Use of Correct and Incorrect Methods of Accounting for Age in Studies of Epigenetic Accelerated Aging: Implications and Recommendations for Best Practices.

Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic "clocks" (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature-1 incorrect and 2 correct-on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices.

Decreasing Survey Response Rates in the Time of COVID-19: Implications for Analyses of Population Health and Health Inequities.

Objectives. To examine whether, and if so how, US national and state survey response rates changed after the onset of the COVID-19 pandemic. Methods. We compared the change in response rates between 2020 and 2019 of 6 (3 social and economic, 3 health focused) major US national surveys (2 with state response rates). Results. All the ongoing surveys except 1 reported relative decreases (∼29%) in response rates. For example, the household response rate to the US Census American Community Survey decreased from 86.0% in 2019 to 71.2% in 2020, and the response rate of the US National Health Interview Survey decreased from 60.0% to 42.7% from the first to the second quarter of 2020. For all surveys, the greatest decreases in response rates occurred among persons with lower income and lower education. Conclusions. Socially patterned decreases in response rates pose serious challenges and must be addressed explicitly in all studies relying on data obtained since the onset of the pandemic. Public Health Implications. Artifactual reduction of estimates of the magnitude of health inequities attributable to differential response rates could adversely affect efforts to reduce these inequities. (Am J Public Health. 2023;113(6):667-670. https://doi.org/10.2105/AJPH.2023.307267).

Contextualizing Response Rates During the COVID-19 Pandemic: Experiences From a Boston-Based Community Health Centers Study.

OBJECTIVES: The focus of this study was to calculate and contextualize response rates for a community-based study conducted during the COVID-19 pandemic, a topic on which scant data exist, and to share lessons learned from recruiting and enrolling for implementation of future studies. DESIGN: The Life+Health Study, a cross-sectional population-based study designed to advance novel methods to measure and analyze multiple forms of discrimination for population health research. SETTING: The study recruited participants from 3 community health centers in Boston, Massachusetts, between May 2020 and July 2022. PARTICIPANTS: A total of 699 adult participants between the ages of 25 and 64 years who were born in the United States and had visited one of the health centers within the last 2 years. MAIN OUTCOME MEASURES: The response rate was calculated as follows: (number of completions + number of dropouts)/(dropouts + enrollments). To contextualize this response rate, we synthesized evidence pertaining to local COVID-19 case counts, sociopolitical events, pandemic-related restrictions and project protocol adjustments, and examples of interactions with patients. RESULTS: Our study had a lower-than-expected response rate (48.4%), with the lowest rates from the community health centers serving primarily low-income patients of color. Completion rates were lower during periods of higher COVID-19 case counts. We describe contextual factors that led to challenges and lessons learned from recruiting during the pandemic, including the impact of US sociopolitical events. CONCLUSIONS: The Life+Health Study concluded recruitment during the pandemic with a lower-than-expected response rate, as also reported in 4 other US publications focused on the impact of COVID-19 on response rates in community-based studies. Our results provide an example of the impact of the pandemic and related US sociopolitical events on response rates that can serve as a framework for contextualizing other research conducted during the pandemic and highlight the importance of best practices in research recruitment with underserved populations.

Impact of Differential Privacy and Census Tract Data Source (Decennial Census Versus American Community Survey) for Monitoring Health Inequities.

Objectives. To investigate how census tract (CT) estimates of mortality rates and inequities are affected by (1) differential privacy (DP), whereby the public decennial census (DC) data are injected with statistical "noise" to protect individual privacy, and (2) uncertainty arising from the small number of different persons surveyed each year in a given CT for the American Community Survey (ACS).Methods. We compared estimates of the 2008-2012 average annual premature mortality rate (death before age 65 years) in Massachusetts using CT data from the 2010 DC, 2010 DC with DP, and 2008-2012 ACS 5-year estimate data.Results. For these 3 denominator sources, the age-standardized premature mortality rates (per 100 000) for the total population respectively equaled 166.4 (95% confidence interval [CI] = 162.2, 170.6), 166.4 (95% CI = 162.2, 170.6), and 166.3 (95% CI = 162.1, 170.5), and inequities in the range from best to worst quintile for CT racialized economic segregation were from 103.4 to 260.1, 102.9 to 258.7, and 102.8 to 262.4. Similarity of results across CT denominator sources held for analyses stratified by gender and race/ethnicity.Conclusions. Estimates of health inequities at the CT level may not be affected by use of 2020 DP data and uncertainty in the ACS data.

The target/perpetrator brief-implicit association test (B-IAT): an implicit instrument for efficiently measuring discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age.

