Baby Boomers and Birth Certificates: Early-Life Socioeconomic Status and Cancer Risk in Adulthood

Lifetime Employment Trajectories and Cancer: A Population-Based Cohort Study

Working life is associated with lifestyle, screening uptake, and occupational health risks that may explain differences in cancer onset. To better understand the association between working life and cancer risk, we need to account for the entire employment history. We investigated whether lifetime employment trajectories are associated with cancer risk. We used data from 6,809 women and 5,716 men, average age 70 years, from the Survey of Health, Ageing, and Retirement in Europe. Employment history from age 16 to 65 was collected retrospectively using a life calendar and trajectories were constructed using sequence analysis. Associations between employment trajectories and self-reported cancer were assessed using logistic regression. We identified eight employment trajectories for women and two for men. Among women, the risk of cancer was higher in the trajectories "Mainly full-time to home/family", "Full-time or home/family to part-time", "Mainly full-time", and "Other" compared with the "Mainly home/family" trajectory. Among men, the risk of cancer was lower in the "Mainly self-employment" trajectory compared with "Mainly full-time". We could show how employment trajectories were associated with cancer risk, underlining the potential of sequence analysis for life course epidemiology. More research is needed to understand these associations and determine if causal relationships exist.

Disparities and determinants of place of death: Insights from the Utah Population Database

To better understand determinants and potential disparities in end of life, we model decedents' place of death with explanatory variables describing familial, social, and economic resources. A retrospective cohort of 204,041 decedents and their family members are drawn from the Utah Population Database family caregiving dataset. Using multinomial regression, we model place of death, categorized as at home, in a hospital, in another location, or unknown. The model includes family relationship variables, sex, race and ethnicity, and a socioeconomic status score, with control variables for age at death and death year. We identified the effect of a family network of multiple caregivers, with 3+ daughters decreasing odds of a hospital death by 17 percent (OR: 0.83 [0.79, 0.87], p < 0.001). Place of death also varies significantly by race and ethnicity, with most nonwhite groups more likely to die in a hospital. These determinants may contribute to disparities in end of life.

Early life adversity, reproductive history and breast cancer risk

Background and objectives

Individuals who experience early life adversity are at an increased risk for chronic disease later in life. Less is known about how early life factors are associated with cancer susceptibility. Here, we use a life history framework to test whether early life adversity increases the risk of breast cancer. We predict that early life adversity can shift investment in somatic maintenance and accelerate the timing of reproduction, which may mediate or interact with the risk of breast cancer.

Methodology

We use population-wide data from the Utah Population Database (UPDB) and Utah Cancer Registry, leading to 24 957 cases of women diagnosed with breast cancer spanning 20 years (1990-2010) and 124 785 age-matched controls. We generated a cumulative early life adversity summation score to evaluate the interaction (moderation) and mediation between early life adversity, reproductive history and their association with breast cancer risk.

Results

Our analyses led to three key findings: (i) more early life adversity, when considered as a main effect, accelerates the time to first birth and death, (ii) early age at first birth and high parity decreases the risk of breast cancer and (iii) we find no association between early adversity and breast cancer risk either as a main effect or in its interaction with reproductive history.

Conclusion and implications

Early adversity elevates the risk of overall mortality through mechanisms other than breast cancer risk. This suggests early life factors can generate different effects on health. Future work should incorporate more complex view of life history patterns, including multiple life stages, when making predictions about cancer susceptibility.

Childhood socioeconomic status, healthy lifestyle, and colon cancer risk in a cohort of U.S. women

Colon cancer is the third most common cancer in the US. While the socioeconomic status -health gradient has been established, findings linking adult socioeconomic status to colon cancer incidence specifically are mixed. Considering childhood socioeconomic status (CSES) and relevant risk factors, including related lifestyle behaviors, may provide more insight. At baseline in 1976, women from the Nurses' Health Study reported CSES as defined by parents' occupation when participants were age 16. Lifestyle-related factors (i.e., physical activity, body mass index, diet, alcohol, and tobacco consumption) were self-reported in 1988 or 1990, and every 4 years thereafter until 2016. Cox regression models estimated hazards ratio (HR) and 95% confidence intervals (CIs) of adopting an unhealthy lifestyle (N = 22,507) and developing colon cancer (N = 100,921) between 1976 and 2016, separately, across parents' occupation levels. During follow-up, 2342 cases of colon cancer occurred. Compared to women whose parents were white collar workers, women whose parents were farmers had lower colon cancer risk (HR = 0.84; 95%CI: 0.72, 0.98), but no differences were evident for women whose parents were blue collar workers in models adjusting for age and familial history of colon cancer. Using the same comparison group, risk of adopting an unhealthy lifestyle over follow-up was not significantly different in women with farmer parents (HR = 0.96, 95% CI: 0.91, 1.02), while children of blue collar workers had slightly greater risk (HR = 1.07; 95%CI: 1.03, 1.12) in age-adjusted models. These findings suggest the impact of CSES on colon cancer risk is modest and varies across outcomes and occupational status.

