Foreign-born Hispanics have better cardiometabolic health upon arrival in the US than their US-born counterparts, yet this advantage diminishes as duration of residence in the US increases. Underlying mechanisms explaining this paradox have been understudied. Using data from the Sacramento Area Latino Study on Aging (SALSA), this study examined immigration history (immigrant generation and duration of US residence) in relation to biomarkers of inflammation (interleukin-6 (IL-6), soluble forms of type 1 and 2 receptors of tumor necrosis factor-alpha (sTNF-R1 and sTNF-R2), C-reactive protein (CRP), leptin, adiponectin) in a sample of 1,290 predominantly Mexican-origin immigrants. Second and ≥3rd generation immigrants had higher IL-6 and leptin levels than 1st generation immigrants living in the US for less than 15 years (2nd generation percent difference = 45.9; 95% CI: 24.7, 70.7 and 3rd generation percent difference = 41.8; 95% CI: 17.7, 70.4). CRP and sTNF-R1 levels were higher among ≥3rd generation immigrants than 1st generation immigrants with less than 15 years of US residency. Worse inflammatory profiles were observed among Mexican-origin immigrants with longer US immigration histories, independent of health, and behavioral factors. Additional research is warranted to understand the factors that shape trajectories of biological risk across generations of Hispanics.

Acculturation markers, such as language use, have been associated with Latino depression. Language use may change between generations; however, few studies have collected intergenerational data to assess how language differences between generations impact depression. Using the Niños Lifestyle and Diabetes Study (2013-2014), we assessed how changes in Spanish language use across two generations of Mexican-origin participants in Sacramento, California, influenced offspring depressive symptoms (N = 603). High depressive symptoms were defined as CESD-10 scores ≥ 10. We used log-binomial and linear-binomial models to calculate prevalence ratios and differences, respectively, for depressive symptoms by language use, adjusting for identified confounders and within-family clustering. Decreased Spanish use and stable-equal English/Spanish use across generations protected against depressive symptoms, compared to stable-high Spanish use. Stable-low Spanish use was not associated with fewer depressive symptoms compared to stable-high Spanish use. Exposure to multiple languages cross-generationally may improve resource access and social networks that protect against depression.

Objective

This study aimed to estimate the association between cycles of poverty, measured by intergenerational educational attainment (IEA), and the burden of obesity and metabolic dysfunction among Hispanic/Latino individuals in the United States.

Methods

This is a cross-sectional study utilizing data from 392 adults linked to 286 biologic parents from the Niños Lifestyle and Diabetes Study and the Sacramento Area Latino Study on Aging. The educational attainment of parents and offspring was dichotomized in order to categorize IEA. Outcomes included obesity and metabolic syndrome (MetS). Model-based standardization with population weights was used to compare obesity and MetS across generations, and Poisson regression was used to estimate prevalence ratios by IEA.

Results

A higher prevalence of obesity and MetS was observed in offspring (54% and 69%, respectively) compared with their parents (48% and 42%, respectively). Compared with stable-low IEA, any category with high offspring education was associated with lower obesity and MetS prevalence. The upwardly mobile group saw the greatest benefit; they were 38% (95% CI: 10%-57%) and 46% (95% CI: 21%-63%) less likely to have obesity or MetS.

Conclusions

IEA strongly patterns cardiometabolic health among Hispanic/Latino individuals living in the United States, suggesting that promotion of higher education is associated with reductions in obesity and MetS, potentially benefitting future generations of this population.

Purpose

United States (US) Latinos have the lowest educational attainment of any US racial/ethnic group, which may contribute to their disparate burden of Type 2 Diabetes. Herein, we aimed to examine the association between intergenerational educational mobility and Type 2 Diabetes among US Latino adults.

Methods

We used data from the Niños Lifestyle and Diabetes Study (2013-2014) and the Sacramento Area Latino Study on Aging (1998-1999) to link 616 adult Latino children to their parents. Model-based standardization and robust Poisson regression were used to estimate the prevalence of prediabetes, Type 2 Diabetes, treatment and glycemic control, and describe their associations with intergenerational educational mobility.

Results

Adult children with stable high intergenerational educational attainment had a higher prevalence of prediabetes (Prevalence Ratio, PR=1.58; 95% Confidence Interval, CI=1.08, 2.34) and lower prevalence of Type 2 Diabetes (PR=0.64, CI=0.41, 0.99), as compared to those who experienced low educational attainment across generations. Downward mobility was associated with a higher prevalence of prediabetes (PR=1.54, CI=1.06, 2.23) and worse glycemic control (PR=2.20, CI=1.13, 4.30), and upward mobility was associated with a lower prevalence of Type 2 Diabetes (PR=0.39, CI=0.22, 0.70).

Conclusions

Our findings from a predominantly Mexican-heritage community suggest that higher education across generations may buffer individuals from glycemic dysregulation. As such, higher education may be a promising public health target to address the rising burden of Type 2 Diabetes in the US.

The Hispanic/Latino population experiences socioeconomic adversities across the lifespan and is at greater risk of cognitive impairment, yet little is known about the role of life-course socioeconomic position (SEP) in cognitive function in this population. Using baseline data (2008-2011) from adults (aged 45-74 years) of the Hispanic Community Health Study/Study of Latinos, we assessed the association between childhood SEP and socioeconomic mobility with cognitive function, and whether this association was mediated by midlife SEP. Childhood SEP was assessed using parental education. An index combining participants education and household income represented midlife SEP. Socioeconomic mobility was categorized as stable low, downward or upward mobility, and stable high-SEP. Cognitive function measures were modeled using survey linear regression with inverse-probability weighting, accounting for covariates. We used mediation analysis to estimate the indirect effect of childhood SEP on cognition through midlife SEP. High childhood SEP was associated with global cognition in adulthood (coefficient for parental education beyond high school vs. less than high school = 0.26, 95% confidence interval: 0.15, 0.37). This association was partially mediated through midlife SEP (indirect effect coefficient = 0.16, 95% confidence interval: 0.15, 0.18). Low SEP through the life course was associated with the lowest cognitive function. This study provides evidence that life-course SEP influences cognitive performance in adulthood.