BACKGROUND: To date, research assessing discrimination has employed primarily explicit measures (i.e., self-reports), which can be subject to intentional and social desirability processes. Only a few studies, focusing on sex and race/ethnicity discrimination, have relied on implicit measures (i.e., Implicit Association Test, IAT), which permit assessing mental representations that are outside of conscious control. This study aims to advance measurement of discrimination by extending the application of implicit measures to multiple types of discrimination and optimizing the time required for the administration of these instruments. METHODS: Between September 27th 2019 and February 9th 2020, we conducted six experiments (984 participants) to assess implicit and explicit discrimination based on race/ethnicity, sex, gender identity, sexual orientation, weight, and age. Implicit discrimination was measured by using the Brief-Implicit Association Test (B-IAT), a new validated version of the IAT developed to shorten the time needed (from ≈15 to ≈2 min) to assess implicit mental representations, while explicit discrimination was assessed using self-reported items. RESULTS: Among participants (mean age = 37.8), 68.6% were White Non-Hispanic; 69% were females; 76.1% were heterosexual; 90.7% were gender conforming; 52.8% were medium weight; and 41.5% had an advanced level of education. Overall, we found implicit and explicit recognition of discrimination towards all the target groups (stronger for members of the target than dominant groups). Some exceptions emerged in experiments investigating race/ethnicity and weight discrimination. In the racism experiment, only people of Color showed an implicit recognition of discrimination towards the target group, while White people were neutral. In the fatphobia experiment, participants who were not heavy showed a slight implicit recognition of discrimination towards the dominant group, while heavy participants were neutral. CONCLUSIONS: This study provides evidence that the B-IAT is a valuable tool for quickly assessing multiple types of implicit discrimination. It shows also that implicit and explicit measures can display diverging results, thus indicating that research would benefit from the use of both these instruments. These results have important implications for the assessment of discrimination in health research as well as in social and psychological science.

Cancer Stage at Diagnosis, Historical Redlining, and Current Neighborhood Characteristics: Breast, Cervical, Lung, and Colorectal Cancers, Massachusetts, 2001-2015.

In the 1930s, maps created by the federal Home Owners' Loan Corporation (HOLC) nationalized residential racial segregation via "redlining," whereby HOLC designated and colored in red areas they deemed to be unsuitable for mortgage lending on account of their Black, foreign-born, or low-income residents. We used the recently digitized HOLC redlining maps for 28 municipalities in Massachusetts to analyze Massachusetts Cancer Registry data for late stage at diagnosis for cervical, breast, lung, and colorectal cancer (2001-2015). Multivariable analyses indicated that, net of age, sex/gender, and race/ethnicity, residing in a previously HOLC-redlined area imposed an elevated risk for late stage at diagnosis, even for residents of census tracts with present-day economic and racial privilege, whereas the best historical HOLC grade was not protective for residents of census tracts without such current privilege. For example, a substantially elevated risk of late stage at diagnosis occurred among men with lung cancer residing in currently privileged areas that had been redlined (risk ratio = 1.17, 95% confidence interval: 1.06, 1.29), whereas such risk was attenuated among men residing in census tracts lacking such current privilege (risk ratio = 1.01, 95% confidence interval: 0.94, 1.08). Research on historical redlining as a structural driver of health inequities is warranted.

COVID-19 and Overall Mortality Inequities in the Surge in Death Rates by Zip Code Characteristics: Massachusetts, January 1 to May 19, 2020.

Objectives. To address evidence gaps in COVID-19 mortality inequities resulting from inadequate race/ethnicity data and no socioeconomic data.Methods. We analyzed age-standardized death rates in Massachusetts by weekly time intervals, comparing rates for January 1 to May 19, 2020, with the corresponding historical average for 2015 to 2019 stratified by zip code social metrics.Results. At the surge peak (week 16, April 15-21), mortality rate ratios (comparing 2020 vs 2015-2019) were 2.2 (95% confidence interval [CI] = 1.4, 3.5) and 2.7 (95% CI = 1.4, 5.5) for the lowest and highest zip code tabulation area (ZCTA) poverty categories, respectively, with the 2020 peak mortality rate 1.1 (95% CI = 1.0, 1.3) times higher in the highest than the lowest poverty ZCTA. Similarly, rate ratios were significantly elevated for the highest versus lowest quintiles with respect to household crowding (1.7; 95% CI = 1.0, 2.9), racialized economic segregation (3.1; 95% CI = 1.8, 5.3), and percentage population of color (1.8; 95% CI = 1.6, 2.0).Conclusions. The COVID-19 mortality surge exhibited large inequities.Public Health Implications. Using zip code social metrics can guide equity-oriented COVID-19 prevention and mitigation efforts.

