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. Author manuscript; available in PMC: 2026 Jan 31.
Published in final edited form as: Health Psychol. 2026 Jan 29;45(5):590–601. doi: 10.1037/hea0001579

Prospective links between childhood family income and subclinical atherosclerosis in a sample of young men

Vínculos prospectivos entre los ingresos familiares en la infancia y la aterosclerosis subclínica en una muestra de hombres jóvenes

Emily J Jones 1, Sydney Damon 1, Portia Miller 1, Tess Dupree 1, Mindy L Coccari 1, Akira Sekikawa 1, Daniel S Shaw 1, Anna L Marsland 1, Elizabeth Votruba-Drzal 1
PMCID: PMC12857746  NIHMSID: NIHMS2121776  PMID: 41609649

Abstract

Objective.

Men who experience childhood economic disadvantage may be at elevated risk for subclinical cardiovascular disease in adulthood, showing signs of disease 10 years before women. Leveraging prospective data from men who experienced low levels of family income in infancy/toddlerhood, we examine the variance in adult carotid intima-media thickness, (IMT), a putative marker of subclinical atherosclerosis, that is related to cumulative childhood family income.

Methods.

Data are from 145 men (31.7 years; 47.6% White) who participated in the Pathways to Health study, which is a follow-up study to the Pitt Mother & Infant Project that began in 1991. Between ages 1.5–17 years, participants’ parents reported on their annual income on 13 occasions, which were averaged together to calculate their cumulative childhood family income. At age ~32 years, men’s carotid IMT was measured by a trained technician using ultrasonography. Linear regression was used to examine the association between cumulative childhood family income and adult IMT in an unadjusted model. Then, we controlled for parents’ educational attainment, men’s socioeconomic status (i.e., income, education, employment), traditional markers of cardiovascular risk (e.g., smoking, blood pressure, adiposity) and race to examine the unique variance in IMT associated with childhood family income.

Results.

Cumulative childhood income was negatively associated with adult IMT (β=−.27, p<.01). This association remained statistically reliable when adjusting for parents’ educational attainment, adult socioeconomic status, and traditional markers of cardiovascular risk (β=−.24, p=.03).

Conclusions.

Pending replication, findings highlight the importance of considering men’s economic upbringing when assessing their risk for subclinical atherosclerosis.

Keywords: childhood income, intima media thickness, subclinical atherosclerosis

Cardiovascular disease (CVD), the leading cause of morbidity and disability in the United States, varies by socioeconomic status (SES) (Benjamin et al., 2019; de Mestral & Stringhini, 2017), including SES in childhood (Galobardes et al., 2006). Compared to adults raised in more socioeconomically-advantaged households, adults who experience socioeconomic disadvantage in childhood may be at greater risk of having a CVD event, including stroke and coronary heart disease (Galobardes et al., 2006). The biological embedding of adversity hypothesis posits that childhood SES may have enduring effects on adult CVD risk because the vast majority of physiological and biobehavioral systems are programmed to respond and adapt to the environment during childhood and adolescence (Berens et al., 2017; Cohen et al., 2010; Jensen et al., 2017; Miller & Chen, 2013; Shonkoff et al., 2009, 2012). Hence, children who are exposed to poverty may develop behavioral, physiological, and psychological mechanisms that help them to thrive in their current socioeconomic circumstances, but could come with unintentional and adverse impacts to their long-term health, including increased CVD risk in adulthood (Evans & Kantrowitz, 2002; Evans & Kim, 2007; Wadsworth, 2015).

Even though CVD is usually diagnosed in mid- to later-life, rates of CVD are steadily increasing among young adults under age 40 (Allen & Wilkins, 2023). Therefore, researchers have recommended focusing on young adults at risk for CVD, intervening with them in the years before clinical diagnosis when physiological CVD risk factors like subclinical atherosclerosis are observable but may still be amenable to change (Wendell et al., 2017). Intima-media thickness (IMT) is a putative marker of subclinical atherosclerosis that is measured noninvasively through ultrasonography, and has been shown to predict future CVD events (Lorenz et al., 2007). As with CVD, IMT varies as a function of childhood SES (Berens et al., 2017). Research using data from the Young Finns cohort has shown that lower childhood SES is associated with greater IMT and greater multi-year progression of IMT among adults in their twenties and thirties (Hakulinen et al., 2016; Kivimäki et al., 2006). A similar childhood socioeconomic gradient in IMT has been observed in other cohorts.(Lamont et al., 2000), including those with more racial diversity (Camelo et al., 2015; Lemelin et al., 2009). For example, using data from over 6800 midlife and older adults participating in the Multi-Ethnic Study of Atherosclerosis, Lemelin and colleagues (2009) found that childhood SES was negatively related to IMT in adulthood. Moreover, the association between childhood SES and adult IMT was independent of adult SES (Lemelin et al., 2009), which highlights that childhood SES plays a unique role in the etiology of atherosclerosis and is not fully explained or attenuated by adult SES (Cohen et al., 2010).