Age at menarche (AM) and age at natural menopause (ANM) define the boundaries of the reproductive lifespan in women. Their timing is associated with various diseases, including cancer and cardiovascular disease. Genome-wide association studies have identified several genetic variants associated with either AM or ANM in populations of largely European or Asian descent women. The extent to which these associations generalize to diverse populations remains unknown. Therefore, we sought to replicate previously reported AM and ANM findings and to identify novel AM and ANM variants using the Metabochip (n = 161,098 SNPs) in 4,159 and 1,860 African American women, respectively, in the Women's Health Initiative (WHI) and Atherosclerosis Risk in Communities (ARIC) studies, as part of the Population Architecture using Genomics and Epidemiology (PAGE) Study. We replicated or generalized one previously identified variant for AM, rs1361108/CENPW, and two variants for ANM, rs897798/BRSK1 and rs769450/APOE, to our African American cohort. Overall, generalization of the majority of previously-identified variants for AM and ANM, including LIN28B and MCM8, was not observed in this African American sample. We identified three novel loci associated with ANM that reached significance after multiple testing correction (LDLR rs189596789, p = 5×10⁻⁰⁸; KCNQ1 rs79972789, p = 1.9×10⁻⁰⁷; COL4A3BP rs181686584, p = 2.9×10⁻⁰⁷). Our most significant AM association was upstream of RSF1, a gene implicated in ovarian and breast cancers (rs11604207, p = 1.6×10⁻⁰⁶). While most associations were identified in either AM or ANM, we did identify genes suggestively associated with both: PHACTR1 and ARHGAP42. The lack of generalization coupled with the potentially novel associations identified here emphasize the need for additional genetic discovery efforts for AM and ANM in diverse populations.

Diverse representation and inclusion are stated priorities for scientific institutions and professional societies, including the Society for Epidemiologic Research (SER). Prior studies have reported persistent underrepresentation and exclusion of marginalized groups across the sciences. We conducted a representation and inclusion survey among SER affiliates in 2021, following up on a similar 2018 survey. In 2021, we observed broad representation from diverse groups across multiple dimensions. However, across both surveys we found persistent underrepresentation of several marginalized groups, including Black or African American and Hispanic/Latinx people. Some groups reported feeling excluded in both the 2018 and 2021 surveys, and there was disproportionately high representation from a subset of higher-ranked US academic institutions. For several indicators of inclusion, perceptions of inclusion were more positive among White respondents compared to other respondents. Opportunities to work towards achieving SER’s diversity and inclusion aims include increasing outreach to epidemiology trainees and Minority Serving Institutions, addressing cultural and financial barriers to participation, and improving access for epidemiologists with disabilities. Iterative follow-up work with diversity and inclusion scholars could improve our understanding of barriers to diversity and inclusion within SER and, more broadly, the field of epidemiology.

Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-valuesbinomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.

US Hispanic/Latino individuals are diverse in genetic ancestry, culture, and environmental exposures. Here, we characterized and controlled for this diversity in genome-wide association studies (GWASs) for the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We simultaneously estimated population-structure principal components (PCs) robust to familial relatedness and pairwise kinship coefficients (KCs) robust to population structure, admixture, and Hardy-Weinberg departures. The PCs revealed substantial genetic differentiation within and among six self-identified background groups (Cuban, Dominican, Puerto Rican, Mexican, and Central and South American). To control for variation among groups, we developed a multi-dimensional clustering method to define a "genetic-analysis group" variable that retains many properties of self-identified background while achieving substantially greater genetic homogeneity within groups and including participants with non-specific self-identification. In GWASs of 22 biomedical traits, we used a linear mixed model (LMM) including pairwise empirical KCs to account for familial relatedness, PCs for ancestry, and genetic-analysis groups for additional group-associated effects. Including the genetic-analysis group as a covariate accounted for significant trait variation in 8 of 22 traits, even after we fit 20 PCs. Additionally, genetic-analysis groups had significant heterogeneity of residual variance for 20 of 22 traits, and modeling this heteroscedasticity within the LMM reduced genomic inflation for 19 traits. Furthermore, fitting an LMM that utilized a genetic-analysis group rather than a self-identified background group achieved higher power to detect previously reported associations. We expect that the methods applied here will be useful in other studies with multiple ethnic groups, admixture, and relatedness.

Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry^1-3. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific^4-10. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate to other populations^11,12. Here we demonstrate the value of diverse, multi-ethnic participants in large-scale genomic studies. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioural phenotypes in 49,839 non-European individuals. Using strategies tailored for analysis of multi-ethnic and admixed populations, we describe a framework for analysing diverse populations, identify 27 novel loci and 38 secondary signals at known loci, as well as replicate 1,444 GWAS catalogue associations across these traits. Our data show evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts and insights into clinical implications. In the United States-where minority populations have a disproportionately higher burden of chronic conditions¹³-the lack of representation of diverse populations in genetic research will result in inequitable access to precision medicine for those with the highest burden of disease. We strongly advocate for continued, large genome-wide efforts in diverse populations to maximize genetic discovery and reduce health disparities.