The goal of this proposal is to test hypotheses about the association between early life circumstances (ELCS) and later life health and survival based on new and extensive additions to a premier longitudinal, familial health database. The proposed study will advance our understanding of these associations because of its in-depth assessment of an entire population spanning more than a century that rely on high-quality socio-demographic, family, medical, and vital records linked into large multi-generational pedigrees. The project is based on the Utah Population Database (UPDB) and links biomarker data collected from two studies: Fertility, Longevity &Aging study (FLAG) and the Cache County Memory Study (CCMS). The purpose of this study is to address the following specific aims:
Aim 1. Expand the data holdings of the existing UPDB by linking new high-quality population- based data to the UPDB to improve measures of ELCs and later-life health of Utah's population. These improvements specifically include: (A) Individual data for all Utahns in the 1900-1930 U.S. Censuses, World War I Draft Registration &Registry Data, and 1921-1936 Birth Certificates;and (B) Diagnosis data from Medicare claims for 2003-2008 that will be added to existing CMS data from 1992-2002. We focus on adverse and beneficial conditions grouped into the following domains: circumstances at birth, socioeconomic status (personal, parental, and neighborhood), social/familial support and stress, fertility, and family history of disease/longevity. Health outcomes are age-specific all-cause and cause-specific mortality, co-morbidity risks, site-specific cancer incidence, and morbidity trajectories.
Aim 2. Test hypotheses that each adverse ELCs as measured in Aim 1 has enduring adverse effects on adult age-specific all-cause and cause-specific mortality and morbidity risks using data contained within the UPDB supplemented with measures acquired as part of Aim 1.
Aim 3. Test the hypothesis that adverse ELCs will be associated with biomarker and clinical measures known to be related to poor health and survival among adults. We will use data from existing data linkages between UPDB and subjects in the FLAG and CCMS studies. Biomarker measures studied include C-reactive protein, white blood count, albumin, uric acid, creatinine, serum cholesterol, glycosylated hemoglobin, dehydroepiandrosterone sulfate (DHEAS &DHEA), fasting glucose and insulin resistance, telomere length, blood pressure, heart rate, grip strength, forced expiratory volume (FEV1), and BMI. We also test if there is effect modification of APOE alleles on the association between ELCS &later-life biomarkers.
This study will identify associations between specific adverse early- and mid-life circumstances and later life-health and survival. The study will expand our understanding of the health effects of ELCS and will help guide the development of interventions for at-risk individuals to be introduced long before the onset of adverse adult health outcomes.
|Martin, Christopher; Leiser, Claire L; O'Neil, Brock et al. (2018) Familial Cancer Clustering in Urothelial Cancer: A Population-Based Case-Control Study. J Natl Cancer Inst 110:527-533|
|Arbeeva, Liubov S; Hanson, Heidi A; Arbeev, Konstantin G et al. (2018) How Well Does the Family Longevity Selection Score Work: A Validation Test Using the Utah Population Database. Front Public Health 6:277|
|Theilen, Lauren H; Meeks, Huong; Fraser, Alison et al. (2018) Long-term mortality risk and life expectancy following recurrent hypertensive disease of pregnancy. Am J Obstet Gynecol 219:107.e1-107.e6|
|van den Berg, Niels; Beekman, Marian; Smith, Ken Robert et al. (2017) Historical demography and longevity genetics: Back to the future. Ageing Res Rev 38:28-39|
|Hanson, Heidi A; Mayer, Erik N; Anderson, Ross E et al. (2017) Risk of childhood mortality in family members of men with poor semen quality. Hum Reprod 32:239-247|
|Norton, Maria C; Hatch, Daniel J; Munger, Ronald G et al. (2017) Family Member Deaths in Childhood Predict Systemic Inflammation in Late Life. Biodemography Soc Biol 63:104-115|
|Caplin, Deirdre A; Smith, Ken R; Ness, Kirsten K et al. (2017) Effect of Population Socioeconomic and Health System Factors on Medical Care of Childhood Cancer Survivors: A Report from the Childhood Cancer Survivor Study. J Adolesc Young Adult Oncol 6:74-82|
|Dribe, Martin; Breschi, Marco; Gagnon, Alain et al. (2017) Socio-economic status and fertility decline: Insights from historical transitions in Europe and North America. Popul Stud (Camb) 71:3-21|
|Hanson, Heidi A; Horn, Kevin P; Rasmussen, Kelli M et al. (2017) Is Cancer Protective for Subsequent Alzheimer's Disease Risk? Evidence From the Utah Population Database. J Gerontol B Psychol Sci Soc Sci 72:1032-1043|
|Hollingshaus, Michael S; Coon, Hilary; Crowell, Sheila E et al. (2016) Differential Vulnerability to Early-Life Parental Death: The Moderating Effects of Family Suicide History on Risks for Major Depression and Substance Abuse in Later Life. Biodemography Soc Biol 62:105-25|
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