年 / 多维度健康结局

Key words

birth cohort / infant cognition / developmental trajectory / adolescent / multidimensional health outcome

参考文献

[1] BLACK M M, WALKER P S P, FERNALD L C H, et al. Early childhood development coming of age: science through the life course[J]. Lancet, 2017, 389(10064): 77-90.

[2] SAFI—STIBLER S, GABORY A. Epigenetics and the developmental origins of health and disease: parental environment signalling to the epigenome, critical time windows and sculpting the adult phenotype[J]. Semin Cell Dev Biol, 2020, 97: 172-180.

[3] SHONKOFF J P, GARNER A S, Committee on Psychosocial Aspects of Child and Family Health, et al. The lifelong effects of early childhood adversity and toxic stress[J]. Pediatrics, 2012, 129(1): e232-e246.

[4] KIM C, SCHILDER N, ADOLPHUS K, et al. The dynamic influence of nutrition on prolonged cognitive healthspan across the life course: a perspective review[J]. Neurosci Appl, 2024, 3: 104072.

[5] PETERSEN I T, BATES J E, STAPLES A D. The role of language ability and self—regulation in the development of inattentive—hyperactive behavior problems[J]. Dev Psychopathol, 2015, 27(1): 221-237.

[6] CALVIN C M, DEARY I J, FENTON C, et al. Intelligence in youth and all—cause—mortality: systematic review with meta—analysis[J]. Int J Epidemiol, 2011, 40(3): 626-644.

[7] DEARY I J, WHITEMAN M C, STARR J M, et al. The impact of childhood intelligence on later life: following up the Scottish mental surveys of 1932 and 1947[J]. J Pers Soc Psychol, 2004, 86(1): 130-147.

[8] GALE C R, DEARY I J, SCHOON I, et al. IQ in childhood and vegetarianism in adulthood: 1970 British cohort study[J]. BMJ, 2007, 334(7587): 245.

[9] MCGURN B, DEARY I J, STARR J M. Childhood cognitive ability and risk of late—onset Alzheimer and vascular dementia[J]. Neurology, 2008, 71(14): 1051-1056.

[10] AGYEKUM M W, YEBOAH S B, DZRADOSI C, et al. Rural—urban differentials in early childhood education and child development: evidence from Multiple Indicator Cluster Survey (MICS) in Ghana[J]. PLOS Glob Public Health, 2023, 3(8): e0002171.

[11] ENGEL G L. The need for a new medical model: a challenge for biomedicine[J]. Science, 1977, 196(4286): 129-136.

[12] ZENG L, DIBLEY M J, CHENG Y, et al. Impact of micronutrient supplementation during pregnancy on birth weight, duration of gestation, and perinatal mortality in rural western China: double blind cluster randomised controlled trial[J]. BMJ, 2008, 337: a2001.

[13] ZHU Z, CHANG S, CHENG Y, et al. Early life cognitive development trajectories and intelligence quotient in middle childhood and early adolescence in rural western China[J]. Sci Rep, 2019, 9(1): 18315.

[14] ZHU Z, CHENG Y, ZENG L, et al. Association of antenatal micronutrient supplementation with adolescent intellectual development in rural western China: 14—year follow—up from a randomized clinical trial[J]. JAMA Pediatr, 2018, 172(9): 832-841.

[15] AUGUSTYNIAK M, MROZEK—BUDZYN D, KIELTYKA A, et al. Stability of the mental and motor Bayley scales of infant development (2nd ed.) in infants over first three years of life[J]. Przegl Epidemiol, 2013, 67(3): 483-486, 581—4.

[16] CARWILE J L, SESHASAYEE S M, ARIS I M, et al. Prospective associations of mid—childhood plasma per—and polyfluoroalkyl substances and pubertal timing[J]. Environ Int, 2021, 156: 106729.

[17] PROSPERI S, CHIARELLI F. Early and precocious puberty during the COVID—19 pandemic[J]. Front Endocrinol (Lausanne), 2022, 13: 1107911.

[18] FILMER D, PRITCHETT L H. Estimating wealth effects without expenditure data—or tears: an application to educational enrollments in states of India[J]. Demography, 2001, 38(1): 115-132.

[19] ALTSCHUL D M, STARR J M, DEARY I J. Cognitive function in early and later life is associated with blood glucose in older individuals: analysis of the Lothian birth cohort of 1936[J]. Diabetologia, 2018, 61(9): 1946-1955.

[20] LI Z A, RAY M K, GU Y, et al. Weight indices, cognition, and mental health from childhood to early adolescence[J]. JAMA Pediatr, 2024, 178(8): 830-833.

[21] WASCHER C A F, KULAHCI I G, LANGLEY E J G, et al. How does cognition shape social relationships?[J]. Philos Trans R Soc Lond B Biol Sci, 2018, 373(1756): 20170293.

[22] 高雨霏, 张力之, 朱文萱, 等 . 中国儿童青少年代谢综合征患病率的Meta分析[J]. 数理医药学杂志, 2024, 37(12): 922-934.

[23] GAO Y F, ZHANG L Z, ZHU W X, et al. Prevalence of metabolic syndrome in Chinese children and adolescents: a meta—analysis[J]. Journal of Mathematical Medicine, 2024, 37(12): 922-934.

[24] YERUSHALMY—FELER A, KASSNER O, FRANK Y, et al. Body composition in pediatric celiac disease and metabolic syndrome component risk: an observational study[J]. Pediatr Res, 2023, 94(2): 618-625.

[25] BAIRD S, CHOONARA S, AZZOPARDI P S, et al. A call to action: the second lancet commission on adolescent health and wellbeing[J]. Lancet, 2025, 405(10493): 1945-2022.

[26] HANEUSE S, VANDERWEELE T J, ARTERBURN D. Using the E—value to assess the potential effect of unmeasured confounding in observational studies[J]. JAMA, 2019, 321(6): 602-603.

[27] HERNÁN M A, WANG W, LEAF D E. Target trial emulation: a framework for causal inference from observational data[J]. JAMA, 2022, 328(24): 2446-2447.

基金资助

国家自然科学基金资助项目(82103867)

陕西省重点研发计划资助项目(2024SF-YBXM-310)

中央高校基本科研业务费专项资金资助项目(xxj032025066)

陕西省创新能力支撑计划资助项目(2023-CX-PT-47)