Structural Racism, Historical Redlining, and Risk of Preterm Birth in New York City, 2013-2017.

Objectives. To assess if historical redlining, the US government's 1930s racially discriminatory grading of neighborhoods' mortgage credit-worthiness, implemented via the federally sponsored Home Owners' Loan Corporation (HOLC) color-coded maps, is associated with contemporary risk of preterm birth (< 37 weeks gestation).Methods. We analyzed 2013-2017 birth certificate data for all singleton births in New York City (n = 528 096) linked by maternal residence at time of birth to (1) HOLC grade and (2) current census tract social characteristics.Results. The proportion of preterm births ranged from 5.0% in grade A ("best"-green) to 7.3% in grade D ("hazardous"-red). The odds ratio for HOLC grade D versus A equaled 1.6 and remained significant (1.2; P < .05) in multilevel models adjusted for maternal sociodemographic characteristics and current census tract poverty, but was 1.07 (95% confidence interval = 0.92, 1.20) after adjustment for current census tract racialized economic segregation.Conclusions. Historical redlining may be a structural determinant of present-day risk of preterm birth.Public Health Implications. Policies for fair housing, economic development, and health equity should consider historical redlining's impacts on present-day residential segregation and health outcomes.

Breast Cancer Estrogen Receptor Status According to Biological Generation: US Black and White Women Born 1915-1979.

Evidence suggests that contemporary population distributions of estrogen-receptor (ER) status among breast cancer patients may be shaped by earlier major societal events, such as the 1965 abolition of legal racial discrimination in the United States (state and local "Jim Crow" laws) and the Great Famine in China (1959-1961). We analyzed changes in ER status in relation to Jim Crow birthplace among the 46,417 black and 339,830 white US-born, non-Hispanic women in the Surveillance, Epidemiology, and End Results (SEER) 13 Registry Group who were born between 1915 and 1979 and diagnosed (ages 25-84 years, inclusive) during 1992-2012. We grouped the cases according to birth cohort and quantified the rate of change using the haldane (which scales change in relation to biological generation). The percentage of ER-positive cases rose according to birth cohort (1915-1919 to 1975-1979) only among women diagnosed before age 55. Changes according to biological generation were greater among black women than among white women, and among black women, they were greatest among those born in Jim Crow (versus non-Jim Crow) states, with this group being the only group to exhibit high haldane values (>|0.3|, indicating high rate of change). Our study's analytical approach and findings underscore the need to consider history and societal context when analyzing ER status among breast cancer patients and racial/ethnic inequities in its distribution.

Feasibility of analyzing DNA copy number variation in breast cancer tumor specimens from 1950 to 2010: how old is too old?

PURPOSE: The purpose of the study was to assess the feasibility of quantifying long-term trends in breast tumor DNA copy number variation (CNV) profiles. METHODS: We evaluated CNV profiles in formalin-fixed paraffin-embedded (FFPE) tumor specimens from 30 randomly selected Kaiser Permanente Northern California health plan women members diagnosed with breast cancer from 1950 to 2010. Assays were conducted for five cases per decade who had available tumor blocks and pathology reports. RESULTS: As compared to the tumors from the 1970s to 2000s, the older tumors dating back to the 1950s and 1960s were much more likely to (1) fail quality control, and (2) have fewer CNV events (average 23 and 31 vs. 58 to 69), fewer CNV genes (average 5.1 and 3.7k vs. 8.1 to 10.3k), shorter CNV length (average 2,440 and 3,300k vs. 5,740 to 9,280k), fewer high frequency Del genes (37 and 25% vs. 54 to 76%), and fewer high frequency high_Amp genes (20% vs. 56 to 73%). On average, assay interpretation took an extra 60 min/specimen for cases from the 1960s versus 20 min/specimen for the most recent tumors. CONCLUSIONS: Assays conducted in the mid-2010s for CNVs may be feasible for FFPE tumor specimens dating back to the 1980s, but less feasible for older specimens.

Jim Crow and estrogen-receptor-negative breast cancer: US-born black and white non-Hispanic women, 1992-2012.