Nevertheless, the existing literature on childhood socioeconomic predictors of IMT in young adulthood has some methodological limitations. Foremost, childhood family income has seldom been used to measure childhood SES even though family income often dictates a child’s quality of housing, health care, and the type of food that families can afford (Duncan et al., 2014; Wise, 2016). For example, families with higher incomes are more likely to afford housing in safe neighborhoods with abundant recreational opportunities and have the financial means to pay for healthy food that may promote long-term cardiovascular health. In contrast, families with low income may be limited to housing in underserved areas with more environmental stressors (e.g., greater exposure to pollution, crime) that could increase risk for atherosclerosis in adulthood (Aris et al., 2021; Jimenez et al., 2019). Existing work has instead used parents’ educational attainment, either alone (Camelo et al., 2015; Lemelin et al., 2009) or as a composite, to measure childhood SES (Hakulinen et al., 2016; Kivimäki et al., 2005). Nevertheless, educational attainment and income are distinct resources for families that may have differential effects on children’s experiences throughout childhood and adolescence, as well as their future CVD risk (Bradley & Corwyn, 2002; Duncan & Magnuson, 2002; Krieger et al., 1997). In fact, only one study of childhood SES and adult IMT has included childhood income (Hakulinen et al., 2016); however, income was dichotomized and then combined with several other socioeconomic, social-emotional, and stress-related factors to create a composite of childhood adversity. While composite approaches like these provide an overall picture of the family environment, they obfuscate the variance in adult IMT that is attributable to family income. This dilution of income’s potential influence matters because policymakers need to know what specific aspects of the childhood environment (e.g., household income, parent educational attainment, food access) are most important for promoting cardiovascular health so that they can be targeted through policies and programs aimed at promoting health equity (Braveman et al., 2005; Duncan & Magnuson, 2002).

Along with overlooking family income, most studies on childhood SES and adult IMT have relied on retrospective reports (Camelo et al., 2015; Lemelin et al., 2009) or measures of SES assessed at only one or two timepoints in childhood and adolescence (Hakulinen et al., 2016; Lamont et al., 2000). While easily collected, these approaches may not reflect socioeconomic circumstances experienced throughout childhood and adolescence, especially for those raised in households characterized by economic instability. Retrospective reports of childhood SES may also be subject to recall bias (Ward, 2011).

To begin to address these limitations, we leverage rich, repeated measures of childhood family income data collected prospectively across 13 waves of assessments during childhood and adolescence to examine whether cumulative childhood income relates to adult IMT among a sample of young men in their early thirties. Men were initially recruited at 18 months with their mothers through Women, Infants, and Children Nutritional Supplement (WIC) centers, which provide health and nutrition services to low-income families. We focus on associations between childhood family income and adult IMT among young men who experienced low levels of family income in infancy/toddlerhood for a few reasons. Foremost, men and women differ in their presentation and course of CVD, which has led some scholars to recommend studying risk factors for CVD separately in men and women (Arnold et al., 2017; Regitz-Zagrosek & Kararigas, 2017). In addition, men evidence signs of CVD up to a decade before women (Regitz-Zagrosek & Kararigas, 2017) as reflected by work showing that young men have greater IMT, on average, compared to young women (Sinning et al., 2011). There is also some research that suggests that childhood economic disadvantage may be particularly detrimental to boys’ long-term social-emotional development and educational attainment (Autor et al., 2019; Ratcliffe, 2015), which could extend to their cardiovascular health as well. Along with these substantive reasons, we also focus on associations among men only because we have access to rich, longitudinal data on childhood economic circumstances and contemporary CVD markers for an all-male cohort followed since toddlerhood. However, we acknowledge that future work is needed to consider the unique role of cumulative childhood family income in shaping young women’s CVD risk and IMT in young adulthood.

In our primary analyses, we examine whether cumulative childhood family income is prospectively associated with men’s IMT in adulthood. Then, we test whether this association remains statistically reliable after simultaneously accounting for a variety of socioeconomic and health-related factors that may be related to childhood family income and adult IMT and contribute to links between the two. It is hypothesized that cumulative childhood family income will be negatively associated with IMT in adulthood, and that this association will be independent of parents’ highest level of educational attainment, men’s race, their adult SES (i.e., current income, educational attainment, employment status), and traditional markers of CVD risk (i.e., smoking, alcohol consumption, blood pressure, adiposity, triglycerides, HDL cholesterol, glucose, glycated hemoglobin).

Methods

Transparency and Openness.

In this article, we report all data exclusions, manipulations, and measures included in the analysis. Data and analytic code are available on OSF at https://osf.io/6nrgs/ (Jones et al., 2025). Analyses were not preregistered.

Participants

Analyses were conducted using data from 145 male participants (M = 31.7 years old) who completed the Pathways to Health (PaTH) study between 2022–2024. The PaTH study seeks to richly characterize developmental correlates of cardiometabolic health among a group of young men who may be at greater risk for CVD compared to other men their age based on their economic circumstances at birth. PaTH participants are part of a larger cohort of men who have been followed prospectively since toddlerhood as part of the Pitt Mother & Child Project (PMCP), a project focused on developmental precursors of externalizing problem behaviors among boys from low-income families. A total of 310 boys and their mothers were recruited into PMCP between 1991–1993 from WIC centers across the Pittsburgh, Pennsylvania area. As a public assistance program, WIC provides low-income families with nutrition services during the prenatal period through children’s fifth birthdays. The sociodemographic characteristics of the PMCP sample (e.g., income, race, relationship status) were reflective of Pittsburgh families receiving WIC services in the early 1990s. All men who participated in PMCP were invited to take part in the PaTH study, with 47% of the original cohort completing the PaTH study. The low response rate may reflect the 30-year passage of time between when caregivers first provided consent for their sons’ participation in PMCP and present-day, with men themselves consenting to participate in the PaTH study. PaTH participants did not differ from the remaining PMCP participants on cumulative childhood family income, the independent variable of interest (t(309) = .69, p = .49; PaTH mean childhood income = $39,588 in 2022 USD; PMCP only mean childhood income = $38,085 in 2022 USD).

Procedure

For the PMCP, participating boys and their parents partook in laboratory and in-home assessments conducted repeatedly throughout childhood, adolescence, and early adulthood. The present analyses draw on 13 waves of annual household income data collected when participants were roughly 1.5, 2, 3, 3.5, 5, 5.5, 6, 8, 10, 11, 12, 15, and 17 years old.