Early-Life Risk Factors for Breast Cancer - Prospective Follow-up in the Northern Finland Birth Cohort 1966

BACKGROUND

While some risk factors for breast cancer have been confirmed, less is known about the role of early biological and social risk factors for breast cancer in adult life.

METHODS

In a prospective follow-up in the Northern Finland Birth Cohort 1966 consisting of 5,308 women, 120 breast cancers were reported via national registers by the end of 2018. Early risk factors were examined with univariate and multivariate analyses using Cox regression analysis. The main results are reported with HRs and their 95% confidence intervals (CI).

RESULTS

In the multivariate-adjusted models, women whose mothers lived in urban areas (HR, 1.68; 95% CI, 1.13-2.51) during pregnancy, were low educated (HR, 2.40; 95% CI, 1.30-4.45), and had been diagnosed with breast cancer (HR, 1.97; 95% CI, 1.09-3.58) had a higher risk for breast cancer in adult life. Lower BMI at the age of 14 associated nonsignificantly with the risk of breast cancer (Mann-Whitney U test, P = 0.087). No association between birth size and breast cancer risk in adult life was found.

CONCLUSIONS

Early-life residence and socioeconomic conditions may have an impact on developing breast cancer in women in adult life. All breast cancer cases of this study were relatively young, and most of them are assumed to be premenopausal.

IMPACT

This study is one of a few prospective birth cohort studies to examine early-life socioeconomic factors and breast cancer risk in adult life. This study is limited due to small number of cases.

Spatial clusters of cancer incidence: analyzing 1940 census data linked to 1966-2017 cancer records

PURPOSE

A life course perspective to cancer incidence is important for understanding effects of the environment during early life on later cancer risk. We assessed spatial clusters of cancer incidence based on early life location defined as 1940 US Census Enumeration District (ED).

METHODS

A cohort of 260,585 individuals aged 0-40 years in 1940 was selected. Individuals were followed from 1940 to cancer diagnosis, death, or last residence in Utah. We geocoded ED centroids in Utah for the 1940 Census. Spatial scan statistics with purely spatial elliptic scanning window were used to identify spatial clusters of EDs with excess cancer rates across 26 cancer types, assuming a discrete Poisson model.

RESULTS

Cancer was diagnosed in 66,904 (25.67%) individuals during follow-up across 892 EDs. Average follow-up was 50.9 years. We detected 15 clusters of excess risk for bladder, breast, cervix, colon, lung, melanoma, oral, ovary, prostate, and soft tissue cancers. An urban area had dense overlap of multiple cancer types, including two EDs at increased risk for five cancer types each.

CONCLUSIONS

Early environments may contribute to cancer risk later in life. Life course perspectives applied to the study of cancer incidence can provide insights for increasing understanding of cancer etiology.

Early life exposures associated with risk of small intestinal neuroendocrine tumors

Small intestinal neuroendocrine tumors (SINT) are rare with incidence increasing over the past 40 years. The purpose of this work is to examine the role of environmental exposures in the rise of SINT incidence using the Utah Population Database, a resource of linked records including life events, cancer diagnoses and residential histories. SINT cases born in Utah were identified through the Utah Cancer Registry with: diagnosis years of 1948 to 2014 and age at diagnosis of 23 to 88 years. Controls were matched to cases 10:1 based on sex, birth year and residence time in Utah. Cases and controls were geocoded to their birth locale. An isotonic spatial scan statistic was used to test for the occurrence and location(s) of SINT clusters. Potential environmental exposures and economic conditions in the birth locales at the time of the birth (1883–1982) were generated using historical references. Conditional logistic regression was used to estimate odd ratios. We report a spatial cluster central to historic coal mining communities, associated with a 2.86 relative risk (p = 0.016) of SINT. Aspatial analyses of industry and mining exposures further suggest elevated risk for early life exposure near areas involved in the construction industry (OR 1.98 p = 0.024). Other exposures approached significance including coal, uranium and hard rock mining during the earliest period (1883–1929) when safety from exposures was not considered. We do observe a lower risk (OR 0.58 p = 0.033) associated with individuals born in rural areas in the most recent period (1945–1982). Environmental exposures early in life, especially those from industries such as mining, may confer an elevated risk of SINT.

Opportunities for life course research through the integration of data across Clinical and Translational Research Institutes

Introduction

Early life exposures affect health and disease across the life course and potentially across multiple generations. The Clinical and Translational Research Institutes (CTSIs) offer an opportunity to utilize and link existing databases to conduct lifespan research.

Methods

A survey with Lifespan Domain Taskforce expert input was created and distributed to lead lifespan researchers at each of the 64 CTSIs. The survey requested information regarding institutional databases related to early life exposure, child-maternal health, or lifespan research.

Results

Of 64 CTSI, 88% provided information on a total of 130 databases. Approximately 59% (n=76/130) had an associated biorepository. Longitudinal data were available for 72% (n=93/130) of reported databases. Many of the biorepositories (n=44/76; 68%) have standard operating procedures that can be shared with other researchers.

Conclusions

The majority of CTSI databases and biorepositories focusing on child-maternal health and lifespan research could be leveraged for lifespan research, increased generalizability and enhanced multi-institutional research in the United States.