PURPOSE: It is unknown whether Jim Crow-i.e., legal racial discrimination practiced by 21 US states and the District of Columbia and outlawed by the US Civil Rights Act in 1964-affects US cancer outcomes. We hypothesized that Jim Crow birthplace would be associated with higher risk of estrogen-receptor-negative (ER-) breast tumors among US black, but not white, women and also a higher black versus white risk for ER- tumors. METHODS: We analyzed data from the SEER 13 registry group (excluding Alaska) for 47,157 US-born black non-Hispanic and 348,514 US-born white non-Hispanic women, aged 25-84 inclusive, diagnosed with primary invasive breast cancer between 1 January 1992 and 31 December 2012. RESULTS: Jim Crow birthplace was associated with increased odds of ER- breast cancer only among the black, not white women, with the effect strongest for women born before 1965. Among black women, the odds ratio (OR) for an ER- tumor, comparing women born in a Jim Crow versus not Jim Crow state, equaled 1.09 (95% confidence interval [CI] 1.06, 1.13), on par with the OR comparing women in the worst versus best census tract socioeconomic quintiles (1.15; 95% CI 1.07, 1.23). The black versus white OR for ER- was higher among women born in Jim Crow versus non-Jim Crow states (1.41 [95% CI 1.13, 1.46] vs. 1.27 [95% CI 1.24, 1.31]). CONCLUSIONS: The unique Jim Crow effect for US black women for breast cancer ER status underscores why analysis of racial/ethnic inequities must be historically contextualized.

Measures of Local Segregation for Monitoring Health Inequities by Local Health Departments.

OBJECTIVES: To assess the use of local measures of segregation for monitoring health inequities by local health departments. METHODS: We analyzed preterm birth and premature mortality (death before the age of 65 years) rates for Boston, Massachusetts, for 2010 to 2012, using the Index of Concentration at the Extremes (ICE) and the poverty rate at both the census tract and neighborhood level. RESULTS: For premature mortality at the census tract level, the rate ratios comparing the worst-off and best-off terciles were 1.58 (95% confidence interval [CI] = 1.36, 1.83) for the ICE for income, 1.66 (95% CI = 1.43, 1.93) for the ICE for race/ethnicity, and 1.63 (95% CI = 1.40, 1.90) for the ICE combining income and race/ethnicity, as compared with 1.47 (95% CI = 1.27, 1.71) for the poverty measure. Results for the ICE and poverty measures were more similar for preterm births than for premature mortality. CONCLUSIONS: The ICE, a measure of social spatial polarization, may be useful for analyzing health inequities at the local level. Public Health Implications. Local health departments in US cities can meaningfully use the ICE to monitor health inequities associated with racialized economic segregation.

Local Residential Segregation Matters: Stronger Association of Census Tract Compared to Conventional City-Level Measures with Fatal and Non-Fatal Assaults (Total and Firearm Related), Using the Index of Concentration at the Extremes (ICE) for Racial, Economic, and Racialized Economic Segregation, Massachusetts (US), 1995-2010.

Research on residential segregation and health, primarily conducted in the USA, has chiefly employed city or regional measures of racial segregation. To test our hypothesis that stronger associations would be observed using local measures, especially for racialized economic segregation, we analyzed risk of fatal and non-fatal assault in Massachusetts (1995-2010), since this outcome is strongly associated with residential segregation. The segregation metrics comprised the Index of Concentration at the Extremes (ICE), the Index of Dissimilarity, and poverty rate, with measures computed at both the census tract and city/town level. Key results were that larger associations between fatal and non-fatal assaults and residential segregation occurred for models using the census tract vs. city/town measures, with the greatest associations observed for racialized economic segregation. For fatal assaults, comparing the bottom vs. top quintiles, the incidence rate ratio (and 95% confidence interval (CI)) in models using the census tract measures equaled 3.96 (95% CI 3.10, 5.06) for the ICE for racialized economic segregation, 3.26 (95% CI 2.58, 4.14) for the ICE for income, 3.14 (95% CI 2.47, 3.99) for poverty, 2.90 (95% CI 2.21, 3.81) for the ICE for race/ethnicity, and only 0.93 (95% CI 0.79, 1.11) for the Index of Dissimilarity; in models that included both census tract and city/town ICE measures, this risk ratio for the ICE for racialized economic segregation was higher at the census tract (3.29; 95% CI 2.43, 4.46) vs. city/town level (1.61; 95% CI 1.12, 2.32). These results suggest that, at least in the case of fatal and non-fatal assaults, research on residential segregation should employ local measures, including of racialized economic segregation, to avoid underestimating the adverse impact of segregation on health.

Metrics for monitoring cancer inequities: residential segregation, the Index of Concentration at the Extremes (ICE), and breast cancer estrogen receptor status (USA, 1992-2012).