In their early thirties, PMCP participants were then re-contacted to participate in the PaTH study. PaTH consisted of a 4-hour laboratory visit that included semi-structured interviews, questionnaires, and numerous physiological assessments (e.g., anthropometrics, blood pressure, blood draw, ultrasound of the carotid arteries to measure IMT). The day before their appointment, participating men were contacted with pre-visit instructions including abstaining from food or drink (besides water), exercise, and tobacco products in the 8 hours before their appointment. Participants were rescheduled if they reported current or recent sickness, were taking any corticosteroids or antibiotics/antivirals, or if they had received a vaccine or tattoo in the prior two weeks. PaTH assessments were conducted by trained research assistants and were held in the morning, starting between 8–10 AM and ending around 12–2 PM.

When participants were minors, their parents provided informed consent for their participation in PMCP. At age ~32, participants provided their own informed consent for participating in the PaTH study. The Institutional Review Board of the University of Pittsburgh approved both PMCP and the PaTH study.

Measures

Cumulative childhood family income

As part of 13 PMCP assessments across participants’ childhoods and adolescence, parents were asked about their household’s annual income prior to taxes. They were asked to include income from all sources, including work, family, public assistance, and child support payments. We used Consumer Price Index (CPI) adjustments to escalate household income to 2022 dollars at each wave to account for inflation and allow us compare income across different waves. Family income data were aggregated across the 13 assessments and averaged together to create a cumulative measure of childhood family income. Cumulative childhood family income was natural log transformed to normalize the distribution prior to fitting statistical models.

Carotid IMT

Carotid IMT was used as a surrogate measure of subclinical atherosclerosis. Carotid IMT was assessed by trained technicians at the University of Pittsburgh Ultrasound Research Laboratory. The inter-tech scan quality control intra-class correlation between technicians in the Ultrasound Research Laboratory is 0.98, and the inter-tech read quality-control intra-class correlation is 0.93. Participants carotid IMTs were measured using B-mode ultrasonography on an Acuson scanner (Acuson-Siemens, Malvern, Pennsylvania) for all but one participant whose carotid IMT was assessed on a GE LOGIQ E9 scanner (GE Healthcare, Milwaukee, WI, USA). Both scanners acquired two digital images of the common carotid artery and one image each of the carotid bulb and internal carotid artery on both the right and left sides of the participant for a total of eight images. The images were scored by software that calculated IMT as the distance between the lumen-intima and media-adventitia interfaces (Artery Measurement System; Goteborg University, Gothenburg, Sweden). Mean measurements were determined for the left and the right sides in 1 cm segments for the near wall and far wall of the common carotid artery and the far wall of the bulb and inter-carotid artery locations. Ten participants had mean data on only the left side and 5 participants had mean data on only the right side. One hundred and ten participants had measurements available for both sides. For men with measurements available from only one side, their IMT measure was set equal to that measure. For men with IMT measures on both the right and the left, their scores were averaged. Nineteen participants had scans that were unable to be scored due to unclear imaging or machine malfunctioning, and one participant declined to be scanned. This resulted in 125 participants with interpretable IMT data; the natural log of this sample was taken to normalize the distribution prior to fitting regression models.

Sociodemographic and Health-Related Covariates

Parents’ highest level of educational attainment.

Along with income, the parent who identified as the primary caretaker of the participant reported on their own educational attainment at each of the 13 PMCP assessments by indicating which of the following options reflected their highest level of completed education: Less than high school; high school degree or equivalent; some college (e.g., an Associate’s degree, vocational/technical program); a Bachelor’s degree; a graduate or professional degree. As some parents went back to school while raising their boys or boys’ primary caretakers (and thus their level of educational attainment) changed during their upbringing, we used the primary caretaker’s highest level of educational attainment completed over the course of their son’s childhood. Parent educational attainment was operationalized as the primary caretaker having completed a high school degree or less, completing some college (e.g., Associate’s degree), or completing a Bachelor’s degree or higher, with primary caretakers who completed high school or less serving as the reference group in statistical analyses.

Adult SES.

As part of their PaTH assessment, participants reported on their individual pre-tax income, highest level of educational attainment, and their employment status. For income, participants selected the range in which their individual pre-tax annual income fell: <$10,000, $10,000-$14,999, $15,000-$24,999, $25,000-$34,999, $35,000-$49,999, $50,000-$64,999, $65,000-$79,999, $80,000-$94,999, $95,000-$109,999, $110,000-$124,999, $125,000-$139,999, $140,000-$154,999, $155,00-$169,999, $170,000-$185,000, > $185,000. Responses were then converted to the midpoint of the selected range (e.g., $29,999.50 for $25,000-$34,999) to get a continuous measure of adult income. As with childhood family income, CPI adjustments were used to convert adult income to 2022 dollars for participants who completed their PaTH assessment in 2023 or 2024. A natural log-transformation was then used to normalize the distribution of adult income prior to fitting statistical models. For educational attainment, participants reported on their highest level of educational attainment, which was then converted to the number of years of schooling completed where “Less than high school” was coded as 10 years, “high school degree or equivalent” as 12 years, “some college (e.g., an Associate’s degree, technical program)” as 14 years, a “Bachelor’s degree” as 16 years, and a “graduate or professional degree” as 18 years. For employment, participants were asked if they were currently employed or not employed. Income, educational attainment, and employment were standardized and then the standardized scores were averaged together to create an Adult SES composite score where higher scores reflected higher adult SES.

Traditional markers of adult CVD risk.

PaTH participants reported on their smoking and alcohol consumption and underwent a series of physiological assessments to measure their resting blood pressure, body mass index (BMI), waist circumference, cholesterol, glucose, and hemoglobin a1c levels. These measures are considered traditional markers of CVD risk and are easily collected and commonly assessed as part of routine doctor’s appointments. For smoking, participants indicated if they currently or formerly smoked cigarettes, which was used to create a binary variable differentiating current and former smokers (1) from non-smokers (0). For alcohol consumption, participants reported the average number of alcoholic drinks that they consumed over the past month. Resting blood pressure was based on the average of 3 readings of systolic and diastolic blood pressure taken over a 6-minute period using an Omron HEM-907XL Professional Blood Pressure Machine and cuff. Prior to the readings, participants had their arm circumference measured twice to determine the appropriate size of occlusion cuff. Then, participants were asked to sit quietly for 15 minutes, keeping their legs uncrossed and feet planted on the floor while their blood pressure was taken. Three participants had blood pressure readings that were suggestive of measurement error or biological implausibility (e.g., 77/59 mmHg), and thus recoded as missing. To assess adiposity, BMI and waist circumference were measured. For BMI, men had their height taken prior to stepping on a Tanita (TBF-410) bioelectrical impedance monitor to measure their weight and calculate their BMI (kg/m2). Using WHO recommendations, waist circumference was measured at the midpoint between the top of the iliac crest and lowest rib using a cloth tape measure (World Health Organization, 2008). Three readings were taken and averaged to calculate mean waist circumference. Participants also underwent a fasting blood draw. Blood and serum samples were sent to the University of Pittsburgh Medical Center’s Clinical Research Laboratory for processing. Triglycerides and HDL cholesterol were measured in serum using a Beckman Coulter AU5800 Analyzer. Glucose levels were measured using a Beckman Coulter AU System Glucose procedure and glycated hemoglobin (A1c) levels, which are reflective of blood sugar over a 2–3-month period, were measured using a Tosoh G8 HPLC Analyzer. One participant had extremely high triglyceride levels indicative of not fasting, severe hypertriglyceridemia, or measurement error; therefore, his data were recoded as missing for all blood markers. Natural log transformations were used to reduce skew for triglycerides, HDL cholesterol, glucose and A1c data. A composite was then calculated by averaging the standardized scores for each of the above 10 markers, reverse-scoring standardized scores for HDL cholesterol so that higher composite scores reflected greater risk.

Race.

As part of PaTH, participating men self-identified their race by selecting one or more of the following options: American Indian/Alaskan Native, Asian, Native Hawaiian or other Pacific Islander, Black or African American, White, Bi- or Multiracial, another race. There was also an ‘unknown race’ option if they did not know their race. Race is a social construct that was adjusted for in analyses to account for racial disparities in exposure to discrimination and the distribution of socioeconomic resources that could contribute to links between childhood family income and adult IMT (Krieger, 2014). As participants predominantly identified as Black or White, a binary race variable was created to compare participants who identified as Black or with another racial group (51.7%; 74.7% of whom identified as Black) to those who identified only as White and not with any other racial group (47.6%). Although not ideal, this approach was taken because separating out individual racial groups was not possible given the limited number of participants who identified with each specific racial group.

Adult medication use and self-reported health conditions.

Participants were asked if they were taking any prescription medications as part of the PaTH health history interview. Medications were coded and used to create a dichotomous variable indicating whether a participant was regularly taking an anti-hypertensive, anti-diabetic, or lipid-lowering medication (i.e., >5 times in 2 weeks), or not. Only two participants were regularly taking these medications. Participants also self-reported whether they had ever been told by a medical professional on two separate occasions that they had high blood pressure, high cholesterol, or diabetes. A dichotomous variable was created to indicate whether participants reported being told they had one or more of these conditions (1 = yes, 0 = no). A total of 20 participants indicated they were told they had high blood pressure (n = 16), high cholesterol (n = 8) or diabetes (n = 3).

Statistical analyses

Prior to fitting statistical models to address our hypotheses, descriptive statistics examined distributions of study variables to identify outliers and determine whether variables needed to be transformed. Independent sample t-tests and chi-square analyses were then used to compare PaTH participants with valid IMT data to those without IMT data. To examine whether cumulative childhood family income was related to adult IMT, we first fit a linear regression model where adult IMT was regressed on cumulative childhood family income. Then, we added parent educational attainment, adult SES, race, and traditional markers of CVD risk in adulthood to the regression model as covariates to test whether cumulative childhood income explained unique variance in adult IMT above and beyond relevant sociodemographic and health factors. Models were then re-run excluding participants who reported taking anti-hypertensive, anti-diabetic, or lipid-lowering medications. We also re-ran models adjusting for whether participants had ever been told by a medical professional that they had high blood pressure, high cholesterol, or diabetes, which are included in a supplemental table.

Next, we ran two post-hoc sensitivity analyses. First, we separated out family income during the first 5 years of life from family income aggregated across ages 6–17 years to test whether early childhood family income was uniquely associated with men’s IMT in adulthood above and beyond family income in middle childhood and adolescence given that some work suggests that early childhood is a developmental period when physiological systems are particularly responsive to environmental inputs (Shonkoff et al., 2009, 2012). For our second set of sensitivity analyses, we explored whether economic upward mobility across childhood and adolescence related to adult IMT by regressing adult IMT on the slope of family income across the 13 waves of PMCP collection, controlling for family income when participants were enrolled in PMCP. The slope of family income was calculated using a multi-level model regressing family income on childhood assessment wave with a random intercept and slope. For sensitivity analyses, we followed the same approach as with our primary analyses. That is, we first examined the association between childhood income measures and adult IMT, and then we adjusted for the socioeconomic- and health-related covariates to test for independent associations. Data were cleaned in SPSS (IBM Corp, Version 29.0.) and analyses were performed in R (R Core Team, 2024).