PURPOSE: To address the paucity of evidence on residential segregation and cancer, we explored their relationship using a new metric: the Index of Concentration at the Extremes (ICE). We focused on breast cancer estrogen receptor (ER) status, a biomarker associated with survival and, etiologically, with social and economic privilege. METHODS: We obtained data from the 13 registry group of US Surveillance, Epidemiology, and End Results (SEER) program for 1992-2012 on all women aged 25-84 who were diagnosed with primary invasive breast cancer (n = 516,382). We appended to each case's record her annual county median household income quintile and the quintile for her annual county value for ICE measures for income (≤20th vs. ≥80th household income quintile), race/ethnicity (black vs. white), and income plus race/ethnicity (low-income black vs. high-income white). The odds of being ER+ versus ER- were estimated in relation to the county-level income and ICE measures, adjusting for relevant covariates. RESULTS: Women in the most privileged versus deprived county quintile for household income and for all three ICE measures had a 1.1- to 1.3-fold increased odds (95 % confidence intervals excluding 1) of having an ER+ tumor. These results were robust to adjustment for age at diagnosis, cancer registry, tumor characteristics (tumor stage, size, histology, grade), and race/ethnicity. CONCLUSION: A focus on segregation offers news possibilities for understanding how inequitable group relations contribute to cancer inequities. The utility of employing the ICE for monitoring cancer inequities should be investigated in relation to other cancer outcomes.

Public Health Monitoring of Privilege and Deprivation With the Index of Concentration at the Extremes.

OBJECTIVES: We evaluated use of the Index of Concentration at the Extremes (ICE) for public health monitoring. METHODS: We used New York City data centered around 2010 to assess cross-sectional associations at the census tract and community district levels, for (1) diverse ICE measures plus the US poverty rate, with (2) infant mortality, premature mortality (before age 65 years), and diabetes mortality. RESULTS: Point estimates for rate ratios were consistently greatest for the novel ICE that jointly measured extreme concentrations of income and race/ethnicity. For example, the census tract-level rate ratio for infant mortality comparing the bottom versus top quintile for an ICE contrasting low-income Black versus high-income White equaled 2.93 (95% confidence interval [CI] = 2.11, 4.09), but was 2.19 (95% CI = 1.59, 3.02) for low versus high income, 2.77 (95% CI = 2.02, 3.81) for Black versus White, and 1.56 (95% CI = 1.19, 2.04) for census tracts with greater than or equal to 30% versus less than 10% below poverty. CONCLUSIONS: The ICE may be a useful metric for public health monitoring, as it simultaneously captures extremes of privilege and deprivation and can jointly measure economic and racial/ethnic segregation.

Police Killings and Police Deaths Are Public Health Data and Can Be Counted.

Nancy Krieger and colleagues argue that law-enforcement-related deaths in the United States should be treated as notifiable conditions, which would allow public health departments to report these data in real-time.

Age at menarche: 50-year socioeconomic trends among US-born black and white women.

OBJECTIVES: We investigated 50-year US trends in age at menarche by socioeconomic position (SEP) and race/ethnicity because data are scant and contradictory. METHODS: We analyzed data by income and education for US-born non-Hispanic Black and White women aged 25 to 74 years in the National Health Examination Survey (NHES) I (1959-1962), National Health Examination and Nutrition Surveys (NHANES) I-III (1971-1994), and NHANES 1999-2008. RESULTS: In NHES I, average age at menarche among White women in the 20th (lowest) versus 80th (highest) income percentiles was 0.26 years higher (95% confidence interval [CI] = -0.09, 0.61), but by NHANES 2005-2008 it had reversed and was -0.33 years lower (95% CI = -0.54, -0.11); no socioeconomic gradients occurred among Black women. The proportion with onset at younger than 11 years increased only among women with low SEP, among Blacks and Whites (P for trend < .05), and high rates of change occurred solely among Black women (all SEP strata) and low-income White women who underwent menarche before 1960. CONCLUSIONS: Trends in US age at menarche vary by SEP and race/ethnicity in ways that pose challenges to several leading clinical, public health, and social explanations for early age at menarche and that underscore why analyses must jointly include data on race/ethnicity and socioeconomic position. Future research is needed to explain these trends.

Reproductive justice and the pace of change: socioeconomic trends in US infant death rates by legal status of abortion, 1960-1980.

US infant death rates for 1960 to 1980 declined most quickly in (1) 1970 to 1973 in states that legalized abortion in 1970, especially for infants in the lowest 3 income quintiles (annual percentage change = -11.6; 95% confidence interval = -18.7, -3.8), and (2) the mid-to-late 1960s, also in low-income quintiles, for both Black and White infants, albeit unrelated to abortion laws. These results imply that research is warranted on whether currently rising restrictions on abortions may be affecting infant mortality.