Results

Preliminary descriptive statistics and correlations between study variables

Among the 145 men who completed PaTH, IMT data were available for 125 participants. The 20 participants without IMT data did not statistically differ from those with valid IMT data with respect to cumulative childhood income (t(143) = .81, p = .42). The groups were also similar in terms of the highest level of education completed by their parents (χ2 = 3.44, p = .49) and their SES in adulthood (t(138) = −.18, p = .86), and race (χ2 = 1.55, p = .21). However, those with IMT data had fewer traditional markers of CVD risk (t(143) = −3.04, p = .006) relative to those without IMT data. Differences in CVD risk may reflect challenges with obtaining high-resolution images of the carotid arteries in individuals with higher levels of adiposity (Nabasenja et al., 2022). See Table 1 for descriptive statistics for the full PaTH sample and the subsample with valid IMT data, and Table 2 for correlations among study variables for the subset of participants with IMT data.

Table 1.

Descriptive characteristics for PaTH participants

All PaTH participants (n = 145) Subsample with carotid IMT data (n = 125)
M(SD) or n(%) M(SD) or n(%)
PMCP Measures Collected in Childhood, Adolescence, or Early Adulthood
Cumulative family income (ages 1.5–17 years; in 2022 dollars) $39,588 ($19,283) $40,110 ($19,768)
Highest level of parent educational attainment (ages 1.5–17 years)
 Less than High School 6 (4.1%) 5 (4.0%)
 High School diploma or GED 25 (17.2%) 22 (17.6%)
 Some college (e.g., Associate’s degree, vocational certificate) 70 (48.3%) 61 (48.8%)
 Bachelor’s degree 44 (30.3%) 37 (29.6%)
PaTH Study Measures Collected in Adulthood (age 32 years)
Age 31.7 (.8) 31.6 (.7)
Race
 Black or African American 56 (38.6%) 46 (36.8%)
 American Indian/Alaskan Native 2 (1.4%) 2 (1.6%)
 Native Hawaiian or other Pacific Islander 1 (0.7%) 1 (0.8%)
 Bi- or multiracial 9 (6.2%) 8 (6.4%)
 White 69 (47.6%) 62 (49.6%)
 Another race 4 (2.8%) 4 (3.2%)
 Unknown race 3 (2.1%) 2 (1.6%)
Annual income (in 2022 dollars) $45,505 ($36,188) $46,871 ($35,701)
Educational attainment
 Less than High School 6 (4.2%) 6 (4.8%)
 High School diploma or GED 60 (41.7%) 53 (42.7%)
 Some college (e.g., Associate’s degree, vocational certificate) 56 (38.9%) 45 (36.3%)
 Bachelor’s degree 20 (13.9%) 18 (14.5%)
 Graduate or professional degree 2 (1.4%) 2 (1.6%)
Currently employed 107 (81.1%) 93 (80.0%)
Traditional markers of cardiovascular risk in adulthood
 Current smoker 79 (55.6%) 70 (57.3%)
 Average number of alcoholic drinks per month 16.0 (29.7) 17.0 (31.2)
 Resting systolic blood pressure (mmHg) 123.8 (13.8) 122.6 (13.2)
 Resting diastolic blood pressure (mmHg) 80.0 (12.5) 78.9 (12.3)
 Waist circumference (cm) 101.8 (18.9) 99.7 (17.4)
 Body mass index (kg/m2) 29.6 (7.4) 28.7 (7.0)
 Triglycerides (mg/dL) 120.2 (89.0) 117.4 (81.0)
 HDL cholesterol (mg/dL) 49.0 (11.9) 49.4 (12.2)
 Glucose (mg/dL) 93.4 (21.7) 92.5 (18.3)
 Hemoglobin a1c (%) 5.6 (1.0) 5.6 (1.0)
Carotid IMT (mm) .60 (.07)
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PMCP = Pitt Mother & Child Project; PaTH = Pathways to Health; IMT = intima-media thickness; M = mean; SD = standard deviation

Table 2.

Correlation matrix

1 2 3 4 5 6 7
1. Cumulative childhood family income (log) 1
2. Parent completed Bachelor’s degree .234* 1
3. Parent completed some college −.131 −.633* 1
4. Adult SES .546* .202* −.194* 1
5. Traditional markers of CVD risk .086 −.076 .013 −.016 1
6. Race −.418* .018 .129 −.251* −.180* 1
7. Intima-media thickness (log) −.269* −.046 .062 −.129 .307* .258* 1
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* =

p < .05; Pearson correlations are reported for correlations between two continuous variables while point-biserial correlations are reported for correlations between dichotomous and continuous variables; SES = socioeconomic status; CVD = cardiovascular risk; Race was coded as 0 = identifying only as white; 1 = identifying with a racial group other than white

Primary analyses

Cumulative childhood family income was negatively associated with men’s carotid IMT (b = −.06, β = −.27, SE = .02, p < .01), such that being raised in a relatively more economically-advantaged household was prospectively related to less IMT in adulthood, on average (see Figure 1). As shown in Table 3, the association between cumulative childhood family income and adult IMT remained statistically reliable when adjusting for parent educational attainment, adult SES, traditional markers of CVD risk in adulthood, and race (b = −.05, β = .24, SE = .02, p = .03). Traditional markers of CVD risk (b = .08, β = .37, SE = .02, p < .001) and race (b = .05, β = .24, SE = .02, p =.01) were positively associated with IMT in models that included cumulative childhood family income as a predictor, such that participants with more traditional markers of CVD risk and those who identified with a racial group other than White tended to have greater IMT, on average. Results remained unchanged when excluding the two participants taking medications for cardiometabolic conditions, and when controlling for whether participants had ever been told by a medical professional that they had high blood pressure, high cholesterol, or diabetes (see Supplemental Table).

Figure 1.

Figure 1.

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Unadjusted association between cumulative childhood family income and men’s intima-media thickness

Table 3.

Results of regression analyses examining associations between cumulative childhood family income and men’s intima-media thickness in adulthood

Carotid intima-media thickness (log; age 32); Base Model Adjusted Model
b β SE p b β SE p
Cumulative childhood income −.06 −.27 .02 <.01* −.05 −.24 .02 .03*
Parent completed Bachelor’s degree .01 .04 .03 .69
Parent completed some college .01 .04 .02 .71
Adult SES .01 .07 .01 .49
Traditional markers of CVD risk .08 .37 .02 <.001*
Race .05 .24 .02 .01*
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* =

p < .05; b = unstandardized beta coefficient, β = standardized beta coefficient; SE = standard error; SES = socioeconomic status, CVD = cardiovascular disease; Race was coded as 0 = identifying only as white; 1 = identifying with a racial group other than white

Sensitivity analyses

In sensitivity models considering the salience of early childhood economic disadvantage on adult IMT, family income during the first 5 years of life was not related to IMT in adulthood over and above family income in middle childhood and adolescence (p = .44), nor in regression analyses adjusting for parental educational attainment, adult SES, traditional markers of CVD risk, and race (p = .61; Table 4).

Table 4.

Results of sensitivity analyses examining whether family income in early childhood is uniquely associated with men’s intima-media thickness in adulthood

Carotid intima-media thickness (log; age 32); Base Model Adjusted Model
b β SE p b β SE p
Family income in early childhood −.02 −.09 .02 .44 −.01 −.06 .02 .61
Family income across middle childhood and adolescence −.04 −.20 .02 .07 −.04 −.20 .02 .09
Parent completed Bachelor’s degree .01 .03 .03 .79
Parent completed some college .00 .03 .03 .81
Adult SES .01 .06 .01 .53
Traditional markers of CVD risk .08 .38 .02 <.001*
Race .05 .23 .02 .02*
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* =

p < .05; b = unstandardized beta coefficient, β = standardized beta coefficient; SE = standard error; SES = socioeconomic status, CVD = cardiovascular disease; Race was coded as 0 = identifying only as white; 1 = identifying with a racial group other than white

In sensitivity analyses considering the role of childhood economic upward mobility on adult IMT, both family income at enrollment (b = <−.001, β = −.19, SE <.01, p =.03) and the slope of cumulative childhood family income were both negatively associated with IMT in adulthood (b = <.001, β = −.21, SE <.01, p =.02; Table 5). That is, lower family income at enrollment into PMCP related to greater IMT in adulthood; and improvements in family income throughout childhood and adolescence were related to less IMT in adulthood. Notably, the association between the slope of childhood family income and adult IMT remained statistically reliable when further adjusting for parental educational attainment, adult SES, traditional markers of CVD risk, and race (b = <.001, β = .19, SE = <.01, p =.04), while the association between family income at enrollment and adult IMT became non-significant (p > .05)

Table 5.

Results of sensitivity analyses examining whether upward mobility throughout childhood and adolescence is associated with men’s intima-media thickness in adulthood

Carotid intima-media thickness (log; age 32); Base Model Adjusted Model
b β SE p b β SE p
Slope of cumulative childhood income <−.001 −.21 .00 .02* <−.001 −.19 .00 .04*
Family income at enrollment <−.001 −.19 .00 .03* <−.001 −.16 .00 .10
Parent completed Bachelor’s degree <.01 .02 .03 .87
Parent completed some college <.01 .02 .02 .86
Adult SES .01 .07 .01 .50
Traditional markers of CVD risk .08 .36 .02 <.001*
Race .05 .24 .02 .01*
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* =

p < .05; b = unstandardized beta coefficient, β = standardized beta coefficient; SE = standard error; SES = socioeconomic status, CVD = cardiovascular disease; Race was coded as 0 = identifying only as white; 1 = identifying with a racial group other than white

Discussion

Subclinical atherosclerosis falls along a socioeconomic gradient with IMT increasing as SES decreases (Ranjit et al., 2006). This socioeconomic gradient dates back to childhood, with children raised in lower SES households evidencing greater IMT in adulthood compared to their peers raised in more socioeconomically-advantaged childhood households (Camelo et al., 2015; Hakulinen et al., 2016; Kivimäki et al., 2006; Lemelin et al., 2009). As extant work on childhood SES and adult IMT has generally relied on parental educational attainment assessed retrospectively or only once or twice in childhood to measure childhood SES, the present prospective study set out to examine the role of cumulative childhood family income on adult men’s IMT among a high-risk sample by virtue of experiencing low income in infancy/toddlerhood. Drawing on repeated measures of childhood family income collected on up to 13 occasions throughout childhood and adolescence, we observed that cumulative childhood family income was negatively related to men’s IMT in adulthood. Moreover, cumulative childhood family income explained unique variance in men’s adult IMT that was not attributed to parents’ highest level of educational attainment, nor other socioeconomic and health-related factors in adulthood.

Findings highlight that among men who experienced low levels of family income in infancy/toddlerhood, IMT in adulthood varies as a function of cumulative childhood family income. This association appears to be independent of parent educational attainment, which itself was not found to be related to adult IMT. Even though childhood family income and parent educational attainment were related to one another in our sample as reflected by a ~$10,000 difference in cumulative family income between parents with (mean = $46,339) and without a Bachelor’s degree (mean = $36,648; t = −2.60, p = .01), our findings suggest that education and income capture distinct dimensions of childhood SES that may differentially shape men’s adult IMT. Results suggest that, at least among men who experienced low income in infancy/toddlerhood, childhood family income may play a more instrumental role in determining adult IMT than their primary parent’s educational attainment. For example, whereas higher parent educational attainment may support and promote health literacy (e.g., understanding food labels and health insurance paperwork (Yin et al., 2009), this knowledge may only go so far in reducing boys’ risk for atherosclerosis in adulthood if their parents cannot consistently afford high-quality food and health-related services. Pending replication, findings suggest that childhood family income may be important for health care professionals to take into consideration when assessing young men’s risk for atherosclerosis.

In an attempt to replicate prior study findings, we regressed adult IMT on parent educational attainment without adjusting for family income or any other covariates and found no significant differences in adult IMT among men whose parents had a Bachelor’s degree (b = −.002, p = .91) or some college experience (b = .01, p = .64) compared to a high school degree or less than high school education. There are several reasons that may explain why our findings failed to replicate prior work linking parental educational attainment to adult IMT. Foremost, our results are based on a high-risk sample of boys who were specifically recruited into the study because their parents were facing economic constraints. As such, parents with post-secondary education may not have reaped the economic returns of post-secondary education, hence why they were seeking public assistance support. Additionally, men in the sample were predominantly raised in Pittsburgh, PA, and the surrounding metropolitan area in the 1990s and early 2000s, which was a time when parents without post-secondary education could earn a livable salary working in the trades. However, this may not be the case in other parts of the country or in present day, when roughly 68% of jobs require some post-secondary experience or higher (Carnevale et al., 2023). It is also possible that our operationalization of parental educational attainment could underlie null findings. Here, parents’ educational attainment was operationalized as parents’ highest level of education achieved over the 13 waves of prospective childhood assessments. However, prior work has used retrospective reports of parent educational attainment, or parent educational attainment measured at one point during childhood (Camelo et al., 2015; Lemelin et al., 2009), the latter of which may not capture changes in parental education that take place when parents return to school while raising their children. Thus, future work is needed to replicate study findings in other high-risk cohorts across the U.S. and to consider how various measures of childhood SES and their operationalization may contribute to links between childhood socioeconomic circumstances and adult IMT.

One could also argue that childhood family income may be related to adult IMT simply because higher childhood income increased the likelihood that boys will complete more years of schooling, be gainfully employed, and have higher incomes in adulthood (Dearing et al., 2024). Thus, it is not really cumulative childhood income, but rather adult SES, that is responsible for differences in IMT between men (Ranjit et al., 2006). In support of this argument, SES was positively correlated with cumulative childhood family income and negatively correlated with adult IMT in our sample (Table 2). However, the association between cumulative childhood family income and adult IMT remained significant even after accounting for variance attributable to men’s own SES in adulthood, and adult SES was not significantly related to concurrent IMT. These findings seem to support the biological embedding of adversity hypothesis as economic disadvantage experienced across childhood and adolescence was associated with young men’s carotid IMT even after controlling for their current income, educational attainment, and employment status in adulthood (Berens et al., 2017; Chen et al., 2022; Jensen et al., 2017). Nevertheless, future work should examine if the association between cumulative childhood income and cardiovascular health persists into later adulthood, especially for men who spend more of their adult years living in affluence as some studies have shown that cumulative SES across the life course may underlie inter-individual differences in IMT among older adults (Carson et al., 2007).

Others may argue that the variance in carotid IMT that is attributed to cumulative childhood family income is simply reflective of differences in traditional markers of CVD risk like blood pressure, cholesterol, adiposity, blood glucose, and smoking. For example, parents with more money may be able to afford healthier food options and housing in safe neighborhoods with fewer stressors and more recreational and health services, which may benefit their sons’ long-term cardiovascular health. Thus, traditional markers of CVD risk (and not childhood family income per se) may be accounting for differences in IMT among men in the sample. Even though research on childhood SES and adult IMT has shown that links between composite measures of childhood SES and adult IMT are attenuated after accounting for traditional markers of CVD risk, like blood pressure, cholesterol, and BMI (e.g., Hakulinen et al., 2016; Lamont et al., 2000) this was not supported in the current study. Specifically, we found that the effect of cumulative childhood family income on adult IMT remained significant when taking into consideration traditional markers of CVD risk; however, it is worth noting that the magnitude of the effect size for cumulative childhood income on adult IMT (β = −.24) was relatively smaller than the effect size for traditional markers of CVD (β = .38). These findings underscore the importance of considering a person’s socioeconomic upbringing in addition to traditional CVD risk markers when assessing their risk for subclinical atherosclerosis. Nevertheless, there were 20 PaTH participants for whom we did not have valid IMT data, and these men with missing IMT data had traditional markers of CVD risk that were roughly one standard deviation higher than men for whom IMT data were available. For example, average BMI for the IMT subsample was 28.7, which is considered overweight, whereas the average BMI for those without IMT data was 35.1, which is suggestive of obesity. Although we cannot say for certain, it is possible that our results underestimate the contribution of cumulative childhood family income to men’s IMT in adulthood given that men with missing IMT data may be at greatest risk for atherosclerosis. Therefore, future work is needed to discern whether the variance in men’s adult IMT that is explained by cumulative childhood family income extends to men with higher levels of adiposity and a greater number of traditional CVD risk markers.

Importantly, results of our post-hoc sensitivity analyses suggest that one reason why cumulative childhood family income may be related to less subclinical atherosclerosis in adulthood is because of economic upward mobility across childhood. Specifically, we observed that economic upward mobility (as reflected by a positive slope in family income throughout childhood and adolescence) was related to less adult IMT in our sample. This aligns with prior research by Cundiff and colleagues (2017), who found that improvements in family SES from ages 7–16 years were associated with fewer self-reported health conditions in adulthood. Although not entirely clear, it may be that as parents move up the economic ladder, they are able to financially invest more in their boys’ health, including accessing high-quality healthcare and recreational resources that they could not afford earlier in their sons’ lives. Thus, programs and policies that provide families with the resources necessary to be upwardly mobile economically (e.g., cash transfers, tax credits), may have the potential to reduce boys’ risk for subclinical atherosclerosis in adulthood. Nevertheless, our findings should be interpreted cautiously until replicated in larger samples given that prior reviews have found inconsistent associations between economic upward mobility and later cardiovascular health, including unintended negative consequences (Chen et al., 2022; Pollitt et al., 2005). Furthermore, recent work by Duncan and colleagues (2025) calls into question the purported physical health benefits of unconditional cash transfer programs as they found null effects of monthly unconditional cash transfers given to low-income mothers over the first 4 years of their child’s life on children’s BMI percentile and health conditions at age ~4 years.

Strengths and Limitations

This study has many strengths; to our knowledge, it is the first to examine prospective and non-dichotomized childhood family income as a driving factor of IMT in adult men. Childhood family income data were collected up to 13 times throughout childhood and adolescence to estimate cumulative childhood family income from 1.5 to 17 years old. This method of data collection allows for a far more robust understanding of the health implications of childhood family income compared to studies that are only able to assess childhood SES at one or two time points in childhood and/or adolescence, or those that rely on retrospective reports. Childhood family income was also escalated to be reflective of the dollar in 2022, allowing for income to be comparable across the years. Furthermore, by not creating a composite score of childhood SES using parental income and educational attainment, we were able to isolate the potential unique contributions of cumulative childhood family income to IMT in adult men. The PMCP (and by extension, the PaTH study) also intentionally recruited Black, multiracial, and White men from families receiving WIC services, which is a major strength of this study as such samples of men are often underrepresented in research. Finally, in addition to utilizing PMCP’s extensive longitudinal data to create aggregate measures of family income and parental educational attainment, we also considered men’s current socioeconomic circumstances in adulthood to test whether contemporaneous educational attainment, employment, and income accounted for the variance in adult IMT that was attributed to childhood income. Moreover, the PaTH study’s focus on health and health behaviors allowed us to covary for traditional markers of CVD risk that may independently associate with IMT (Giudice et al., 2012; Koskinen et al., 2009; Kotsis et al., 2006).

Despite such prominent strengths, the current study also has several limitations. Data were only collected from men, and so findings cannot be generalized across the sexes. Enrolled participants all experienced low family income in infancy and/or toddlerhood and came from families who were actively seeking public assistance. With this in mind, PaTH participants may have experienced unique encounters with economic disadvantage during developmentally significant times, compared to the general population. As such, findings may not be generalizable to men who experienced middle- or high-income circumstances in infancy/toddlerhood, or those who experienced low income in infancy/toddlerhood whose parents did not seek public assistance. Additionally, as we looked at childhood family income accumulated across the first 13 waves of data collection, we did not attend to other potentially salient dimensions of family economic circumstances, including income volatility and wealth, which may also be important. Due to the dichotomization of race and limited representation of important racial/ethnic subgroups within this sample, we were also unable to explore nuanced racial variability within this relationship. Future studies with larger, more diverse samples may be better positioned to further extrapolate upon the intersection of race and income on later adult IMT. Another limitation is that, despite having data on 145 participants, only 125 participants had interpretable IMT data. As described earlier, the 20 participants with missing data had a greater number of traditional CVD risk markers and so we were unable to determine if results were attenuated or strengthened based on these factors among the most proximally impacted individuals. As such, findings cannot be generalized to individuals at the highest risk of CVD. Furthermore, our measure of smoking differentiated current and former smokers from non-smokers. However, there may be differences in IMT between current and former smokers depending on the duration and quantity of their exposure to nicotine (Baldassarre et al., 2009). Finally, all findings presented are correlational. While they offer significant insight into potential targets for improving health equity, they do not establish causality. As such, findings should be interpreted cautiously.

Conclusion

Childhood income can have lifelong effects on CVD in adulthood, especially for individuals who experience low income early in life. In the current study, we find that childhood family income may independently contribute to the development of atherosclerosis in young men who experienced low income in infancy/toddlerhood, which may ultimately progress into CVD in later adulthood. The association is above and beyond that of parental educational attainment, traditional markers CVD risk, and contemporaneous measures of SES in adulthood. Pending the replication of findings in larger, more diverse samples that include both men and women across broad ranges of socioeconomic and racial backgrounds, results suggest that childhood family income may serve as one potentially modifiable target for policy interventions aimed at reducing CVD risk in young adults.

Supplementary Material

1

Public health significance:

Among boys who experience low levels of income in infancy/toddlerhood, improvements in cumulative childhood income may decrease the risk for developing atherosclerosis in young adulthood. Moreover, findings suggest that when assessing patients’ cardiovascular disease risk, it may be helpful for medical professionals to consider childhood economic conditions in addition to measuring traditional markers of cardiovascular disease risk and current socioeconomic circumstances.

Disclosures and Acknowledgements.

Data and R code for this project are available on OSF at https://osf.io/6nrgs/. This research was supported by a grant from the National Heart, Lung, and Blood Institute (R01 HL152444; MPIs: Shaw, Marsland, Votruba-Drzal). The authors declare no conflicts of interest.

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